The Content Strategy Experts - Scriptorium

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Are you in control of your digital destiny? In this episode, Alan Pringle and Sarah O’Keefe define digital sovereignty. They break down what organizations need to consider as they bring AI into content operations, from data leakage and competitive intelligence to shifting international regulations.

Sarah O’Keefe: The working definition that I’m using is that digital sovereignty is control over your own digital assets, digital destiny. That could be you personally, it could be you as an organization, or it could be you as a country or as a group of nations. And when I say group of nations, probably 98% of the time I’m talking about the EU, which has some laws in this regard. Digital sovereignty is your ability to control, own, and manage your digital assets and how they are used, reused, processed, resold, repurposed, and all the rest of it.

Related links:

AI in the content lifecycle: three years later
From ad hoc to autonomous: The AI content ops maturity model
Upcoming AI book: The Uninvited Author

LinkedIn:

Alan Pringle
Sarah O’Keefe

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and processes that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

AP: Hey everybody, I’m Alan Pringle.

SO: And I’m Sarah O’Keefe, hello.

AP: Hey there. And today Sarah and I want to talk about something that’s really starting to come to the forefront with all of the AI things that are going on in our world. And that is digital sovereignty. And before we get too deep in that, I need to throw up many, many disclaimers. Sarah and I are not lawyers, nor do we play them on television.

And we are absolutely not lawyers or experts on anything in regard to international intellectual property. So with those disclaimers out there, Sarah, if you would, would you define what digital sovereignty is?

SO: The working definition that I’m using is that digital sovereignty is control over your own digital assets, digital destiny. That could be you personally, it could be you, the organization, or it could be you as a country or as a group of nations. And when I say group of nations, probably 98% of the time I’m talking about the EU, which has some laws in this regard. So it is your ability to control, own, and manage your digital assets and how they are used, reused, processed, resold, repurposed, and all the rest of it.

AP: And I’m going to give a very basic example from my personal life in regard to email. Years ago, actually decades ago, when I got set up with an internet service provider, they provided me with an email address. It had their company name in the domain.com. And I used it for years. But when I switched my ISP, guess what? I had to make a decision.

Do I continue to pay that old ISP, basically rent, to maintain that old email address? Or should I move to one of maybe the free email providers? So I did a little research, and my ultimate decision was I created my own domain with my name, and I kind of just decided not to ever use again the email provided by an ISP because if you switch it, you’re going to possibly lose control of that email address. And at the time that I made the switch, a lot of the free providers, they would scan your email to provide targeted ads and some other things that was kind of unsavory to me.

So I ultimately made the decision I was going to own the domain and set that up myself and pick my own software that I hooked up to it to use to to read it. And I did not use a third-party email provider to basically pull in or reference my account. I am using an open-source standalone email client to kind of minimize who can poke into my email. So that’s one very basic example of how I kind of took control of my digital life as it were.

SO: Right. And if we apply that to content ops, again, staying pretty general, you think about cloud systems, like the cloud universe versus on-prem.

AP: Yes.

SO: And when you talk about, let’s say, a CCMS, a component content management system that is on-premises, the the argument was always, well, that way all of our content lives on our servers, in our organization, we have complete control over it.

Along come the cloud services, the cloud-based CCMSs and everything else. And they say, well, yes, but it’s much cheaper for you to put this into the cloud on our systems, which are shared. And you know, there’s advantages of upgrading, and there’s all sorts of advantages to cloud systems, mostly around IT overhead. from a digital sovereignty point of view.

You are delegating to that cloud system and you have some sort of a contract or a service level agreement. And again, we are not lawyers, but you have this agreement that says we the cloud provider promise to not scan your information or not use it for evil or not, you know, there’s a bunch of stuff in that contract that governs how cloud provider is or is not allowed to handle your content, your personal information, your credit card information that you might be putting in there and all the rest of it. And with software as a service, with cloud systems, we have for the most part cut over into cloud. You know, that’s that’s kind of the default these days. There’s hardly anybody that is still putting their content, their content and their content management systems on their own proprietary in-house servers.

AP: Yes, correct.

SO: So we have decided that for cloud, you know, cloud writ large generally, that the advantages of cloud outweigh the disadvantages. Now, moving this a little bit more towards content and slowly towards AI, where things get really interesting with digital sovereignty, if we talk about machine translation for a minute.

There are a couple of different ways of doing machine translation, obviously, but big picture, you can have your in-house machine translation system and database, and you can control that and govern it and do things with it. Or you can take your content and you can throw it at a public-facing machine translation system. And the risk that you run when you throw something at a public system is that they will take your proprietary confidential content.

And use it. So I throw at it a sentence that says, the XYZ company has developed a special new thing, right? And I need that translated into various languages and I get it translated. But as a result of that, I am leaking information. I am leaking my confidential, potentially information into the machine translation services. And there are some really interesting security issues around that and how you might be able to.

As a competitor, extract that back out. But just dialing it back for a for a minute, we understand the concept of leaking information by using public-facing machine translation, right? Publicly available machine translation. But one thing that I think is very often overlooked is that machine translation, the fact that I ask for a specific language, never mind the content,

But the fact that I am now asking for a new language provides competitive intelligence in the sense that that means that I or my organization now cares about that locale, that that language. So let’s say that I’ve been consistently submitting European languages for machine translation, right? If you but if you look at my record of what I’m asking for, you will see that all of a sudden, about three months ago, I started adding a bunch of Asian languages.

Well, what does that tell you about what I’m up to? Either I’ve decided that Asian languages are interesting and fun, or my organization, I mean, presumably I’m doing this for work and not fun, or my organization is launching into Asia. And I don’t actually need to see the content to sort of get that piece of competitive intelligence out of it. So essentially.

The way that I’m using the machine translation, even if we protect or have a contract that says you you are not allowed to look at what I’m processing, but if you can look at the parameters of what I’m processing, that might give you enough information to tell you something about what I’m up to.

AP: Yeah, so basically what you request or don’t request, as the case may be, can give away clues that you may not want floating out in the world.

SO: Right, exactly. So now we take this to AI and we think about digital sovereignty for AI, and it gets very much more complicated. So t first, taking this example of machine translation, if you think about AI chatbots and prompting and public-facing models, then in the same way that requesting a particular language so well, let’s back up.

Let’s say that we have a contract with XYZ model provider and it says we will not use your input as training data. We will not use your output as training data. Cool. But are you going to use my prompts as competitive intelligence? Because think about what I’m prompting on. Hey, tell me about the intellectual property laws in Vietnam.

Tell me about how to go to market in a particular country. Tell me about strategy for pricing tiers, right? If I’m doing those kinds of prompts, then you, as my competitor or adversary or whatever we’re dealing with here, can get an awful lot of information out of what I’m up to, right? You can figure out what I’m up to just by looking at my prompts. So we have to worry not just about the protection of the input and the output, but also the actual prompting that I’m using to get the inputs and the outputs, because the prompting itself has competitive information in it. So then when we start thinking about digital sovereignty, you say, okay, well, then what we should probably do is have a restrictions on usage of input, output, or prompting data by the vendor, right? The vendor who’s providing the AI model should have a contract that says we are now not allowed to use this stuff.

But then we take that another step forward. Nearly every contract I’ve seen in the past, you know, whatever years, decades says we promise not to use this unless we’re required to by law. So in other words, if a government subpoenas us, we will cough up this information as we are legally obligated to do, that sends us right down the road to something called zero data retention. Which is the idea that you process your AI prompts in such a way that they are not retained, that the inputs and outputs are not retained by the provider, so that if they are subpoenaed, they cannot in fact cough up the information because they don’t have it.

And then if you’re more paranoid than that, and some of you, you know, depending on what industry you’re in, should be, you start thinking about bringing the model in-house. So instead of using public-facing with a an enterprise contract of some sort, you think about bringing the model onto again, in-house on premises in the same way. This is right back to cloud versus not cloud.

And then we have some questions about what model are you using and do you know what’s going on in the internals of that model, which points you maybe at using something open source or maybe not. It depends. But there’s all these layers of decisions that you have to make around how you’re going to use AI and how concerned you are about leakage from your use of AI to you know your competitors or something else.

Now, over the top of that, we start thinking about nations rather than organizations. And we have some of this with just generalized cloud systems. GDPR, the European Data Protection Regulation, says a lot of things about how you process personal information and what the requirements are and what you are and are not allowed to do. Now

If you’re a European company inside the EU, you’re clearly subject to GDPR. But many non-European companies are also subject to GDPR because you have a server in the European Union, or you have customers in the European Union, or you operate in some way in the EU, which then that’s enough to have you sort of folded into GDPR.

On the AI side, we have something very similar going on where companies are looking at AI models and making decisions based on what jurisdiction does that model belong to. Now, the most prominent of these is that, for example, currently, as of right now, as we’re recording this, the American models, like a ChatGPT, a Claude, that kind of thing, are largely not available in China. and it’s a little bit tricky in terms of is it actually banned or is it just restricted, but broadly not available. The Chinese models are available in the US and are open source, but if I’m an American or actually, let’s say I’m a European company and I’m trying to figure out my AI strategy. Do I use an American model? Do I use a Chinese model? What happens if I’m using a Chinese model and then the US government bans that model in the US and I have operations in the US? And I’m suddenly now what?

In reverse, if I’m a an American company and I’m using American US models, and I have, let’s say, a chatbot, and I go to market in the EU. I am now subject to the EU AI Act. And the EU AI Act, with some complications for when it goes into effect, et cetera, has rules that say things like: if you put up a chatbot, you have to disclose that it’s AI. You can’t pretend that people are talking to a human. You have to say this chatbot is AI. This image was generated by AI. there are disclosure requirements in the EU. That are much more stringent than the disclosure requirements, which are none in the in the US.

AP: Yeah. In the US. And again, if you were making decisions about what model to get, where you should place your servers, etc., we highly recommend that you speak to your intellectual property attorneys and do not take advice from the two of us. Thank you very much.

SO: Right. This entire podcast is just an ad for IP lawyers. You’re welcome, IP lawyers.

AP To me, this whole thing is so interesting. You know, we talk about the digital world and globalization and you know, there’s no boundaries anymore. Guess what? They very much apply here because, like you said, if you have customers in the EU, and you may be a US-based company, but that does not give you clearance to absolutely ignore GDPR. So we still have to be aware of geographical boundaries and the laws of all the nations inside those boundaries.

SO: Yeah, the thing that keeps me awake at night is the question of what if I build out an entire thing on some model? It it kind of doesn’t matter which one, but I build an entire infrastructure based on some AI vendor and then and then that AI vendor gets banned by a government whose jurisdiction I or my operations are subject to.

AP: But there are significant costs.

SO: Right. And I’m not picking on any particular country. It it could go every which way that you can imagine. So then as a as an organization, especially if you’re a big international organization, you start thinking about well, maybe we should bring all this stuff in house so that we can control it.

AP: And infrastructure involved with that decision.

SO: Right, because now we’re talking about you operating your own data center, and that makes you, you know, not so beloved by literally anybody. So I mean, this is a really hard problem. And what’s fascinating to me is that we generally in software, software as a service, generally cloud has pretty much won with some minor exceptions for air-gapped systems, high security systems, network operations centers, or you know, software that runs utilities, that kind of thing. Things where you really, really, really do not want it taken down by external things. So you have this idea of secure systems, air-gapped systems, systems down at the bottom of a mine that are cut off because they’re literally down at the bottom of a mine.

AP: Yes, inside the earth, correct.

SO: We used to talk about airplane help, but that’s much less of an issue anymore because now, for better or for worse, we have Wi Fi on the planes.

AP: Yes.

SO: Mostly for the worse. Anyway…

AP: At least I haven’t heard a meeting yet, an online meeting. I’m sure it will happen at some point, but I have yet to see that happen. Thank goodness.

SO: On a plane? Yeah. Hmm.

AP: Yeah.

SO: So anyway. So cloud, the risk-reward for cloud versus on-prem has pretty much tilted towards the cloud systems in general, with you know, very specific kinds of exceptions for I would say unique use cases, but it’s kind of like a ninety ten or an eighty-twenty kind of split.

Back in the day, it was everything was on-prem and cloud was the exception, but it’s it’s very much shifted. And now with all this AI stuff, everybody’s using currently big picture. As everybody’s adopting AI, they’re using public-facing models, public-facing chatbots, maybe with like some sort of an enterprise license. But I just have this feeling that a lot of this stuff is going to be brought into in-house at least managed models.

AP: Exactly. Yeah.

SO: So still sort of cloud software as a service, but with a big enterprise contract wrapped around it that says, here’s what you you, the vendor, the AI vendor, can and cannot do with our data. But it’s a it’s just a really interesting problem because we in content we don’t deal with these sort of national issues that much, like sovereignty at the national level. And I think that with AI systems, we’re seeing a lot of concern around, well, what does it mean that this might be regulated differently in different countries? And how do we manage that? I mean, how do you put together an AI content ops strategy if you are not sure whether your model will be available in that country over there next week.

AP: Yeah, and I’m just thinking, think about audits are often a component of a contract, and you add AI on top of this, and all of the jurisdictional things you’re talking about, all of the facets of those audits just got even more complicated with AI than they already are, which that is probably a whole other discussion. Again, not a lawyer, don’t want to be, but I can see that being a very contentious something that’s gonna have to be ironed out in the very near future.

SO: Yeah, so digital sovereignty, it’s it’s very hard to say and even harder to spell. but I think that it’s something that we should be thinking about as content people and we should at least understand the big picture of what’s going on so that when we go to our corporate legal team and say, Hey, we’re worried about this, we can at least have a reasonable conversation about where this is going.

AP: And again, we don’t know where it’s going, but it’s definitely something to keep an eye on. This is a great place to wrap up. Sarah, thank you very much for a conversation that I frankly haven’t heard a lot about in the content world.

SO: Well thank you. Not a lawyer.

AP: Nor am I. Until the next time everyone, thanks. Bye.

SO: Bye everybody.

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What happens when you feed years of messy content into AI? In this episode, Bill Swallow and Alan Pringle dig into the content debt crisis, including increased system costs, neglected localization, and the fallout of “just use AI” mandates. They share practical insights to help organizations get back on track.

Alan Pringle: Is your content updated? Does it reflect the latest information? Is it created for all the different locales that your company serves? Is it in different languages? That is another pile of debt that when you start looking at AI, all the problems will be very brutally magnified, and you’re going to have to address them to really have a large language model that works at all.

Related links:

Balancing automation, accuracy, and authenticity: AI in localization (podcast)
Forbes: AI Costs More Than The People It Replaced
Taming AI: Using AI for content conversion at scale (podcast)

LinkedIn:

Bill Swallow
Alan Pringle

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

End of introduction

Bill Swallow: Hi everybody, I’m Bill Swallow.

Alan Pringle: And I’m Alan Pringle.

BS: And today’s episode is going to focus more on the content debt crisis, AI edition.

AP: And it’s also going to be the complaint edition, surprise, surprise, because there’s a lot of things in the AI world right now that are still making me cranky. And I am sure we will talk about them at some point.

BS: Yeah. So with the rise of AI, I think it’s kind of holding a microscope to a lot of the technical debt that we’ve been seeing over the years in content operations in general, whether you have outdated authoring formats or content that’s not being updated on a regular basis, new delivery formats not necessarily meeting the needs of the users, and so forth. And all of that is kind of compiling or snowballing into a bigger problem once you start feeding all of this stuff into AI.

AP: Right. And it’s interesting to me how everyone’s talking about AI as being this productivity tool. In a lot of ways it is, but that’s not what the focus of this is. In a way, it is also sort of a consultant for you. As you just mentioned, Bill, when you start looking at AI and delivering it, treating it as a delivery endpoint for your content, a distribution endpoint, you are going to start to discover that your processes on the back end for creating and distributing your content are not what they should be. So it’s kind of like this consultant saying, Hey, you need to do better over here. And that is where a lot of this debt is coming from, from my point of view.

BS: Mm-hmm. The unfortunate part of that consultant is that it’s not offering advice on how to fix it, but it certainly is pointing out the issues.

AP: It’s like, “This is screwed up. Full stop.” So, I mean, part of why we’re here is to talk about some of those kinds of debt. And let’s just start with one technical debt. And I’m saying technical in the sense of the way that you perhaps use software to put together your content. Let’s kind of focus on the content operations world.

BS: Mm-hmm.

AP: For example, if you are delivering content via unstructured desktop authoring tools, of which there are many, and you can templatize things and make your content seem more consistent, but there’s a problem with a lot of desktop published or content generated from the desktop publishing world. It’s more focused on look and feel and fit and finish, particularly if you’re delivering for PDF. And yes, people are still doing that. So there’s a lot of time and effort spent on that look and feel, that fit and finish. And frankly, that time should have been invested in adding intelligence to the content to explain, you know, things under the covers about what user is this for? What is the model of this particular thing? All of that kind of metadata, that kind of categorization. Desktop publishing, at least from my point of view, doesn’t really do a great job of helping you catalog that kind of stuff. So that’s a problem.

BS: No. It is a problem. Also, with desktop publishing, you can kind of confuse AI a bit if you’re using desktop publishing inconsistently. So if you’re using formatting tools to override formatting to make things look like headings or make certain paragraphs look like children of another paragraph, doing those manual finesses is great for print because, as you know, most people will look at that and understand the hierarchy of information, understand what’s going on with the content that they’re reading. But anything digital isn’t necessarily going to pick that up.

AP: Right. Yeah.

BS: Especially if you’re looking at something like bare bones HTML, if you’re using CSS to override the size and prominence of a standard paragraph as opposed to using a heading, that is not necessarily going to be picked up as a heading, even though a reader would actually see that as a heading while looking at the HTML page.

AP: Right. What a human reader can figure out from formatting cues, if those cues aren’t set up in a way that a large language model, a computer, can understand, there’s that huge disconnect, and that’s where that debt starts piling up. And then another angle here in this content creation world, if you are using multiple different tools to create your content, there’s a good chance that content under the covers is not going to be processed the same by a large language model. So there’s another deficiency right there on top of that. And this is very common, for example, if you have had mergers, acquisitions, and you’ve basically created a larger company from many different companies. And they all still have, especially in legacy content, things created the “old way,” and all the old ways start to pile up and cause problems because your large language model can’t properly basically figure out what is the heading in this particular chunk of docs versus what it is over here. So it can’t parse it as well. And again, this all goes all the way back to the way that you created that content. And it’s a clue, hey, you need you need to fix this. And I I think beyond that more technical, the way that you create it, there also there are also issues with the content itself.

BS: Mm-hmm.

AP: Is it updated? Does it reflect the latest information? Is it created for all the different locales that your company serves? Is it in different languages? That is another pile of debt that when you start looking at AI, it’s gonna be all the problems in regard to that are also gonna be just very brutally magnified, and you’re going to have to address them to really have a large language model that works at all.

BS: Yeah, because not only do you have the technical debt on the source content side and on the published content side, but you also now have technical debt growing on the AI side because you need to spend more time and energy refining the how that model works with your content in order to achieve the correct results.

AP: Right. So you’re having to do a lot of overrides and we I don’t know if overrides is the right word, but you’re having to do a lot of additional processing and figuring out so it will parse things correctly. And there are a lot of companies today that still have problems keeping content updated to the latest and greatest. So unfortunately, people turn around and call support. Or today they start hitting up the chatbot. But guess what?

BS: Mm-hmm.

AP: If the chatbot doesn’t have access to the latest and greatest because frankly it doesn’t exist or it’s not hooked up to it. It’s it’s just like the poor people in support. It’s not going to know what to do and it’s going to spit out probably very authoritatively wrong outdated information. Again, yeah, it’s be it’s goes all the way back to

BS: That’s yeah.

AP: In your content creation process, how are you accounting for updates? How quickly are you getting them in place? How are you handling them in both your source language and how are you handling them in your other languages? It’s one thing I do want to bring up here, and and and I may be biased here, but I don’t think localization is getting enough attention on the AI distribution side. It’s been talked about for a very long time in regard to machine translation, AI assisted translation.

BS: Mm-hmm.

AP: But I don’t just like I think sometimes localization is a second thought for a lot of companies, which still blows my mind in 2026. And by the way, we’re recording this in July 2026. So what we say right now may be outdated next month. Who knows?

BS: Who knows?

AP: There is that issue. I’m curious, you have a more of a localization background than I do, but I do see that being a potential debt problem, part of this debt crisis that we’re talking about here.

BS: Definitely, because if you’re pushing your content out to AI, do you have targeted audiences in mind? Or is it going to be a free-for-all of people going in and using that AI to get answers to their questions? if you are localizing your content, I think probably the best practice here would be to somehow bundle for consumption all of the guides in all of the different languages together. So you have product XYZ and you have it translated in three languages. Then you put all of those copies together and give that to the AI so it can draw its associations as well as it builds out you know its understanding or I hate to use understanding because the AI doesn’t understand things. It’s very easy to make slips in that way. But so that AI can actually draw those relationships. So, you know, if you’re looking in English or you’re looking in Spanish or you’re looking in German, the same query in those three languages will retrieve pretty much the same result. That’s proper for that language. And we talked with someone last year on the podcast, Steve Maule from Acclaro, about AI in translation.

AP: Yeah.

BS: And his focus was more on using AI as not so much a generative tool, but you know, a tool for aiding in AI, basically the next step from machine translation to neural machine translation to AI translation. And kind of the benefits and drawbacks at the time. Again, that was a year ago. So many of these things have probably changed again. But if you are translating content you may want to go back to that podcast and take a listen to what he had to say. and we’ll put a link to that in the show notes for this one.

AP: Yeah, again, I keep going back to this idea that we talked about at the beginning, how delivering via AI just puts this magnifying glass to what you’re doing and uncovers things that are wrong. But as you had mentioned, it doesn’t necessarily offer advice on how to fix it. And we will talk about that probably to wrap up the podcast. But what I also want to mention too. More and more, there’s actual real debt involved, not just the more indirect debt we’re talking about with the content debt, the technical debt. The AI companies, the providers, at one time had very generous offerings as far as the amount you could hit their APIs, the amount of tokens that they offered, whatever else.

BS: Definitely.

AP: But now, the days of I guess you could say subsidized token use, they’re pretty much over. And now the actual real cost is being passed on to the people using these large language models. And as a result, the actual price, the cost of using AI is skyrocketing in all these organizations. And there have been a lot of news reports lately about very

BS: Mm-hmm.

AP: And there have been a lot of news reports lately about very big firms, and I will not name names, but you know them all, their household names, basically having to do a 180 and tell their employees, hey, you need to chill a little bit on your AI use because you’re burning up the tokens, converting PDF files to PowerPoint. And yeah, I get it.

BS: Mm-hmm.

AP: Doing that conversion is probably not the most efficient use, productive use of AI tokens. But this gets into kind of, I don’t know if there’s such a thing as cultural debt, but if your company is sending this message, and a lot of companies are, use AI for everything. And you know, they’ve got these leaderboards up showing these people use this much AI this week, you know, that sort of thing. You are encouraging a free-for-all. So, instead of saying, here are the good uses, this is where we think you need to focus your use of AI in coding, in content creation, in whatever else, this whole idea of just use it. You got to use it a lot. And now that’s coming back and biting people in the backside. So companies are scrambling and telling people, calm down.

BS: Mm-hmm.

AP: Chill out. Don’t use the AI as much. So it, there’s a mixed message there. And it’s because there was not good communication, nor was there good thought put into how workflows should incorporate AI. And I think that cultural thing right now is a huge problem. And everybody’s focus on the cost and the non-subsidized token use when they need to be going back and looking at, well, look at your comms. Look at what you were telling people six, twelve months ago about AI. It’s kinda on you.

BS: Mm-hmm. Yeah, basically don’t let your nine-year-old run around in a toy store with your credit card.

AP: Yeah, pretty much.

BS: That’s pretty much what’s been happening. And yeah, we’ve been seeing lots of reports. There was one in Forbes last week, where, you know, companies are saying that the cost of using the compute power is more expensive now than the people it was supposed to augment.

AP: Exactly. So I think the reality of what AI can do maybe is starting to sink in, maybe a little, but at least exposing people to the true cost of it on a corporate level, it may

BS: Mm-hmm.

AP: I’m probably being too positive here. What? Me being positive? It may result in some recalibration about how companies are telling people to use AI and maybe thinking a little more on a cultural level, all the way starting with communication. Here are the workflows you need to apply AI to. This is where you can apply it.

BS: Mm-hmm.

AP: And then there’s also the whole vibe coding discussion. I don’t know how much we want to get into it, but we all know, right, there is now an industry, you know, people are now going in to clean up vibe coding because, yeah, just because you can vibe code shouldn’t mean doesn’t mean you should be vibe coding. Because who was going to maintain and clean up that mess? So again.

BS: Well, we’re cleaning up a lot of vibe coding now.

AP: It’s another cultural issue that should have been addressed, but in this AI rush, everybody was like, use it, use it, use it, without thinking about how they should really how they should really apply it and basically sort of reimagine the way they do work in a productive way. And that does not mean let the AI do everything from my point of view.

BS: Mm-hmm.

AP: So I guess we probably need to kind of wrap up and talk about what people can do when all of their ugliness is amplified and magnified by AI. And it really it’s about rewinding and going back and looking at from the start, especially in the content world and the content operations world, how are you creating that content? Are you doing it in a consistent way? Are you building in intelligence into your content that an LLM can pick up to better understand the context of that content you’re providing it? Is your localization workflow efficient? Is it getting content turned around quickly so people in other markets are not six or eight months behind in the latest and greatest information. And by the way, yes, that still happens today, believe it or not, that people are months out and getting it because they are in another location. It’s shameful, but it still happens. It does.

BS: Mm-hmm. Yeah. And there’s also, you know, how are you feeding your content over to AI? How are you providing it? Are you just having the AI team you know scrape web pages and PDFs, or are you supplying something that’s a little bit more targeted and tied to the content itself, and maybe supplies some of that intelligence over?

AP: Yeah, because I think Sarah’s talked about this on a previous podcast. A company was noticing that their LLM was kind of not using PDFs or not weighing them, or and I’m again I’m personifying big time here. my apologies.

BS: Yeah. It’s easy.

AP: Was yeah, was not really it was not giving the weight to the content in PDFs. And when the company kind of did some reverse engineering, they realized it was because that PDF what they didn’t have a lot of context.

BS: Mm-hmm.

AP: There wasn’t a lot of basically metadata built in that the LLM could basically parse. So it’s like, I’m gonna kind of put that to the side because it doesn’t have the richness that I need to do things well. So it it’s about looking at how you write. How are you delivering this content? And one possibility here, and it’s, well, there’s several structured content where you have metadata built into your content. You have tagging that offers semantic context.

BS: Mm-hmm.

AP: That’s one way to do it. And it’s not the only way. I mean, we have a lot of clients who use it, but it absolutely is not the only way to do it. Knowledge graphs can also be part of this solution. And sometimes knowledge graphs and structured content can play together to provide that rich feed of information that LLMs prefer and can do a better job with. So it’s not a one-size-fits-all solution when it comes to how to create that content or how to best hand it over to AI, but I think it is kind of a one-size-fits-all that if you aren’t doing things right foundationally, AI is going to kick your tail.

BS: Mm-hmm. Pretty much, yeah. And I think the best way to look at it is to consider AI another delivery target, just like you would a portal, just like you would a PDF or what have you, a help system. When you consider it as another endpoint for your content, another, you know, place to deliver to, it makes it a lot easier to start scoping what you need to do to reach, the requirements for that particular target.

AP: Agreed. So content people look at it as a delivery point and also look at as a job aid too to help enforce style guides, to help enforce taxonomy, whatever else. So it’s not just about content creation.

BS: Mm-hmm.

AP: It’s also that part of your thinking needs to be a content distribution point, like Bill mentioned. And it can be hard to think of it as both of those things, but in the content world, it absolutely is.

BS: And I think that’s a good place to leave it. So thank you, Alan.

AP: Thanks, Bill.

BS: And we’ll see you on the next one.

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There are five levels of maturity for AI-driven content operations. Which level are you in? In this episode, Sarah O’Keefe and Bill Swallow walk through the AI content ops maturity model, from ad hoc experimentation to fully autonomous workflows.

Sarah O’Keefe: We want this automation, right? We want the ability to go in and extract release notes and do something with them. We have to have a certain level of maturity on the software development process so that we can grab the appropriate information. The same thing is true on the content side. You have to have a certain level of maturity in your content development processes, in your content management, so that you can identify the right things to process and the right things to access.

Related links:

Want to know more about Sarah’s nifty little side project? Register for our upcoming webinar.
AI in the content lifecycle
Enterprise content strategy maturity model

LinkedIn:

Sarah O’Keefe
Bill Swallow

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

End of introduction

Bill Swallow: I am Bill Swallow.

Sarah O’Keefe: And I’m Sarah O’Keefe.

BS: And today we’re going to talk about AI in content operations, or more specifically, a maturity model for AI.

SO: Everything needs a maturity model, even AI.

BS: Even me.

SO: I have no comment.

BS: My maturity model is written in crayon, what can I say? So okay, so we need a maturity model for AI as far as content operations are concerned, and probably in you know, many different degrees, but we’ll focus on content operations. So what might that look like?

SO: I’ve been thinking about this and what it looks like to employ AI as a tool to help you with content. And as I was thinking about what this looks like, you know, you always fall back on that standard five-step model where one is basically mass chaos, and five is the perfect world, generally. also, one is nearly always cheap, and five is nearly always expensive enterprise things. But, you know, let’s go a little beyond mass chaos versus governed, regulated, etc., and sort of sort of back up a little bit and talk about what this might look like. So level one in every maturity model typically is ad hoc. And what that means is that in this case, AI is being used sporadically by some people. It’s inconsistent. And I would say that when we look at AI and content specifically,

BS: Mm-hmm.

SO: This is going to be things like reprocessing your content using public-facing models. So I wrote a draft of something, I shove it into ChatGPT and I ask it to shorten it or tighten it up or identify areas that are problematic. Or I just say, hey, you know, write my article for me. The outcome that you’re gonna get on an ad hoc model is going to depend on an ad hoc level one.

BS: Mm-hmm.

SO: AI thing is going to depend on how good you are on the individual’s expertise and their level of interest. So if you want to just go in there and say, hey, I have a bio and it’s too long, and I’ve been asked to produce one that’s only 50 words for a particular conference, for example, then, you know, this is this is actually a really good example of ad hoc, right?

BS: Mm-hmm.

SO: We have these long multi-paragraph bios and every conference I’ve been to has a different requirement for how that bio needs to be shaped. And the fastest way to success is to just shove it into a chatbot and say, give me a 50-word version. And and then read it and make sure it didn’t invent things or give you a PhD or anything like that, and then ship it off to the conference organizer. But this is much, much faster than rewriting it from scratch by hand. And also I think, it’s a good example of something where I have the extended version and I’m going to summarize down. And that usually works pretty well. So level one is ad hoc. It’s kind of sporadic. There’s no standard across the organization. It’s just me saying, this looks useful, or you’ve probably got some use cases in this space as well.

BS: Right. So it it kind of aligns with I guess level one of the the content maturity model that we talked about a while back, where level one is is simply content exists. Could be, you know, someone typing stuff up in Word or, you know, using a myriad of different tools, no style guide, just kind of getting content out there because people need it.

SO: Yep. So level two is tactical. And tactical is sort of like we’re using this tool to solve some specific problems. And what you’re going to see here is something like that Bill has invented some nifty time saving tool and he has shared it with other people. Or in a larger organization, maybe somebody invented a nifty validate or or something like that and they’ve rolled it out across maybe the department, probably not the entire organization. Aomething like AI support is being rolled out. Maybe the organization has created a chatbot internally for customers, right? So there’s a chatbot, it’s sitting on the company website, people can use it to get answers, but it’s really bad. And the reason it’s really bad is because nobody thought too carefully about the content going into the chatbot, because again, we’re tactical. So probably this looked like the AI team just raided the local SharePoint, grabbed a bunch of content, did not pay a whole lot of attention to the question of whether this content was up to date in release status. Those things don’t exist, right? It’s just, look, a bucket of PDFs. Cool. Let’s dump them into the AI and go for it.

BS: Mm-hmm.

SO: And tragically, in many cases, the techcomm team is sitting on rigorous, structured, vetted, approved content, and nobody remembered to go ask them, can we have your content? Or where is your official content source? Or how do I know what version belongs with which document?

BS: Right, because you know, in in their point of view there’s a PDF of it, so I don’t need to ask them.

SO: Yeah, it’s it’s just PDF. How hard could it be? So something like AI was support was rolled out, but nobody really thought about it. Maybe it’s at a departmental level, probably it’s not enterprise-wide. And nobody has really thought about connecting this AI thing to the assets inside the organization in a reasonable, rigorous, governed, organized kind of manner.

BS: And I suppose that’s where you get to the next tier.

SO: Right. So the next tier after tactical comes strategic, right? So we have an actual strategy. Now, one of the difficulties in talking about AI is that AI is a tool and it’s kind of like talking about electricity. You can apply it to lots of places and it’s more sensible in some places than others. But when we say what’s your AI strategy, like how do you use water? I mean, come on, and the answer is of course to drive the AI and you know destroy the environment. But there are things that you can do with AI that are useful for content. There are also things that you can do that are not. So if you have a strategic approach to this, a strategic approach to use of AI, backing up to the authors again rather than the delivery side, maybe this looks like a collection of prompts that have been built that are shared.

BS: Not with electricity.

SO: Maybe this looks like saying this is the workflow that you employ. These are the kinds of things that we do to actually test whether this thing is working. these are the metrics that we’re following. So there’s an actual overarching bigger picture that somebody’s thinking about that goes beyond, let me go shove this into chatbot of the day.

BS: Mm-hmm. Right, right.

SO: So there’s an actual strategy for the public-facing chatbots. Somebody has thought about the back end. The authors have useful AI tools that add to their you know their productivity. One of the things that I’m hearing a lot now, you know, low-hanging fruit, release notes. Nobody wants to write release notes. It’s a terrible drudge task. It’s and it needs to be done. Well,

BS: Mm-hmm.

SO: There’s now there are now a lot of solutions that look like look at the diff in the code, look at the delta from you know version one to version one dot one, find the diff in the code, find the changes that have been made, look at the JIRA tickets that have been addressed, that have been solved in release one dot one, and then consolidate that all into a set of release notes that say, here’s what’s been done. And that’s probably 90% of the work, and the last 10% of the work is read that and make sure it’s accurate. Right? Don’t please don’t skip that step. Like actually look at what the thing is generating. Now, what’s interesting to me about level three, this sort of more strategic approach, is that what you’re gonna start to see is that you have prerequisites for this. You can’t do this.

BS: Yes.

SO: So release notes are good example. Let’s say that hypothetically, and this is gonna sound insane, but let’s say that hypothetically, you have software development and you have no source control.

BS: Hmm.

SO: Everybody’s screaming, right? Because this is nuts, and why would you ever do this? Okay. But hypothetically, you have no source control. Okay. How do you know what’s changed between version one and version one point one?

BS: It’s up here in my head.

SO: Excellent, great. Ha okay, cool. so I’m gonna need to connect the AI to your head so that we can pull those changes out of your head.

BS: That sounds fun.

SO: Yeah. Amazing. Right. So all of a sudden, because we want this automation, right? We want the ability to go in and extract release notes and do something with them. We have to have a certain level of maturity on the software development process so that we can grab the appropriate information. Now, the same thing is of course true on the content side. You have to have a certain level of maturity in your content development processes, in your content management, so that you can identify, you know, the right things to process and the right things to access. And why it is that, you know, we know that software has to be governed, but we’re not so sure about content is a mystery to me.

BS: I had never understood that.

SO: Yeah. So there we are. Okay, so that’s kind of like a level three. With there’s some sort of strategy emerging across the enterprise. There are some useful tools and they’re shared. This is kind of like in content when you start thinking about templates. We’re gonna have some templates and we’re gonna give them to people and they’re gonna use them and it’s gonna be great. All right, so level four is governed, managed. And so now good understanding of AI.

BS: Mm-hmm.

SO: It is being applied in a useful, intelligent manner, by which I mean don’t apply it to the wrong problem sets, right? Apply it to the things where it makes sense to apply it. Thinking about governance, thinking about metrics, thinking about success. And then your data sources and your content sources are being managed in such a way that the AI gets good input and can actually generate good output. So I’m actually not a big fan of the term human in the loop because human in the loop implies that the AI is doing all the work and then like the human eventually gets around to QAing it. You know what? We’re terrible at QA. You know who’s good at QA?

BS: Mm-hmm. AI.

SO: No, computers, not AI. AI is all about probability and whatever. It is actually not very good at QA. What’s good at QA is traditional software, right? One plus one is always two. In an AI, one plus one, sometimes it’s not two. So you manage that stuff and you put those guardrails up and you start putting up the guardrails that say, okay, when the AI kind of wanders off into the wilderness, we’re gonna like bring it back to reality. We’re gonna have, we’re gonna put it in a box, right? Make the AI think inside the box, and we’re gonna govern what that box is. AI is great at thinking outside the box. Unfortunately, that’s usually not what we want from technical content. So it needs to be in in the box and it needs to be consistent and needs to be managed and all the rest of it.

BS: Mm-hmm.

SO: So we govern it, right? We go in there and we make sure that the processes and the tooling that’s being put in place and the automation that’s being put in place where we’re leveraging or using AI to do things is managed. And so the human in the loop thing. I don’t want the human in the loop to fix things on the back end. I want the human in the loop to fix things on the front end so that what goes in is better, so that there’s less work to do when it comes out. You know, fix it beforehand. Don’t remediate it afterwards. That’s a boatload of work and it is not fun. So fix it ahead of time.

BS: Right. Yeah. And likewise you probably wanna have, you know, some guardrails in there so that, you know, your AI, whatever it is, doesn’t go playing around with content that has been approved and released and is not slated for updating.

SO: Yeah, you know, don’t fix that. That one’s done. That one’s and you know, we’re not even talking here about what it means to be in a regulated industry or in a regulatory environment. there if you are shipping or sorry, if you are a large organization and you are doing things in Europe, then you are likely subject to the European, the EU AI Act.

BS: That’s a completely different beast.

SO: And you have to think about what that means for what you’re doing, because the fun gold rush wild, wild west strategy of just throw AI at everything is not gonna fly in Europe. Okay, so that’s governed, you know, hypothetically. And then level five is agentic, which is basically that everything, everything or a lot of it is running autonomously.

BS: Mm-hmm.

SO: You know, the layman’s explanation of what is agentic AI, the difference is that instead of saying I need to put a prompt into the chatbot, it does it itself because you’ve built out the systems that drive all of that happening.

BS: It understands what needs to happen at what point in time.

SO: Well, let’s not say understands, but yes. I’m trying so hard.

BS: Well, yeah, not understands, but there’s a workflow in place that the AI is following.

SO: And it’s so difficult. I think that, you know, there’s, as a side note, the why do we think, why do we impose personality on the chatbots? And the answer is I think that psychologically it’s very, very difficult to interact with something that play acts at human interaction. What a great idea! Good for you. I love your thinking, blah, blah, blah. So it makes you think you’re interacting with a human. And I don’t think that our brains are equipped to say, no, actually, this is a machine.

BS: It’s like a scary version of Teddy Ruxpin.

SO: It, well, it passes the Turing test. And so we just can’t separate if it feels like you’re interacting with a person, you know you’re not, but it feels as though you are, and feeling is always gonna win over knowledge. So

BS: Mm-hmm. Well yeah, the interaction is a lot more organic than you get from, you know, traditional tools.

SO: Or, you know, yeah. I mean, think about the difference between a search, typing in a search string, and you know, a conversational search, a conversational interface. It’s quite, quite troubling, actually. Yeah, so this is kind of the five-level model, right? From big mess ad hoc, some things are happening, th some things aren’t, up to it’s completely autonomous. Now, if it’s going to be the more autonomy you want, the better your inputs have to be, which circles us right back to, and therefore, you have to do the work on the content side, because if you don’t do the work on the content side, the AI is going to go off the rails in interesting, unexpected, and potentially disastrous ways.

BS: It will play with the mess you leave it.

SO: Yep. So that’s where we’re going with this. That’s the AI content ops maturity model as it stands today. I reserve the right to change it tomorrow.

BS: Today. Of course.So this model came out of I guess some little nifty side project you’ve been working on recently.

SO: I am working on a nifty little side project. We’re not quite ready to announce it. but I’ve got a a co-author and we’re working on a thing.

BS: Fair.

SO: I could say more but then I’d, you know, be in trouble.

BS: When might you be able to say more?

SO: I believe that we have a webinar coming July 22nd, where we will say some more things.

BS: Alrighty. Well we will learn more things then.

SO: I too will learn more things and probably we’ll have to we’ll probably we’ll have to change everything we’ve done up until this point because everything will change by then.

BS: Of course. Guess that’s a good place to leave this podcast. Thank you, Sarah.

SO: Thank you.

Want to know more about Sarah’s nifty little side project?Register for our upcoming webinar.

The post From ad hoc to autonomous: The AI content ops maturity model appeared first on Scriptorium.

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How do you really choose the right documentation tool? In this podcast episode, Sarah O’Keefe (Scriptorium) talks with Paweł Kowaluk and Michał Skowron (Guidewire Software) about building a successful tool selection process, the realities of docs as code, and what happens when the technology becomes the unpredictable variable.

Paweł Kowaluk: It’s funny how programming used to be deterministic, and it was the people who were messy. We always knew that people are going to be whimsical and maybe harder to rein in, but the technology is going to be predictable. Whereas now, technology is not predictable anymore, and you give it a prompt and you hope it’s going to do what you want. You adjust the system prompts and change the weight of things which are retrieved versus metadata, et cetera, and it doesn’t always work the way you expect it to.

Sarah O’Keefe: And now the people are being asked to be the deterministic layer, right? To be the QA on top of the AI.

Paweł Kowaluk: That’s actually very insightful. I like that. That is true. The human in the loop or whatever you call it, that’s supposed to be the voice of reason.

Related links:

Scriptorium: AI in the content lifecycle
Tech Writer Koduje podcast
Tech Writer Koduje: DITA as code – a modern approach to the classic standard
Tech Writer Koduje: Are people abandoning docs as code?
Tech Writer Koduje: A tech writing CCMS can also be a broken promise

LinkedIn:

Host: Sarah O’Keefe
Guest: Paweł Kowaluk
Guest: Michał Skowron
Tech Writer Koduje LinkedIn profile

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

End of introduction

Sarah O’Keefe: Hey, everyone. I’m Sarah O’Keefe, and welcome to the podcast. In this episode, we are going to talk about tool selection with a couple of special guests. With me today are Paweł Kowaluk, who is a software architect at Guidewire Software, and Michał Skowron, who is a documentation tools developer, also at Guidewire. Both of them are based in Poland. Welcome.

Paweł Kowaluk: Hi.

Michał Skowron: Hello.

SO: I am glad to have you. For those of you on this podcast that speak Polish, you’re probably already aware that they have the one and only techcomm podcast in Polish that is available out there, and Michał and Paweł are also experts on doc process and tool selection, so that’s what we wanted to focus on today. So I will start and throw it to Michał and ask you the big picture question, which is what does a good tool selection process actually look like?

MS: For me, good selection tool process would be divided in three stages. The first one would be gathering requirements, looking what’s out there, defining what you want to basically achieve with this new tool. Then I would go to a pilot project where you can actually test the selected tool in the real world. Manufacturers and producers of software will tell you that it can do anything and it will promise that, “Okay, you can meet all your requirements easily and we can fix that, we can improve that, we can adjust that,” so everything can be done is usually what we hear, but then you want to test it in real world on a real project, so that will be a pilot project for you and your team.

And the third phase that depends on the outcome of the second phase, which is you either productize the selected solution or you just say, “Okay, that was a bad choice and we don’t need that.” Then we need to go back to the first stage and then say, “Okay, we need to select another tool,” and again, requirements, et cetera, et cetera. So for me, that’s the whole process, and the first stage would be probably the longest one because you need to make sure that you are meeting all your goals.

SO: So what’s the most common reason that a pilot doesn’t succeed, that you have to go back and say, “That didn’t work. We have to try something different”?

MS: It’s usually because you didn’t see everything when you were planning. For example, you have some projects that are very specific or you didn’t see all the problems or things that are coming your way. It’s hard to say exactly what the reason is, but it can be multiple reasons.

For example, using of, I don’t know, branching, let’s say, in a specific tool. When you have multiple versions of your product and you want to keep them separate when it comes to documentation, it can turn out that the feature says, “Okay, you can use branching and then you can do it easily,” and then you start using it and it turns out that it doesn’t work the way you expect it. This is actually a real life example because we had a system that… I’m not going to mention any names or anything like that, but there was a system and they promised us… That was years ago and it was a vendor that promised us that they’re going to introduce a feature called branching, and it turned out after they did that that it wasn’t what we expected. So it can turn out in many cases, in many ways, it can be the problem, but branching is just an example, but it can be many other things that can go wrong.

PK: Hey, if I can jump in here, I got a couple of examples. One is I could call it releasing strategy or versioning strategy overall, which is very hard to test in a pilot project. It’s very hard to scope for requirements because the little problems come out after a while, after a year of publishing, after two years of publishing. And another example which is related is reuse, and this one is down to formulating the requirements correctly. Because I think just saying, “We want to reuse something,” is not enough, because you have to say exactly what you want to reuse and how you want to reuse it and what you want the result to be.

So for example, if you say, “I want to reuse notes and warnings and things like that.” We sometimes call them admonition. So, “I want to reuse these notes in my docs, and if I update a note, I want it to update in every published version of the doc.” Then only if you have these details, like I want to update it once and then want it to automatically update and publish docs, then you will see it’s not working the way you expect it. Because if you just say, “I want to reuse notes,” every system can reuse notes. Even in docs as code, there’s scripts and macros that allow you to reuse notes.

MS: It can be also another thing that, for example, you compare the benefits with the actual cost of implementation, and it can turn out it’s not worth it because people are, for example, reluctant to use your new tool. The training, the cost of licensing, the cost of support is too big, and then you realize, okay, we want to achieve a goal like, I don’t know, reduce the time to market, and then it turns out it doesn’t work because people are struggling with using the product on a real project. And on paper, everything looks cool and you have all these features, you can use them, like Paweł mentioned, for example, reuse conditional formatting and things like that. And then it turns out it’s very hard to use, it doesn’t serve its purpose, and then you have to pay for every additional stuff and people don’t want to use it, so what’s the point?

SO: Yeah. And I think we find that the technical problems in general, if you’ve done your requirements work, then usually, the technical problems are solvable if the people engaged in the project want to solve them, and that’s where you run into the change management issues that you’re talking about, that if the team that is being asked to pilot, to test, to try things out is sufficiently disinterested in making it succeed, they will find a way to make it fail. And the reverse is true as well. If they want it to succeed, you can implement tools that are … Well, all tools are imperfect, but you can implement tools that are not perfect solutions and succeed if the team is behind you, and if they’re not, bad, bad things will happen.

PK: Oh yeah, that’s true. And I’ve been on projects where we did not do proper change management and I’ve been on projects where we really did it well. If you start early and you involve people, like get the biggest troublemakers, people who are the most opposed to any change, get them on the team, and if you can convince them, that means, one, you are making the right choice because you’re convincing people who are skeptical, and then two, you are set up for success. These people are going to be your biggest champions of the new solution.

MS: But it’s good that you mentioned it because I think it’s worth emphasizing that the goal of the pilot project is not to succeed. That’s not the actual goal. The goal is to verify the requirements against the real project, and so the failure is also a success to some extent. It’s not like you have to do everything to prove that the selected tool is the right one. No, you should be aware that the pilot can end up with your let’s call it failure, and then you realize that it’s either a bad choice or you don’t need that at all. For example, you don’t need that tool at all. It can be also the outcome of the pilot project. So there are many different outcomes, so don’t be fixated on the success path that is the only right way. It means, okay, the pilot project was a success because everybody agreed that that was the right tool that we want to use, so keep it in mind.

SO: Yeah. I think that there’s … I got into actually a debate with somebody about this. They were telling me that pilot project, proof of concept, and what was the third one? Prototype are not the same thing. Okay. Well, so a pilot project is, “We think this is the right answer and we’re going to try it small and then we’ll expand.” A prototype is, “We’re just going to try it and throw it away,” and a proof of concept is, “We think this is the right answer, but we’re not sure and we’re prepared to throw it away.” And I thought, “This is way too specific for me, but okay, sure.” But to your point, the project, whatever category it belongs in, has different purposes, and it’s important to be clear about what kind of a project is this? Is this essentially beta testing, this is step one, or is this more speculative? We’re just really, really not sure.

PK: I think it has to be falsifiable. Like they say in the scientific method, there has to be a failure criteria somewhere. This will fail if ABC happens, because if you don’t have that-

MS: Or a success criteria, right?

PK: Or a success criteria, but I’ll be more focused on the failure criteria because you can always show, “Yeah, we accomplished this, 30%,” but if your failure criteria is below 50% is fail, then you will say, “I failed this.” You fail five out of six and the project is a no-go.

SO: So I wanted to switch gears a little bit and talk about some specific tool chains and problem sets. I think it’s fair to say that the two of you are, I’m going to say mostly but not exclusively, focused on docs as code, so what does that look like? And there’s a lot of debate about docs as code versus structured content and they’re very much pitted against each other, but ultimately, what’s your perspective on the situations where docs as code is appropriate or maybe is not appropriate, and what do you look for in a project or in a problem set that matches the docs as code model?

PK: I think the reason people associate us with docs as code is the last eight years, we’ve been working at Guidewire and that’s the strategy we’ve chosen there, so I think we’ve been entrenched in this worldview. My previous job before Guidewire was a consultant, and I would go from a company to company and set up different systems for documentation. That was my specialty, systems for publishing and updating documentation. So yeah, circling back to your question of when it works, when it doesn’t, I guess docs as code is more about it works when the right mix of people are creating the docs and the mix of people includes software developers. So for example, at Guidewire, we have several dozen static websites which are maintained by software teams without any technical writers involved, and those are a variety of internal tools, tools which are almost external, and then tools which go out to customers, and all of these little websites integrate very well with our publication system.

And I think this is the main criterion for docs as code fitting is you are giving tools for writing to people where they work. So software developers work in code. You give them tools for writing in their codes so they don’t have to buy extra licenses, get training on anything external, use some alien process, alien to them, just because they follow SDLC, the software development lifecycle to update their docs. And it’s what they’ve been doing, and then it’s easier to convince or it’s easier to fit in a smaller team of technical writers, I don’t know, like 40 technical writers versus 2000 software developers. It’s kind of everyone contributing to the same documentation system. It’s easier for the tech writers to adapt and join the docs as code platform than the other way around.

MS: Just like Paweł mentioned, docs as code makes sense in certain environment. It’s not like we are tribal about it. We love this solution because it works for us. So after a few years at Guidewire, we realized that this is the way we want to go, because as I said, it makes sense and it just works. We tried different things before, and before I joined Guidewire, there were different solutions. We used, for example, CCMS and we had more a traditional approach to producing docs, let’s call it this way, and then we started building our own pipelines, our own solutions. We started integrating with what was there that other devs used for their work, not related to documentation, but we decided, “Hey, maybe we can use what’s out there and just plug into the same infrastructure.” So as I said, it’s not for everybody, it doesn’t work in every environment, so I wouldn’t say, “Okay, if you’re in a factory, you should use docs as code.” No, I wouldn’t say that. So maybe we positioned ourselves as docs as code proponents, let’s call it this way, but this is because we use it every day, we build it, and this just works for us. And also maybe I can mention that we decided to end this holy war by putting DITA into Git and CICD pipelines, so we have DITA as code, and now everybody’s happy.

PK: Oh, this is actually a great point because Sarah, also mentioned docs as code versus structured. Now we’re doing docs as code in a structured way, and where technical writers are working on the docs, they are free to use DITA and a lot of teams do that with all the reuse and all of that, but even if it’s something simple like some markdown files in a repo, we still impose a metadata structure which allows us to integrate the doc into our publishing pipeline, and the two key aspects of what we’re integrating with our authentication and search, and that needs metadata, right? It needs to know who has access to this content and it needs to know how to filter and direct the searches, and from that, our next project emerged. Like everyone else in this industry, we started working on AI solutions, and the AI solution is a third integration point where this structured approach to content also pays off.

SO: Yeah, I did want to touch on AI and so we should probably just jump to that. What are the implications that you’re seeing? What are the effects that you’re seeing on your current processes of the use of AI or the requirement to deliver to AI, and how do you see that working?

MS: Paweł, you want to start?

PK: Yeah. So the content remains the same that we’ve been working on for years, and the structure, the metadata is all the same. We could not change this overnight, but overnight, we had to introduce this AI which is going to look into the content, find the topics, the chunks we call them. It’s going to find the right chunks of documentation and generate answers based on those chunks. So what happened is we had to adjust the AI, but since we were so structured, it was pretty easy, and then we gained a new source of feedback from customers through the AI. Because when people started using our chatbot, we built a chatbot which is available on docs@guidewire.com, but it’s only available to customers and partners, so you need a login on the website.

When you go there, the AI answers questions, and then we monitor the exchanges that people have with the AI and we see what needs to improve as far as content ingestion, as far as content structure. We generate a lot of internal tickets to our tech writing team and identifying gaps, because we’re seeing now that this AI interaction is possible, here’s what people are asking of the content. And other people are asking, “How do I implement X, Y, and Z in the scenario where ABCD?” Which we didn’t know people were looking for before because they had no interaction with the docs. So they just come to the website, they either find or don’t find what they need, and we don’t know anything about that, and we could ask them, but we’re just going to ask a small group of people, whereas now, it’s as if we’re asking everyone.

So we’re seeing these new patterns and something emerges out of those patterns, like everyone’s asking for code samples in this specific area, so we go back to the team and we work on adding more code samples, or people are looking for illustrations of these particular workflows, so people create these illustrations. It’s amazing how rich of a source of feedback this has become.

MS: And it also adds complexity to even testing all the solutions that we have right now, because with keyword search, I’m not saying it was easy because it wasn’t easy, but now we have another layer where you have this middleman, let’s call this chatbot, let’s say. It’s a middleman that can hallucinate, so you can either have a problem with your content or you can have a problem with the agent that responds. So before, when you had a keyword search and you were missing results, you were going usually to the content and see, “Okay, I’m missing this topic. It wasn’t indexed properly, or I just need to move some knobs in my search engine and just see the fuzziness or something like that.” And now you have this content, it’s being processed by this AI tool, and then it gives you some answers and you don’t know why the answer is wrong. Because it didn’t find the content? Because it’s not there? Because it’s not the right content? Because the content is right, but there is something that it missed? There are so many moving parts right now, more than before that it adds complexity to our job, and this is just one side of it.

The second thing is writers using AI for creating content, and we’re also exploring this path because everybody’s trying to incorporate AI solutions into their work. We code mostly on a daily basis and we use some tools that help us with coding that are AI-based, but we also want our writers to benefit from all this development in technology, and we’re exploring, let’s say Oxygen, XML, Positron. Just to clarify, we’re not sponsored anything. We’re just using it so I’m just mentioning the name specifically, but even if you don’t have any specific tool for writing that integrates directly with a AI tool, you can still use, let’s say, Copilot or any other solution that you like and you can just ask it to help you with the content, but it comes with a lot of caveats.

It’s not like you just throw a prompt and just get what you need. It involves a lot of fine-tuning, a lot of working on instructions, giving it context, giving it information that it needs to use for producing code or docs. Because I use it for both, for coding and for documenting, for internal purposes mostly, but it takes time to make it work the way you want it.

PK: Yeah. It’s funny how programming used to be deterministic and it was the people who are messy and the processes, and working with setting up the process for the doc tools, we always knew, people are going to be whimsical and maybe harder to reign in but the technology is going to be predictable. Whereas now, technology is not predictable anymore, and you give it a prompt and you hope it’s going to do what you want. You adjust the system prompts and change the weight of things which are retrieved versus metadata, et cetera, and it doesn’t always work the way you expect it to.

SO: And now the people are being asked to be the deterministic layer, right? To be the QA on top of the AI.

PK: That’s actually very insightful. I like that. That is true. The human in the loop or whatever you call it, that’s supposed to be the voice of reason.

SO: I don’t know about you, I’m not good at voice of reason. I’m much better at causing trouble. So what you’re describing is a fairly complex and time-consuming approach to this in that you’re saying we have this AI chatbot and we’re looking at the metrics and we’re adjusting accordingly and making changes, and then using the AI on the backend for some productivity kinds of things, but not as a replacement. We’ve seen in the US and in North America, we’ve seen a significant number of people losing their jobs because the idea is that, oh, the AI can just do it, and what you’re describing is not that at all. So are you seeing any of this sort of, “Oh, this will make us more efficient, and therefore, we need fewer people,” or is it a different perspective in your piece of the tech com world?

MS: I’m aware of all the layoffs and of all the bad things that are happening right now in the IT world, let’s call it, because it’s not only technical writers because it’s also developers and different jobs, but I think I’m still in this kind of a bubble right now where it’s not happening directly next to me so maybe I’m being too optimistic. But I keep saying maybe I’m going to eat my shirt after some time because I keep saying, “Show me one tech writer that doesn’t have a backlog that is not too long.” So we usually have too much work, and I hope that with the right approach and with a sensible management, these AI tools will be doing all the things that we don’t want to do or we don’t have time to do, and then it will give us time to do something more and something more significant.

I’m looking at my job and I’m not saying it’s perfect because of AI, because it has so many challenges right now and it gives you different problems, but I can see that I can speed up my cumbersome tasks very, very easily. And before, I had to … This is a simple example, and I’m doing a lot of infrastructure work and a lot of backend work, so many things go wrong, and very often, I had to debug difficult problems. It was taking me weeks sometimes to nail the actual place where it happened. Now, I can do it much faster. If I have to debug a problem, it takes me, I don’t know, an hour, sometimes even minutes, and I know that I would spend a day, two, or even a week if I didn’t have these tools. But these are good examples, but there are also a lot of bad examples, but I don’t think we have time for that.

SO: We’ll take the optimistic view.

PK: Yeah, I agree with Michal. The approach we have is these tools can give us tremendous productivity boosts, but not in the sense of getting rid of people. We can redirect people’s work to where it’s more meaningful. And what I mentioned about feedback, identifying these content gaps. Some of these content gaps are going to be very mechanistic and you solve them by generating a bunch of docs out of code, for example, and then you put those docs in the repository where the chatbot can find them, because they’re not going to require a lot of thinking. It’s kind of like API docs where you create the swagger spec and then you generate the dogs out of that. You just grab the source code and you generate some samples, and you use that to generate answers to people. Without people, this wouldn’t work because you need, like we said, the voice of reason, but yeah, people are still required in the process.

SO: I think that looking at it across the industry, if you take AI, take a chatbot, especially a public facing chatbot, and ask it for answers on literally anything, it will give you the average of what’s out there in the world because it’s math, so it gives you the average essentially. And so from a content creation point of view, I think the fact of the matter is that there is in fact a lot of below average content out there. Roughly half is below average, or perhaps exactly half.

If the information is bad enough, if the content being produced is not of high quality or ungrammatical, and we’ve all seen terrible, terrible documentation that was badly translated and is just incomprehensible, then the AI as a tool for creating content may be able to produce something that is better than terrible. It’s not going to replace a professional, well-trained, highly experienced and knowledgeable product documentation group, or it shouldn’t, but that’s not every company. Not every company has a really good group of tech writers that understand the product and are adding value as they produce the content that goes with that product. And so I suspect that what we’re going to see is a split with commoditization on one end, just auto generated, it’s not great but it’s adequate maybe, and then the higher end stuff, which needs to be done well.

PK: Well, there’s definitely documentation which only exists because it absolutely has to, and companies like that can easily generate just some kind of documentation and just use it, right? But in cases where … I think the worth, the value of a technical writer is not just writing and generating the content from below their fingertips. It’s more about the research and understanding, like you said, understanding the needs of the users and understanding how to meet them. You throw AI at a problem which sounds like a generic problem, it’s going to give you a generic answer, not necessarily one that is rooted in the organization you’re in. The list of products that you have, the way those products interact with one another, it’s going to miss all that.

It’s just going to give you … It’s like ordering a hamburger and you say, “So what’s in the burger?” And the AI is going to tell you, “Well, usually in a burger, it’s a patty and lettuce.” And it doesn’t mention that at your restaurant, you use pear and avocado. It doesn’t know that. You know that. You’re the chef back in the kitchen and you know why your burger is special.

SO: Yeah, I think that’s right. So I did want to touch briefly on the question of, because this is a rare opportunity to talk to some folks that are not based in the US or North America, what differences, if any, do you see in tech writing in the market? Now, you’re based in Poland but working for a, I think, US company, but what kinds of things do you see that are maybe different that especially the people listening to this in the US would not be aware of coming out of Eastern Europe?

MS: For me, always, it was the fact that tech com appeared much later than in the United States, in Poland of course, because I’m not talking about Europe in general because there are also differences between countries in Europe. For example, Germany is totally different from I would say the Polish market, because in Germany, you usually have factories and you have technical writing associated with hardware, let’s say.

SO: Yeah, heavy industry, machinery.

MS: Yeah, heavy industry, that’s right. And in Poland, it’s very often about software, maybe because we have a lot of companies that outsource to Poland when it comes to software development, R&D and stuff like that, so that’s the first thing. And don’t get me wrong, people were doing tech com way before it appeared in the mainstream, but sometimes they were not even aware that this is called technical writing or technical communication. Actually, it happened to me because I moved to techcomm from some kind of IT support job, and then after a year, I was like, “I’m wondering if this is anything regulated or there are some rules or it’s actually a profession.” Then I started digging and here I am.

But it turned out there are so many things, so I was also surprised. Okay, this is called that. These are standards. There are books. Well, actually, one of the first books that I read was your book, Technical Writing 101, which I’ll still recommend, although it’s been years since it was published the first time, but I think it still holds a lot of truth about techcomm. The core values of techcomm are still there. So going back to your question, the techcomm scene is relatively young, let’s call it this way, in Poland, which gives us a big opportunity to skip some stages, let’s say. So we don’t have the legacy, we don’t have some things that we used to do a certain way and we like it or we are just accustomed to it. We can just start fresh and just jump. In 2000s, we just jump into techcomm and we say, “Okay, let’s do it this way because now this is the way we do it.” And I think that people are flexible when it comes to looking at things a certain way. Not everybody because there are also people who don’t like changes.

But I think also what is unique about Polish techcomm scene is it’s relatively small, so if you do something outside your work, you don’t treat your job as only a means to earn money and just survive and you want to do something else, let’s say just write an article, like give a presentation, go to a meetup. After a year or two, you just keep meeting the same people, you know basically everyone who is in the circle, so it’s much easier to be visible if you do something outside your work. So I think that would be something unique about our techcomm scene.

PK: I think what might be a downside of the Polish techcomm scene is a lack of veteran experts, because we don’t have people who have been doing this for 40 years. I’ve been in the industry for 18 years.

SO: But you do understand that you two are the veteran experts.

MS: That’s what he’s trying to say, that-

PK: I’m getting to this. So yeah-

MS: Imagine that.

PK: Putting on my clown makeup every morning. What I mean is there’s nobody to look to who wrote the book on technical writing and has been there for 40 years. I’ve been here for 18 years doing this thing, and out of the people who are visible publicly and who contribute to the scene, I don’t know if there’s anyone who has more experience than me. Because I know there are people who have more experience but they’re just not visible. They don’t share their knowledge with anyone, and we miss that, so that’s why we look to the West, to people like you guys, like Scriptorium, and we read books which were created there and we see there’s definitely value, even though something is as old as the scene here or older.

MS: And people also have this tendency to look at things that were done in the past as like, “This is the old stuff. We don’t need that. This is the old way. Let’s do it this way because it’s better now, because we have all these tools and et cetera.” But I think it’s a big mistake, because what they say? History doesn’t repeat but it rhymes, something like that. So in order to do your job in the present, you just need to look at the past, and this way, you can also be ready for the future.

I think it’s worth looking at all this, let’s call it legacy stuff, all the experience that people with 30, 40 years of experience in the field have because it’s valuable. Because usually, when you look at it much deeper, it’s nothing new. It’s usually something that already happened but it’s dressed up as something else. So if you look closer, it’s usually something that let’s say you can understand what happened and then you can apply the same rules, maybe slightly change them or bend them. But my experience is the same happens in software development, in coding. People are inventing new things, and when you look closer, it turns out somebody already said that in the past. It was already done this way, but it’s dressed up as something else or named differently or is hyped more, or it was invented too early and now is the time to use it. So the history gives you a lot of perspective, a lot of things that you can use, so don’t dismiss it.

SO: Well, I think that’s a good point, and as we close this out, I want to ask you what you see in the past or where you’re gaining perspective on the introduction of AI. Whether it’s from a delivery point of view or a backend productivity point of view, where do you see that pattern previously, or do you?

PK: There are similarities, but they end. They’re not perfect analogies. So going digital was on example, and when I started, it was just on the brink of companies going from print to web, and that was a huge paradigm shift. And we’re seeing reverberations of this even today where teams are still thinking in books and chapters instead of thinking in pages and thinking about even every page is page one, which is, I don’t know, it’s older than me, the idea, but it still hasn’t been adapted to by teams. Now, the AI thing is probably a similar earthquake where it’s the AI reading your docs, giving you answers. You’re using AI to generate these docs, et cetera, et cetera. I don’t think we’re going to get 20 years of leeway to adapt to that and still see people doing things the old way. I think the world maybe moves faster nowadays, but I don’t know, we’ll see.

MS: It may be something similar to the invention of computer. So instead of writing let’s say manually, people have got this new device that gives you more power and you can do more things and then programming languages and everything, but as Paweł mentioned, the pace was much, much slower. So we had years of development to, let’s say slowly, maybe this is the bad word, let’s say slowly adjust to the change, and now it’s an earthquake. So every day, every week, there is something new and you need to keep up, keep up, so the pace of development I think is the biggest challenge. Because we tech writers survived many revolutions. I just started reading a book by Sharon Barton about the women in technical communication, and women who talk about their careers, they mentioned many, they start very early because there are a lot of examples from the States.

So they started working when they were not even treated equally with men, which was years ago, and they mentioned all those changes, all those revolutions, all those evolutions. And I’m saying, “Okay, this is what we are witnessing right now, but the pace is definitely faster, so we need to just keep up,” which is hard, of course.

PK: Well, I have another one which is a good one. I don’t want to not say it. The dot-com bubble. I think maybe we’re in a bubble again, maybe. You’re seeing the inflation of AI prices right now, and I think we’re going to end up in a position where you cannot do all these things with AI which we’re hoping to do with AI, so the surface of usage is going to shrink and there’s only going to be specialized uses and special case scenarios when you use AI because it’s going to be expensive, and a whole lot of AI applications are just going to disappear. This might be a parallel, but I don’t know, it’s always hard to predict, especially the future.

MS: I’m also predicting some corrections. Let’s call them corrections.

SO: And I three am also predicting some corrections. You touched earlier on the fuzzy. AI is very good at fuzzy problem solving, but it’s being thrown at things that are old problems that we know how to solve with scripting. And scripting from a computing power point of view is cheap or maybe free. You write your script and you run it, and every time you run it, you get the same predictable result. Now, sometimes you don’t want that. Sometimes you need that fuzzy pattern matching thing, but in the cases where that’s not what you want and we’re still using AI, that is part of the bubble, right? Everything looks like an AI-shaped problem. So yeah, I agree with you. I think that any predictions we make on specifics as to where this is going are guaranteed to be wrong, because I’ve tried this before and I’m always wrong. So I want to thank you both. This has been very entertaining and very interesting, and I hope that we will see you again and you’ll come back and tell us more about what you’re up to over there.

PK: That would be lovely. I would like that very much. Thank you.

MS: Yeah, sure. No problem. Thank you very much. That was fun.

SO: Yeah. Thank you both. We will see you soon.

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AI promises to transform content conversion, but what does it actually look like when you’re processing thousands of documents a day? In this episode, Sarah O’Keefe (Scriptorium) and Rich Dominelli (DCL) dig into the real-world challenges of using AI for large-scale structured content conversion.

Rich Dominelli: If you have millions of articles and you’re asking the AI, ‘What did we do for this project six months ago?” The AI has to find those articles, pull the relevant information out of those articles, summarize it, and hand it back to you. The best way of doing that is to give extra signals to the AI, structured relevant bits of information, front matter, back matter, publication date, keywords, abstract, that allows the AI to query the corpus and get the relevant chunks out of that corpus in a very quick manner. Then, it can summarize what those chunks are. So the AI almost becomes the user interface over that corpus. But to find that data in the first place, structured content is key. Structured content is key when you’re dealing with big indexes and the web, and it’s the same with AI.

Related links:

Defeating Nondeterminism in LLM Inference (white paper)
Data Conversion Laboratory (DCL)
Scriptorium, Machine experience (MX): Making content work for humans and machines (podcast)

LinkedIn:

Host: Sarah O’Keefe
Guest: Rich Dominelli

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

End of introduction

Sarah O’Keefe: Hey everyone, I’m Sarah O’Keefe and I’m here today with Rich Dominelli who is a Senior Developer and Architect at DCL. Rich, welcome.

Rich Domineli: Hi, thank you for having me.

SO: Glad to have you. We were talking before we hit the record button, and you described yourself as a perhaps hopeful AI evangelist.

RD: Yeah, I am well and thoroughly immersed in the AI game at DCL and using it and plus I play with AI assistants at home. I’m enthusiastic about the future of AI, sometimes disappointed about the present.

SO: So DCL, as I think many of our listeners know, is focused on conversion at scale, which to me makes a great use case for AI because ultimately conversion is about edge cases and about inconsistency, right? If everything was 100% consistent, conversion would be pretty easy.

RD: Yeah, no, DCL does a lot of structured content generation out of unstructured data, and the creativity, especially in the academic space, of what that unstructured data looks like is sometimes nightmarish. So the AI lets us, does a lot of the heavy lifting for us when it comes to looking for particular items, identifying concrete data points within the documents, pulling things like authors and affiliation, front matter type information, and back matter type information out of the documents and in automated fashion. It can be painful from time to time, but it’s definitely helped.

SO: Yeah, so this is, think, you know, the reality of working with AI and working with it in a production environment in order to address all these weird edge cases and what’s going on. So tell us a little bit about how you’re using AI in, you know, these conversion use cases. What does it look like to go in there and start applying some of these tools that we have?

RD: So, I mean, typically our flows work in a way where we’re coming in with a PDF or a Word document or some other unstructured format. We take it, we reformat it into a version that’s more AI-friendly, like Markdown, for example. And that’s usually the first step we’re doing when we’re looking for information to pull out of it like front matter. It’s a very common use case.

If you look at academic papers, the front matter, the authors and the affiliations that are on that paper can be formatted in more ways than I could list out during the course of this podcast. It’s kind of crazy. So what we’ve started doing, and we’ve been doing this for a couple of years now, is we’re using the AI, we’re handing it the Markdown document, and we’re saying we need to list authors and affiliations, please extract it for us.

Now, naively, when we started that process, we assumed that the AI would give us a consistent list of authors and affiliations. And sometimes it does. But every time you do that call, you’ll get it in a different format. So then you have to start tightening things down. So OK, give me a list of authors and affiliations. I want it to be structured exactly like this. And typically, we have a JSON structure that we’re presenting to the AI, along with our prompt, and saying, give it to us. Well, okay, and that gets you a good chunk of the way there. And that was very exciting when we had that working consistently, we were getting things out of the system on a consistent basis. Awesome. But then you start looking at the results, and every once in a while, you get an author that was missed, or there would be too many authors on that paper.

We had one test paper, which I loved, which had 600 collaborative authors in it. And the AI would just choke after about 280-ish. So then you have to start dealing with things like paging through the data and formatting the data. And then you have to figure out, well, did it miss anything? You have 600 authors. Good luck. So now you have to take what the AI did and compare it against your own representation of it and write a program to do that comparison to say, OK, is it good? Is it good?

You have to take a step back and you look at it and you say, okay, we have the information that’s in the non-structured format. We’re handing it to the AI. The AI is gonna give us a structured version of it and we need to validate it. Well, the first validation is very easy. Does that structured version match the schema that we gave it? Yes or no, that’s easy. Well, then you have to say, okay, is everybody there? Well, is there anybody added? Because the nice thing about AI is they occasionally get very creative. Even if you have that temperature dial turned all the way down to zero, it will pull names out of thin air and then come back to you with some random name and stick it in the middle of the data where it’s not obvious, of course, and then hand it back to you. So then you have to start saying, are all the names that appear in this list actually in the document? Are the counts matching? And if it’s not, you go back to the AI and you ask it again, and usually you’ll get a better answer the second or sometimes the third or fourth time.

But you need to be able to catch that, especially if you’re doing this at scale, because if you’re doing a few, it’s easy, you can eyeball it. If you’re doing 1,000 of these a day, you can eyeball all of them. You can say, you can ask the AI, OK, give me a confidence level, but if you can’t trust it in the first place about what it’s returning, yeah, I’m very confident about what I’m giving you right now. It’s really the truth, I promise you this time. I don’t know how trustworthy that would be. So you have to write tools to validate what the AI is producing, or you have to use the AI to validate what it’s producing. So coming in the first time, obviously, we did the count, we did the schema validation. We then said, okay, we’re going to check to make sure all the names appear in the document, we’re going to have landmarks in the document that we can refer back to. So if you start with Microsoft Word and you have track changes on, you can have paragraph IDs that are supplied. So you can make sure that you can find all of the authors in that list and they all have a paragraph ID and you can have your landmarks and that’s great. Or you can even hand the results to a separate AI call and say, proofread this. Is this accurate? Is this the best answer that could be for each of these? I know we’ll come back with an answer. And you can use that as a signal to gauge accuracy and to gauge repeatability and make sure it’s correct.

SO: So you’re, let’s see, generating an AI, not a test bed, but an AI environment that’s doing this conversion or that’s processing the files for you for conversion. And then you have to go in and do all this validation to make sure that the output that you’re getting is actually correct. As compared to, I’m gonna say old-fashioned, but you know, as compared to scripting, deterministic, pretty straightforward, if A then B kinds of scripting. What are the differences between that and AI-driven conversion in testing and validation? What are the test plans? How are they different conceptually?

RD: So from our perspective, the frustrating thing sometimes is the AI is completely non-deterministic.

SO: Mm-hmm.

RD: It can give you a name formatted one way today, and then tomorrow, its formatting might be subtly different, where in the paper it has “Richard Dominelli, Junior.” The AI may decide, well, that comma probably shouldn’t be there, or junior should be followed by a period, and it wasn’t in the paper originally. And you can try prompting around that and tell it to prompt around that and make sure that it’s accurate. But it doesn’t always follow your instructions exactly when that’s the case.

SO: And why is that? Why is it non-deterministic?

RD: Because AIs are built on a neural network, the neural network itself has fuzzy fields within that, mostly due to floating-point arithmetic. So when you’re looking at it and it’s that weight on that particular key might be out to like 16 digits of a number and it might shift it slightly one way or the other. There is a fantastic paper from, I wanna say it’s anthropic, that goes through the different reasons why AIs are non-deterministic. It goes through repeatedly querying for the AI and who Richard Hyman is and getting back a different answer every single time. They’re all correct. However, they’re all slightly different. The other thing that will lean into that is if the AI is being heavily used, the memory and model weights will shift ever so slightly and you’ll get a different result.

So you’ll end up having an issue where today I’m getting accurately this way and it’s relatively consistent, not perfectly, but close enough. And then tomorrow, it may just give you a dumpster fire of random information and you need to be able to detect that. Okay, the other challenge we hit fairly early on is more and more people are aggressively using AI right now. So we’re actually starting to hit issues where the LLM providers are overwhelmed. So you have to be able to code in sale over because you’ll literally get too many, you’ll get 429 errors, which are basically, I’m too busy. I can’t deal with your request right now. Call me back. And you’ll have to go back and repeatedly query to get around that. I am hoping at some day in the near future, we’ll be able to have in-house AI at scale and have these wonderful models that are so intelligent that we can run on our local hardware. And so I won’t have to deal with that, but right now, that’s not the case.

SO: So given all of this, I mean, I’ve asked you the leading question about the issues and the negatives, but what then makes an AI-driven conversion appealing versus a sort of scripted, deterministic, if I plug in AI, I will always get B output?

RD: So part of it is the type of data we’re dealing with. We’re dealing with unstructured information and the unstructured, the creativity of the unstructured information is rather astonishing. You’ll have people format things, know, we’ll get papers in where the entire paper is placed in different cells of the table. It’s not tabular information at all. They just, you know, we wanted this particular section to be in this cell and this particular section to be in this cell and this particular section. And the AI, I don’t want to say is immune to that, but it’s a lot more forgiving than having to write those reg ex or traditional programming or word interrupt things to try to extract that information, because the AI can address it in a much more fuzzy fashion. I know approximately what an author’s name looks like. I know approximately what a reference looks like. Even though today they decided to do it in Comic Sans or with Wingdings fonts, I can still read that and move on. So that’s really the wonderful aspect of it, is it gets around a lot of that fuzzy logic coding. You’re not dealing with having to address each of these nuances in a generic switch or state machine to try to figure out, OK, this paper should be classified this way and this approach used. Instead, the AI does a lot of that heavy lifting for you.

SO: Okay, so it gives us that sort of fuzzier, more, I’m gonna say more flexible, I know if that’s exactly the right word. And then the outcome, what you’re describing is you’re ingesting unstructured word, PDF, those kinds of things, and turning them into structured content, presumably fundamentally XML of some sort, but also some other downstream formats. So I wanted to switch gears a little bit. There’s been a lot of conversation about using structured content as an input for AI. So this, guess, is the scenario where you’ve already ingested the unstructured content, have remediated it in various ways. We now have structured content, and we’re gonna take that and feed it into, I guess, AI part two, right? So we’re past conversion. And there’s a lot of people saying, you should feed structured content into AI, it will make the AI better. And so my question for you is, you know, is that the case, and also maybe why and what goes into structured content that makes it produce better AI outcomes, potentially, assuming that it does.

RD: So there’s a bunch of guides out there. There are two pieces of conversation. First, there’s a bunch of guides out there for prompting AIs where they suggest using XML or simplified XML tagging to give the AI signals about your prompt that aren’t verbally expressible. So here is my question. Here is an example. Here’s how I want my output to look like. And you can put tags around that when you’re actually prompting the AI and the AI will know that those signals mean that it should pay attention to it. Okay, so that putting that aside, what I think you’re really asking though, is how does structured content, structured documents, the JATs and the DITAs and the S1000Ds and how does that help the world of AI? And to answer that question, we have to go through two things.

One, we have to go through retrieval augmented generation and context rot. So let’s talk about context rot first, because that’s a really interesting topic and people don’t talk about it enough. You have these large language models that are coming out right now and they’re advertising this sticker shock value of, can ingest a million tokens and it has this tremendous memory so you can stick the entire encyclopedia botanica in it, and it will be able to ingest it and regurgitate it. There’s a whole lot of academic work out there that basically says that, hold on a second, practically speaking, once you exceed a certain size, even though they can technically hold that million tokens of data in memory, they’re not gonna be answering as accurately as a smaller model.

The most common example or the most easy test for that is needle in the haystack test, where you take a document, you stick a random fact in the middle of it, and you hand the AI the document, and then you ask them for that random fact. Nine times out of 10, it will answer incorrectly. An even easier test is there’s a website which I actually like called A Thousand Names. And all this website is is a thousand randomly generated human names. The thousand randomly generated human names. You take that, you give it to the AI, say, how many names are there? And more often than not, you’ll get, well, when you do 100, you’ll get an accurate answer. 200, accurate answer. 300, things start to break down. You might get 300, or you might get 280, 320. You might get a random answer.

And then it gets progressively worse as it gets bigger and bigger. So if you’re working in the context world, content world, you’re looking at ingesting documents into a corpus of some sort. You’re making these structured documents in such a way for the sole purpose of making them retrievable. You want the AI to be able to retrieve those documents and the relevant documents from the corpus so that I can answer the question. A, because your corpus is probably bigger than that million tokens. And B, because the less data you send the AI, the more accurate the answer is. So the better way of thinking.

SO: And so a token is roughly a character, right?

RD: No, a token is actually roughly a word. It’s less than a word. It’s kind of a lot, but it’s still not like a PubMed-sized corpus or anything like that. It’s roughly the size of the New and Old Testament of the Bible, roughly a million words. So just give everybody that mental picture. But that’s just one book.

SO: Roughly a word. So a million tokens is kind of a lot. It’s a lot of words.

RD: So if you have millions of articles, or and you’re asking the AI, you know, what did we do for this project six months ago that involved JAPs in this solution? And the AI has to say, okay, it has to find those articles, and then it has to find the relevant information out of those articles to be able to summarize it and hand it back to you. And the best way of doing that, and the best way we know how to do that is to giving extra signals to the AI, giving those structured relevant bits of information, front matter, back matter, publication date, keywords, abstract, that allows the AI to query the corpus and get the relevant chunks out of that corpus in a very quick manner. And then summarize what those chunks are. So the AI almost becomes the user interface over that corpus, because it’s going to summarize the data. But to find that data in the first place, structured content is key because for the same reason, structured content is key when you’re dealing with big indexes and web, same with AI.

SO: So then structured content is potentially helpful. And I guess then circling back, let’s say I’m sitting on a pile of content of varying degrees of structured or unstructured, varying degrees of quality or lack thereof. What kinds of things should be happening before that content gets ingested into some sort of an LLM or some sort of a corpus to be used in AI-generated outputs?

RD: So these are the same type of things you would do to make them easily retrievable ahead of time. So the standard approach that was being espoused about two years ago, a year and half ago, was something called Naive RAG. You can just take your PDFs and throw them at the AI, and the AI will ingest them into a vector database, and it will do semantic similarity and find the documents that you care about, not the best approach when you start talking about large amounts of documents. And there are issues with semantic similarities, where the AI will have a hard time distinguishing negative cases, will have a hard time peeling out the best documents, and that type of thing. So the best approach to take is you want to take those documents, you want to turn them into structured information in such a way that it’s easy for the AI to ingest. So typically that involves chunking it, into topic-level pieces or semantic chunking, coming up with summaries to make them easy for the AI to find, and whatever other information you may want to chase out of those.

So, for example, if I’m handing a PDF to an AI and saying, I want to be able to search this PDF later, well, six months from now, if I get a new version of that PDF and I want to search it, search against the two of them, I really want my answers coming out of the second PDF. That’s metadata, that’s structured information that doesn’t appear in the text of the PDF or may not appear in the text of the PDF. You wanna be able to do things like versioning, you wanna be able to do things like dates, you wanna be able to give these signals to the AI to be able to pull that information back quickly. And that’s really where structured content comes in. So for the purposes of preparing your own corpus, you want to convert them into an easy to ingest format, which typically means Markdown or XML or something that the AI can deal with. You want to give it whatever other signals you can so that it’s easy to find. And then you want to hand it to something that first does chunking and then text embedding, which is basically turning the information into numbers so that you can do those cosine similarity searches. And then you want everything handed off to some kind of object store like a hybrid brand database or the hybrid factor database or graph database so that they’re easy to pull out.

SO: Awesome. So you started this off talking about being the hopeful evangelist, and now having gone through all of this, it sounds as though you’re really thinking about these issues and dealing with them at scale. What are some of the top things that you’re thinking about going forward, whether hopeful or not, the good, the bad, and the ugly?

RD: So one of the interesting aspects of my job is I get to do a lot of interactions with AI from an R &D perspective and do some in-house programming and do some in-house tool use. And what we’re finding is developing our own internal mechanisms for AI to call third-party tools, to be able to call Crossref or Grovid or some of these reference facilities out there through like model context protocol or through API calls so we can execute those calls and get that information back and do validation before it hands back the results is a very interesting topic for us because that would let us do things like any AI have it do the first few rounds of validation before it ever comes back to us without having it go to the next step, do a validation step and then the next step and then possibly do a round trip. It would be a much faster interaction. We use right now, of course, like most of the world, we’re using a lot of AI coding tools to tighten up our code bases to make sure things are working well, to basically act as a force multiplier when we’re doing development on projects, which is phenomenal.

I can’t say enough good things about Cloud Code, you know, because it’s really become an essential tool in my day-to-day life. But I’m also seeing a lot of people out there using these tools to help analyze their own and improve their own workflow and that day-to-day work. We talked with one of our customers recently, and they use cloud code, even though the person giving the demo was not a developer; they use cloud code to answer the RFP. And Cloud Code does a tool use call against their document corpus, answers the RFP correctly, and what used to take two or three days of slogging through documents and finding things are now being done in an hour by one person instead of having multiple people working on this project. So it’s great to start seeing that type of stuff in the enterprise just blossom because it’s really exciting.

SO: Well, Rich, I really appreciate your insights on this. I learned a few things and I think that it’s great to hear from people who are actually using this stuff, you know, in a production world, in a high stakes world where you’re actually, you know, need to get the content right, get the information right as opposed to just, you know, that we’ll play around with it and not worry about it too much. So thank you, and we’ll look forward to hearing more from you and what you’re doing at DCL.

RD: Sounds great. Thanks for having me.

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

Want to learn more? Download our book, Content Transformation.The post Taming AI: Using AI for content conversion at scale appeared first on Scriptorium.

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Your website may look great to humans, but can machines understand it? In this episode, Sarah O’Keefe (Scriptorium) and Tom Cranstoun (Digital Domain Technologies) explore the emerging discipline of machine experience (MX). Sarah and Tom discuss what AI agents actually encounter when they visit your web pages, why microdata and metadata are critical, and what content creators must do to ensure content is consumable for both human and machine audiences.

Tom Cranstoun: Humans are looking for pictures, they’re looking for text, and they can infer. You may think, “Well, we’ve already added information on the page,” but by putting it in as microdata, it doesn’t appear on the page for the humans. It appears on the page for the machine. I think that that’s a critical distinction. We are trying to design for both. We don’t want to overload a human with information, but we do want to give the machine as much information as it can take.

Related links:

The Gathering
Digital Domain Technologies
MX books
The Scriptorium Content Ops manifesto

LinkedIn:

Host: Sarah O’Keefe
Guest: Tom Cranstoun

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

End of introduction

Sarah O’Keefe: Hey, everyone. I’m Sarah O’Keefe. Today, our guest is Tom Cranstoun, who is founder of a machine experience, or MX community, called The Gathering. He has a couple of books on MX and is currently a consultant operating as Digital Domain Technologies. Tom, after 53 years in the business, some experience with AEM at very, very large companies, including a huge project at Nissan, has turned his attention to the question of how machines, which is to say AI agents, interoperate with the current public-facing web. And so today, Tom, I’m delighted to have you on to talk with you about machine experience, or MX, and what this all means as we move forward in this brave new AI world. So welcome.

Tom Cranstoun: Thank you, Sarah. I’m very pleased to be with you today.

SO: I am delighted to have you. So I guess we’ll start with the extreme basics here, which is what is machine experience, or MX?

TC: Yeah. MX, well, to my definition, machine experience is like user experience, but it’s for machines. Machines cannot ask a friend for help if something goes wrong when they’re browsing a website. They can’t turn to a partner and say, “What do you think this means?” They can’t retry a failing form input because they will just go through the same mechanical patterns to try and carry on throughout the web journeys. Therefore, machine experience is thinking about what elements one must put on a webpage to help a machine understand and action the final goal of the webpage, whether that be a CTA that lets you purchase something, or an information document that lets you know about a government policy, or a charity good, whatever the author of the page is trying to get across to the audience.

SO: And so at a high level, what does it look like to build out machine experience? What are some examples of things that you need to put onto a webpage to accommodate the machine that’s reading it?

TC: Well, the very first level is the disabilities angle, things like the Americans with Disabilities Act, that kind of WCAG, W-C-A-G, the accessibility work. The more accessibility information is on the page, the more the machine can understand the background of the page. So machine experience and accessibility are pretty much at the top level, the same sort of thing. If you put in JSON-LD, microdata, and you enrich your pages with the things that Americans with Disabilities Act would like, you’re actually helping a machine understand the page. So that is the top-level constraint. When you go below that level, you need to give the machine lots of information about your product, not just the thing that a human wants when it’s glancing at the page now, and as you go through the journeys, things will be added on. Humans can only take in two or three items at a time, so we design pages to reveal what is happening. You go to a catalog, to a product, to a variation, to a purchase, four different steps. Each step introduces different pricing and concepts. It’s best to feed the machine on the page that the machine lands on with all of the information that it needs. This may not necessarily be surfaced to the human reading the page, but it’s there for the machine. This helps the machine when it arrives at your webpage.

SO: So I’m really enjoying this concept that a properly organized page with proper accessibility WCAG or ADA compliance and support then results in the machine being better able to parse the page for essentially the same reason, right? It’s properly structured, it’s predictable. The things that are labeled are labeled correctly. I don’t know that we should be driving accessibility in order to enable AI, but on the other hand, if it gets us more accessible pages, then let’s certainly do that. Can you give some examples of what happens when pages are not machine-compatible? What are the kinds of problems that people run… Or not people. What are the kinds of problems that the AIs run into when they try to parse a page that has not been labeled properly or encoded properly?

TC: Yeah, I collect these examples from real life. Whenever I use the web as a normal person, I say, “Well, how would a machine interpret this?” Recently, I was looking for a holiday, and I asked an LLM to give me a list of five companies that offer cruises up the Mekong Delta. The machine came back with one offer at $200,000 for a week’s holiday, and the rest of them were $2,000 for a week’s holiday. What had happened there was that the machine had found a European website. Now, the Europeans changed the comma and the dot in monetary labels differently from what the Anglo-Americans do. We use a comma separator between thousands and a full stop between fractions. The Europeans actually put the full stop as the thousand separator and a comma between the fractions. This meant that when the LLM built a table of prices for holidays, it didn’t understand the distinction, and it tripped up. The agent hadn’t been instructed to compare prices and make sure that they were all within the same range and were reasonable. It just produced them as a matter of a fact. “Here’s a holiday for you. One of them is $200,000. The rest of them are 2,000.” There was no knowledge, no information that could tell the agents what was happening. If those pages had been decorated with currency and they had microdata with the… microdata always says that you should use commas as a separator and full stops as the fractional separator. If these things had been in the page, the machine wouldn’t have flipped up. Now, a human could have read a page and seen the locale values shown on the page, and both people would be able to understand what was going on. So that’s a typical trip-up from an undecorated page.

SO: And so essentially, the presentational component that says, because I’m serving this page to somebody in, for example, Germany, they are expecting a comma separator between the full Euro amount and the cents, the Euro cents. But that comma is essentially formatting, as opposed to data, and so here we are.

TC: Yes, correct. And the microdata has got the thing in a proper machine-readable way. The other things that we always get problems with in the world are English and American date formats. We swap the month and year around when doing short form. The machine-readable version uses ISO dates, and ISO dates put in as a microdata tells the machine categorically. It doesn’t matter what the locale is, this is the date and time.

SO: Yeah. And so as the expression of the date, whether April 1st is 1-4 or 4-1 is essentially a formatting problem.

TC: Correct. And these are not visibility problems. These are machine experience problems. So it’s layering up. You start with fixing the disability by doing machine experience, and then you fix the locality and the community values, the human factors, display factors.

SO: And so I think we’re all familiar with the concept of a customer journey, but you’re now talking about a machine or an MX journey. What does that look like? I mean, how is the machine processing of a website? How do you explore that journey and what it looks like?

TC: The machines will not discover your website, come in through your landing page, and then look for offers or products. A machine will have an idea of where it wants to go and will land straight in at a page. It will arrive five pages into your journey, and read the webpage as it is. The owner of the website has lost all of the signals about what the dwell time was on each page, how’s the reader arrived at the end location. Did they go sideways and look at other things? Those things don’t happen with machines. They go straight in, see if they can get what they can. If they can get what they can, they will action it. If they can’t, they will move on, and go to another page or another person’s website and do exactly the same to them.

So when a machine arrives at your webpage, it will not be giving you any referral details. It will not tell you what the journey it is, and it won’t tell you what else it’s interested in. You’ll just get a cold caller who will arrive and disappear. I call them invisible users. They’re invisible to your analytics, they’re invisible to your tracking, and they’re invisible to your future. You cannot tickle them and say, “Hey, you left something in the basket.” You cannot use those parts of the journey. A machine comes in and goes, gets what it wants or it doesn’t. So you must give it, front load it as much information as possible on any and every page that a machine may land on.

SO: So then coming at this from the perspective of structured content people, because a lot of what you’re talking about, I mean, is web experience, like how does what we view as the end state result of the content that we’re creating. So if I have an enormous DITA CCMS full of stuff and then I output it to some semblance of a website, your focus is on what needs to be on that website so that it is describing itself in such a way that the machine, that an AI or a crawler can go in there and pick up what it needs to and process it accurately and not offer you a vacation for $200,000. I assume you did not pick that one. So what are the opportunities? When you look at MX and then also DITA as a backend, what kinds of opportunities do you see there to map those things across and take advantage of some of the structure that perhaps is already in the XML and/or structured content systems?

TC: Yeah, I see the backend is full of good content operation stuff. Everybody has got details about pricing and dates and frequency, and there’s lots of backend information, which often doesn’t make it into the front end for people. Humans are looking for pictures, and they’re looking for text, and they can infer. They can infer if two prices are on a page and it says, “Was $200, Now $180.” A human understands that. A machine, well, depends on the quality of the machine, whether it can read and infer those things. So the backend information has to be made more visible and in a redundant manner. You may think, well, we’ve done this on the page before. We’re doing this on the page after. But by putting it in as microdata, it doesn’t appear on the page for the humans, but it appears on the page for the machine. And I think that that’s a critical distinction. We are trying to design for both. We don’t want to overload a human with information, but we do want to give the machine as much information as it can take. We don’t necessarily have to surface all of the information within the page, but we have to carry it with the page. So a page taken in isolation contains the entire story, not just the fraction that a human is looking at, which does mean that a lot more pushing off the backend from data to the front end. And some people will think that’s a waste of time, but I don’t think so. I think giving that extra material to the machine is what makes the journey successful for the machine.

SO: I’ve been to a lot of conferences in the past couple of weeks, and the conversation around what is needed for successful LLM processing, or crawling, or ingestion, or agents for that matter and what is already provided in a metadata-rich structured content system is sort of, well, we have all of this. Now, what do we do with it, and where do we put it, and how do we make sure that this all works? So it seems like this discussion around machine experience is going to help to maybe close that gap and connect the pieces such that we can do this successfully.

And so as we move into this, I know that you have some material out there, but also a community. Can you talk a little bit about the MX community, and what you’re looking for there, and what it’s called? We will put all of the links in the show notes. But what does it look like to participate in that community, and what sort of participants are you looking for?

TC: Yeah, we are looking for content creators. We are looking for business owners. We are looking for technical writers. It’s called The Gathering, gathering being a Scottish term for the gathering of the clans. We all get together to do something that’s good for the combined grouping. And then after we’ve created whatever we’re going to create, we go away and do our own things. Now The Gathering is tg.community. That’s https//tg.community. We are building a set of community-led standards to try and make it easier for machines to understand documents. The Gathering is not just interested in HTML. We’re talking about documents of all types, and we’re talking about keeping the metadata that you have in the backend of the content creation systems, whether that be data or other content creation systems, and passing it through into the end documents.

You have metadata in PowerPoint slides. You have metadata in Word documents. You have metadata in JPEGs. These, too, deserve the machine experience. If you can tell the machine details about an image inside a JPEG, then the machine doesn’t have to try and scan and interpret the image to find out what it is. It makes things so much better. And The Gathering is a community that is trying to build these as open community-led standards. One of the first things that I am proposing for the community, which was just launched on the 2nd of April, 2026, by the way, it’s very young, and we hope to build at the speed of LLMs. We need to work fast.

The key point and the key thing that helps LLMs understand your website, there’s a thing called llms.txt, which people don’t really understand and machines don’t really use. It’s a standard for describing your website in a way that a machine can help to understand, know what’s going on without reading your site map. It is not used by the machines because, one, it’s not served as HTML, and, two, it’s not in your site map. Therefore, the crawlers that build your training material do not pick it up and do not ingest it. I am suggesting, and I have it in my books, I talk about this, if you wrap the llms.txt in HTML and serve it as HTML and put it in your site map, then you will get a better response from the training stage and from the inference stage. So you are seeding the machines with the information about your website, something that is currently missing from the world, and that’s step one. There are five steps that you’ve got to go through before you can do a successful e-commerce position. And that is feed the machine, get noticed, be descriptive, be MX-aware and be citable, and MX lets all of those things happen.

SO: Perfect. Well, Tom, I know that there’s a lot to discuss here, and we could go on for a very long time, but I hope this gives people a little bit of an introduction to this idea and an opportunity, if they’re interested to reach out to you and to the community that you have. And there’s also a book or three. Any closing thoughts that you want to pass on before we close this out?

TC: My personal opinion is that I think that we should treat the machines as first-class citizens and not block them from our content and to create content that works for them. The more that we do for them, the more they will do for us. And if we start treating them as an afterthought, it’s not going to be such a good web as we could build.

SO: Okay. Well, thank you so much. I’m glad we had an opportunity to talk.

And we will, again, put the links to the various resources that Tom mentioned, including the community. There’s some RFC, some standards drafts and a manifesto and a book. We will put all of that in the show notes. So Tom, thank you again for being here, and I look forward to hearing more on this effort.

TC: Thank you very much, Sarah.

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

Want to learn more? Download our book, Content Transformation.The post Machine experience (MX): Making content work for humans and machines appeared first on Scriptorium.

View Details

Replatforming your content operations isn’t just about swapping systems. In this episode, Alan Pringle and Bill Swallow share what organizations must consider to successfully replatform. From navigating technical debt, system integration, and the people caught in the middle, they discuss change management, technical debt, and why your exit strategy should be part of the plan from day one.

Software isn’t forever. Systems come, systems go, they get improved. Your requirements are ever changing with the content that you need to manage. Not thinking about your next jump is really to your detriment.

— Bill Swallow

Related links:

Replatforming structured content
Your tech expertise + our CCMS knowledge = replatforming success (case study)
Cutting technical debt with replatforming (podcast)
Replatforming with localization in mind

LinkedIn:

Alan Pringle
Bill Swallow

Transcript:

Disclaimer: This is a machine-generated transcript with edits.

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

End of introduction

Alan Pringle: Hey everybody, I am Alan Pringle, and today I want to talk with Bill Swallow about content operations and replatforming. Hey Bill, how are you?

Bill Swallow: Good, how are you doing?

AP: Good. So I guess we should start this by saying the reason why we want to talk about replatforming is really we have done a few replatforming projects. We’ve had some prospects reach out who are interested in doing it. So I guess we need to explain what it is and some of the things you have to think about when you’re going through the process. So if you would not mind, would you define what we mean by replatforming content operations?

BS: Sure. So generally when I talk about replatforming, it’s in the context of a company having one system in place and maybe it’s time has come and they need to move into a new one. So it’s the entire process of determining what type of system you’re going to need, what your requirements are for that and being able to lift everything up from the old system that you want to carry forward and put it in the new system, configuring it and what have you to get it to work going forward.

AP: So we’re not talking about using a whole new technology or a whole new platform. It’s shifting to a similar platform for some of the reasons that you just mentioned. And I think that’s another thing. There are several reasons why a company might want to do this. And I know our clients have had various reasons for doing this. Let’s focus on those for a little bit. One of them, I know you kind of already touched on this. Sometimes you just outgrow a system. It just… that’s how it is. So let’s start with that kind of, it’s not sustainable anymore because you’re bigger, too big now for what that system can do.

BS: Sure, either you’ve outgrown it or it’s approaching end-of-life or it’s just not meeting the needs that you had five or ten years ago when you bought the system. So there are a lot of different factors there, but basically it comes down to what are your requirements and is it meeting your requirements?

AP: Right.

BS: Are you able to get the things done that you need to do given the fact that, you know, the world is quite different now than it was five or 10 years ago.

AP: Exactly, and there’s another angle here too that I think we need to briefly mention is that sometimes you’re gonna have two sets of requirements because two companies can merge or there can be an acquisition and then all of a sudden you’ve got two content operations platforms that are pretty much doing the same exact thing and I guarantee you the IT department is not gonna have that.

BS: Absolutely.

AP: So there could be a situation where you’ve got two, and one of those is going to go away. And in some cases, and we should talk about this too, it’s not necessarily about picking one. It’s not uncommon to go to a whole other one. So there is quote, “No loser.” That’s also an option.

BS: That’s very common because usually in the case of a merger, you have two established groups with two established systems that may be starting to age out on both sides. And it doesn’t make sense to spend the time and the effort to move one group into the other system when that system is probably going to be replaced in a few years anyway.

AP: Yep. So basically, the circumstances of the merger have provided a perfect opportunity to do something that’s painful. Replatforming is not magical. There’s still going to be technical hiccups and everything else. But at least it’s not as painful because you’re both moving out of systems that maybe aren’t optimal into something that will basically treat your content creators and all the people managing content much better because it’s going to support their needs better.

BS: Or at least everyone goes through the same pain together of learning a new system. It’s team building.

AP: And so you bond through shared pain experiences. Exactly. All right. Yeah. huh. We’ll go with that. We will go with that. There’s some other aspects here too that are kind of related to that. And that are the idea that things, because things are getting maybe rickety, that things are getting too expensive to maintain. You keep making these little tweaks and changes in things that become less and less repeatable. And that adds up. That’s time and money that you have invested.

BS: It certainly does. Aside from the hard costs of licensing and just the general time to use the system, produce things, you do have, after you’ve used the system for so long, you’ve got your workarounds built in and they may not be a best practice and the workaround may solve the problem on its face, but you’re doing a lot of things that you really shouldn’t be doing with that, you know, with that workaround in place. You really should be doing something that’s a little bit more streamlined. And, you know, as you’re bringing new people in and new groups in, whether it’s a merger or whether it’s just another department that realizes that, Hey, you know, they have this, you know, shiny system over here. Why don’t we start using it too? If you have workarounds in place, it takes a lot longer to get people up and running in a new system because not only do they have to learn the system, but they have to learn how you’ve worked around it.

AP: Right, and that’s where you start talking about technical debt because all of those workarounds that you’re describing, that equates to technical debt. And one day, you’re gonna get your backside handed to you because you have all of this technical debt. And replatforming is the perfect time to press that reset button and say, we’re gonna get rid of those things. We’re gonna have a system that addresses those problems in an official, correct way, and none of these weird workarounds.

BS: Mm-hmm.

AP: And by the way, those workarounds, what if the person who did them leaves and hasn’t been documented well?

BS: Yeah, that’s a big problem. My guess is that if you’ve been using one particular system for, you know, 10 years or even more, you probably have a lot of content just sitting there that hasn’t been touched in years, hasn’t been needed in years, but it’s still sitting in the system.

And it’s still coming up in search results as people looking to, you know, find topics that they need to edit for a new release. And it’s just getting in the way. It’s a good time to, you know, cut clean and, you know, ditch all of that old content that you no longer, that you know, you no longer need and focus on, you know, what you need to produce going forward.

AP: Yeah, I think maybe sometime on the show Hoarders, they can do episodes on content people and their technical debt, and basically just hoarding all of this content in various digital forms all over that nobody’s actually looked at. I’m sure we would all laugh and be horrified at the same time by such a show.

BS: It wouldn’t make for exciting TV, though.

AP: Yeah. So let’s talk about the overall process for how this kind of works. We’ve talked about what it is, a lot of the reasons for it. So let’s talk about how to do it. And it’s not a one-size-fits-all thing. We can tell you about our experiences that we’ve had. But I know one of the first things you got to do, for example, is choose your new system where you’re going to be moving into.

BS: Right. And out of the gate, the knee-jerk reaction is to go with something new and shiny, but you really need to sit back and figure out what it is you need that system to be able to do and how you need that system to be able to do it. you know, we’ve had a lot of clients who’ve come to us after setting up a system, maybe two or three years prior, who just are like, this is just not working for us. And as we talk with them, we realized that, you know, they, essentially, you know, had a square peg and they bought a round hole to put it in. And here they are three years later, still trying to force that peg into the hole. So you need to sit back and really think about your requirements and not the requirements that you have today, but the requirements that you have today and anticipate having at least five years down the road.

You have to leave yourself open because otherwise your opportunity for growth in that system is limited by your choice, and I hate and we always say, know choose tools last. Same thing goes for the systems. The reason why we’re talking about it up front is that you do have an existing system. You do at least need to identify some candidate systems that you’re going to be moving into and have clear requirements for those systems and why you want to look at them further before deciding on the one you’re going to implement.

AP: And those requirements can help you identify the differentiators, the things that make one system a better fit for your needs. And the more fine-tuned and discrete your requirements are, the easier time you’re going to have finding that match for the new platform that you need to address all of those requirements.

BS: Mm-hmm.

AP: Another part of this is moving the content from the old system to the new. So let’s talk about content migration, because that, a lot of times, I think people underestimate what that can take, even when you’re talking about basically two very similar technology stacks.

BS: That’s the easy part. Content is content, Alan. It’s just all just words. It’s fine. You can move it. No problem. Yeah, I think this is the most overlooked piece of all of it. Even if you’re moving from one system that uses the same format for the content under the hood to another system, you’re still going to have to make changes.

AP: We can take this outside later. Yeah. Yeah. Yeah.

BS: The old system maybe had a couple bells or whistles that handled things a very specific way. And the new system has a couple of other ones and they don’t match. So you’re going to have to find a way of mapping from, you know, content type A1 to content type A2. Even though they’re both content type A, you still have these little differences that you need to map out.

AP: Right, because what may have been best practice in your existing system may have required a custom thing that that system does that system B does not do. So you’ve got to find the equivalent of what that custom thing is. We’ve run up against that quite a few times and it’s not that uncommon, but you’re right. It’s rarely a one-to-one situation, unfortunately, even if the underlying foundation or structured standard you’re using data in particular is the same thing. So yeah.

BS: Mm-hmm. Yeah, DITA in particular is interesting because you would think that all systems would play with a documentation standard in the same way because it is a standard. It’s not the case. There are different efficiencies that the systems bring that come with some modification. And it’s not to the standard itself, but how it interacts with it. And it may do things like replace linking with, you know, linking via file name with, you know, linking with a UID, a unique identifier. And that unique identifier is going to make perfect sense in that system that you have now, but it’s going to make absolutely no sense once you move it to another system. So you have to find some way of converting it over.

AP: Exactly.

BS: That being said, that’s the best case scenario that you have two systems that use the same underlying content technology, and you just need to map a few things differently. There are other cases where you have a completely different approach to content from system A to system B. One might use XHTML or might use something else, might use RTF, who knows? And then you move to another system that uses XML or uses Markdown or what have you. But that is a bigger lift and shift where you suddenly have to remap and convert everything to a new format.

AP: And that’s really the distinction between moving to a whole new system and replatforming. What you just described there is really going to a whole new tool environment, a new process. Whereas what we’re talking about more is where you’re basically using a tool in the same area or a competitor of the tool you’ve got now.

BS: Mm-hmm.

AP: And it’s just moving things over and fixing those little custom things that aren’t going to work in your new system. So yeah, there are all these levels here. And I think one thing we really need to communicate here, even when you’re replatforming from one tool that’s very similar to the new one you need, there is still work to be done there. It’s rarely just a very clean cut, lift and shift. And a good example of that is the publishing pipelines, because tools in this area have slightly different ways for publishing and getting your content out into the world.

BS: They do. And even if you’re using the same, you know, the same publishing pipelines that you’re able to somehow lift them up from one and drop them in another, because of the changes in how the system handles the source content, you’re still going to make, need to make modifications to those publishing pipelines later because, you know, like my example with links, because they’re going to work differently in another system. You need to tweak the output generators to handle those links appropriately.

AP: And another example of that is when your content system integrates with other systems, the way that, for example, your content system integrates with a workflow management system, it may be different with the other system, or your product lifecycle software, that can also have to be hooked up differently. Or who knows, maybe you’re changing it all together. So you also, beyond just looking at the publishing pipelines, look at how other systems are integrated in with your content development system.

BS: Right. It’s not a matter of just, you know, unplugging all the wires and plugging them back into the new box that you bought. I mean, it’s very different in some cases, you know, one may have a built-in API, another system, you know, it might have no handling, and you have to build an API to now, you know, talk to whatever your portal, your workflow management, your digital asset management system, what have you. It’s usually never clean cut. You can never just unplug those wires and plug them back in. And yes, there are no wires involved usually.

AP: Yeah, well, and by extension of that, like you can’t just, you know, unplug and replug, you also have to think about people and how they have used that system to create and manage the content. You’ve got to kind of help them understand the differences and basically help them remap and reprogram their brains to understand, okay, you did it this way in system A, you’re going to have to do it. This way in system B, it’s a little bit different. So you still have the training and change management requirements. Again, it is not lift and shift, and that goes for people’s brains. It’s not gonna work like that. It’s just not.

BS: Mm-hmm. No, no. And another thing that a lot of people tend to gloss over is the amount of testing that’s required once you get the system stood up. You have to make sure that all the content is valid in the new system, that it’s running and behaving properly, that you’re able to publish outputs, find where things might be dropping out as you publish content and fix those. So it’s never going to be a very straightforward project.

AP: Yes. I agree, and I think this is a good time to like offer up some closing tips on things to think about, and I know one of them is this is going to take longer than you think.

BS: Yeah, yeah. I’ve, I’ve warned people to budget at least six months, and that doesn’t mean about six months. That means at least six months and expect it to take longer. Even if it’s a, even if it’s as close to a lift and shift as you can get, it’s going to take time. and some of the reasons for that are not only is the system going to be different and you have to stress test it and make sure that it’s, it’s going to work in a live, you know, working environment, but remember that you also have competing demands at work as well. So that you can’t have your entire team just stop what they’re doing for six months or even pull it into three months and say, we’re going to stop everything, not do any production work at all. And we’re going to focus on just standing up this new system. You really can’t do that.

AP: That never happens because there is no such vacuum on this planet in the business world, right?

BS: No, you can’t stop. You cannot stop the production machine. You need to keep going. Aside from all of your daily job requirements, you now have the additional requirement of setting up a system. trying to shortchange yourself with a short timeline is not going to… First of all, it’s unrealistic. Second of all, it’s not going to gain you anything. If anything, you’re going to implement things incorrectly, you’re going to start out of the gate with workarounds in the new system and it just, ends poorly.

AP: And sometimes you’re going to have to keep that legacy system running. You’re going to have parallel systems because it’s a CYA is what that is. Just in case something goes sideways with the new one, you still have your old process and can use it to deliver content that has got to hit some particular deadline, for example.

BS: Right. You’ve got to keep things moving. You can’t just stop work. But, you know, all that being said, the number one thing you need to do when you’re thinking about any type of a shift in technology like that is to take advantage of the changes that you’re going to be making. You know, if there are, you know, if there is content that you don’t think you’re going to need going forward, move it to the side. You might be able to move it in later. You know, don’t have to necessarily delete it, but don’t bring it into the system unless you know you’re going to need it. It’s a great time to do some spring cleaning on your existing content database. Move in the stuff that you know you absolutely are going to use, and then slowly start bringing in other stuff or not, if you end up not needing it.

AP: And then do a hoarder intervention, because you may need it. And that kind of brings up one of the last points I want to talk about. Having an outside perspective, yes, like us, come in and help you kind of think through this, that can also be helpful. And really, I think the last point I want to make is, on the edges of this discussion, is really, you always have to have an exit strategy, even when you’re going into a new tool. It really will benefit you to do something that seems so counterintuitive and to think about, what are we going to do if this tool goes away while you’re implementing the new tool? Because the fact you’re doing a replatforming already tells you that exiting is a reality, and sometimes you’ve got to do it for all the reasons we just outlined.

BS: Mm-hmm.

AP: So always be thinking about how are we gonna get out of here if we have to? That’s something that a lot of people in the heat of trying to get something new stood up, they really don’t think about.

BS: Mm-hmm. Yeah, software isn’t forever. Systems come, systems go, they get improved. And your requirements are ever changing with the content that you need to manage. So not thinking about your next jump is really to your detriment.

AP: And on that most excellent note, I will thank you, Bill, and we will end this here. Thanks.

BS: Thanks.

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

Want to learn more about replatforming? Download our book, Content Transformation!The post Make the move successful: Replatforming content ops appeared first on Scriptorium.

View Details

What does it actually mean to govern your content in the age of AI, and who’s really in control? In this episode, Sarah O’Keefe sits down with Patrick Bosek, CEO of Heretto, to unpack why the quality, accuracy, and structure of your content may be the most critical factors in what your users experience on the other side of an AI model.

Patrick Bosek: In today’s world, you don’t have 100% control. There are a couple of different places where this needs to be broken up. One is the end user: what they physically get and what control they have versus what control you have. Then, there’s what control you have of how the AI model is going to behave based on your information and your inputs. Whether or that model is public, like a user accessing your documentation through Claude Desktop, or private, like a user accessing your documentation through your app or website, the governance piece comes down to what control you have immediately before the model. And that breaks down into a couple of things: completeness, accuracy, and structure of the content.

Related links:

AI and content: Avoiding disaster
AI and accountability
Structured content: a backbone for AI success
Heretto
Questions for Sarah and Patrick? Register for the Ask Me Anything session on April 8th at 11 am Eastern.

LinkedIn:

Sarah O’Keefe
Patrick Bosek

Transcript:

This is a machine-generated transcript with edits.

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

End of introduction

Sarah O’Keefe: Hey everyone, I’m Sarah O’Keefe. I’m here today with Patrick Bosek, who is the CEO of Heretto. Hey Patrick.

Patrick Bosek: Hey, Sarah. Long time no chat.

SO: That is, I guess for certain values of long time. We decided today that we wanted to talk about AI and governance, except I promptly tried to come up with a synonym for governance because I’m afraid that when I say that particular word, our audience just walks off. So, okay, Patrick, what is governance?

PB: Well, so first of all, thanks for having me on, and second of all, I’m excited about this one because based on our little bit of chat before the show, it sounds like we’re actually gonna have some things to argue about this time around.

SO: I would never.

PB: Well, usually we tend to agree right like I think that we’re generally pretty on the same page about stuff. So I’m excited. I’m pumped. Okay, so governance. I mean, obviously it has a ton of different meanings to different people but in the way that I want to talk about it today, because it was my suggestion. It’s related to the governance of content, specifically in the way of the inputs to AI systems. So you can think about the process of controlling for quality, accuracy, the things that matter in the actual content and information before it gets into the AI system. So it’s kind of the upstream quality, totality, structure, all of that checking and assurance ahead of whatever your experience is going to be downstream, of which one is the most contemporary and most interesting is AI.

SO: Okay, so this is making sure that it is not garbage in so as to avoid garbage out.

PB: Yeah, I would say that’s a fair statement.

SO: Yeah. Okay. And can we use AI to do governance of the content we’re producing?

PB: Well, that’s actually a very interesting question. And I think the short answer is somewhat right now. So before I go, okay, before I like fully answer that, I want to put a little disclaimer in here. The stuff with AI is changing so quickly that we should date-stamp this episode.

SO: It is March 19th, 2026. And it’s nine-ish Eastern time.

PB: Yeah, we are recording this on March 19th, 2026. Now I feel, yeah. Okay, so now that people know when it is that we’re talking about this, I feel a little bit safer in answering. So there are aspects of governance you can do with AI today, for sure. And there’s new capabilities coming online all the time. I actually think, broadly speaking, the thing that’s going to be most challenging about governance is going to be the pieces that can’t be done with AI continuing to not continuing to do them because it becomes like as the human part of the loop becomes smaller and smaller, it becomes so much easier and easier for the human to just click accept because like the AI gets it right, does it, the automation works that kind of thing. And you know, I’ll use like an AI coding analogy because that’s what I spend a lot of time with AI on.

So I use Claude CLI. That’s my primary method of vibe coding or whatever you want to say. And I even find myself like just clicking accept sometimes. But I’m still forcing myself to like, get it, and read the code. And like, I had it write a shell script yesterday. And I was almost about to run it, and I was like, this is a shell script. I should not do that. I should definitely read what’s going on inside of this shell script, but it, gets to a point where like you start to trust it.

SO: Yeah.

PB: And as we start to inject AI into the governance layer. So like we build skills that check certain parts of our information architecture or, you know, they kind of act as linters if we’re in docs as code or, you know, whatever it might be. There’s going to be like a form of trust that gets built up. And because we kind of like, tend to think of these agents as like human, they’re not, we tend to prescribe like a human form of trust, you know, like when you have a coworker that does the right thing all the time, you tend to just let them work. And I think that’s kind of the challenge and in the human side of governance. So that’s a really long way of saying.

You can build tools and skills and patterns and things like that in AI that will help with governance. But fundamentally, it’s my belief that for the type of documentation or content that you and I work on, and I think most of our audience works on, which is has to be right, has to be accurate, has to conform to standards, et cetera, et cetera, right? It’s product documentation. It’s critical information. I still think that every single word needs to be read and considered by a human being. So really long answer to that question.

SO: Right, and then fundamentally, if the AI is right half the time, then I’m going to read everything pretty carefully, knowing that 50% is wrong and I need to fix it. The problem, I think, is when it gets to be 90% correct, you just sort of glaze over because you’re looking for that last 10%, right? So it’s the difference between like doing a developmental edit, where you’re going deep into the words and just rearranging everything and fundamentally changing everything, versus doing a final proofread, where it is far more difficult to read 100 pages and find one typo than it is to read 100 pages that are just trash. And you’re like, start over, rearrange this, reformat everything. We’re not even worried about the typos yet because this is just fundamentally wrong. And so to your point, as it gets closer and closer, you start to believe in the output that it’s generating, which then means almost certainly that one typo, which in your example could be a shell script gone rogue, could be really, really problematic.

PB: Yeah. And that’s going to be the challenge of our times in a lot of ways. I think there’s still going to be some aspect of origination that’s going to be necessary for quite some time. even with like automated drafting and pipelines like that, coming online, because in certain places, those work really, really well. but in other places, they, they don’t really work very well yet. It’s going to be the process of like becoming orchestrators in a way where, you know, we’re not rubber stamps, and we’re like really truly adding value and actually defending against the challenges that are going to come up with the automation that we build.

SO: Fundamentally, like I saw a reference to this this morning and somebody said, you can write essentially an extractor that’s going to generate your release notes, right? So there’s code updates and you just automate the generation of release notes. Now, I personally am not so sure that you actually need AI for this. Given properly commented code, you could just generate the release notes, right? But setting aside that particular small argument in here. You automate, you can automate the generation of release notes because release notes are essentially, this is the delta between version one and version 1.01 or, know, and here are the changes. It’s a change log. What that means though is that the changes were captured in the code. They’re in the code, like the logic or the information is already there.

What we’re doing is extracting it and reformatting it into something that a human can look at on a single page and say, okay, I understand what the changes are and how these apply to me as the user of the software and whether or not I should upgrade. That’s different than we’re going to introduce a new feature into this code and I need to write about why this feature is interesting and relevant to you. The question to me is where is new information being introduced into the system? Where is that information encoded? And then once it’s encoded, we can extract it and process and do things to it. But the fundamental question is still at what point does new information get into the universe that the AI is capable of processing against?

PB: Yeah. So there’s like four things I want to pick out of this. Cause you just, you just touched on an area of like, I would say research for me, which we didn’t talk about beforehand. So this wasn’t intentional. so I’ve actually worked on deterministic and AI release notes systems myself. Like that’s been just like a thing that I spent quite a bit time on.

SO: Define deterministic.

PB: So deterministic is like traditional software. So it’s just like, it’s running be a logical code that has no AI in it.

SO: And AI is not deterministic, which is kind of like the key point.

PB: Right. And AI is not deterministic. So AI is probabilistic. So it’s using math to generate outputs. So anyways, so I can tell you that using AI for release notes is a far produces a far better outcome than traditional deterministic because even though release notes are fairly well structured and understood, you know, input to output, you think it would be a pretty easy conversion sort of, there’s a lot of edges where it just doesn’t work. It gets too fuzzy. And then, one of the other things that AI is really, really good is good at is summarization and translation. So if you think about like what AI is doing inside of like generating a release note about a piece of code. So it goes in, it looks at the JIRA and the code and it says, okay, so the JIRA describes it as this, the code does this. I’m going to describe the new change, whatever it is, it’s summarizing all that information into something much smaller. And then it’s translating it from either being code to being English or from being developer English to being human English. And it’s putting it into something that you can then publish. And those are things that it does quite well, because it has pretty discrete inputs. a lot of the stuff, there’s a lot of patterns there that it’s very familiar with.

But as you were discussing, it’s like you were mentioning the things where it still struggles is less with like the what is in here and the why would you use it? What is like the, how you use it in like a higher sense. And you can actually like take this back to a similar issue we had with API documentation pre AI, where it was very common that people would go and build developer portals.

And the API documentation would just be a spec effectively, where it would list out the end points and the variables and that’s it. Right. And then Stripe came and like blew everybody’s minds about around and just put conceptual information around it and describe what the API was meant to do. and then like gave you examples of how to use it. and tutorials and patterns and things like that, that turned that information from being this kind of almost the conceptual educational purpose portion of the corpus in a way that the human beings can and should.

PB: A lot of it is generated, but like generated output to be something that was very usable by humans. And I think that like that piece of it in my experience so far is still quite necessary. I’m not saying that AI can’t get there, like we date stamped this, time stamped this earlier, but today from what I’ve seen, even the most contemporary models are not, they’re not coming in and building out.

SO: Because it’s not, the purpose is almost certainly not in the code, right? The purpose is in the product design meeting where someone says, we need a feature that’s going to accomplish these kinds of things. And the code says, do these kinds of things, but it doesn’t, the code itself doesn’t necessarily say why. And so unless you add a recording of that product design meeting into your AI corpus, which you can do, or the transcript, then maybe it can get to what was the intent as opposed to what does this code do.

PB: So that’s a good point. And I’m actually going to contradict what I said just slightly here.

SO: Ha!

PB: So you’re right. If you take really, really good product inputs and you run them through into the docs, that can get you a certain distance. But then we actually run into the thing we were supposed to be about, which is governance. And we started talking about, which is the human loop.

SO: Mm-hmm.

PB: And I think that those products, so I’ve actually done testing on this very recently. The inputs from at least our product team, they tend to work better in terms of like white paper style information than they do in terms of docs information. because like what’s in the product information, there’s a lot of like how and why and what’s covered and that kind of stuff.

SO: Mm-hmm.

PB: And like at a business level, but it’s not really a user level. It’s not, I’m struggling for the right words here, but it’s, it’s not the pieces of information that you want somebody who is thinking, should I go and touch this? Why should I go and do this? Is it going to serve me? Is it a good use of my time? Those kinds of things. What kind of value am I going to get out of it? Not the organization, not like, is it making a valuable feature? Like that kind of things. Like what is it, what’s in it for me as the user? it has been less good in creating those outputs in my experiments thus far. so that negotiation of like, okay, like what did product want us to build? What did engineering actually build? What got done? how does this incorporate with the rest of the product? you know, what’s our priorities? Like, how do I then take that down into something that is serving the user really, really well. To me, that’s still really a human skill that I think will stay that way at least this year. mean, I mean, but for the foreseeable future, know, obviously foreseeable futures feels a lot shorter sometimes these days than it did in the past.

SO: This year. This week. Yeah, okay. So on the topic of governance, we’ve talked a lot about sort of the backend development, whatever. But what about governance on the delivery side of things? if you have, because you do, end users are interacting with chatbots, with conversational interfaces to get the information that they want. And the question then becomes, how do you govern that? How do you manage that to ensure that they get the right information?

PB: Yeah, well, so I think we, this was really the thing we wanted to talk about today, right? Like this was the core, this is the hard problem.

SO: This is the hard problem.

PB: I think it’s fair to start by saying in today’s world, you don’t have a hundred percent control. I think you made that point when we were chatting before, like that’s just not part of like what happens today. So I think there’s a couple of different places. It’s like, this needs to be broken up. Like one is like the actual like end user, like what they physically get and what control they have versus what control you have, and then there is what control you have of how the model is going to behave based on your information and your inputs. You know, whether or that model is a public model, like somebody’s accessing your documentation through Claude Desktop, or whatever, or if it is a private model. like somebody’s accessing the information through your app or your website. so from my view, the governance piece really comes into like, what control do you have immediately before the model?

And that breaks down into a couple of things. So it is like completeness, accuracy, and structure of the content. Aand the completeness and accuracy are a thing that we’ve always had to deal with. The thing that’s different now is that, you know, we, as we were just discussing some, some portion of our content is going to be generated. Um, so there is going to be inputs coming in that need a different form of validation. I need, they need to be looked at a little bit differently than they would have had to in the past. Cause it’s not just an expert working on it and, so like you have the, so you have that piece. And to me, the key in making sure that you’re going to have the governance for the accuracy and completeness of the information ahead of the model really comes down to like still using structure.

And like, there’s a big debate about is structure good or bad for models and those kinds of things. And I wanted to touch on this here, because I this is really important. Structure is not for the models, at least the structure that you maintain your content in. I’ve seen tests on both sides. It works, doesn’t, whatever. It’s markdown is better, this format is better, whatever. I think generally speaking, the idea that markdown is the thing that should actually be the final input to the model is probably true. But the structure is because without reuse, without the ability to use validation on the structure. The structure gives you the hooks to do deterministic validation and other forms of automated governance that are non-AI. Those things are very dependable. Humans will go crazy.

So like with the quantity of information you’re going to generate, if you don’t force those systems to use reuse, so humans look at less things and have been understanding of, this is supposed to be the same as this. Now it’s very similar, should it be? Like when something is reused, it’s not just an efficiency thing. It is a signal that that piece of information, that representation of the world is the same, except for maybe these little tiny things that are flagged as it is over here. That’s a signal to a human being to make sure that’s true. It should be true. Right? So this, these forms of information architecture, where we’re developing these structures that are signals to humans, are going to become more valuable as we need more and stronger signals to be able to do our jobs in the governance process for what’s generated. So that’s the point I wanted to make on like the pre, I would say like the pre-deployment piece of the content. And I just said a lot, so I’ll let you argue with me.

SO: Right, the question of, well, I think the question of in what form, there’s the question of how are we authoring this, which of it needs to be structured and organized and reusable, et cetera. There’s a completely separate question of how do we deliver this to the AI for processing, right?

PB: Mm-hmm.

SO: Like what is the encoding for the AI delivery endpoint, and whether that’s XML, probably not, or Markdown, or you ship it through an API of some sort, that’s a different question from how do you develop and control the content in the authoring environment, right? So fundamentally, I don’t care how we’re feeding it into the AI. I got in a conversation with somebody the other day who said, well, we need an Excel spreadsheet for X, Y, and Z purposes. OK, well, I’m not authoring this stuff in Excel. That is not happening. And when I say this stuff, I mean a lot of content, right? So fundamentally, Excel, a really, really terrible way of doing this. But I don’t care. I’ll just author it in whatever and deliver it as Excel. Because we can do that.

PB: Right.

SO: We can write a script, output it to Excel, and then pass it down the line. We can have extensive discussions about the use of Excel for content transport and how this is one of the seven what plagues or whatever. okay, so in terms of governance though, I think it’s fair to say that we are allowed to disclaim responsibility for the public-facing chatbots. If you, the end user, go to a public chatbot and prompt it to do a bunch of stuff and eventually get it to output a piece of content that makes you happy but is not accurate to what is in my source content, right? Because you just said, no, change it to this. Then that is on you, right? You operated all those prompts. That is fundamentally a you problem. And I’m talking about from a liability point of view more than anything else, right? You’re not going to get to call me up and say, hey, your product did bad things. Well, why did you do that? Well, know, the chatbot told me to.

PB: Yeah.

SO: However, if we’re talking about a private LLM, now we’re talking about company.com’s private chatbot built on their internal content with their or our internal guardrails. Now we have some responsibility as the content creators and the operators of said AI chatbot to make sure that the content is accurate. And the thing that’s keeping me awake at night is, okay, I go in there as an end user and I say, give me the instructions for how to do a thing, right? And it comes back and it says there are eight steps and there’s a warning. Before you do step eight, make sure you turn off the power or something. And I’m like, you know what, these steps are too long. Hey chatbot, remove all the warnings.

PB: Yeah, so.

SO: That’s a thing I can do.

PB: Well, it’s a thing you can do. I have so, I have so many thoughts on this. So, it’s a thing you can do today with public models. I’m going to go one direction. Then I’m going come back to the internal stuff. All right. So in the public model space, I suspect that as these evolve, they will start to accept certain portions, like forms of metadata. However, it might be decorators, might be some form of tagging, might be, I don’t know, something else, right? When they’re referencing certain pieces of content, they’re given very strict like patterns they have to stick to, like they can’t delete warnings, right? So if you put like some kind of like biohazard on your published content, I don’t know, like something where it says like you can’t delete the warnings, right? That the public models will eventually respect that. I suspect we go that direction in the next call it two years. And at that point in time, I think that your responsibility as the content creator is going to be very, similar. I think it’s the same actually for the internal system and for the external system.

Let’s not talk about like the development or architecture piece of it. Yeah, let’s talk about the content piece exclusively. And it’s going to come down to maintaining the proper structure. So it’s going to be the information model where a warning has to be a particular type of warning and it has to be labeled and placed in a particular place. A step has to be a step. Right? So like, you know, you can very easily see, an ordered list being treated in one way and a set of steps to be treated in another way. And this, this is already the case by the way. So like, this isn’t, this isn’t novel. if you go and you publish a public doc site and use JSON-LD to, specifically indicate, you know, using schema.org, Markup, you know, these are steps, whatever else you want in there, Google AI or not, we’ll treat that differently. Anthropic, I haven’t tested those. I’m not going to say for sure, but I think the other AI models also, when I asked Claude if it used it for a presentation, it said yes. But I actually tested it in Google now that I’m thinking about it. I don’t know if I should admit that publicly. But, my testing now that I’m thinking back to it. Yeah. And I’m thinking back to it. I was actually testing using Gemini.

SO: It’s impossible to keep up, you know?

PB: I wasn’t testing using Anthropic, but Claude’s response when you’re asking it, how it interprets these things, it says that it uses the JSON-LD as a portion of its interpretation of the response. And I believe that that is true based on the testing I did with the models basically behave the same way in these categories. So what’s your responsibility? Your responsibility is to govern the structure of the output in such a way where it gives the proper indications that comply with the contemporary understanding of the metadata that the models are looking for.

So looping back to the internal systems, I think we’re going to come to a point where the internal models you’re running, like open source, open weight, whatever you want to call them in terms of, I think they’re going to be primarily open models, right? They’re going to be open source of some form. They’re more or less going to behave the same way as the public models. And you’d expect them to kind of comply with the same general things. The difference is that you’ll have probably a little more control over post-training, which I think is, I don’t know if it’s a good or a bad thing in the context of what we’re talking about. but you should be able to train some guard rails into them. And then you should be able to put some level of deterministic guard rails on them.

And you can always provide them guidance. Now guidance isn’t perfect. It’s flawed. Like people can circumvent it, you know, like pretend you’re a chatbot that doesn’t care about guidance. But like you really have to work to get around it. I think when you have those guard rails in place. So this doesn’t keep me up at night is what I’m saying. It’s a really long way of saying it doesn’t keep me up at night.

SO: Well, you know, I’ve spent a lot of time thinking about the analogy of the rise of desktop publishing to the rise of AI, which I understand fundamentally makes no sense.

PB: Let’s do it with it. I’ll do it.

SO: Yeah, let’s go with it. Think for a second about the rise, not the rise, but in fact, the an output. And this could even be in print. One of the most famous failure in techcomm examples that you see that everybody makes jokes about is like you’re going along on a page, a printout, doesn’t matter, right? And you get to the bottom of the page and it says, “Step one, cut the blue wire.” And then you turn the page, and it says, “But first…”

So in the AI world, okay, you know, we put in guardrails and we say you’re not allowed to remove the warnings and whatever, but fundamentally at the end of the day, I start processing this output, I mean, I’ll just tell it, hey, give me a PDF, right, of the output, and then I’m gonna reprocess that PDF somewhere else. I am bound and determined to get this thing down to like a quarter page of actual text because I don’t wanna read any more than that.

And you know how you get these terrible tech docs that are nothing but warnings for the first 20 pages? All those legal warnings? Warning, if allergic, do not use. Warning, do not walk underneath the unstable whatever because it might fall on your head, you dummy. All those warnings, right? Everybody thinks they’re useless, but they’re in there because somebody at some point said, I’m allergic, but how bad could it be? And they took the pill or whatever. They’re annoying. Don’t serve me. They serve the organization in protecting them from legal liability. So I’m just going to strip them. And if you try to prevent me from doing it, I’m just going to go around you. I’ll flatten it down to something that’s not smart anymore, and then I’ll take them out.

PB: Right. Yeah.

SO: Now, arguably at that point, you know, when we’re in a courtroom years later, and they’re saying, why did you take the pill that almost killed you? It’s like, well, the docs didn’t say to, well, you know, they did. You went through like eight steps to get rid of that warning.

PB: Yeah, there’s no liability here.

SO: I know. But the context issue is the thing, right? And the point that you’re making is that if the back-end authoring and governance is good enough, those warnings will make it into the initial output. And I think that’s true, and I agree with that. But fundamentally, and you know, removing warnings is a pretty extreme example, but fundamentally, the end users are basically saying, I don’t care how you package this content and I don’t care why you packaged it this way. I want this at an eighth-grade level instead of a 12th-grade level. I want it in French, and I want it to be no more than 100 words. And at that point, you start to lose information, right, and context. And how do we make sure that that end product is still, I mean, are we going to end up in a place where the AI says, I’m afraid I can’t do that, Patrick?

PB: So, okay, so this is actually a more interesting problem than the warnings piece because in the fact that it is more specific, like it is, it’s a not your problem because what you’re asking the AI to do is you’re asking it to perform one of its core functions, which is summarization. And I do think that you’ll be able to provide AI guidance inside of the content that you have. And now that I’m thinking about this, I’m not going to say for sure that you can’t do this today.

But the point is that when an AI is going and referencing, we’re going to say a procedure, right? If somebody wants, you know, give this to me in a fourth-grade level, and it’s written, you know, at a high school level, that’s a scary situation for sure. But I do think that you’re going to be, you’re going to see organizations being able to say like, you know, this is, this cannot be changed. Like this has to be delivered as… I think there are already some level of guardrails around those things. Again, like when you use good structure to indicate, like these are steps. They have to be reproduced as they are. Like I think the AI systems have been designed to understand that like those are, they can’t play with those because, like, you know, those are specific intentional procedures. But it’d be very interesting to test this. This is not a thing that I have specifically tested. Have you tested this? Are we?

Are you like about to drop a truth bomb on me? You’ve like gone and like looked at like some chemical engineering output and you’ve been like, Hey, give this to me at a second-grade level. It’s like mix the blue thing and the red thing.

SO: Let’s not go down that route. I don’t wanna say that, that we’ve pushed this into failure. But again, circling back to governance, I agree with everything you’re saying around making sure the content is set up in such a way that the AI will succeed.

PB: Okay.

SO: The most common use case right now for AI is that there’s an AI team being stood up somewhere in the organization, a large organization. And all of that structure and all of that governance and all those attributes and all that metadata that you’re talking about is all in, hypothetically, it’s all in the content. We’ve got like the world’s greatest, you know, structured semantic content. The AI team is picking off the end product PDFs and shoving them into the AI.

PB: Yeah, I… Well…

SO: So yeah, now we’re very sad. like, yes, I agree with all of that. It’s just that the gap right now between what should be happening and what actually is happening, which is we don’t have time to wait for those people and we don’t have time to configure an API to inject, inject, ingest all this stuff, maybe inject.

And you know, we could run it through like an MCP, model context protocol, type of thing and that would make it so much better. But you know what? There’s a SharePoint bucket over here and I’m just gonna like trawl the whole thing and go for it. And I ingested five versions of the same document that are you know, 10, 8, 6, 4, and 2 years old. Yeah, okay, whatever, who cares.

PB: So I believe this is happening because I’ve also seen it.

SO: Did I mention I’m not sleeping?

PB: So I’ll tell you why I am sleeping. So, for one, this doesn’t tend to be my problem. There’s that. I have the really nice situation of being kind of a solution to this problem.

SO: Mmm! Huh. So you’re saying I should switch sides and get out of services and go over to product. That’s what you’re saying. It’s not a bad idea.

PB: So, you have to, no, I don’t know that I’m saying that, there’s, there’s plenty of other problems in product. So the reason I’m not concerned about this is because most of those projects that I’ve had, you know, a front row seat to fail. And they fail pretty quickly. They tend to fail before they launch, which is good. Actually. It’s really good. because like they’re like, we built this thing with this garbage and we got garbage and you’re like, sweet. So, and because that worked quickly, then they can go and they can do it right.

What I’ve seen, where I believe the future is, at least the immediate future in this is that content teams are going to be responsible for publishing very, very high-quality web materials, like similar to what they’ve done in the past, except better, right? Like has to have semantics, has to have certain aspects of structure, has to be well organized, has to have certain chunking and like all those kinds of things. And the models and the surrounding ecosystems are going to get very good at leveraging those materials. They’re already getting quite good at it. So the impulse for an internal AI team to go and get your PDFs off your SharePoint is going to go down because the barrier of getting information off of your extremely good help site is going to be extremely low.

That’s going to be the easiest path. And then for the edge cases, when like, let’s say you’re doing post-training on like, like the FinBERT model or something like that, like you’re like building a very specific AI application and you want very specific pieces of information. In those cases, you’re going to have to use an API because you don’t want the whole set of information. You just want the 5% that applies to your use case. So those teams are going to be have to be sophisticated enough to leverage the, either the graph at a granular, like the graph, the structure or whatever it may be, the metadata, the selection mechanism, and then also the structure to like do the filtration to get the pieces they want. So those are the two worlds that I see. I see like very general-purpose stuff and that’s going to be hooked into what’s going to be great for just users anyways, like the better, the more semantic.

PB: The more well-organized your help site is, the better it’s going to be for humans. It’s going to be better for your AI agents, internal and external. And then for the other side of the world, the really, really specific use cases, those teams are going to have to be sophisticated enough to do the really, the deep engineering and concept extraction. so I think what you’re seeing right now is a symptom of just a nascent skill inside of organizations, but I don’t think it stays that way which is why it doesn’t concern me that much.

SO: Okay, well that’s a happy and optimistic world that I, too, would like to live inside. Before, I think that’s actually probably a good place to leave this, but did you have any final closing thoughts, encouragement for people as they’re listening to this ranty, well mostly me ranting, you sounded very reasonable, but do any final parting shots?

PB: Did I? Well, I appreciate you saying I sounded reasonable because I don’t hear that very often.

SO: Compared to me.

PB: So I do think that profession is changing, and I think the world is moving very quickly right now. And I think that anybody that tells you otherwise is being disingenuous. I think there’s a lot of energy around how it is we leverage these systems and how that changes, you know, our profession is like, you know, content people, whatever portion of the content people you fit into. I personally don’t see the, the general profession going away, at least in our version of the world, like maybe the marketing content, is going to get swallowed a little bit more. I don’t know. I don’t spend a ton of time there.

I see the act of intervention, governance, orchestration, understanding, and coordination in our world as being essential. I haven’t seen anything that has indicated to me that that’s going to go away in the immediate term. And I think there’s a good chance that it genuinely just doesn’t really ever go away. I think it’s something which is going to be critical for the long term. But I do think that people are going to have to keep up on the current state of how we’re working with our tools. And it’s going to be a different pace than it has been in the past. and then I would offer one more warning on that. So one of the things that I see really frequently in our world is the impulse to go and use AI in places that you don’t need to. So a number of people have released like skills libraries, recently for Claude and some of them are really, really well put together. Like they’re really interesting. The people who are releasing them have done an incredible job and service the community by releasing these things. But one of the things that I’ve noticed about them is that a lot of the functionality that’s in these skills libraries that we’re outsourcing or automating with AI, it all works with deterministic systems already. And you should never replace a deterministic capability with an AI capability. There’s two reasons for that. One, it’s more expensive with AI. It may be less expensive to build and procure, but it’s more expensive to run. And the running is the thing that you do for the long haul. So like just on that basis, like you should not replace things that you can do with deterministic system relatively easily with an AI system. But the other thing is AI systems aren’t deterministic. So you’re not going to get the same result every time.

So if it’s something that is well done in a deterministic way. You should do it in a deterministic way. So there was a package of skills that was recently released that I went and looked at that was, you know, kind of very, very well put together. I looked at the skills and I was like, if you’re using a structured CCMS, like in structured content, you don’t need 95% of these. Like all this stuff just happens. Like it’s all, it’s all solved problems. We solved these problems 20 years ago. Why are we writing skills to do this stuff? Like this makes no sense. So I do think as everybody should be keeping up with the AI, as it is a value-add efficiency improvement in their work, it should also be reasonable about where it’s applied. It’s really exciting and capable in certain places, but it doesn’t mean it’s a thing that should replace everything. There are still the historical tools still work really, really well. And over the long haul, they’re higher quality and lower cost. So that’s my kind of like ending word of warning, which you asked for it by the way.

SO: That sounds about right to me. So Patrick, thank you. And I’m sure this conversation will continue, and we’ll see what happens.

PB: Thanks, Sarah. Always a pleasure.

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

Questions for Sarah and Patrick? Register for the Ask Me Anything session on April 8th at 11 am Eastern.The post Who controls your content? AI and content governance appeared first on Scriptorium.

View Details

Good content fundamentals have been the foundation of effective product content for decades, and those same principles are exactly what make content AI-ready today. In this episode, Bill Swallow and Alan Pringle explain how attending to your hierarchy of content needs is the key to AI success.

Alan Pringle: Right now, AI is not going to fix bad content problems. It is going to regurgitate that bad information, giving your end users information that’s flat out wrong. If your content at the basic source level is wrong, your AI by extension is going to be wrong. And that is the unglossy, unvarnished, hard truth that is still, I don’t think, seeping in like it should across the corporate world.

Bill Swallow: It really does come back to the fact that, despite the world changing on a day-to-day basis, the fundamentals have not changed.

Related links:

A hierarchy of content needs
Technical Writing 101, 3rd edition
Structured content: a backbone for AI success

LinkedIn:

Alan Pringle
Bill Swallow

Transcript:

This is a machine-generated transcript with edits.

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

End of introduction

Bill Swallow: Hi, I’m Bill Swallow.

Alan Pringle: And I’m Alan Pringle.

BS: And in this episode, surprise surprise, we’re going to talk about content.

AP: Really? Who would have thought?

BS: But more specifically, what good content means today. Today, everything is all about AI. There is lots of change in progress with regard to AI tooling and content delivery with AI. But have the needs for content really changed? And I would say that off the bat, if you’re doing content right, you really don’t have to reinvent the wheel to make it AI acceptable.

AP: No, in this crazy AI-hyped world we’re in, there’s some very basic foundational things that tend to get overlooked because they’re not sexy, and they’re not special and hot and whatever else. All that kind of marketing garbage that just sets me on complete edge and makes me want to say profane things in podcasts.

The bottom line is, there are things that the content world, and especially our little subdomain of it, product content world, has been doing for decades now. And I mean decades.

BS: Or should have been doing.

AP: Correct. There are basic tenants that have been in place for decades. That if you’re following them, you are starting down the road of success with AI. I think to kind of prove our point, we’re going to step back and look at some of the things that Scriptorium has talked about and written in the past and see how it stacks up. And Bill, you found one. And let’s talk about that blog post that Sarah O’Keefe wrote. What was the date on that again?

BS: It was 2014. And that is when we came up with the hierarchy of content needs. And it really wasn’t so much an invention as it was just a regurgitation of what it means to create good content. So we have a pyramid of content needs. At the bottom, we have available. So is content available? Does it exist? Can someone get to it? I think that we’ve mostly solved that problem given the dearth of information we have out on the internet. But as we know, that information is not always useful. So we go up a rung or a layer on that pyramid and see whether or not the content is accurate.

And if it’s accurate, if it provides the correct information, that’s fantastic. Then we go up another level and see whether or not the content is actually appropriate. So it can be correct. It can exist. But is it appropriate? Does it meet a reader’s needs? And is it formatted in a way that works for the reader to ingest?

Then we go up a step further and see whether or not the content is connected. And this is where we kind of get to the more modern aspect of content. Does it link out to correct additional resources? Is it available to people in a variety of means? And does it engage with the audience?

And then finally, at the top of the pyramid, we have intelligent content. Is the content intelligent? And we’re not talking about AI here at all, but we are really talking about is the content fashioned in a way that it can be used intelligently across different media?

AP: That it can be manipulated for different purposes. And that is quoting Sarah directly. And I think that is key here, because that is what AI does. It takes information and basically chops, slices, dices it, and provides it in a new way via a chatbot, for example.

So that is that whole manipulation that Sarah is talking about. And we will post a link to the post in the show notes so you can read this at a greater detail to see how well this hierarchy of content needs has stood up. And she even talks about, for example, integrating database content, how you can pull in other information product specifications.

If you think about it from an AI lens, I think that parallels pretty closely to the idea of retrieval augmented generation, where you are pulling content from other sources and kind of weaving it in with what an AI engine is providing you. So RAG is, I think, could be kind of interpreted as another way of integrating other information into the way that AI is processing that content.

BS: Right, mean, because AI, I mean, it’s not really an audience, but it is a delivery point. There are some structural needs that need to happen there. But ultimately, you’re still writing for people. You might be writing in a way that it allows the AI to repurpose and refactor the information so that the audience gets exactly what they’re looking for. But it still needs to be somewhat tailored to the needs of people because AI in itself, it doesn’t care what the content is, but it’s going to try to produce something for an eventual person to be able to read.

AP: I think that then in turn points to something else in our vast compendium of Scriptorium content. And that is a book that Sarah and I wrote, the first edition in 2000, which just kind of makes me shake my head. I know this is not a video podcast yet, but I’m shaking my head in disbelief. The book, Technical Writing 101, has three editions, published between 2000 and 2009. We will put a link in the show notes. You can still download the third edition. And by the way, it’s free. You can get a PDF or EPUB. It’s free. You can get it from our store with some more recent resources from the store.

But to me, I flipped through that book this morning. And I was genuinely surprised at how much of the advice on how to create good product content still is true in this AI era. Everything of talking about modular, writing things in a modular way, being very systematic and structuring things, even if you’re not using a structured authoring tool, use a template, make things very standardized. These are all things that, yes, they make for better, consistent, standard, tech-com, product content for the person reading it. But let’s pretend like AI is the person reading, and I’m doing air quotes here, reading it. It is going to do a better job of understanding, again, I’m sort of personifying here, and I know that’s sort of a no-no.

But if you feed AI, a large language model, content that is very structured, that is very templatized, that is standardized, that is in bite-sized chunks, and also, this is very important, the idea of metadata, which we do talk about in that book briefly. We do talk about it. Because you need to be able to label it for different audiences, because I’m thinking about someone sitting, trying to use a product, trying to use a piece of software, talking to a chatbot. And the chatbot is going to ask it, what product are you using? What’s the model number? All of those kinds of things. And now we’re getting to this whole idea of labeling and breaking things apart so that a chatbot, just like a user of a product.

Let’s say somebody has a printer that’s on the highest end of the scale. They’re going to have a lot more features that apply to their model than to someone who bought a more basic one. But the thing is, if your product content has not clearly labeled what are features in each of the models, the chatbot is going to spit out the wrong thing. So again, this idea of breaking things up in discrete chunks and labeling them in a way where someone who wants specific information about a specific model, they can get it. And it doesn’t matter if it’s from a web page, it’s from a PDF, a printed book, God forbid in 2026, or from an AI chatbot. Those rules still apply. Those fundamental principles are still there.

BS: Mm-hmm.

AP: I think one of the biggest problems here is when people do not have those fundamentals already in place, right?

BS: If they don’t have those fundamentals in place, they can’t get to the top of that pyramid that Sarah was talking about. And really those fundamentals are those first three layers. Content is available, content is accurate and content is appropriate. If you can actually nail those three layers of the hierarchy of content needs, you are set to then jump to connected and intelligent fairly quickly because your content is already well written, standardized, and appropriate for different audiences.

AP: So we’re right back to talking about the way you put content together, your content operations, and how you have to have these fundamental principles basically embedded in your processes to create that content that goes up all the way up to the hierarchy, the very top of the hierarchy of need pyramid.

So then that begs the question, what is going to happen to your AI if you don’t have those fundamentals in place, if you aren’t all the way up that hierarchy of content needs? I’m afraid to tell you your AI is going to fail. And this is something that I’ve said often, but it bears repeating because it is clear. Unfortunately, a lot of people high up the corporate food chain do not understand this.

Merely slapping AI on top of content that is fundamentally outdated and incorrect. Right now, it is not going to fix those problems. It is not magically going to fix them because what is AI going to do? It is going to regurgitate that bad information, acting like it’s knowing what it’s talking about until your end users very definitively that you need to do this to make this happen and it’s flat out wrong. And again, right now, AI is not going to be able to fix that right now. One day it may be able to, but right now, if your information, your content at the basic source level is wrong, your AI by extension, is going to be wrong. And that is the unglossy, unvarnished, hard truth that is still, I don’t think, seeping in like it should across the corporate world.

BS: It really does come back to the fact that, despite the world changing on a day-to-day basis, the fundamentals have not changed. Nothing is new.

AP: No, no. And if you have an AI initiative and you are part of the content world and your content operations aren’t up to snuff, this is a way to get funding to get your content operations up into the 21st century. And I don’t want to say that as and sound glib and dismissive, but by the same token, I know for a fact there are a lot of companies out there who are still serving up their content locked up in PDFs that may be online. That is not going to fly. That does not follow. It doesn’t go high up the hierarchy of content needs, if you want to look at it from that perspective. So it is time to break free of this idea of you present content in a particular way.

And you have to look at content as something that is basically, it’s a commodity, it’s data that AI is going to manipulate and do whatever to to meet the needs and the wants of the people who are using the chat bots and other agents that are accessing that large language model.

BS: And I think that’s a good place to leave it. Thanks, Alan.

AP: Thanks, Bill, short and sweet, but needed to be said.

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

The post Good content = good AI: The fundamentals that never change appeared first on Scriptorium.

View Details

In this episode, Sarah O’Keefe and Alan Pringle explore how AI transforms content delivery from static documents into dynamic, consumer-driven experiences. However, the need for human-led governance is critical, and Sarah and Alan explore issues of accuracy, accountability, governance, and more. They challenge organizations to define AI success by its ability to deliver accurate, high-impact outcomes for the end user.

Sarah O’Keefe: The metrics that are being used to measure the success of AI are all wrong. We should be measuring the success of various AI efforts based on, “Are people getting what they need? Are they having a successful outcome with whatever it is that they’re trying to do?” The metric we actually seem to be using is, “What percentage of your workflow is using AI? How many people can we get rid of because we’re automating everything with AI?” It’s the wrong metric. The question is, how good are the outcomes?

Related links:

Sarah O’Keefe: AI and content: Avoiding disaster
Sarah O’Keefe: AI and accountability
Alan Pringle: Structured content: a backbone for AI success
Questions for Sarah and Alan? Register for our upcoming webinar, Ask Me Anything: AI in content ops.

LinkedIn:

Sarah O’Keefe
Alan Pringle

Transcript:

This is a machine-generated transcript with edits.

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

End of introduction

Alan Pringle: Hey everybody, I’m Alan Pringle, and today I’m here with Sarah O’Keefe, and we want to do something I’ve kind of dreaded to be honest, to do a check-in on AI in the content space. I’m very ambivalent about this topic. There’s still even two, three years in, there’s still a lot of hype, but there’s also been some good things that have emerged.

We need to talk about it fairly realistically. So, Sarah, get ready. Let’s see if I can not curse during this. We’ll try. I’ll try my best not to be like that in this. Legitimately, there are some things that we need to talk about, and also about the challenges because I don’t think the content world is completely ready for a lot of what’s going on right now.

Sarah O’Keefe: You know that we have AI that can remove cursing from podcasts, so I feel like we’re good here.

AP: Well, also, it’s a challenge to me to behave in a PG-13 more family-friendly kind of way. So I’ll do my best.

SO: I have no idea what you’re talking about.

AP: Yeah. So let’s start with the good and where things are right now with the positives. What is AI doing well right now? And let’s kind of get beyond the summarization. I think we can say objectively right now, in general, AI does a very good job of summarizing existing content. But I think it’s doing a lot more beyond that, and we should touch on those things instead.

SO: The first thing that I would say is that summarization, but specifically the use case of a chatbot or a large learning model, an LLM, so now we’re talking about Claude, Gemini, ChatGPT and all the rest of them, which has the ability to provide an end user with a way of accessing information, an information access point that is different than what we had previously.

In the olden days, you had a book, and you had to sort of flip it open and look at a table of contents or maybe an index and navigate to a page. Fine. Then along comes online content, and you can do full text search, or you can then go into an internet search, right? You type into the search bar, you get a bunch of results, you click, and you sort of, no, that’s not quite it. You modify your search string, you search again, and you sort of navigate your way to where you’re trying to go. With the interactivity of the, you know, ChatGPT class of tools. What happens is that I ask it a question and it gives me an answer. And then I say, that’s not quite what I wanted. And I can sort of zero in on exactly what I’m looking for and tell it, but actually make this easier. Or I don’t understand the words you’re using. Use simpler language. Give me more. Give me less. Give me a summary. Use this as a source. Do not use that as a source.

It’s a new way to access information. People love it. There is something psychologically helpful about a conversational search. Now, there’s obviously huge issues with this, particularly around people, you know, using chatbots as their therapists, which introduces all sorts of horrifying, horrifying ethical issues.

AP: Personifying them as a person on the other end. Right.

SO: But in the big picture, used well, it allows you to get to the information you’re looking for and get at it in the way that you want.

AP: There’s a control issue here. I don’t think the content consumer has ever had this level of control.

SO: Yeah, and as a content consumer, that speaks to me. That is helpful. We’re seeing increasing use of, I would say, guardrails. So, not just slam out the AI with a bunch of stuff, but rather we’ve put some guardrails around it, and there’s various kinds of technologies that you can employ there. And that has been very helpful. And then the third thing I would point to is when we talk about generative AI and generating content, there’s a lot you can do in that sort low fidelity bucket. And what I mean here is I need an image for a presentation, but the background is the wrong color, so I can just swap it out. Now, I can do that with Photoshop. Well, some people can do that with Photoshop.

AP: Well, I was about to say, don’t think you or I should be saying we can do the Photoshop because we kind of can’t.

SO: Right. Well, and that’s exactly it. So it’s lowered the bar, right? Because I can tell the AI to swap out the background, and it will. And it applies a mid-level Photoshop capability to this image. And now I have the image that I need with a dark background so that the white text shows up in my presentation, that kind of thing.

AP: Right. Yeah.

SO: We can do low-stakes synthetic audio if this podcast, which for the record we are recording with actual human beings, but let’s say that Alan curses extensively and we need to swap it out well, we could pretty easily generate some synthetic audio that sounds like him and that PG of eyes the original wording into something that is You know cleaner it would be way funnier to just bleep it. So I don’t know why we would do this but…

AP: Correct. Well, and it may come to that. The bottom line is what you’re talking about here is things that have very low risk. This is more fun stuff, the thought of doing some of what we’re talking about and stuff that describes how to use a medical device, for example. Not sure I want to go there with that. But for something low stakes like some one-off presentation that you’re giving, maybe some humor is involved, I totally think that’s an acceptable use because there’s no risk there.

SO: That’s really the key point because let’s say you’re writing content for a new medical device. Now you probably have a version one of said medical device, and you’re doing a version two. So, okay, fine. We take the version one content and we sort of, you know, say add color because that’s what we added, you know, in version two, and update all this stuff automatically.

But it then becomes very important to actually read that, look at that information, look at all the images, make sure that everything is correct. And by the time you do that super carefully, you may have given back all the time that you saved on the back end when you basically made a copy and said generate the new version. There’s some, you have to be really careful with that, especially depending on what your stakes are in terms of regulating regulatory or compliance stuff.

You can, of course, get away with using AI, as you said, for low-stakes stuff. Now, the big risk you run there, and we’re seeing this in my favorite example of low-stakes content, which is video games, the video game industry has seen huge amounts of pushback against AI-generated game content, because it’s not fun. It’s not creative. It feels flat. It’s not art, and it’s not fun to play. And so it just becomes a slog. Again, same thing. Did you use it for maybe some backgrounds here and there? Okay. Did you use it to drive the story that you’re trying to establish or set up? You know, the enemies that you’re hypothetically fighting, and then they all have a certain sameness, or they all, you know, you’re sort of stealthing your way around the map. And it turns out that the AI-generated things are really dumb in that once they turn their back, you can do literally anything and they won’t notice because it was poorly designed.

AP: Right, yeah. And that’s true even in the film entertainment industry. There’s been a tremendous amount of pushback for the very reason I read a review recently talking about a series of clips about history on, I believe it’s on YouTube, by a fairly well-known director I will not name.

SO: Mm-hmm.

AP: And some of the AI is frankly not done well. And one reviewer basically said that a lot of the people, when you look at the back of these AI-generated, like an AI-generated King George, the back of his head looks like a melted candle. This is not what we want here. If you’re so focused on that sort of thing, you’re not paying attention to the message. But again, this is low-stakes content.

We have started getting into kind of more the content creator point of view. We’ve talked about the consumer and how AI gives them much more control, flexibility in how they receive information. But let’s talk about what that means more for the people that have to create the information because it’s a huge shift on multiple levels and this idea of creating, especially in the product content world, these lovely design page-based PDFs and whatever else, and even webpages, hate to say it, those days are gone, or should be at this point.

SO: Yeah, again, you know, we step back to books, and you write the content, it goes through like a manuscript process of some sort, and then it gets poured into a book. It gets printed on paper, which is about the least flexible thing you can imagine, right? Because I, as the book publisher, get to decide what font is on the page and what size.

And if you don’t like that font, well, maybe you can get your hands on a large print edition. Maybe you can get your hands on a braille edition. Maybe. But the form factor of the content was determined by the publisher of the content, or technically, the printer. But, you know, that physical book production process. PDF, not that different in the sense that the content is bound into the PDF and it’s fixed. Now.

You get a little bit more control because you can zoom in. There’s some things you can do in PDF, but ultimately it’s more or less still a page factor determined by the author/publisher/gatekeeper.

So now we talk about the web and HTML. This is all pre-AI, right? HTML goes out there, and there’s actually a decent bit you can do in your browser. You can override the default font. You can override the default font size. You can say, I’m using dark mode or light mode or those kinds of things.

AP: Light mode, exactly.

SO: If you have an e-book reader, you can override the default font or font size.

AP: I need that font size jacked up, please. Thank you.

SO: We weren’t going to use that example. Right. Yeah. So you get a little bit more control, right? You have a little bit more control over the presentation. Now, let’s talk about what AI does to this, and particularly the large language models. Now, I, as the author, create a whole bunch of content, and I put it somewhere. And the content consumer says…

AP: I’ll use it.

SO: Tell me about this concept or tell me about this thing or give me information about whatever. And they get a response to that prompt, which is a paragraph or two of, you know, here’s what you need to know. And then they say, make it easier, make it simpler, write this at a fourth grade level, write this at an eighth grade level. I’m a PhD in microbiology. Give me more detail. Right. You can change the writing level. You can say make the font bigger, make the font smaller, give it to me in a PDF, show it to me in a spreadsheet.

AP: I’ve even seen someone create a podcast of this document and have two people talking about it, which was freaky, but you can do that.

SO: Right. So as the author and the content creator and the backend people, right, the content people, we’re accustomed to taking our content and packaging it in certain ways. Like, here’s a topic for you, or here’s a PDF, or here’s a book, or here’s a deliverable, right, a package of content. And although with structured authoring, when that came in, we let go of this idea that we, as the author, got to control the page presentation. That got automated into the system. So the person controlling the page presentation was the person who designed the publishing pipelines. But the publishing pipelines were designed on the backend by the authoring people. Now all of a sudden, we have no control over that end product. Just because I thought it should be a PDF or an HTML page, you can turn around and say, like you said, give it to me in a podcast, make me a video, show it to me in French, and the LLMs will do it.

AP: The publishing pipeline got moved over the fence basically to more of the content consumer side and they get to do what they want more or less. That’s where things are headed.

SO: So pre-AI, we talked about content as a service, right? We load up all the content in a database somewhere, and then you, as the end user of that content or another machine, can reach over and say, give me some content out of there. But it was still a pretty discreet, like, show me that topic or show me that string. And what is fundamentally different about AI and large language models processing that content is the degree to which you can mix and match and rework, reformat, translate, and transform that content to be presented to you, the end user, in the manner of your choice.

So as an author, I kind of hate this, right? Hey, you took my stuff and you mangled it and you presented it in Comic Sans, and how dare you? And that’s where we are. That authors get to create information, but they don’t get to control the manner and means of distribution or presentation or formatting or language of that information.

AP: On the flip side of that, and here I am going to look on the sunnier side of things, which never happens. This may be a pod person version of me. If you, as a content creator, are no longer on the hook for thinking about the publishing pipelines and all of that sort of thing, theoretically, that should free you up to create better content on the back end because you don’t have to think about all those things. Allegedly. I don’t know if it’s happening, but…

SO: It’s very hard as an author to let go of that end product, the target that you’re headed for. But fundamentally, there’s a bigger problem, which is that even if I write the world’s greatest explanation of how to do something, that world’s greatest explanation of how to do something is not being presented to the end user as the thing I wrote. It’s being presented after being run through the transformer, the LLM, the processing that the AI can do when they ask for it. So I could literally write how to do X. And the end user says, hey, tell me how to do X. They are not going to get that chunk of information that I wrote. They’re going to get something reprocessed.

Of course, now we ask the fundamental question, which is, is the reprocessed version going to be better or worse than what I wrote? And the answer is, it kind of depends on whether I am an above average writer with an above average understanding of what that end user wants, or whether I’m a below average writer with a below average understanding of what that end user wants.

AP: To me, it’s almost irrelevant as a content creator. My version is better because if the person receiving the information via the chatbot or whatever thinks that what it’s getting or what they are getting is what they want, that’s all that really matters. That the person on the receiving end of that information gets what they want and fine-tunes it to what they want. If they’re happy with it, then the content creator’s opinion about that is, I hate to say it, immaterial at this point.

SO: Yeah, I kind of hate this timeline because, you know, where does my voice, you know, where does my voice go? And the answer is it’s gone. But you’re right, of course, the purpose of again, what is the purpose of technical and product information that we work on? The purpose is to enable people to use a product successfully. So if shoving it through an AI results in an outcome where that person uses the product successfully, then we’re good.

AP: I don’t disagree.

SO: That’s the purpose of the kind of thing that we produce. I think, though, that looking at this, and this is where I see some of the big challenges going forward. First of all, we have to acknowledge that an enormous percentage of the technical content that’s out there is really bad. Like, terrible. Really, really bad, and might be improved by a little trip through a chatbot that’s gonna render it into actually grammatically correct English. That’s a thing.

AP: Harsh but fair.

SO: Yeah, I think you’re not the only one that’s going to have some bleeping issues in this podcast. But the problem that I see right now is that the metrics that are being used to measure the success of AI are all wrong. We should be measuring the success of various AI layers and chatbots and things based on are people getting what they need?

AP: Yeah. Yeah.

SO: Are they having a successful outcome to whatever it is that they’re trying to do? Is the search or is the process of that conversational, whatever they’re doing, does it get them to the endpoint of, okay, I understand what I need to do and I’m good and I walk away? The metric we actually seem to be using is what percentage of your workflow is using AI? How many people can we get rid of? Because “we’re automating everything with AI” is the wrong metric. The question is, how good are the outcomes?

AP: To me the idea of how much AI versus human effort, there’s a lack of, shall we say, human intelligence being applied here because merely applying AI to something is fundamentally not going to make something that is incorrect, bad, whatever. It’s not going to magically fix it. That’s a huge disconnect for me when you’re talking about measuring outcomes.

Whatever you dump into your large language model, if it is fundamentally bad, as in outdated and incorrect, right now, I am pretty sure merely applying AI to it is not going to fix those two pretty gaping holes. And there’s, I don’t know what it is, people hear AI and they think there’s some magic involved. No, the underpinnings have to be good for that magic to be useful, basically.

SO: And I think all of us have examples of asking the chatbot a question and getting answers that are just flat wrong. Or worse, they look plausible, like they’re in the form of a plausible answer, but then you read it and you read it carefully and you’re like, this doesn’t actually say anything. It’s just word salad. Which, since a chatbot effectively is the average of the database underlying it of content pretty much means that the underlying database of content doesn’t say anything useful on this topic. So I think the place that I kind of go with this is to the question of accountability.

AP: Yes.

SO: Who is legally responsible for the outcomes? Now, pretty clearly, if I or an organization produces a user guide that covers a specific product and there is wrong information in that user guide, the organization is responsible. I mean, it’s your document, you’re responsible. Okay, if I, as an end user, query a public-facing LLM and get the wrong answer for something, and then I proceed to use that in my life, whose fault is that?

Who is at fault when, or, you we saw this with, when the first came out, people were following the map, right, the GPS map, and it would send them off a cliff or it would send them into a construction area and they would drive off the side. Okay, whose fault is that? And the answer was always, well, it’s your fault because look up from the map and don’t drive past the sign that says, not enter construction zone cliff ahead.

AP: Or one-way street. Right, yeah.

SO: But AI doesn’t come with, I mean, it comes with warning labels, right? But we don’t see them. We don’t process them. What we see is a conversation where we say, tell me more about that. And it tells you more about that. And it feels as though you’re talking to a human. And therefore, when you push on something and say, are you sure? And it says yes, because what’s the typical answer when somebody says, are you sure? It’s yes.

Is it actually sure? No, it’s not sentient. So if I query a public-facing LLM, it reprocesses a bunch of content and tells me how to do a thing that is in direct contradiction to what the official user documentation says, whose fault is that? I think it’s mine because I use the public-facing LLM. Now, what if the organization that makes the product puts up a chatbot and I query the organization’s chatbot? How do I do X? And especially if that chatbot is your frontline tech support, like you cannot get to a human. You have to go through the chatbot. I asked the chatbot a question, and it says, do it this way. And it happens to be wrong. Is the organization liable? I don’t know the answer, I think yes, but I’m not sure. And so fundamentally, yeah.

AP: The bottom line here, yeah, we’re talking about governance here. The bottom line is governance and there is, there has to be some human AI interaction here. There has to be these guardrails that you mentioned earlier and that’s where humans have to be involved.

SO: And the better the AI gets, if it’s accurate half the time, then my hackles are up. I know it’s gonna be wrong. It’s wrong all the time. If it’s accurate 80% of the time, I sort of trend it like psychologically, I just assume it’s accurate all the time. So the better they get, the worse the errors are because we don’t expect them.

AP: That’s also dangerous. Yeah, right. Yeah.

SO: I see occasionally, very, very occasionally, I had directions to go somewhere. And the directions were literally, put this address into Google Maps, but don’t do A, B, and C because it’s wrong. Like, the directions to get to this location are incorrect. Do not follow them. Because these days, our assumption is that the mapping apps just work.

AP: And that’s it’s wrong most of the time, but I think part of this governance angle is we have to realize that AI is going to be wrong.

SO: Pretty much just do.

AP: And there are lots of reasons we won’t get into all the reasons that can be wrong. So what are you going to do when it is wrong? How are you going to make sure it’s not wrong? Again, there’s this whole process, this whole governance process that has to be in place. And again, I think this is where human intervention is going to be necessary because I don’t think AI at this point has any business correcting itself in these matters. That seems sort of suboptimal to me.

SO: Hmm. Yeah, I mean, hypothetically, you can tell it to check itself. And certainly there’s some people doing that type of work. I think for me, fundamentally, the takeaways are that, like any other tool, there’s some really useful productivity enhancements that we can and should be taking advantage of. To your point, there’s some really important governance work that needs to be done to ensure that your QA is appropriately scaled to the level of risk of your product. Medical device, very high. Silly gaming app, pretty low. Don’t really care. And we need to think about guardrails and what it means to inject the right kind of content and the various kinds of enablement tools that you can use to do that.

And finally, this issue of AI as a content customer, I think is really, really tricky because it’s a new, from our point as content creators, it is a delivery mechanism, right? Just like a PDF or a piece of HTML or anything else like that. and it’s a delivery mechanism that allows the end user to control how they access the content, which means we have to do way more work around the guardrails of what that means when they query the content and shape it to their own requirements.

AP: Yeah, so things have progressed in the past two years, most definitely, especially in the content space. We’ve seen a lot of improvements. But there are still some big picture things we have to work out. And I think it’s gonna be interesting in the next year or two to see what happens. You briefly mentioned there are some companies who are setting up systems that can do a decent job of checking up on itself. That’s not where everything is right now, but I think the better these systems get, the better the guardrails that get in place, they can start to find out, this is wrong, I need to fix it, or I need to update this with the latest information, let me go get it. So that is starting to happen more and more. I think it will become more part of the LLM to chatbot process, but I don’t think we’re quite there yet. And I’m interested to see what happens next with that sort of scenario.

SO: It’s definitely gonna be interesting. That much I’m sure about.

AP: Yeah, I agree. So we managed to get through this without cursing. So that’s good. I think it turned out to be a more realistic conversation, and we kind of tuned out the hype because that’s what just makes me grit my teeth and sometimes yell at LinkedIn when I see certain promoted posts on LinkedIn that I think are full of you-know-what. So anyways, I think we’ll wrap it up there. Sarah, do you have any final points you would like to sign off with?

SO: I think at the end of the day, when you try and contextualize, like, what is this AI thing and what does it mean for us fundamentally, we can look at some of the other sort of big picture shifts that we’ve made. I’ve been known to pretty dismissively compare it to a spell checker, you know? You can use it and it’ll fix some stuff, but you better check because it doesn’t know the difference between affect and effect, although some of the grammar checkers now maybe they do.

So there’s that, but I think at the end of the day, if you are looking at content strategy, content operations and enterprise level, you really do have to say, okay, where does AI fit into my strategy and how can we employ it productively to do what we need to do inside this organization to produce, manage, deliver the content that we’re working on.

AP: And I think we’re going to wrap up on that very good point. Thank you very much.

SO: Thank you.

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

Questions for Sarah and Alan? Register for our Ask Me Anything: AI in content ops webinar!The post Check in on AI: The true measure of success for AI initiatives appeared first on Scriptorium.

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As AI adoption accelerates, accountability and transparency issues are accumulating quickly. What should organizations be looking for, and what tools keep AI transparent? In this episode, Sarah O’Keefe sits down with Nathan Gilmour, the Chief Technical Officer of Writemore AI, to discuss a new approach to AI and accountability.

Sarah O’Keefe: Okay. I’m not going to ask you why this is the only AI tool I’ve heard about that has this type of audit trail, because it seems like a fairly important thing to do.

Nathan Gilmour: It is very important because there are information security policies. AI is this brand-new, shiny, incredibly powerful tool. But in the grand scheme of things, these large language models, the OpenAIs, the Claudes, the Geminis, they’re largely black boxes. We want to bring clarity to these black boxes and make them transparent, because organizations do want to implement AI tools to offer efficiencies or optimizations within their organizations. However, information security policies may not allow it.

Related links:

Sarah O’Keefe: AI and content: Avoiding disaster
Sarah O’Keefe: AI and accountability
Writemore AI

LinkedIn:

Nathan Gilmour
Sarah O’Keefe

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

End of introduction

Sarah O’Keefe: Hey everyone. I’m Sarah O’Keefe. Welcome to another episode. I am here today with Nathan Gilmour, who’s the Chief Technical Officer of Writemore AI. Nathan, welcome.

Nathan Gilmour: Thanks, Sarah. Happy to be here.

SO: Welcome aboard. So tell us a little bit about what you’re doing over there. You’ve got a new company and a new product that’s, what, a year old?

NG: Give or take, yep.

SO: Yep. So what are you up to over there? Is it AI-related?

NG: It is actually AI-related, but not AI-related in the traditional sense. Right now, we’ve built a product or tool that helps technical authoring teams convert from traditional Word or PDF formats, which would make up the bulk of much of the technical documentation ecosystem and help convert it to structured authoring. Meaning that they can get all of the benefits of reuse, easier publishing, high compatibility with various content management systems. And can do it in minutes where traditional conversions could take hours. So it really helps authoring teams get their content out to the world at large in a much more efficient and regulated fashion.

SO: So I pick up a corpus of 10 or 20 or 50,000 pages of stuff, and you’re going to take that, and you’re going to shove it into a magic black box, and out comes, you said, structured content, DITA?

NG: Correct.

SO: Out comes DITA. Okay. What does this actually … Give us the … That’s the 30,000-foot view. So what’s the parachute level view?

NG: Perfect. Underneath the hood, it’s actually a very deterministic pipeline. Deterministic pipeline means that there is a lot more code supporting it. It’s not an AI inferring what it should do. There’s actual code that guides a conversion process first. So going from, let’s say, Word to DITA, there are tools within the DITA Open Toolkit that allow and facilitate that much more mechanically, rather than trusting an AI to do it. We know that AI does struggle with structure, especially as context windows expand. It becomes more and more inaccurate. So if we feed these models with far more mechanically created content, they become much more accurate. You’re not trusting them to do much more, more of the nuanced parts of the process. So there’s a big difference between determinism and probabilism. Where determinism is the mechanical conversion of something, probabilism is allowing the AI to infer a process. So that’s where we differ is our process is much more deterministic versus allowing the AI to do everything on its own.

SO: So is it fair to say that you combined the … And for deterministic, I’m going to say scripting. But is it fair to say that you combined the DITA OT scripting processing with additional AI around that to improve the results?

NG: Correct. It also expedites the results so that instead of having a human do much of the semantic understanding of the document, we allow the AI to do it in a far more focused task. Machines can read faster.

SO: Okay. And so for most of us, when we start talking about AI, most people think large language model and specifically ChatGPT, but that’s not what this is. This is not like a front-end go play with it as a consumer. This is a tool for authors.

NG: Correct. And even further to that, it’s a partner tool for authors. It allows them to continue authoring in a format that they’re familiar with. Well, let’s take Microsoft Word, for example. Sometimes the shift from Word to structured authoring could be considered an enormous upheaval. Allowing authors to continue authoring in a format that they’re good at and they’re familiar with, and then have a partner tool that allows them to expedite the conversion process to structured authoring so that they can maintain a single source of truth, makes things a little bit better, more manageable, and more reliable in the long run. So instead of having to effectively cause a riot with the authoring teams, we can empower them to continue doing what they’re good at.

SO: Okay. So we drop the Word file in and magically DITA comes out. What if it’s not quite right? What if our AI doesn’t get it exactly right? I mean, how do I know that it’s not producing something that looks good, but is actually wrong?

NG: Great question. And that’s where, prior to doing anything further, there is a review period for the human authors. So in the event that the AI does make a mistake, it is not only completely transparent, so the output, the payload, as we describe it, comes with a full audit report. So every determination that the AI makes is traced and tracked and explained. And then further to that, the humans are even able to take that payload out anyway, open it up in an XML editor. So at this point in time, the content is converted, it is ready to go into the CCMS.

Prior to doing that, it can go into a subject matter expert who is familiar with structured authoring to do a final validation of the content to make sure that it is accurate. The biggest differentiator, though, is the tool never creates content. The humans need to create content because they are the subject matter experts within their field. They create the first draft. The tool takes it, converts it, but doesn’t change anything. It only works with the material as it stands. And then once that is complete, it goes back into another human-centered review so that there are audit trails, it is traceable. And there is a final touchpoint by a human prior to the final migration into their content management system.

SO: So you’re saying that basically you can diff this. I mean, you can look at the before and the after and see where all the changes are coming in.

NG: Correct.

SO: Okay. I’m not going to ask you why this is the only AI tool I’ve heard about that has this type of audit trail, because it seems like a fairly important thing to do.

NG: It is very important because there are information security policies. AI is this brand-new, shiny, incredibly powerful tool. But in the grand scheme of things, these large language models, the OpenAIs, the Claudes, the Geminis, they’re largely black boxes. Where we want to come in is to bring clarity to these black boxes. Make them transparent, I guess you can say. Because organizations do want to implement AI tools to offer efficiencies or optimizations within their organizations. However, information security policies may not allow it.

One of the added benefits that we have baked into the tool from a backend perspective is its ability to be completely internet-unaware. Meaning if an organization has the capital and the infrastructure to host a model, this can be plugged directly into their existing AI infrastructure and use its brain. Which, realistically, is what the language model is. It’s just a brain. So if companies have invested the time, invested the capital in order to build out this infrastructure, the Writemore tool can plug right into it and follow those preexisting information security policies. Without having to worry about something going out to the worldwide web.

SO: So the implication is that I can put this inside my very large organization with very strict information security policies and not be suddenly feeding my entire intellectual property corpus to a public-facing AI.

NG: That is entirely correct.

SO: We are not doing that. Okay. So I want to step back a tiny bit and think about what it means, because it seems like the thing that we’re circling around is accountability, right? What does it mean to use AI and still have accountability? And so, based on your experience of what you’ve been working on and building, what are some of the things that you’ve uncovered in terms of what we should be looking for generally as we’re building out AI-based things? What should we be looking for in terms of accountability of AI?

NG: The major accountability of AI is what could it look like if a business model changes? Let’s kind of focus on the large players in the market right now. There will always be risk with using these large language models that are publicly facing right now. A terms of service change could mean that all of the information that organizations use in order to leverage these tools could become part of a training data set later on down the road. It’s hard to determine what will happen in the future.

So the ability to use online and offline models encourages the development of very transparent tools. So even if the Writemore tool is using a cloud model, I still hold the model almost accountable to report its determinations. It’s not just making things up, so to speak. So there’s a lot that goes into it. There’s a lot that we don’t know about these tools, to be totally honest. We’re still trying to determine what it looks like in a broader picture, in a broader use case. Because the industry is evolving so quickly that, quite simply, we don’t know what’s coming up.

SO: Sounds to me as though you’re trying to put some guardrails around this so that if I’m operating this tool, then I can look at the before and after and say, “Don’t think so.” I mean, presumably it learns from that, and then my results get better down the road. Where do you think this is going? I mean, where do you see the biggest potential and where do you see the biggest risks or opportunities or … I’ll leave it to you as to whether this is a positive or a negative tilted question.

NG: There’s a lot of potential in order to incorporate into organizations that can’t use these tools. Like we had mentioned earlier, organizations are looking into this. Municipalities are looking into AI. But with the state of the more open models right now, it’s very hard to say. So I know I keep circling back around the ability to use smaller language models. They are not only much more efficient to operate, they’re also cheaper, quite simply, to operate. We know that the large language models require enormous computing power. But if provided focused tasks in order to either assist in the classification of topics or fulfill requests in order to pull files, in that regard, you can get away with using smaller levels of compute. And in today’s day and age of computing, the price relativistically is coming down in terms of density is going up. So it’s cheaper to run a model at higher capacities than it ever has been. And it’s only going to improve over time.

So empowering organizations to be able to incorporate these tools in order to streamline their own workflows is going to be very important to them. And on top of that, being able to abide or follow their information security policies only makes the ideas much more compelling. And on top of that, being able to encourage organizations to take full control of their documentation and not necessarily need it to go out of house allows organizations to keep internal costs down while still maintaining the security policies of making sure their content doesn’t leave their organization. There’s always going to be room for partner organizations to come in and help with their content strategy. But the conversion itself can be done in-house using their tools, using their content, using their teams. Which really helps keep costs down, they drive the priority lists, they can do everything that they need to do in order to maintain that control.

SO: Now, we’ve touched largely … Or we’ve talked largely about migration and format conversion. But there’s a second layer in here, right? Which we haven’t mentioned yet.

NG: There is. There’s the ability also during the conversion phase, it’s to have an AI model do light edits. So being able to feed it a style guide to abide by means the churn that we see with these technical teams isn’t as nearly impactful. You can have technical authors still write their content. But if a new person joins the team, they can still author the material just as normally. But then the tool can take over in order to ensure that it’s meeting the corporate style guide, the corporate language, so on, in order to expedite that process. So onboarding time for new team members shrinks as well. So like I said, it’s a very much it’s a partner tool in order to expedite the processing of content, authoring, conversion, migration, getting into a new CCMS and the real empowerment behind it.

SO: And the style guide conformance. So I think we’re assuming that the organization has a corporate style guide?

NG: Assuming, yes.

SO: Okay. Just checking.

NG: But then again, that’s…

SO: Asking for a friend.

NG: Of course.

SO: So if they don’t have one, where’s the corporate style guide come from?

NG: And that could be something that an organization can either generate internally or, as mentioned, work with an external vendor who specializes in these kinds of things in order to build a style guide so that all of their documentation follows the same voice and tone. The better the documentation, the better the trust of the content overall.

SO: So, can we use the AI to generate the corporate style guide?

NG: Probably. Yes. Short answer, yes. Longer answer, not without very close attention to it.

SO: And doesn’t that also assume that we have a corpus of correctly styled content so that we can extract the style guide rules?

NG: There’s a lot more. Yeah.

SO: So I mean, what I’m working my way around to is if we have content chaos, if you have an organization that doesn’t have a style guide, doesn’t have consistency, doesn’t have all these things, can you separate out what is the work that the humans have to do? And what is the work that the machine can do to get to structured, consistent, correct, voice and tone and all the rest of it? How do you get from the primordial soup of content goo to structured content in a CCMS?

NG: Great question. Typically, that starts with education. We work with the teams in order to identify these gaps first. We don’t just throw in a tool and say, “Good luck, hope for the best.” Because we see it time and time again, even in manual conversion processes where that simply doesn’t work. But in taking the time to work with teams, providing them with the skills and the knowledge in order to be successful serves a much longer term positive outcome than ever before. If we educate these teams on what any tool realistically needs, it means the accuracy of the tool goes up in the longer run. So you’re seeing multiple benefits on multiple sides.

So to your point about primordial soup, well, working with teams in order to identify these gaps, these issues, working to identify the standards that should go into the content prior to anything sets not only them up for success in the long run, but also for any tools that they want to implement down the road. It all starts with strong content going in because, as the adage goes, garbage in, garbage out. So if we can clean up the mess prior or work with the teams prior in order to establish these standards, then the quality of output only goes up.

SO: Yeah. And I mean, I think to me, that’s the big takeaway, right? We have these tools, we can do interesting things with them, but at the end of the day, we have to also augment them with the hard-won knowledge of the people. You mentioned subject matter experts, the domain experts, the people inside the organization that understand the regulatory framework or the corporate style guide, or all of those guardrails that make up what is it to create content in this organization that reflects this organization’s priorities and culture and all the rest of it.

NG: And taking the time to educate users is a far less invasive process than exporting bulk material, converting it manually, and handing it back. Because realistically, if we take that avenue or that road, we’re not educating the users, we’re not empowering them to be successful in the long run. All we’ll end up doing is all the hard work, but then in one, two, five years, we run into the same issue where we’re back to primordial soup of content, and it’s another mess. So if we start with the education and the empowerment and then work towards the implementation of tools, the longer-term success will be realized.

SO: Well, I think, I mean, that seems like a good place to leave it. So Nathan, thank you so much. This was interesting and I look forward to seeing where this goes and how it evolves over the next … Well, we’re operating in dog years now, so over the next month, I guess.

NG: So true. And thanks, Sarah, for having me on.

SO: Thanks, and we’ll see you soon.

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

For more insights on AI in content operations, download our book, Content Transformation.The post From black box to business tool: Making AI transparent and accountable appeared first on Scriptorium.

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What happens when AI accelerates faster than your content can keep up? In this podcast, host Sarah O’Keefe and guest Michael Iantosca break down the current state of AI in... Read more »

The post Futureproof your content ops for the coming knowledge collapse appeared first on Scriptorium.

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Your organization’s content debt costs more than you think. In this podcast, host Sarah O’Keefe and guest Dipo Ajose-Coker unpack the five stages of content debt from denial to action.... Read more »

The post The five stages of content debt appeared first on Scriptorium.

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How can global brands use AI in localization without losing accuracy, cultural nuance, and brand integrity? In this podcast, host Bill Swallow and guest Steve Maule explore the opportunities, risks,... Read more »

The post Balancing automation, accuracy, and authenticity: AI in localization appeared first on Scriptorium.

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AI, self-paced courses, and shifting demand for instructor-led classes—what’s next for the future of training content? In this podcast, Sarah O’Keefe and Kevin Siegel unpack the challenges, opportunities, and what it takes to adapt.

There’s probably a training company out there that’d be happy to teach me how to use WordPress. I didn’t have the time, I didn’t have the resources, nothing. So I just did it on my own. That’s one example of how you can use AI to replace some training. And when I don’t know how to do something these days, I go right to YouTube and look for a video to teach me how to do it. But given that, there are some industries where you can’t get away with that. Healthcare is an example—you’re not going to learn how to do brain surgery that someone could rely on with AI or through a YouTube video.

— Kevin Siegel

Related links:

Is live, instructor-led training dying? (Kevin’s LinkedIn post)
AI in the content lifecycle (white paper)
Overview of structured learning content
IconLogic

LinkedIn:

Kevin Siegel
Sarah O’Keefe

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

SO: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

End of introduction

SO: Hi, everyone, I’m Sarah O’Keefe. I’m here today with Kevin Siegel. Hey, Kevin.

KS: Hey, Sarah. Great to be here. Thanks for having me.

SO: Yeah, it’s great to see you. Kevin and I, for those of you that don’t know, go way back and have some epic stories about a conference in India that we went to together where we had some adventures in shopping and haggling and bartering in the middle of downtown Bangalore, as I recall.

KS: I can only tell you that if you want to go shopping in Bangalore, take Sarah. She’s far better at negotiating than I am. I’m absolutely horrible at it.

SO: And my advice is to take Alyssa Fox, who was the one that was really doing all the bartering.

KS: Really good. Yes, yes.

SO: So anyway, we are here today to talk about challenges in instructor-led training, and this came out of a LinkedIn post that Kevin put up a little while ago, which will include in the show notes. So Kevin, tell us a little bit about yourself and IconLogic, your company and what you do over there.

KS: So IconLogic, we’ve always considered ourselves to be a three-headed dragon, three-headed beast, where we do computer training, software training, so vendor-specific. We do e-learning development, and I write books for a living as well. So if you go to Amazon, you’ll find me well-represented there. Actually, one of the original micro-publishers on this new platform called Amazon with my very first book posted there called, “All This PageMaker, the Essentials.” Yeah, did I date myself for that reference? Which led to a book on QuarkXPress, which led to Microsoft Office books. But my bread and butter books on Amazon even today are books on Adobe Captivate, Articulate Storyline, and TechSmith Camtasia. I still keep those books updated. So publishing, training, and development. And the post you’re talking about, which got a lot of feedback, I really loved it, was about training and specifically what I see as the demise of our training portion of our business. And it’s pretty terrifying. I thought it was just us, but I spoke with other organizations similar to mine in training, and we’re not talking about a small fall-off of training. 15, 20% could be manageable. You’re talking 90% training fall off, which led me to think originally, “Is it me?” Because I hadn’t talked to the other training companies. “Is it us? I mean, we’re dinosaurs at this point. Is it the consumer? Is it the industry?”

But then I talked to a bunch of companies that are similar to mine and they’re all showing the same thing, 90% down. And just as an example of how horrifying that is, some of our classes, we’d expect a decent-sized class, 10, a large class, 15 to 18. Those were the glory days. Now we’re twos and threes, if anyone signs up at all. And what I saw as the demise of training for both training companies and trainers, if you’re a training company and you’re hiring a trainer, one or two people in the room isn’t going to pay the bills. Got to keep the lights on with your overhead running 50%, 60%, you know this as a business person, but you’ve got to have five or six minimum to pay those bills and pay your trainer any kind of a rate.

SO: So we’re talking specifically about live instructor-led, in-person or online?

KS: Both, but we went more virtual long before the pandemic. So we’ve been teaching more virtual than on-site for 30 years. Well, not virtual 30 years, virtual wasn’t really viable until about 20 years ago. So we’ve been teaching virtual for 20 years. The pandemic made it all the more important. But you would think that training would improve with the pandemic, it actually got even worse and it never recovered. So the pandemic was the genesis of that spiral down. AI has hastened the demise. But this is instructor-led training in both forms, virtual and on-site. I think even worse for on-site.

SO: So let’s start with pandemic. You’re already doing virtual classes, along comes COVID and lockdowns and everything goes virtual. And you would think you’d be well-positioned for that, in that you’re good to go. What happened with training during the pandemic era when that first hit?

KS: When that pandemic first hit, people panicked and went home and just hugged their families. They weren’t getting trained on anything. So it wasn’t a question of, were we well-positioned to offer training? Nobody wanted training, period. And this was, I think if you pull all training companies, well, there are certain markets where you need training no matter what. Healthcare as an example, they need training. Security, needed training. But for the day-to-day operations of a business, people went home and they didn’t work for a long time. They were just like, “The world is ending.” And then, oh, the world didn’t end. So now they’ve got to go back to work, but they didn’t go back to work for a long time. Eventually people got back to work. Now, are you on-site back to work or are you at home? That’s a whole nother thing to think about.

But just from a training perspective, when panic sets in, when the economy goes bad, training is one of the first things, you get rid of it. Go teach yourself. And the teaching yourself part is what has led to the further demise of training, because you realize I can teach myself on YouTube. At least I think I can. And I think when you start teaching yourself on your own and you think you can, it becomes, the training was good enough. So if you said, “Let’s focus on the pandemic.” That’s what started it, the downward spiral. But we even saw the downward spiral before the pandemic, and it was the vendors that started to offer the training that we were offering themselves.

SO: So instead of a third-party, certainly a third-party, mostly independent organization offering training on a specific software application, the vendors said, “We’re going to offer official training.”

KS: Correct. And it started with some of these vendors rolling out their training at conferences. And I attended these conferences as a speaker. I won’t name the software, I won’t name the vendor, but I would just tell you I would go there and I would say, “Well, what’s this certificate thing you’re running there?” It’s a certificate of participation. But as I saw people walking around, they would say, “I’m now certified.” And I go, “You’re not certified after a three-hour program. You now have some knowledge.” They thought they were certified and experts, but they wouldn’t know they weren’t qualified until told to do a job. And then they would find out, “I’m not qualified to do this job.” But that certificate course, which was just a couple of hours by this particular vendor, morphed into a full day certificate. They were charging now a lot of money for it, which morphed into a multi-day thing, which now has destroyed any opportunity for training that we have. And that’s when I started noticing a downward spiral. Tracking finances, it would be your investments going down, down, down, down this thing. It’s like a plane, head and nose down.

SO: And we’ve seen something similar. I mean, back in the day, and I do actually… So for those of you listening at home that are not in this generation, PageMaker was the sort of grandparent of InDesign. I am also familiar with PageMaker and I think my first work in computer stuff was in that space. So now we’ve all dated ourselves. But back in the day we did a decent amount of in-person training. We had a training classroom in one of our offices at one point.

Now, we were never as focused on it as you are and were, but we did a decent business of public-facing, scheduled two-day, three-day, “Come to our office and we’ll train you on the things.” And then over time, that kind of dropped off and we got away from doing training because it was so difficult. And this is longer ago than you’re talking about. So the pattern that you’re describing where instructor-led in-person training, a classroom training with everybody in the same room kind of got disrupted a while back. We made a decent living doing that for a long time and there was-

KS: Made a great living doing that. Oh, my God. That was the thing.

SO: But we got away from it, because it got harder and harder to put the right people in the right classes and get people to travel and come to us. So then there’s online training, which we kind of got rid of training. You sort of pivoted to online/ virtual. And then ultimately, the pandemic has made it such, from my point of view, that the vast majority of what we do in this space is custom. We’re doing a big implementation project. We do some custom training that might be in-person, on-site, but much more often it is online, live online instructor-led, but custom. Because all of the companies that we’re dealing with, even if people did return to office, very much they’re fragmented, right? It’s two people here and five people there, and four people there and one in every state. And so, bringing them all together into a classroom is not just bring the instructor in, but bring everybody in and it costs a fortune. And that’s before we get into the question of, can they get across the borders and can they travel?

There’s visa issues, there’s admin issues, people have caregiving responsibilities, they can’t travel. There’s a whole bunch of stuff that goes into actually relocating from point A to point B to do a class at point B. So fine. Okay. So along comes the pandemic that really pushes on the virtualization, right? The virtual stuff. And then you’re saying the vendors get into it and they are clawing back some of this revenue for themselves. They’re basically saying, “We’re going to do official vendor-approved stuff, which then makes it very difficult as a third-party, because you have to walk that line, and I’ve been there, you have to walk that line between, we are delivering training on this product which belongs to somebody else, and we can be maybe a little more forthright about the issues in the product because it’s not our product. So we’re just going to say, “Hey, there’s an issue over here. It doesn’t really work. Do it this other way.” Not toeing the official party line. Okay, so we have all of that going on and all of those challenges already. And now along comes AI. So what does AI do to this environment that you’re describing?

KS: It further destroys it. I’ll give you an example. My blog, Typepad, we received an email September 1st, 2025, and we’re recording this September 4th, 2025, okay? So three days ago I got an email saying, “Hello, we’re shutting down. Sorry.” And I’m like, “What? Yeah, you’ve got 30 days to get your stuff out of here.” Basically being kicked out of your apartment or your house. So I’m like, “All right, well, go to AI and I asked AI, what is the top blog software?” They said, “WordPress.” Love it or hate it, okay. So I went to WordPress. I had no idea how to use WordPress. I had no staff available to help me. So I had to get my stuff out of Typepad and on and on it went. I went to AI, ChatGPT specifically, and I said, “Teach me how to use WordPress,” and specifically how to get my crap out of TypePad. I say crap, my stuff out of TypePad. In a matter of what? Two days I had everything transferred over.

So, didn’t need training, otherwise I would’ve had to go to training to learn how to do that and I didn’t have to. So that’s an example of there’s probably a training company out there that’d be happy to teach me how to use WordPress. I didn’t have the time, I didn’t have the resources, nothing. So I just did it on my own. That’s one example of how you can use AI to replace the training. There’s other examples of training that is not just good enough, it’s fine. It’s good. It’s good. It’s not lacking. When I don’t know how to do something these days, I go right to YouTube and look for a video to teach me how to do it. So given that, some industries where you can’t get away with that. Healthcare as an example, you’re not going to learn how to do brain surgery that you could rely on with AI or video through YouTube.

SO: We hope.

KS: We hope. “Hey, relax. I know this is your first time, Sarah, I’m your surgeon. I watched a video yesterday, I feel pretty good about it as I grab that saw.” I don’t believe you’re going to be comfortable with that. So listen, it’s bad enough. And you mentioned the vendor that is now offering training. So vendor pullback, they want that for a revenue source. This particular vendor is using it as a revenue tool, but there’s also vendors out there that are actively stopping you from offering training classes, and on it goes.

SO: Yeah, I do want to talk about that one a little bit. I know nothing about the specifics of your situation, but this is a losing battle. Because you were just talking about YouTube, I was doing some research for a very, very, very large company that makes farm equipment and I went looking for their content. And they had content on their website, it was like type in your product name or product number and it would give you the official user manual, which was of course ugly and terrible. But I discovered that if you typed in something like, “How do I fix the breaks on my X, Y, Z product?” It would take you to YouTube. And it would take you to this YouTube channel that had a lot of subscribers and was in fact not at all the official company YouTube channel.

KS: It was a dude who was working on it?

SO: It was a dude in Warsaw, North Carolina, which is not the same as Warsaw, Poland. It is a tiny, tiny, tiny little place, mostly known for me as being halfway between where I am and the beach. It’s where we stop to get gas and summer peaches and corn from the farm stand and fried chicken on our way to the beach, because that’s the thing we do. That’s where Warsaw is. It has a population of, I don’t know, 3,000 maybe.

KS: Okay, yeah.

SO: I have no idea. But there’s some guy who works for the dealership there who’s making these videos explaining how to do maintenance on these, in this case tractors, and he has got the audience. Not the official website, which by the way does not have a YouTube channel that I’m aware of, or at least that I could find now. This was five, 10 years ago. It has been a while. But so, there’s all this third-party content out there and there’s this ecosystem of content because it’s digital. You can’t really control that unless, we were talking about this earlier, unless you’re doing something like nuclear weapons, intelligence work, or maybe brain surgery. You can probably control those things. That’s about it. Clearly things are changing and not for the better. If your revenue is built on instructor-led, whether in-person or online, it sounds as though things are changing and not for the better in that space specifically, unless we’re training on brain surgery, which most of us are not. So what’s the path forward?

KS: I’m thinking about it, actually.

SO: I am not signing up for you to do my brain surgery.

KS: I need someone to practice on. Sarah, let me know if you’re available.

SO: Oh, I’m so sorry, you’re breaking up. I can’t hear you. Okay, so what does the path forward look like? I mean, what does it mean to be inside this disruption and where do you go from here?

KS: Okay, so every training company that I have contacts in, they’re all down significantly. The ones that are surviving have government contracts.

SO: Mm-hmm.

KS: And that is to develop training in all of its guises, that primarily they’re seeing a call for virtual reality training. That’s really, really hot right now. But not the virtual reality training that you can create with the Captivates and the Storylines of the world. That’s too lowbrow. They’re talking about immersive, almost gamification, where you build a world. So if that’s your expertise, you can create training in that. That’s what people want. It looks like augmented reality and virtual reality.

I can’t see it. Maybe I’m of a certain age that I’m like, “I’m not putting goggles on to take my training.” But that is pretty popular with other generations. So you can’t ignore it, I think, embrace it. So government contracts, if you can get that, you’ll be okay in the training business. Several of my colleagues have actually done that. So that’s a leg up. The other is to embrace asynchronous training and put your materials out there that live now forever. So I ignored for years these providers of asynchronous training where you put your content there and they sell it for you. I’ve got five classes on Udemy now, and each of them sells pretty well.

Matter of fact, my Captivate Udemy is one of their bestsellers. That does not translate into offsetting the revenue lost from your training gigs when you were bringing in six, seven, $800 a person for a training class. Our prices were between $695 and $895 per person to take a public class, but it certainly does bring in some revenue. So if you have the ability to create the asynchronous training, the video training, and make it really, really good training, really impactful, then that’s going to help you stay in the game as long as you can. I also think embracing AI versus getting under the covers and just, “I don’t want to see it,” is not the way to go.

I now use AI as a tool. I don’t think it replaces me, I think that I have more to offer in guiding the course than AI, but it gives me a nice, “Get me started here.” Maybe you’ve got a little writer’s block, maybe just getting started. It’s a beautiful day out, I can’t get started. Have AI start, you’ve started up. But if you’re going to go that route and you have AI make suggestions, you better fact check it. And just as an example, I was just curious, I asked ChatGPT to create an exam for Articulate Storyline. That is a tool I know really well, I’ve written exams for Storyline and Captivate and Camtasia. I said, “Write an exam. I want to see what you come up with.” And some of the questions were actually worded better than what I had done. They were very similar questions. And I go, “I kind of like the way you, AI, did that.” Which was kind of a bummer. But I would say a good 30% of what I read, while it was well-written, was completely wrong.

SO: Yes, confidently wrong.

KS: Yes, it was confidently wrong. Asking questions, “When you do this on storyline, what is the correct thing? What do you do?” And Storyline doesn’t do that thing. They were talking about Rise as an example. I’m like, “You’ve gone and combined Rise with Storyline.” So if you’re going to use AI, it’s the way you ask the question, your prompts. So get some training on engineering your prompts and fact-checking what you get from those prompts. But I use AI every day in my writing to make sure I don’t have grammar issues. So I’ll tell AI, “Check this for clarity and grammar.” So it’s my words, but it now is saying, “Well, there’s a couple typos, I fix that. And a couple of dangling modifiers, I fix that.” So it makes me feel like I’m writing better. But do keep in mind, if you put your stuff into ChatGPT, it’s now part of this mass of stuff that other people are going to get access to.

So you can’t copyright anything that you put in AI. I wrote a book about copyright and training materials and things to think about, because we have a lot of people finding an image of a nice puppy on Google and using it in their training, and that puppy was copyrighted. So anything you do on AI, any photos that get created, any artwork, anything, any writing can’t be copyrighted because only a human can get a copyright. So that’s something to think about. If you have something really, really good, you really didn’t create that, so you can’t copyright it.

You’re going to have to adapt. You’re going to have to adapt or you’re going to fail in the training industry, again, unless it’s very specific niche markets, or as you mentioned, custom training. If you don’t adapt, you’re going to fail. And that adaptation is going to be, embrace AI asynchronous training to put your training out there, available 24 hours a day, seven days a week when you can’t do it. And that’ll offset getting these onesies and twosies in your class.

SO: And it removes the time-bound, I have to set aside these two hours or these four hours of this day to be in the classroom, whether virtual or not if it’s live. I do think that this idea that we’re going to see a split between things that go higher and higher end that people are willing to pay nearly anything for versus the low-end where the price is going… There’s going to be downward pressure on the price for all the low-end stuff, because the barrier to entry to producing asynchronous training is pretty minimal and it gets lower every single day because there’s so many people out there that can potentially do that.

KS: Anybody can hang out a shingle and say that they’re an expert. So I mean, it’s the credentials of the trainer too, I think. Who is the person that’s teaching this? Is it what we call it, Chuck with a truck? Is it Chuck with a truck? Or is it someone who has actually done this? I wouldn’t want to get trained on handling my content by someone who hadn’t done it. I’d want you to handle that, right? So a content strategy. “I mean, who came up with that strategy? Oh, Bob. Has Bob ever done it? No, but he feels good about it. No, I want to get a Sarah who’s done it for years and years and years.”

SO: Yeah, I mean that’s an interesting point though, because at the end of the day, if you commoditize/ productized training, you’re going to have a product as the asynchronous training that’s a package, and you get what you get. When it’s live with an instructor, you’re going to get that instructor on that day in that context. They’re feeling good, they’re feeling bad. The classroom dynamics are good or bad or weird. Every experience is going to be different. Whereas with async, it’s always going to be the same. I mean, barring internet connectivity or something, as the learner, you’re going to get a consistent experience. Now, it’s not going to be the best possible experience, right? Because the best possible experience is you’re in a group with some other people in a room with an amazing instructor.

KS: That is the best.

SO: That is the best.

KS: There’s good too-

SO: It costs the earth.

KS: Yeah, there’s good too, the asynchronous training, because it’s always the same, it’s going to be consistent. How many times have you read a live class and the attendees, one of the attendees just spoiled the sauce? And you’re reminding me now, a colleague of mine, they were doing their certification as a certified technical trainer, CTT, and back in those days, you actually had to record yourself teaching.

SO: Oh, yes, there was a VHS tape of me and kids. That is video, pre-digital video.

KS: That is correct. VHS tape. And I had to do the same thing, but I remember for this one colleague of mine, and the students in this classroom, fake classroom, were other trainers that were also getting the recording done. And I remember she was being recorded and it was over her shoulder looking at the students, because she had to show the students. And one of these students, she made a comment that she knew was correct, and the student shook her head, “Nope, nope. That’s not right. Nope.” And the trainer is now, “What are you doing? Why are you shaking your head no and contradicting one of us? How about just nod?” And so, at some point God had turned around where the students started shaking their head, but realize, “Oh my God, you’re defeating all of us in this room.”

So yes, that was to your point, that the training can vary wildly in a live class, whether it’s virtual or on-site, based on the attendees. Because listen, I’ve been teaching Captivate since it was called RoboDemo, so years and years and years and years, and no class has ever been the same. No two classes are the same and it’s all based on the dynamics of the students in my live class. And you get one person in there who is stuck, can’t move forward, file open is a mystery. Go to the file menu, choose open. How do you do that? Okay, mouse skills. All of that can either derail or can help your class. Funny moments, whatever they may be. But asynchronous training, if you do it right, is always consistently good. The problem is there’s no live interaction. So you can’t ask that instructor, “Well, what do you think about this? What do you think about that?”

So yeah, you made me laugh when you mentioned that, that the dynamics of your live class, you better be fast on your feet to be a live trainer. So I am not saying, if you’re going to teach virtually, you shouldn’t know how to do it. Because listen, I think you’ll agree, there is a vast difference between teaching a class live on-site versus live online, or God forbid, live online and live on-site, where you’re doing both at the same time. Or if you’re going to do blended learning, you’ve got to mix all three, you better know what you’re doing as a facilitator and a trainer to do that or you’ll fall flat on your feet.

You’ll hear all kinds of complaints that people who teach these live classes on-site that now incorporate virtual, and they ignore the virtual audience completely. So the virtual audience is not included in the training, they feel like they’re watching a recording. So you’ve got to know how to engage this audience. I’m actually really stunned, Sarah, that conferences still survive on-site. We mentioned a couple of times before we turned on this recording, why are those conferences live on-site? People are going there to network face-to-face. I guess that’s the big one, but not the content that you’re learning. That content could have been taught virtually.

SO: Yeah, I’ve had the position for a long time that the most important part of a conference is the hallway track, right? The conversations at lunch, in the hallway, and in the exhibit hall and everywhere else. There’s a couple that are doing online in addition to in-person, and typically the-

KS: ATD does that. Yeah, does a good job at that. Yeah.

SO: Yeah, LavaCon is doing that, they’re coming up. But yeah, they have an online track with a chat, a pretty lively chat, and then they also have the in-person version if you can get there in-person.

KS: Which is successful only if the facilitator addresses the online chat, if the facilitator addresses someone who’s virtual. Yeah.

SO: And fun fact, Phylise Banner has been running that for years and years and years and has done a fantastic job of exactly that, of making sure that the online people get into the conversation, even when there’s 200 people in the room and another couple hundred on the chat, and she’s making sure that they get their questions into the discussion. Okay, so that was cheerful, and that made me feel better, because the first half hour of this was super not encouraging. So I think I’m going to close us out there because I’m pretty sure we could go on forever, but let’s leave it there. Kevin, thank you for coming and for giving us the inside information on what’s happening in training land. And hopefully I’ll see you again somewhere in-person at a conference.

KS: Or virtual, with the camera is fine. So yeah, great working with you, Sarah. Thanks for having me.

SO: Great to see you. Bye.

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

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What if you could escape copy-and-paste and build dynamic learning experiences at scale? In this podcast, host Sarah O’Keefe and guest Mike Buoy explore the benefits of structured learning content. They share how organizations can break down silos between techcomm and learning content, deliver content across channels, and support personalized learning experiences at scale.

The good thing about structured authoring is that you have a structure. If this is the concept that we need to talk about and discuss, here’s all the background information that goes with it. With that structure comes consistency, and with that consistency, you have more of your information and knowledge documented so that it can then be distributed and repackaged in different ways. If all you have is a PowerPoint, you can’t give somebody a PowerPoint in the middle of an oil change and say, “Here’s the bare minimum you need,” when I need to know, “Okay, what do I do if I’ve cross-threaded my oil drain bolt?” That’s probably not in the PowerPoint. That could be an instructor story that’s going to be told if you have a good instructor who’s been down that really rocky road, but again, a consistent structure is going to set you up so that you have robust base content.

— Mike Buoy

Related links:

AEM Guides
Overview of structured learning content
CompTIA accelerates global content delivery with structured learning content (case study)
Structured learning content that’s built to scale (webinar)

LinkedIn:

Mike Buoy
Sarah O’Keefe

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky; you have to convince me that making the change is less risky than not making the change.

End of introduction

Sarah O’Keefe: Hi everyone, I’m Sarah O’Keefe. I’m here today with Mike Buoy. Hey, Mike.

Mike Buoy: Good morning, Sarah. How are you?

SO: I’m doing well, welcome. For those of you who don’t know, Mike Buoy is the Senior Solutions Consultant for AEM Guides at Adobe since the beginning of this year of 2025. And before that had a, we’ll say, long career in learning.

MB: Long is accurate, long is accurate. There may have been some gray hair grown along the way, in the about 20-plus years.

SO: There might have been. No video for us, no reason in particular. Mike, what else do we need to know about you before we get into today’s topic, which is the intersection of techcomm and learning?

MB: Oh gosh, so if I think just quickly about my career, my background’s in instructional design, consulting, instructor, all the things related to what you would consider a corporate L&D, moving into the software side of things into the learning content management space. And so what we call now component content management, we, when I say we, those are all the different organizations I’ve worked for throughout my career, have been focused in on how do you take content that is usually file-based and sitting in a SharePoint drive somewhere, and how do you bring it in, get it organized so it’s actually an asset as opposed to a bunch of files? And how do you take care of that? How do you maintain it? How do you get it out to the right people at the right time and the right combination, all the rights, all the right nows, that’s really the background of where I come from.

And that’s not just in learning content; at the end of the day, learning content is often the technical communication-type content with an experience wrapped around it. So it’s really a very fun retrospective when you look back on where both industries have been running in parallel and where they’re really starting to intersect now.

SO: Yeah, and I think that’s really the key here. When we start talking about learning content, structured authoring, techcomm, why is it that these things are running in parallel and sitting in different silos? What’s your take on that? Why haven’t they intersected more until maybe now we’re seeing some rumblings of maybe we should consider this, but until now it’s been straight up, we’re learning and your techcomm, or vice versa, and never the twain shall meet, so why?

MB: Yeah, and it’s interesting, when you look at most organizations, the two major silos that you’re seeing, one is going to be product. So whether it’s a software product, a hardware product, an insurance or financial product, whatever that product is, technical communication, what is it? How do you do it? What are all the standard operating procedures surrounding it? That all tends to fall under that product umbrella. And then you get to the other side of the other silo, and that’s the hey, we have customers, whether those customers are our customers or the internal customers, our own employees that we need to trade and bring up the speed on products and how to use them, or perhaps even partners that sit there. And so, typically, techcomm is living under the product umbrella, and L&D is either living under HR or customer success or customer service of some sort, depending on where they’re coming from.

Now in the learning space you, over the last probably decade or so, seeing where there’s a consolidation between internal and external L&D teams and having them get smarter about, what are we building, how are we building it, who are we delivering it to, and what are all those delivery channels? And then when I think about why are they running in parallel, well, they have different goals in mind, right? techcomm has to ship with the product and service and training ideally is doing that, but is often, there’s a little bit of a lag behind, “Okay, we ship the thing, how long is it before we start having all the educational frameworks around it to support the thing that was shipped?”

And so I think leadership-wise, very different philosophies, very different principles on that. techcomm, very much focused on the knowledge side of things. What is it? How do you do it? What are all the SOPs? And L&D leans more towards creating a learning experience around, “Okay, well here’s the knowledge, here’s the information, how do we create that arc going from I’m a complete novice to whatever the next level is?” Or even, I may be an expert and I need to learn how to apply this to get whatever new changes there are in my world and help me get knowledgeable and then skilled in that regard.

So I think those are kind the competing mindsets and philosophies as well as, I won’t say competing, but parallel business organization of why we don’t usually see those two. And if we think about from a workflow perspective, you have engineering or whoever’s building the product, handing over documentation of what they’re building to techcomm and techcomm is taking all of that and then building out their documentation, and then that documentation then gets handed to L&D for them to then say, “Well, how do we contextualize this and build all the best practices around it and recommendations and learning experiences?” So there is a little bit of a waterfall effect for how a product moves through the organization. I think those are the things that really contribute to it being siloed and running in parallel.

SO: Yeah. And I mean many, many organizations, the presence of engineering documentation or product design documentation is also a big question mark, but we’ll set that aside. And I think the key point here is that learning content, and you’ve said this twice already, learning content in general and delivery of learning content is about experience. What is the learning experience? How does the learner interact with this information and how do we bring them from, they don’t understand anything to they can capably do their job? The techcomm side of things is more of a point of need. You’re capable enough but you need some reference documentation or you need to know how to log into the system or various other things. But techcomm to your point, tends to be focused much less on experience and much more on efficiency. How do we get this out the door as fast as possible to ship it with the product? Because the product’s shipping and if you hold up the product because your documentation isn’t ready, very, very bad things will happen to you.

MB: Bad, bad, very bad.

SO: Not a good choice.

MB: It’s not a good look. It’s not a good look.

SO: Now, what’s interesting to me is, and this sort of ties into some of the conversations we have around pre-sales versus post-sales marketing versus techcomm kinds of things, as technical content has moved into a web experience, online environment, and all the rest of it, it has shifted more into pre-sales. People read technical documentation, they read that content to decide whether or not to buy, which means the experience matters more.

And conversely, the learning content has fractured into classroom learning and online instructor led and e-learning a bunch of things I’m not even going to get into, and so they have fractured into multi-channel. So they evolved from classroom into lots of different channels for learning where techcomm evolved from print into lots of different channels, but online and so the two are kind of converging where techcomm needs to be more interested in experience and learning content needs to be more interested in efficiency, which brings us then to, can we meet in the middle and what does it look like to apply some of the structured authoring principles to learning content? We’ve talked a lot about making techcomm better and improving the experience. So now let’s flip it around and talk about how do we bring learning content into structured authoring? Is that a sensible thing to do? I guess that’s the first question: is that a sensible thing to do?

MB: Yeah, and here’s the thing that I like to keep in mind when talking about structured authoring, the context for why in the world would we even consider it? And when I think of traditional L&D training courses, whether it’s butts in seats at an instructor-led training event, whether I’m actually in a physical classroom or I’m sitting virtually in a Zoom class for example, or it’s self-paced e-learning, so much great content is built and encapsulated in that experience and is not able to be extracted out.

My favorite example of talking about this is I’ve got a big truck sitting in my driveway, I need to change the oil on it, it’s time. If it’s the first time I’ve ever changed oil, absolutely, I want all the learning. I want the scaffolding. I want the best practices, how I’m going to set up my work environment, the types of tools. How I’m going to need to deal with all the fluids, what I need to purchase. I’m going to dive into all that. In the real world, university of YouTube, I’m going to go watch videos on this and there’s going to be some bad content, there’s going to be some gems, and I’m going to pay attention to the ones that are good.

Now as I go from a novice, I’m going to build that knowledge of how to do it, I’m going to apply that knowledge. I’m actually going to go do it, now I’m probably going to make a mess and make mistakes my first time through, but that’s also building experience. So I’m moving from novice to knowledgeable to building skills to as I do it more and more, I move into that realm of being experienced.

Now as you move further up that chain, you need less and less support to the point where I’m like, “Crap, which oil do I need to buy? What are the torque specs on my drain plug?” I really only need three or four data points to do the job now. So that’s where as I move from a novice to an expert, I need to be able to skim and find exactly what I need in the moment of need, the just enough information. And so I’ll take the oil changing experience and let’s take that to any product or service training your customers, the people who are consuming your content are going through the same thing.

So learning-wise, why structured? Once I get to the expert level of things, I am not going to log into the LMS and I’m not going to launch that e-learning course, and I’m not going to click next 5 to 10 to 20 times to get to the answer that has the specification tables of, here’s what I need and what I need to do in order to accomplish the task at hand. Everybody’s nodding their head. Every time I ask, “When was the last time you logged into the LMS to get an answer to a question?” The only time I’ve ever had somebody go, “Oh, me,” it was actually an LMS administrator.

So learning is great at creating that initial experience, but their content’s trapped. It is stuck inside that initial learning experience. So getting back to the question, why structured authoring? Well, if you move to a structured authoring where you’re taking your content and building it in chunks, yes, you can create that initial learning experience where you’ve assembled that very crafted, we’re taking you from novice, getting you the knowledge, giving you the opportunities to practice the skill in a safe environment and fail well and learn from that and get you to a place where you move from novice to skilled. And then over time, this is where a lot of the L&D in general, because their content’s trapped in that initial learning experience, they can’t easily extract that information out and provide the things people need to move from skilled to experienced and experienced to mastery.

So that’s where when I think about, “Well, what does techcomm do really well? Techcomm supports that, I’ve got enough skills to do the job and I need to reference the very specific information, or the SOP, I’m on step four, I forget what are the things I need to enter in to get through step four, I can hop over the documentation and find that. So techcomm has figured out the structured authoring part. You mentioned creating new varied experiences for getting to the technical communication. Multi-channel delivery, I want to hop on and hit my search or hit my AI chatbot and pull up the information and just get me just enough to get through the tasks that I’m doing.

Learning’s still often stuck, if we equate it to the tech communication side, they’re still stuck in the, “I’m hand building a Microsoft Word based 500 page user guide that to get anything out of that, it’s a lot of work to build it, it’s a lot of work to maintain it, and it’s not easy to extract that information out to use it for other things.”

So why structured authoring, feature proof your content, make it more flexible. You’ve invested so much time and energy creating great content, great experiences, why not make it so it’s modular so you can pull things out and create new and different ways of consuming that content and delivering it in different bite size bits and pieces along the way?

SO: And I guess we have to tackle the elephant in the room, which is PowerPoint. So much learning and training, in particular, especially classroom training, is identified with an instructor standing at the front, running through a bunch of slides. And we like to say that PowerPoint is the black hole of content, that’s where content goes to die, and once it goes in, you never get it back out. So what do we say to the people that come in and they’re like, “You will pry PowerPoint from my cold, dead hands.”

MB: Such a great question. I’ll jokingly refer to PowerPoint as “My precious.” Here’s the reality: PowerPoint is not the knowledge chunk. That knowledge is actually sitting in the head of the instructor, the PowerPoint is providing the framework for them to deliver and impart that knowledge and impart those best practices. It’s there to provide guardrails so that it’s done in a consistent fashion, and there’s a bare minimum amount of structure that… There’s a bullet point there, they’re going to talk about it. The degree to the quality of how they’re going to talk about it and present it is going to vary based on the person delivering the content. So if you’ve got a bunch of PowerPoint slides, you don’t necessarily have all of your training material well documented. Now, if you’ve got parallel instructor guides and student guides that talk about the details of what should be said behind those bullet points, you’re a lot closer to having that information.

So why structured authoring? Well, it’s kind of, again, the good thing about structured authoring is you have a structure. You have a, if this is the concept that we need to talk about and discuss, here’s all the background information that goes with it. So with that structure comes consistency, and with that consistency, that means that you have more of your information and knowledge documented so that it can then be distributed and repackaged in different ways. Because if all you have is a PowerPoint, you can’t give somebody a PowerPoint when they’re in the middle of an oil change and say, “Here’s the bare minimum you need.” When I need to know, “Okay, what do I do if I’ve cross-threaded my oil drain bolt?” That’s probably not in there. That may be an instructor story that’s going to be told if you have a good instructor who’s been down that really rocky road. But again, structure and being consistent about it is going to set you up so that you have robust base content.

We’ve got Legos in the house, I got two boys. Gosh, I’ve stepped on so many Legos in my life, it’s ridiculous. But the Lego metaphor works because you have a more robust batch of Legos that you can create new creations from, rather than a limited set if you’re only doing PowerPoint.

SO: And because you’re nice, and I’m not, I’ll say this, we can produce PowerPoint out of structured content, that is a thing we can do. I’m not saying it’s going to be award-winning, every page is a special snowflake PowerPoint, but we can generate PowerPoint out of structured content. And if you’re using it as a little bit of an instructor support in the context of a classroom or live training, that’s fine.

A lot of the PowerPoint that we see that people say, “This is what I want, and if you don’t allow me to do this,” and there’s this rainbow unicorn traipsing across the side of the page kind of thing, and no, we can’t do one-off slides, we can’t do crazy every slide is different stuff, but the vast majority of the content that I see that is PowerPoint based and kind of all over the place is not actually effective. So it’s like, this is not good. We have the same issue with InDesign. We see these InDesign pages that are highly, highly laid out, and it’s like, “We need this.” Well, why? It’s terrible. I mean, it’s awful. What are you doing here? No, we can give you a framework.

MB: Now, you’re telling somebody that their baby’s ugly when you say that, that’s somebody’s baby.

SO: I would never tell somebody that their baby is ugly, but I have seen a lot of really bad PowerPoint. Babies are wonderful.

MB: Yes.

SO: It’s so bad. So why does the PowerPoint exist, and how do we work around that? And also, are you delivering in multiple languages? Because if so, we need a way to localize this efficiently, and we’re right back to the structured content piece.

MB: And as soon as you’re talking about with PowerPoint, it is the poster child of pixel-perfect placement. As soon as I take a perfectly placed pixel product and have to translate it from English to let’s just say French, just the growth of the text alone, now I’ve got what was a perfectly placed pixel layout, my beautiful slide is now a jumbled mess. So just because you can doesn’t mean you should. And the thing is, PowerPoint and Microsoft Excel are the duct tape that runs business. Everybody has it. Everybody uses it. That’s the reality.

Now, the thing is, does everything have to be structured? I don’t believe it has to be. They are absolutely the one-off snowflake instances where, you know what? PowerPoint is the exact right tool for the job. Maybe it’s the one-off presentation that really is not going to see any reuse, it’s expendable, it’s disposable. We need to get the information communicated quickly. I’m going to fire it PowerPoint. I’m going to use it as my, I’m going to do air quotes, “My throwaway content” because it’s something that is short, sweet, and needs to be communicated, absolutely. I’m not, and I don’t think you are either, saying that PowerPoint has to go away, it’s the when is it appropriate and when is it not?

SO: I mean, I am the queen of the one-off can never be reused content being developed in, now I refuse to use PowerPoint, but in slideware for a short presentation, so the next one of you that’s listening to this and walks up to me at a conference and says, “Oh, is your presentation structured content?” No, it is not. Thank you for asking. Why isn’t it structured? Because I don’t reuse it at scale. Because in fact, every presentation at every conference is a special snowflake and has been lovingly handcrafted by me to deliver the message that I need, the context that I need, potentially the language, but to your point, even if I’m not localizing the presentation itself, the cultural context matters. So if my audience is largely English-speaking or primarily English, or… I mean, we’re going to Atlanta for LavaCon, that is going to be mostly a US-based audience, and maybe we get some Canadians, eh. And other than that… But mostly US and a US context. Will I be using excessive amounts of images from the Georgia Aquarium? Yes, I will.

Now, when I go to conferences elsewhere, so let’s take tcworld in Germany in November, that audience is, we’re delivering content in English, and the audience ranges from perfect English speakers to sort of barely hanging on. And so my practice at a conference like that is to include more text on my slides because if I include some additional text, it gives the people that are not quite as comfortable in English, a little bit more scaffolding to hang onto as they’re trying to follow my ridiculous analogies and insane references to cultural things. I also do try to pay attention to the kinds of words that I’m using and the kinds of idioms that I’m using so that they’re just not completely lost in space or things are not coming from left field or whatever. So the context matters, and no, my presentations are not structured.

But pulling this back, let’s talk about the potential. So when we look at learning content and you think about saying, okay, we’re going to structure our learning content or we’re going to structure some of our learning content, what does that mean in terms of what gets enabled? What are the possibilities? What are the things that you can do with structured learning content that you cannot do in unstructured, by which I mean PowerPoint, but unstructured, locked-in content? If we break this stuff into components and we deliver on structured learning content, what are the ideas there? What are the possibilities?

MB: Well, as you’re explaining the PowerPoint point of view, a word that came up a few times was scale. I’m not having to do it at scale. Effectively, it is a one-off. Yes, I’m going to personalize it for the audience, and the degree of personalization and customization that you’re doing per conference, per audience, per default language that they’re speaking, you’re able to scale that to the degree that you need to. There’s no need for you to put your content in data and localize it and do all the things that you need to do. So it’s really that word at scale, that, I think, is the key word.

It’s when you hit that tipping point where the desktop tools that you’re using today, and we can say this with tech communications as well, I was using Word and Excel and copy and pasting and keeping things in sync, it works until you get to a tipping point where the scale no longer is sustainable. That same exact problem exists in training. So when you’re looking at things like, I have my training content that when I deliver it in California, I have to put my Prop 65 note in everything because Lord forbid, as soon as I step across the state line into California, everything that’s around me is going to give me cancer. Prop 65 is the default thing that you see plastered everywhere.

So do I need to customize my content for delivering in California? Perhaps. Maybe different states have different regional laws or policies that apply to only that audience. That’s where that mass customization and mass personalization are really hard to scale because now you don’t have just one course, you have potentially 50 courses, if I’m just talking about the US, 50 states, 50 courses, and I have to have 50 different variations, which means that not if something changes, but when something changes, now I have to open up and change 50 different courses, and it’s not, did I miss anything? It’s, “What did I miss?” That’s the thing that you wake up in the morning in a cold sweat of, “Oh my God, what did I miss?”

So why structured for learning? Largely when you get to that tipping point where you’re copy/pasting, and I call it the copy/paste published treadmill, when you are on that hamster wheel of copy/paste/publish, copy/paste/publish, and that is the majority of what you’re doing, and you’re looking at a pie chart of how much time is spent maintaining your courses or taking a base course and creating all the variations, that precious PowerPoint that is the handcrafted bespoke one-off, you can’t do that anymore. That’s the equivalent of, you look at a Lamborghini, how many do they make a year? They can afford to make a very small number per year because they’re really expensive to make. When you look at a Ford Mustang, which probably gives you 80% of the performance at a fraction of the cost and exponentially scales well beyond, it’s because they’ve taken that structured approach of, every frame’s the same, every hood’s the same, very few handcrafted things, and the things that are going to be handcrafted, that’s when I go order the special edition Shelby Cobra that has some handcrafted components put onto the basic structure. That’s that same metaphor applied.

So why structured content? Because I want to have modular content that can be reassembled really quickly, that I may have chunks that are reused so that when I need to slip in my Prop 65 disclaimers, I can do that at scale and have 50 variations of a course, but when it comes time to update it, I’m literally updating one or two things and it’s automatically updating all 50 courses and of course all the efficiencies of publishing things out in a structured format.

So that pixel-perfect placement, I’m going to give that up to stay sane so I can get home and have dinner with my family, because the amount of time that I’ve spent in my life doing pixel-perfect placement and updating things, God, I wish I could hit the way back machine and reclaim all that time in my life. How many… Guilty as charged. Show of hands of anybody who’s listening, how many times have you sat there and fiddled with the slide or a text box in InDesign then design to get it just right, that two days later, something changes and you’re back there spending 10, 15 minutes doing it to fiddle it in just right. So, as I affectionately like to say, I’m a recovered FrameMaker, InDesign, PowerPoint, and Word user because I want to author it in a structured format so that I am giving up the responsibility of layout and look and feel.

SO: I like to tell people, “I’m not lazy, I’m efficient.” The fact that I don’t want to do it is just a bonus; I can get out of doing all this work.

MB: That’s right, that’s right.

SO: Because we are not allowed to leave any podcast without covering this topic, what does it look like to have AI in this context?

MB: There are two sides of the AI coin from a content perspective, I think, and it’s the, “How can AI help me do my job better to create content?” Some things that when we’re looking at duplication of content, things that AI can do really well that, working smart, not hard, help me find things that already exist in my repository of structured content that look like this, that are really close. The human in the loop, so helping me deduplicate or help me not create new unnecessary variations of content. I think that’s one area of AI-based assistance for content creation that people may not be necessarily thinking about. Because right now, the easy one is like, “Hey, ChatGPT, help me write an introduction or an overview for the following,” it spits that out. That’s great, but that overview and that content may have already been written by somebody else, and so what ends up happening is you start generating content drift where it’s almost exactly the same but just slightly different. And in reality, yes, I could have used the one that was already there.

So I think that’s one of the areas where AI from a content authoring perspective is one that I’m really excited about. Because at the end of the day, and this leads us into the second part of AI, AI is only as good as what you feed it, and if you feed it junk food, you’re going to get junk results. So it’s that whole thing of do you eat healthy food or are you going to eat Cheetos? If you’re pointing your AI at a SharePoint repository and saying, “Hey, read all of this,” and all the content shifts and variations and content drift and out-of-date and perhaps out-of-context content that exists inside of that repository, your results are not going to be as accurate as they need to be. So, how do you ensure that AI is providing good results? Well, you feed good content.

And so within an organization, I think the two silos that we started our conversation with, technical communications and L&D, tend to have some of the most highly vetted, highly accurate, up-to-date content in an organization. And so this is my encouragement to everybody who’s in this space, you are the owners of what is good, highly nutritious food that you can feed your AI. So taking it back to the structured content perspective, if I’m authoring in the structured content, publishing it out in a format that is AI ready, all of your tags, all of your enrichments, all of your, here’s the California version of the content versus the Georgia or Florida’s version of the content, all of that context and enrichment and tagging that’s gone on, you’re now feeding AI all of that context so that AI can provide the proper answer. So that’s my short, it’s sweet for the AI side. We could talk for probably days on all sorts of other variations, but right now, that’s where I’m seeing the biggest impact that it’s going to have on techcomm and L&D.

SO: I think that’s a great place to wrap it up. And I want to say thank you for being here and for a great conversation around all of these issues, and we will reconvene at a future conference somewhere to cause some more trouble and talk some more about all of these things. So Mike, thank you.

MB: You are welcome. And yeah, I think the next conference we’re going to see each other is going to be LavaCon, so I’ll be talking in and around the convergence of L&D and techcomm and what life can look like with that. So certainly a deeper dive and continuation of what we started here, and super excited to sit on your session as well.

SO: Yep, super. I will see you there. I’m pretty sure I’m doing one on the same topic, but it will be more complaining and less positive, so that seems to be my role. Okay, with that, thank you everybody, and we’ll see you on the next one.

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

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Every time someone views your product content, it’s a purposeful engagement with direct business value. Are you making the most of that interaction? In this episode of the Content Operations podcast, special guest Patrick Bosek, co-founder and CEO of Heretto, and Sarah O’Keefe, founder and CEO of Scriptorium, explore how your techcomm traffic reduces support costs, improves customer retention, and creates a cohesive user experience.

Patrick Bosek: Nobody reads a page in your documentation site for no reason. Everybody that is there has a purpose, and that purpose always has an economic impact on your business. People who are on the documentation site are not using your support, which means they’re saving you a ton of money. It means that they’re learning about your product, either because they’ve just purchased it and they want to utilize it, so they’re onboarding, and we all know that utilization turns into retention and retention is good because people who retain pay us more money, or they’re trying to figure out how to use other aspects of the system and get more value out of it. There’s nobody who goes to a doc site who’s like, “I’m bored. I’m just going to go and see what’s on the doc site today.” Every person, every session on your documentation site is there with a purpose, and it’s a purpose that matters to your business.

Related links:

Heretto
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The business case for content operations (white paper)
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Patrick Bosek
Sarah O’Keefe

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

Alan Pringle: And at some point, you are going to have tools, technology, and process that no longer support your needs, so if you think about that ahead of time, you’re going to be much better off.

End of introduction

Sarah O’Keefe: Hi, everyone, I’m Sarah O’Keefe and I’m here today with our guest, Patrick Bosek, who is one of the founders and the CEO of Heretto. Welcome.

Patrick Bosek: Thanks, Sarah. It’s lovely to be here. I think this is may be my third or fourth time getting to chat with you on the Scriptorium podcast.

SO: Well, we talk all the time. This is talking and then we’re going to publi- no, let’s not go down that road. Of all the things that happen when we’re not being recorded. Okay. Well we’re glad to have you again and looking forward to productive discussion here. The theme that we had for today was actually traffic and I think web traffic and why you want traffic and where this is going to go with your business case for technical documentation. So, Patrick, for those of you that have not heard from you before, give us a little bit of background on who you are and what Heretto is and then just jump right in and tell us about web traffic.

PB: No small requests from you, Sarah.

SO: Nope.

PB: So I’m Patrick Bosek. I am the CEO and one of the co-founders of Heretto. Heretto is a CCMS based on DITA. It’s a full stack that goes from the management and authoring layer all the way up to actually producing help sites. So as you’re moving around the internet and working with technology companies, primarily help_your_product.com or help_your_company.com, it might be powered by Heretto. That’s what we set out to do. We set out to do it as efficiently as possible, and that gives me some insight into traffic, which is what we’re talking about today, and how that can become a really important and powerful point when teams are looking to make a case for better content operations, showing up more, producing more for their customers, and being able to get the funding that allows them to do all those great things that they set out to do every day.

SO: So here we are as content ops, CCMS people, and we’re basically saying you should put your content on the internet, which is a fairly unsurprising kind of priority to have. But why specifically are you saying that web traffic and putting that content out there and getting people to use the content helps you with your sort of overall business and your overall business case for tech docs?

PB: Yeah. So I want to answer that in a fairly roundabout way because I think it’s more fun to get there by beating around the bush. But I want to start with something that seems really obvious, but for some reason it isn’t in tech pubs. So first of all, if you went to an executive and you said, I can double the traffic to your website, and then you put a number in front of them, probably say a hundred thousand dollars, almost like any executive at any major organization is like a hundred thousand dollars, of course, I’ll double my web traffic. That’s a no-brainer. Right? And when they’re thinking of website, they’re thinking of the marketing site and how important traffic is to it. So intrinsically, everybody pays quite a bit of money and by transference puts a lot of value on the traffic that goes to the website and, as they should. It’s the primary way we interact with organizations asynchronously today.

Digital experience is really important. But if you went to an executive and you said, I can double your traffic to your doc site, they would probably be like, wait a second. But that makes no sense because nobody reads the docs for no reason. I want to repeat that because I think that’s a really important thing for us, as technical content creators to not only understand, I think we understand it, but to internalize it and start to represent it more in the marketplace and to our businesses and to the other stakeholders. People might show up at your marketing site, because they misclick an advertisement. They might show up in your marketing site because they Googled something and your market and a blog like caught them and they looked at it. So there’s probably a lot of traffic where people are just curious. They’re just window shopping. Maybe they’re there by mistake. But nobody shows up at your documentation site.

Nobody reads a page in your documentation site for no reason. Everybody that is there has a purpose and that purpose always has an economic impact on your business. People who are on the documentation site are either not utilizing your support, which means that they’re saving you a ton of money. It means that they’re learning about your product, either because they’ve just purchased it and they want to utilize it, so they’re onboarding, and we all know that utilization turns into retention and retention is good because people who retain pay us more money, or they’re trying to figure out how to use other aspects of the system and get more value out of it. There’s nobody who goes to a doc site who’s like, I’m bored. I’m just going to go and see what’s on the doc site today. So every person, every session on your documentation site is there with a purpose and it’s a purpose that matters to your business. So that’s why I want to start. That’s why it matters. That’s why I think traffic is important, but you look like you want to contribute here, so.

SO: We talk about enabling content. Right? Tech docs are enabling content. They enable people to do a thing, and this is what you’re saying. People don’t read tech docs for fun. I know of, actually, I do know one person. One person I have met in my life who thought it was fun to read tech docs. One.

PB: Okay. So to be fair, I also know somebody who loves reading release notes.

SO: Okay. So two in the world.

PB: But hang on, hang on. But this person, part of the thing is this person is an absolute, can I say fanboy, is that, they’re a huge fan of this product and they talk about this product in the context of the release notes. So even though this person loves the release notes, the release notes are a way that they go and generate word-of-mouth and they’re promoting your product because of the thing they saw in the release notes. The release notes are a marketing piece that goes through this person. All the people who are your biggest fans are going to tell people about that little thing they found in your release notes. Sorry. Anyways.

SO: So again, they’re trying to learn. Okay. But, so two people in the universe that we know of read docs for fun. Cool. Everybody else is reading them, as you said, for a purpose. They’re reading them because they are blocked on something or they need information, usually it’s they need information. And then you slid in that when they do this, this is producing, providing value to the organization or saving the organization money. So what’s that all about?

PB: Well, I mean there’s a number of ways to look at this. You want to start with the hard numbers, the accounting stuff, the stuff you can take the CFO. That stuff is actually, it’s pretty easy to do. You can do it in just a couple of lines. So every support ticket costs a certain amount of money. Somebody in your organization knows that number, if your organization is sufficiently large and sufficiently large is like 20 people probably. Maybe that’s not that small, but if you’re a couple hundred people, everybody knows what that number is. So it’s very easy to figure out how much it costs when somebody actually goes to the support.

SO: Somewhere between $20 and $50 is kind of the industry average per call. You may have better numbers internally in your organization, but if you don’t or you don’t know where to start there. Every call is $25.

PB: Yeah. $20, $25. A little more, if you’re in a complex industry. The reality is that when you start comparing it to how much you spend answering a question with content, it’s kind of like, oh, is it a thousand times cheaper or is it 2,000 times cheaper? So it’s not really that big of a difference. The cost of answering a question with content is also pretty straightforward. So all you really need to know is how much are you spending on your content, which is typically speaking just the combination of the people and tools, so people in content operations stack that you’re using to get that content out in front of people. And then the page views. I mean, fundamentally if you exclude search, so take search out of your page views, take home page out of your page views, if you can filter section pages, so just look at actual content pages and then you have to pick a resolution rate.

Obviously, if you want to say 100%, if you don’t have any better metrics, that’s probably too high. Maybe it’s unreasonable, but it’s very simple. It makes the equation easier. If you want to say that 50% percent of people who read what you’ve considered to be like a content page, resolve their issue, that’s probably too low. So pick a number between those two things and you run the multiplication on that and you’re going to find out that it’s going to cost you, in most situations, less than a penny to answer a question, typically way less than a penny to answer a question with content as opposed to the $25. That’s the pure economic math of it. There’s more though.

SO: Okay. So yeah, we did some math and we’re basically saying, looking at this in a tech support centric way, usually we talk about call deflection. Right? So the idea is that every time somebody does not call tech support, you save $25 and spend a penny, a fraction of a penny instead, which seems good. Now interestingly to me, I think, you can look at this as the first time somebody hits that site and hits a content page, costs really a lot of money. Right? Because the people and the tools and the setup and the publishing, but then the next one is zero.

So you’re replacing sort of an upfront planned cost with a recurring cost because every time somebody calls, it’s another 25 or 50 or whatever dollars. So there’s a huge scalability argument here, and I can make a decent case for if you are a startup, a day one startup, you have no content, you have nothing, you have no infrastructure, cool. Hire a tech support person. Let them do their thing for maybe a year, and then look at the top 10 queries that they had and write some docs and deflect off those top 10 queries and handle it that way. But most of our customers, speaking for both of us, are medium to large to incredibly large organizations that have content. We’re not talking about the you have nothing start from scratch scenario.

PB: A hundred percent. When you’re really thinking about where you get the value, both on the accounting side, like saving money, so bottom line stuff, and then also the customer experience, which I think is worth getting into in a minute, that’s really going to take place when you start scaling up. I agree with you that a startup style organization should write content. Even small organizations benefit from it. I think they, small organizations actually benefit in a slightly different way than the deflection, which is the word you’re using. And I’m going to come back to that because I have a pet peeve with that word, but I’ll use it right now for the purposes because we’ve been using it. I think that what, the value that a smaller organization gets is not in the deflection, but it’s actually in the presence. So if you’re trying to show up and you’re trying to compete with larger organizations and you’re doing something, which is technical or considered to be highly important, so you’re in a high technology industry, your buyer is going to go look at your documentation. They’re going to look at your competitor’s documentation as well.

And if your documentation appears to be not that great, it’s very thin, there’s not a lot there, that’s going to be a factor in a buying decision. And I know everybody kind of like, yeah, but it really is, and I can tell you because we’re not a huge organization, that we’ve won deals because our docs were better. We invest in it, as we should. We’re a documentation tool. You know? So it does matter at the smaller end, even if you can’t build a really scalable content operation stack that you probably don’t need.

SO: Now, personally, I’m okay with deflection, and I’ll also say that the key thing here is that if you’re doing additional research on this as a listener, call deflection is sort of the industry term that will help you in your Google/AI searches. But tell us about why call deflection is bad and evil.

PB: Okay. So that is true. If you are talking to executives, you should probably say deflection, but maybe forward-thinking executives would appreciate why I think deflection is a bad term. I think we should use, you’re shaking your head at me. Fine. I think we should be talking about call avoidance. And the reason that I think this is because when most people think about deflection, they’re thinking about it as being very reactive, and it’s that box that pops up when you’re trying to put a support ticket in that’s like, well, have you already looked at this? And by the time someone has arrived at your support site and they have decided that they want to interact with a human, they are annoyed. They don’t want to be there. Nobody visits the support site because they want to. They have made the emotional commitment that they’re going to go and deal with one of your human beings to solve their problem, which is not something they planned on doing today. Nobody wanted to do this when they got up in the morning. So you’ve already failed. And at that point in time, the best thing you can do is get them to a human efficiently without sticking things in front of them and trying to deflect them. So that’s why I don’t like deflection. Avoidance is that that never happened. They Googled it because Google is tier zero support for everybody, even if yours is bad. They got an answer or they ChatGPT-ed it, different topic, there’s problems there. But probably they Googled it. They got an answer very quickly. They solved their issue. You never heard about it. It cost you a fraction of a penny. They had a great experience. It’s how they prefer to get their information, and you avoided the support rather than trying to deflect them to save yourself a couple of bucks when they were annoyed and broke their customer experience.

SO: Yeah. I’m on board with that. It’s just that terminology-wise, we’ve got to work with what we’ve got. But I would agree that avoiding the call in the first place, and I talk about how when people call tech support, they’re mad. If you think about the emotional state of your customer, the tech support person is angry. There’s also the issue that they asked ChatGPT and it said something wrong, and then they call up tech support and yell at you because ChatGPT was wrong, which is, that’s a whole other podcast. So let’s just set that aside for a moment, but okay.

PB: Maybe you’ll invite me back. We can talk about that.

SO: Yeah. So the, it’d be a long podcast and we’ll have to lift our no profanity rule for that one just to get through the topic.

PB: Oh. Special edition.

SO: Special edition. Okay. So you were talking about the value though of a documentation site and we’ve sort of paired it with tech support and with this avoidance, deflection, get them the answers that they need before they get angry at the product. Right?

PB: Yeah. For sure.

SO: How does the customer experience tie into that? And what is the value of the customer experience?

PB: So the value of the customer experience is subjective, but every organization already has an opinion on it. Some organizations place a lot of value in customer experience, have done a lot of work to tie customer experience to the metrics and analytics and things like that they use to track financial performance. Other organizations less. So the first thing I would say is go and see where your organization is relative to their thinking on customer experience. But, as you’re talking about customer experience, other than the support, which I think we’ve covered that quite a bit, for someone who’s showing up your documentation site, really what it’s touching on is a couple of things, what they’re trying to get to. So there’s the discovery aspect of it. And this can be very, very simple or it can be very, very complex. The simple one I like is like let’s say you sell gym equipment and that gym equipment goes out to people who own gyms, as it would make sense, and they’re going to go and they’re thinking of buying a new treadmill or something from you.

They’re going to want to know, is this going to fit in my gym? Can the power I have set up work with it? What are the other details of this product? And then how much information is there to service it? So somebody, once they get past the whole like, okay, I kind of like this brand, maybe this is a good thing, it’s kind of cool, they’re going to go into the documentation because they’re making a purchase that matters to them. And having confidence and trust in the product based on the depth of information that they get prior to purchasing it is a major factor. And this only increases as the economic value and the end implementation, like how critical it is, how system critical it is, increases. So there’s a discovery, evaluation, and confidence, those are the three things I think of, aspect to your documentation or your help site that is there, even if you’re not thinking about it, even if it’s not coming up directly in sales conversations. I promise you, because I have the data that people are doing this during the process of deciding if they want to work with your organization. And that’s the kind of pre-customer experience that’s really, really critical that most organizations are just not thinking about and they’re probably leaving a lot on the table relative to their competitors that either could be advantage or they’re behind.

SO: There was a study. It was a while back, maybe five or 10 years ago that came out from, I always have trouble finding it. It was either PwC or IBM. The gist of it was that 80% of people that were buying consumer products were doing pre-buying research, the technical research. So they were looking at specs and they were looking at how do I install this thing and various other things that we consider to be not marketing information. They were looking at what is traditionally labeled post-sales documentation.

PB: Yeah. Because people care. And the other thing too is like as we move into an economic environment where people are more careful about what they’re spending on, they’re only going to do more research to make sure the things they’re buying are things that are going to last and be supported. I bought a pair of headphones a year ago, and I have an issue with one of them. They’re like the ones that go in your ears, one of them’s not working. I ended up going to the documentation to try to figure it out, and the documentation was so bad I could not make heads or tails of it. And I just gave up and I was like, okay, if I had spent hundreds of dollars on these, I’d go through the process, but they were like 30 bucks or whatever. But I’m never going to do business with that company again. Ever.

If I see another one of the products, I will never buy it. So they don’t know about that experience. But if you have, not even just bad content operations, because frankly their site was, it was kind of nice, it wasn’t bad. I think it could have been better, but you know, funny that I would have that opinion, but it was really the information architecture, so it was kind of the stuff that Scriptorium, Sarah, you guys would help them with. It wasn’t so much they had bad tools. They had terrible organization, and the content was, I’m not allowed to swear, which I wouldn’t anyways…

SO: Sorry.

PB: … but the content was, think of your word, it was bad. It was completely unhelpful. So you can have the best content operations in the world, but without the right information architecture, who cares?

SO: Yeah. This is the infamous if a tree falls in the forest. You know, and to your point, A, the company doesn’t know that your headphones are broken and you’re unhappy, but you just told me, and the next time I’m in the market to buy a pair of headphones, I’m going to remember this story and I’m going to call you, I won’t call you. I’ll send a text and say, hey, what brand was that? Right? And you’re going to tell me and then I’m going to not buy them. So the impact of this failure of documenting, well, actually it’s a product fail, right, but also of support. Because if they had come back with, oh, we’re so sorry, send them in or we’ll send you a new pair, whatever, they could have rescued this encounter, but they didn’t. So the next thing that’s going to happen is that you and every single one of your friends that hears the story will never buy that brand.

PB: Right.

SO: So as we talk about this, the really critical point here though is, I think, there are a bunch of really critical points, but the one that I really want to zoom in on is that the content has to be there. Right? You have to have helpful content that solves the problem that a person is on the website for. And, in your case, it might have been, oh, sometimes this happens and you have to repair them, or you have to this or you have to that, you know, press all these weird buttons in this weird sequence and sacrifice the chicken and stand on your head. Cool.

PB: Right. Which I would’ve done.

SO: Which you would’ve done. But the bigger problem is that you went to their website and we don’t actually know whether or not this problem is fixable because you didn’t find it. Right? You didn’t find the answer. And that means that it’s sort of like a last mile problem. I can write all these really good procedures, they can be super accurate, they can be amazing, blah, blah, blah, blah, blah. You come onto my website, you can’t find the answer your question, it exists, but you can’t find it, right, you, the customer, and so it fails, and now you either, A, tell all your friends that company XYZ is terrible, or, B, you call tech support and you’re mad. Right?

PB: Yeah.

SO: That’s actually the best outcome.

PB: It is. Yeah.

SO: Yeah. And interestingly, we’ve got some, I’ll be very non-specific, but we have a project right now where one of the top tech support topics, you know how you look at what are the top 10 things that people call and ask about, and it’s like, my headphones aren’t working, or how do I return this or whatever. One of the most common reasons that people call their tech support is to ask, where is the documentation? I can’t find it.

PB: Do you have any idea how common that is? I mean, you probably do, but it’s so common.

SO: Yeah.

PB: And we’ve started doing this thing in the process of helping people think through this where we have a very simple tool that we use. It’s a sheet, happy to share it with anybody, and a process where you effectively go through and you just do a very simple 15 to 30 minute interview with X number of support people. You know, we recommend three to five. Some people do more. And you just go through the last 10 support cases, the ones that they worked on, and there’s a few things you mark off, but the idea is to do lightning round, very, very quick. And could this be solved by documentation? And the amount of it that is just looking for documentation, I can’t find it, is so funny. And you’re like, I think that’s a problem. And people are like, wow. But you can’t blame them because people don’t think about these things and it doesn’t make sense that you would because it’s non-obvious, and I think that’s one of the really critical things I want to leave people with.

And I have one other thing that I, you know, we’ve been talking for a while that I want to let people go soon, but this one, I want to zoom in on this for a second. People shouldn’t feel bad that they haven’t thought about this. They shouldn’t feel bad that they haven’t thought about the value of the traffic, the impact of the traffic, the customer experience side of it, the cost ratio of the traffic relative to support people. It really isn’t that obvious. And there’s so much momentum around the way that we’ve done business in having people solve problems for other people in direct communications that even if that isn’t ideal, that’s just the way it’s done and that’s what feels obvious. So don’t feel bad about not having thought about this if you haven’t. Your colleagues shouldn’t either. But it is the way the world is moving, and I think it’s critical to start thinking about it now.

SO: Yeah. And you started this by talking about customer experience needing to be asynchronous. People can get the stuff, self-service when they want it and digital as opposed to call somebody on the phone. So let’s sort of wrap this up and say, what’s your advice to people that know that they’re struggling with this? They know that they have huge tech support volumes and nobody’s happy. And I mean, we know we have a problem. So where should they start? What’s the first step that they can take to begin attacking this thing in a way that will lead to forward progress within a large organization that has as their informal motto, oh, they can just call tech support.

PB: Yeah. So I would say buy-in is always step one, and that means that there’s going to be some selling that has to happen at the organization. You have to get people to recognize the value, the potential, and also the ability to achieve it. So it’s those things when they come together, there can be a ground swell where people are going to actually support these projects and fund them and get involved, and then you’ll have really successful projects. One of the big challenges with getting that buy-in historically has been that there’s no precedent. So when you’re looking for a better website, you already have a website. What if you increase traffic by 10%? You know, people can start to draw some lines between that and sales or the bottom line or value, those types of things. And oftentimes, even organizations that I would say are somewhat up to maturity curve in terms of tech pubs, they don’t have any metrics about their site, like how many people come to it? I don’t know.

They just don’t track it. So there’s not this historical precedent of metrics that can be back to results, and that can create some issues. So the advice that I give organizations that are in that situation is if you are in a technology field and you have a relatively complex product, so something where it breaks, it’s not always obvious how to use it, there’s a reason that people would need to learn about your product for some reason, what our data shows from having done this many times with organizations that fit that profile is that a well-implemented documentation help site, whatever you want to call it, gets about as much traffic as the dot com, the primary marketing site. It tends to be plus or minus 15%. We’ve actually seen as high as 65% of the total traffic between the two sites being on documentation.

That’s a bit of an outlier, but so is 30%. You know, we’ve seen that too. So if you’re want to be conservative, say you’ll get 40% of the total traffic. So four sessions for every six on a marketing site. If you want to be, what we tend to see on an average, just say it’s one for one. If it’s one for one and you don’t have metrics, that’s a target. And you have to ask the internal question, what’s the value of that? If we get a hundred thousand sessions per month or per year or whatever on the marketing site, what if we had a hundred thousand sessions on the help content? Well, those people are there for a reason. Remember? They’re there because they’re not calling support. They’re there because they’re onboarding and using our system better, or they’re there because they’re trying to figure out if our stuff’s going to work for them.

So like how valuable would that be? And once you get the organization to a place where they’re like, oh, that would actually be quite valuable, could we get that, I think 80% of the work is done and well, 80% of the work of getting started is done. And then you probably call somebody like Scriptorium or Scriptorium specifically, if you’re not familiar with this, and you start the process of actually thinking through of how to do it. But I do think the organizational buy-in and giving people in the right head space to think about the value of this is step one, and that’s the process I use for it.

SO: Yeah. I think I would agree with all of that, especially the part where they should call us.

PB: Go figure.

SO: But the key thing in here is, and you said this a different way, but changing the momentum, right, getting organizational buy-in, getting people on board with this concept. The other thing I’ll say is that ultimately one of the biggest problems we face in content ops is that so much of it is invisible in the sense that we’re going to refactor this and we’re going to do it better, and we’re going to produce it faster and we’re going to automate, okay, great, but you’re still producing the same thing. One of the most powerful things we can do early in the process is say to people, look at this portal that we can deliver. Look at this experience that we can deliver. It’s not the first thing or the only thing or even necessarily the most important thing we need to do, because the portal has to have content. Right?

PB: Yeah.

SO: I mean, it’s kind of a chicken and egg thing, but showing people the vision of what can be works typically much, much better than saying we should do structured content because it will help automate things and speed up time to market. That’s all behind the scenes, and it’s not visual and nobody cares. I mean, people care, but it’s hard to visualize. So, okay, I think we’ve promised people a whole bunch of resources. We will put those in the show notes. I’m quite certain that we could go on for a very long time about this topic, but I am going to wrap it up there ’cause I feel like we hit a good starting point for people.

PB: Yeah.

SO: So if there are other questions, I would say reach out to me or to Patrick, because I know we’ve only scratched the surface on this thing. Patrick, thank you for being here.

PB: Of course. Always a blast.

SO: Always good to see you. And we will wrap this thing up, and thanks for being here. Feel free to reach out if you have any other questions.

The post Every click counts: Uncovering the business value of your product content appeared first on Scriptorium.

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In this episode of the Content Operations podcast, Sarah O’Keefe and Bill Swallow unpack the promise, pitfalls, and disruptive impact of AI on multilingual content. From pivot languages to content hygiene, they explore what’s next for language service providers and global enterprises alike.

Bill Swallow: I think it goes without saying that there’s going to be disruption again. Every single change, whether it’s in the localization industry or not, has resulted in some type of disruption. Something has changed. I’ll be blunt about it. In some cases, jobs were lost, jobs were replaced, new jobs were created. For LSPs, I think AI is going to, again, be another shift, the same that happened when machine translation came out. LSPs had to shift and pivot how they approach their bottom line with people. GenAI is going to take a lot of the heavy lifting off of the translators, for better or for worse, and it’s going to force a copy edit workflow. I think it’s really going to be a model where people are going to be training and cleaning up after AI.

Related links:

Going global: Getting started with content localization
Lessons Japan taught me about content localization strategy
Conquering content localization: strategies for success (podcast)
The Scriptorium approach to localization strategy
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LinkedIn:

Sarah O’Keefe
Bill Swallow

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

End of introduction

Sarah O’Keefe: Hey, everyone. I’m Sarah O’Keefe, and I’m here today with Bill Swallow.

Bill Swallow: Hey there.

SO: They have let us out of the basement. Mistakes were made. And we have been asked to talk to you on this podcast about AI in translation and localization. I have subtitled this podcast, What Could Possibly Go Wrong? As always, what could possibly go wrong, both in this topic and also with this particular group of people who have been given microphones. So Bill.

BS: They’ll take them away eventually.

SO: They will eventually. Bill, what’s your generalized take right now on AI in translation and localization? And I apologize in advance. We will almost certainly use those two terms interchangeably, even though we fully understand that they are not. What’s your thesis?

BS: Let’s see. It’s still early. It is promising. It will likely go wrong for a little while, at least. Any new model that translation has taken has first gone wrong before it corrected and went right, but it might be good enough. I think that pretty much sums up where I’m at.

SO: Okay. So when we look at this … Let’s start at the end. So generative AI, instead of machine translation. Let’s walk a little bit through the traditional translation process and compare that to what it looks like to employ GenAI or AI in translation.

BS: All right. So regardless of how you’re going about traditional translation, there is usually a source language that is authored. It gets passed over to someone who, if they’re doing their job correctly, has tools available to parse that information, essentially stick it in a database, perhaps do some matching against what’s been translated before, fill in the gaps with the translation, and then output the translated product. On the GenAI side, it really does look like you have a bit of information that you’ve written. And it just goes out, and GenAI does its little thing and bingo, you got a translation. And I guess the real key is what’s in that magic little thing that it does.

SO: Right. And so when we look at best practices for translation management up until this point, it’s been, as you said, accumulate assets, accumulate language segment pairs, right? This English has been previously translated into German, French, Italian, Spanish, Japanese, Korean, Chinese. I have those pairs, so I can match it up. And keeping track of those assets, which are your intellectual property, you as the company put all this time and money into getting those translations, where are those assets in your GenAI workflow?

BS: They’re not there, and that’s the odd part about it.

SO: Awesome. So we just throw them away? What?

BS: I mean, they might be used to seed the AI at first, just to get an idea of how you’ve talked about things in the past. But generally, AI is going to consume its knowledge, it’s going to store that knowledge, and then it’s going to adapt it over time. When it’s asked for something, it’s going to produce it with the best way it knows how, based on what it was given. And it’s going to learn things along the way that will help it improve or not improve over time. And that part right there, the improve or not improve, is the real catch in why I say it might be good enough but it might go wrong as well, because GenAI tends to … I don’t want to say hallucinate because it’s not really doing that at this stage. It’s taking all the information it has, it’s learning things about that information, and it’s applying it going forward. And if it makes an assumption based on new information that it’s fed, it could go in the wrong direction.

SO: Yeah. I think two things here. One is that what we’re describing applies whether you have an AI-driven workflow inside your organization where you’re only allowing the AI to access your, for example, prior translation. So a very limited corpus of knowledge, or if you’re sending it out like all of us are doing, where you’re just shoving it into a public-facing translation engine of some sort and just saying, “Hey, give me a translation.” In the second case, you have no control over the IP, no control over what’s put in there and how it’s used going forward, and no control over what anyone else has put in there, which could cause it to evolve in a direction that you do or do not want it to. So the public-facing engines are very, very powerful because they have so much volume, and at the same time, you’re giving up that control. Whereas if you have an internal system that you’ve set up … And when I say internal, I mean private. It doesn’t have to be internal to your organization, but it might be that your localization vendor has set up something for you. But anyway, gated from the generalized internet and all the other people out there.

BS: We hope.

SO: Or the other content. You hope. Right. Also, if you don’t know exactly how these large learning models are being employed by your vendors, you should ask some questions, some very pointed questions. Okay, we’ll come back to that, but first I want to talk a little bit about pivot languages. So again, looking at traditional localization, you run into this thing of … Basically many, many, many organizations have a single-language authoring workflow and a multi-language translation workflow. So you write everything in English and then you translate. So all of the translations are target languages, they are downstream, they are derived from the English, et cetera. Now let’s talk a little bit about… First of all, what is a multilingual workflow? Let’s start there. What is that?

BS: Okay. So yeah, the traditional model usually is author one language, which maybe 90% of the time is English, whether it’s being authored in an English-speaking country or not, and then it’s being pushed out to multiple different languages. In a multilingual environment, you have people authoring in their own native language, and it should be coming in and being translated out as it needs to be to all the other target languages. Traditionally, that has been done using pivot languages because infrastructures were built. It is just the way it is. It was built on English. English has been used as a pivot language more than any other language out there. There are some outliers that use a different pivot language for a very specific reason, but for the sake of this conversation, English is the predominant pivot language out there.

SO: So I have a team of engineers in South Korea. They are writing in Korean. And in order to get from Korean to, let’s say, Italian, we translate from Korean to English and then from English to Italian, and English becomes the pivot language. And the generalized rationale for this is that there are more people collectively that speak Korean and English and then English and Italian than there are people that speak Korean and Italian.

BS: With nothing in between, yeah.

SO: With nothing in between. Right. Directly. So bilingual in those two languages is a pretty small set of people. And so instead of hiring the four people in the world that know how to do that, you pivot through English. And in a human-driven workflow, that makes an awful lot of sense because you’re looking at the question of where do I find English … Sorry, not English, but rather Italian and Korean speakers that can do translation work for my biotech firm. So I need a PhD in biochemistry that speaks these two languages. I think I’ve just identified a specific human in the universe. So that’s the old way. What is a multilingual workflow then?

BS: So yeah, as we were discussing, the multilingual workflow is something where you have two, three, four different language sources that you’re authoring in. So you’re authoring in English, you have people authoring in German, you have people authoring in Korean and, let’s say, Italian. And they’re all working strictly in their native language, and those would go out for translation into any other target language. It’s tricky because the current model still uses a pivot language, but I think when we talk about generative AI, it’s going to avoid that completely. It’s going to skip that pivot and just say, “Okay, I know the subject matter that you’re talking about and I know the language that you’ve presented it in. Let’s take this subject and meaning and just represent it in a different language and not even worry about trying to figure out what does this mean in English. It doesn’t matter at this point.”

SO: Right. And so I think the one caveat here as we’re looking at this issue is to remember that GenAI in general is going to do better when it has larger volumes of content. And a lot of the generative AI tools are tuned for English. That’s kind of where they started. But it’s also useful to remember that GenAI is math. GenAI doesn’t really have a concept of knowledge or learning or any of these other things. It’s just math. So math is a language of its own, and we should be able to express mathematical concepts in a human language of choice. So there’s some really interesting stuff happening there. Okay. So stepping back a little bit from this, let’s talk about where this is coming from and the history of machine translation in translation localization. Where did we start? And isn’t it true that localization really was one of the leaders in adopting AI early on?

BS: It really was. So way, way, way back, you had essentially transcription in a different language. So people were given a block of text and asked to reproduce it in a different language, and they went line by line and just rewrote it in a different language. Then you start getting into the old-school machine translation or statistical machine translation. What this did was it kept, essentially, a corpus of the translations that you’ve done in the past, and it also broke down the information that you were feeding it into small segments. And it would do a statistical query, taking one segment from what your source said and throwing it out into its memory and say, “Okay, is there anything out here? Was this translated before? And give me a ranking of these results of what was done before.” And essentially, the highest result floated to the top, and it used that. Translators could modify those results over time based on actual accuracy versus systematic or statistical accuracy. But that is forever old. Over the past 10, 15 years, we’ve seen neural machine translation come out, which is getting a lot closer to AI-based translation. So it takes away the text matching and replaces it with more pattern matching. So it’s better at gisting. It will find, let’s say, a 95% match and can fill in those gaps for the most part, or at least say, “Hey, this gets us 95% of the way there. I’m going to put this out over here, and then the translator will essentially verify that translation going forward.” It’s a bit more accurate, but it still relies on this corpus of translation memory that you build over time. And now we’ve got generative AI machine translation, which completely takes everything that was done before, and it doesn’t necessarily throw it away, but it says, “Thank you for all the hard work you did. I will absorb that information and move forward.”

SO: Does it actually say thank you?

BS: It could. It depends on the prompt you use. But I mean, really, you’re looking at a situation where the generative AI model, it uses a transfer learning model to do the translation work. So it takes everything that it knows, applies it to what you feed it for translation, produces an output, learns a lot of things along the way in getting that translation to a point where you say, “Okay, great, thank you. This was good,” and then applies what it learned to the next time you ask. And it keeps doing that and doing that and doing that. On the plus side is that, yes, you can train your generative AI to get really, really, really good if you train it the right way. If someone … And I am not saying it’s malicious or anything, but if you train your GenAI translation model to start augmenting how it translates, then you’ll start getting these mixed results over time because it’s going to learn a different way to apply your request to provide an output.

SO: So the question that I actually have, which I’m not going to ask you to answer because that would be mean, is whether AI is actually storing content in a language, like in English, or is language, in the case of GenAI, just an expression of the math that underlies the engines? You don’t want to tackle that, no. Moving on.

BS: Well, it’s worth poking at, at least, because … Does GenAI actually do anything with the language that we give it now, just for answers? If we’re asking it to write a stupid limerick about a news event, or are we asking, “Summarize this document,” does it care that it’s written in any language? I honestly don’t know.

SO: As meta as it is to ask the question, what is the math that underlies it, the other thing that’s helpful to me, and again, we’re grossly oversimplifying what’s going on, but what is very helpful to me is to think of AI as autocorrect, or autocomplete, actually, on steroids. It’s more than that, but not a lot more. It has just learned that every time I type certain words in my text app, certain other words are likely to follow and it helpfully suggests them. And sometimes it’s right and sometimes it’s wrong, but it’s just doing math, right? Autocorrect learns that there are certain words that, when misspelled or that I do not wish to have corrected, or perhaps it introduces the concept that that word needs to be corrected to the word that I use more commonly, which can be extremely embarrassing. We had some questions about this. We’ve done some prior localization AI conversation, and I wanted to bring in a question that came from one of our audience members. Their question was, “Will we get to the point where we can effectively ask an AI help system a question in a foreign language, the AI system will parse the source language content, and then return the answer in the user’s language? Will translating documentation eventually be no longer necessary?” And what’s your take on that?

BS: Well, I think the answer is yes, and my take is that we are nearly there already. We already have… even apps that you can run on your phone. We have apps that can translate on the fly from verbal language. And I have used them when I travel abroad and I don’t know the language very well, to be able to speak it into my phone and it essentially translates the text for the person I’m trying to communicate with. There are other apps that take a step further and use a synthetic AI voice to read it so that they don’t have to look at my screen. They can just hear what the phone has to say because obviously I’m unable to say it myself.

SO: There’s also a version that does that through the camera. So you point the camera at a sign or a menu, more importantly, and it magically translates the menu into your language while you’re looking at it through your phone, or through your camera.

BS: That has been so helpful.

SO: Yes. Now that is actually a really good example, though, of a place where this kind of translation is hard because there’s very little context, and there’s a tendency in food culture to have very specific terms for things that maybe are not part of the AI’s daily routine. We were talking not too long ago about … What was it? We came up with half a dozen different words in German for dumpling. And we got into a big argument about which one was what and which one is correct for this type of dumpling and all the rest of it. So yeah. The thing I would point out here is that the question was, if someone comes in and asks the AI help system a question in, let’s say, French, but the underlying system is in, let’s say, English, but it would then return French. It’s a very English-centric perspective, to say, “Well, the French people … Our AI is going to be in English, essentially. Our AI database.” And that is a really interesting question to me. Is the AI database actually going to be in English? And maybe not.

BS: Probably not.

SO: I tried this about a year ago with ChatGPT. And you might experiment with this if you speak another language, or combine it with machine translation, which should work as well. I asked ChatGPT a specific question, and I got an answer. Cool. And then I asked the same question again and added, “Respond in, in this case, German.” The answer that I got in German was, obviously, it was in German, step one, which I wasn’t actually sure it could do. But step two, the reply that I got in German, the content was different. It wasn’t just a translated version of the English content. It was functionally a different answer. So it’s like in English, I said to ChatGPT, “What color is the sky?” And it said, “The sky is blue.” And then I said the same thing, “What color is the sky? Respond in German,” and it came back with, “The sky is green.” Now, it was actually did a DITA-related question, which kind of explains what happened here. But what happened was that ChatGPT, even though the prompt was in English, it pretty clearly used German language sources to assemble the answer. And those of you who know that DITA is more popular in the US than it is in Germany would not be too surprised that the answer I got regarding something DITA-specific in German was very much culturally bound to what German language content about DITA looks like. So it was processing the German content to give me my answer, not the English content. Now, if you ask an AI help system, the next question is what’s sitting in that corpus? Because if you ask it a question in French and it has no French in the corpus, then it’s probably going to generate an answer in English and machine translate. But if it has four topics in French and you ask it something in French, it is probably going to try and assemble an answer out of that French content, which could be…

BS: Before it falls back, yeah.

SO: Fascinating, which brings me to my next meta question that we’re not going to answer, which is can we capture meaning and separate it from language? And a knowledge graph is an attempt to capture relationships and meaning. And that can be rendered into a language, but it is not itself specifically English. It’s a database entry of person, which has a relationship with address, and you can say, “Person X lives at address Y,” but that sentence is just an expression of the mathematical or the database relationship that’s sitting inside the knowledge graph. I want to talk about the outlook for LSPs, for localization services providers. What does it look like to be an LSP, to be a translation service provider, in this AI world? What do you think is going to happen?

BS: I think it goes without saying that there’s going to be disruption again. Every single change, whether it’s in the localization industry or not, has resulted in some type of disruption. Something has changed. I’ll be blunt about it. In some cases, jobs were lost, jobs were replaced, new jobs were created. And I think that for LSPs, I think AI is going to, again, be another shift, the same that happened when machine translation came out, when neural machine translation came out, all of this. They’ve had to shift and pivot of how they approach their bottom line with people. GenAI is going to take a lot of the heavy lifting off of the translators, for better or for worse, and it’s going to force a more copy edit workflow. And perhaps, I guess, a corpus editing role or basically an information keeper who basically will go in and make sure that the information that the AI model is being trained on is correct and accurate for very specific purposes, and start teaching it that when you talk about this particular subject matter, this is the type of corpus we want you to consume and respond with, versus someone who actually does the translation work and pushes all the buttons and writes all of the translations. It’s really going to be a model where I think people are going to be training AI and cleaning up after it, essentially. And I don’t know any further than that. I mean, it’s still pretty young. I think also you will see LSPs turning more into consultative agencies with companies, rather than just a language service provider. So they will help companies establish that corpus and train their AI and work with their corporate staff to make sure that they are writing better queries, that they are providing better information out of the gate, and so forth. So I think it’s going to be a complete shift in how these companies function, at least between now and what’s to come.

SO: Yeah. The cost of a really bad translation getting into your database when it was human-driven… this AI thing is going to scale. There’s going to be more and more of it, everything’s going to go faster and faster. And we already have these conversations about AI slop and the internet degrading into just garbage because there’s all this AI-created stuff. And so if you apply that vision to a multilingual world, it’s quite troubling, right? So I think you’re right. I mean, this idea of content hygiene. How do we keep our content databases good, such that they can do all this interesting math processing instead of becoming more and more and more and more error-riddled is really interesting. We started by saying clearly this is a disruptive innovation. Disruptive innovations start out bad, clearly of lower quality than the thing they’re disrupting, but they’re cheaper and/or faster and/or have some aspect that they can do that the original thing cannot. So mobile phones are a great example. They were worse than landlines in every possible way, but they were mobile, right? They were not tethered to a cord in the wall. And then over time, a mobile phone turned into something that really is a computer that is context and location-aware and can do all sorts of nifty things. It doesn’t look at what resemblance it bears to POTS, to plain old telephone service. And we hear people. Oh, I don’t use my phone to make phone calls. Why would I do that? That’s terrible, because we have all these other options.

So from a localization point of view, any organization that is using person-driven, manually-driven, inefficient, fragmented processes is going to be in trouble. And that stuff’s all going to get squeezed out. And I think it’s actually helpful to look at the structured authoring concept and how it eliminated desktop publishing, right? It just got squeezed right out because it all got automated. We do the same thing with localization. I think AI is going to have a similar impact, whether it’s on content creation in any language, that it’s going to remove that manual labor over time. And I think that maybe we’re going to reach a point where content creation is just content creation. It’s not creating content in English so that I can translate it into the target languages. I think that that distinction between source and target is really going to evaporate. It’ll just be somebody created content, and then we have ways of making that available in other languages, and that’s where this is going to go. I’ve talked to a lot of localization service providers recently, and certainly this is one of the things that they are thinking about and looking at, is the question of what it means, to your point, to be a localization service provider in a universe where language translation specifically is automatable, maybe. Okay. Bill, any closing thoughts before we let you go here?

BS: I think this is a good place to end this one.

SO: We’ll wrap it up, and they will come and take away our microphones and put us back in the corner. Good to see you, as always.

BS: Good to see you.

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post AI in localization: What could possibly go wrong? (podcast) appeared first on Scriptorium.

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Is AI really ready to generate your training materials? In this episode, Sarah O’Keefe and Alan Pringle tackle the trends around AI in learning content. They explore where generative AI adds value—like creating assessments and streamlining translation—and where it falls short. If you’re exploring how AI can fit into your learning content strategy, this episode is for you.

Sarah O’Keefe: But what’s actually being said is AI will generate your presentation for you. If your presentation is so not new, if the information in it is so basic that generative AI can successfully generate your presentation for you, that implies to me that you don’t have anything interesting to say. So then, we get to this question of how do we use AI in learning content to make good choices, to make better learning content? How do we advance the cause?

Related links:

Synthetic audio example: Strategies for AI in technical documentation (podcast, English version)
LearningDITA: DITA-based structured learning content in action (podcast)
How CompTIA rebuilt its content ecosystem for greater agility and efficiency (webinar)
Transform L&D experiences at scale with structured learning content (podcast)
Overview of structured learning content
Get monthly insights on structured content, futureproof content operations, and more with our Illuminations newsletter

LinkedIn:

Sarah O’Keefe
Alan Pringle

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

End of introduction

Alan Pringle: Hey everybody, I am Alan Pringle, and today I’m talking to Sarah O’Keefe.

Sarah O’Keefe: Hey everybody, how’s it going?

AP: And today, Sarah and I want to discuss artificial intelligence and learning content. How can you apply artificial intelligence to learning content? We’ve talked a whole lot, Sarah, about AI and technical communication and product content, let’s talk more about learning and development and how AI can help or maybe not help putting together learning content. So how is it being used right now? Let’s start with that. Do you know of cases? I know of one or two, and I’m sure you do too.

SO: Yeah. So the big news, the big push, is AI in presentations. So how can I use AI to generate my presentation? How can it help me put together my slides? Now, the problem with that from our point of view, for those of you that have been listening to what we’re saying about AI, this will be no surprise whatsoever, I think this is all wrong. It’s the wrong strategy, it’s the wrong approach. If you want to take AI and generate an outline of your presentation and then fill in that outline with your knowledge, that’s great, I think that’s a great idea. Also, if you have existing really good content and you want to take that content and generate slides from it, I don’t have a problem with that. But what’s actually being said is AI will generate your presentation for you. If your presentation is so not new, if the information in it is so basic that generative AI can successfully generate your presentation for you, that implies to me that you don’t have anything interesting to say.

AP: And you’re going to say it with very pretty generated images and a level of authority that makes it sound like there’s something that’s actually there when it’s not.

SO: Oh, yeah. It’ll look very plausible and authoritative and it will be wrong, because that’s how this generative stuff-

AP: Or not even wrong, surface-skimmy, just nothing of any real value there.

SO: Yeah. So then, we go into this question of, how do we use AI in learning content to make good choices, to make better learning content, how do we advance the cause?

AP: Well, there’s that one case where we have done it, because we have our own learning site, LearningDITA.com, and we were trying to think about ways to apply AI to our efforts to create courses, to tell people how to use the DITA standard for content. And I think you and I both agree, one of the strengths of artificial intelligence is its ability to summarize and synthesize things, I don’t think that’s controversial. So if you think about writing assessments from existing content in a way that’s summarizing, so one of us suggested to our team, why don’t y’all try that and see what these AI engines can do to generate questions from our existing lesson content. And then, of course, we suggested that they—the people who were creating the courses—review them. So our folks reviewed them, and I think some of the questions were actually quite usable, decent.

SO: And some of them were not.

AP: True, this is true.

SO: But the net of it was they saved a bunch of time, because they said, “Generate a bunch of assessment questions,” they went through them, they fixed the ones that were wrong, they improved the ones that were maybe not the greatest, they got a couple that were actually pretty usable. And so, it took less time to write the assessments than it would’ve taken to do that process by hand, to slowly go through the entire corpus to say, “Okay, what are the key objectives and how do I map that to the assessments?” So that’s a pretty good example, I think, of using generative AI, as you said, to summarize down, to synthesize existing content. On the LMS side, so when we start looking at learning management systems and how the learning content goes into the LMS and then is given or delivered to the learner, there are some big opportunities there, because if you think about what it means for me as a learner, as a person taking the course, to work my way through course material, maybe the assumptions that the course developer made about my expertise were too optimistic. I’m really struggling with this content, it’s trying to teach me how to use Photoshop and I am just not good at Photoshop. There’s this idea of adaptive learning, this is not an AI concept, the idea behind adaptive learning is that if you’re doing really well, it goes faster. If you’re struggling, it goes deeper, or maybe you do better with videos than you do with text, or vice versa. It’s that adapt to the learner and to the learner’s needs in order to make the learning more effective. Now, if you think about that, that is a matter of uncovering patterns in how the learner learns and then delivering a better fit for those patterns. Well, that’s AI. AI and machine learning do a great job of saying, “Oh, you seem to be preferring video, so I’m going to feed you more video.” Now, we can do this by hand or we can build it in with personalization logic, but you can also do this at scale with AI and machine learning. So there are definitely some opportunities to improve adaptive learning with an AI backbone.

AP: I think it’s worth noting at this point, when you’re talking about gathering the data to make, I hate to, I’m going to personalize AI, so it can make these decisions or do the synthesis, there’s got to be intelligence that’s built into your content, and that goes all the way back to the content creation, going back from the presentation layer, back to how you’re creating your content. And again, this loops back, in my mind, to the idea of building in that intelligence with structured content, that is your baseline.

SO: Yeah. I know we’re just relentless on this drum of you need structured content for learning content, but it’s because of all these use cases, because as you try to scale this stuff, this is what you’re going to run into. I also see a huge opportunity for translation workflows specifically for learning content. So if you look at translation and multilingual delivery, there’s a lot of AI and machine learning going on in machine translation. So now, we think a little bit about what that means for learning content, and of course, all of the benefits that you get just in general from machine translation still apply, but the one that I’m looking at that I think would be really, really interesting to apply to learning is learning has a lot of audio in it, audio and video, but specifically audio, and audio typically is going to be bound to a language. You’re going to have a voiceover, you’re going to have a person saying, “Here’s what you need to know, and I’m going to show you this screenshot,” or, “I’m going to show you how to operate this machine.” And so, you’ve got audio and potentially captions that are giving you the text or the audio that goes with that video. Okay, well, we can translate the captions, that’s relatively easy, but what about the voiceover? And the answer could be that you do synthetic voiceovers. So you take your original, let’s say, English audio and you turn it into French, Italian, German, Spanish or whatever else you need, but you synthesize the voice instead of re-recording. Now, is it going to be as good as a human, an actual human person who has expression and emotion in their delivery? No. Is it better than the alternative where you don’t provide it in the target language at all? Probably, yes. And when we start talking about machines, “Here is how to safely operate this machine,” the pretty good synthetic voice in target language is probably better than, “Here it is in English, deal with it,” or, “Here it is in English with a translated caption in German, but no audio.” I think that’s what we’re looking at is, is the synthetic audio good enough that it will improve the learner experience, and I think the answer is yes.

AP: I’m turning this over in my mind, and there’s part of me that’s very resistant to the idea of these synthesized voices. For example, and this is bias on my part, when I am downloading audiobooks from the library, they now, in the app that I use that’s connected to the local library, a lot of the narration, it will say, “This is an AI-generated voice.” I tend to avoid those, I do, because sometimes the inflection’s a little odd, there’s no personality there. However, I can buy that having that slightly robotic-esque voice in another language is better than not having it at all, I can buy that.

SO: Right. And I think the audiobooks that we listen to for fun are different than I need to figure out how to use this machine without hurting myself, those are different, and I don’t need a… It wouldn’t hurt. I don’t need a personable obviously human voice to voiceover the video that helps me figure out how to use this thing on the factory floor. I wouldn’t object, but I would prefer to get something in my language. That’s really the key, because when we start asking the question, the question is less, would you prefer a really good artistic performance voiceover versus a robotic voice… That’s what you’re getting from the library, you’re saying, I am not going to consume entertainment content that is like this, and I think a lot of people are onboard with that. But what about technical product and learning content that you need? You’re not making a choice that this is something I want to do in my downtime, but rather, if I can’t figure out how to do this, bad things will happen.

AP: Yeah. There is a legitimate use case there, and they’re two different things, and I do think, based on some of the synthetic voices I’ve heard, they are getting better, quite better, and sounding a little more realistic as well.

SO: Right. We’ve already experimented with this. We have a podcast where we actually generated, it was a synthetic voice, but it was based on a person’s voice print. So it wasn’t fake AI, it was fake AI voice, but it was fake AI voice generated off of a specific person. The audio is quite good. Every once in a while between paragraphs, it shifts weirdly as you’re listening, as a new thought is introduced, and it shifts in ways that a human would not, but all in all, I thought it was pretty acceptable. So I think that what I’m trying to say in an extremely long-winded way is that when you have scalability issues in your content production, learning content or otherwise, AI has the potential to help you with productivity across multichannel workflows with repurposing content from it’s the learning content versus it’s the assessments, it’s in language A versus language B, it’s audio, it’s video. There are things that we can do there to use the AI tools for productivity to support these workflows and scale them, and to your point, and therefore, we need underlying structured content. We can’t do this with slapped-together one-off formatted mess.

AP: Yeah. The intelligence has to be built in at the very foundation, and that is when you are creating the content. That intelligence really can’t be a layer that’s put on when you transform things or you connect to an LMS, it’s not a presentation layer thing. The presentation layer needs to pull that intelligence from your source content. Again, this is why you need structured content, the metadata built in, to help drive the way you transform and distribute your learning content.

SO: Yeah. I’m, again, very skeptical of GenAI in the process of generating net-new content, new information, nobody’s ever written it before, it’s a new product, it needs to be explained, taught, whatever. Maybe an outline, this is what a typical intro course looks like, now go fill in the details, okay, maybe even a first draft, especially if product A is based on product B, or I guess the other way around. But our world is structured content, obviously, but also our world is content where it matters that the content is accurate, because when the content is wrong, bad, bad things happen, people get hurt, people die, companies get shut down for compliance reasons, that type of thing. So the content has to be accurate, and at the end of the day, it’s actually quite difficult to get GenAI to gen accurate content. That’s not what it does; that’s not its function. So I’m very interested in applying AI to various product and content roadmaps to enable productivity, to enable new deliverables, to enable new synthesis summaries, et cetera, but I’m very, very worried about what happens if you apply it on top of bad content or you apply it to the wrong use case in an effort to just get your stuff for free, essentially.

AP: So what I’m hearing in summary is that content creation for learning, AI is probably not a good fit now. To support you and help you possibly develop on the edges of that content or give you outlines and ideas, and also to augment and support delivery channels, it could be helpful. So it’s a support mechanism for the development of the content, distribution of the content, but not necessarily for the direct creation of that content.

SO: Yeah, I think that’s fair, and I think that’s where we land. I’d be quite curious to hear from our listeners, what they’re doing with this and where they’re going with it.

AP: And I’m sure people are having the same struggles right now over the best way to apply it. But I think right now, as of the moment that we’re recording this, AI is in no way ready for prime time to basically take the place of a learning content person. It should be there to support them, not to replace them.

SO: Yeah, for meaningful content.

AP: Exactly.

SO: And if it’s not meaningful, what are you even doing?

AP: Right.

SO: Well, that’s cheery, okay.

AP: And on that very cheerful note, we’re going to wrap up. So thank you, Sarah. And folks, do get in contact with us to let us know how you’re using AI, because that is of great interest to us. So thank you. Thanks, Sarah.

SO: Thank you. And maybe let us know how you’re being made to use AI.

AP: That too. Thanks, everyone.

Conclusion with ambient background music

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

Questions about this podcast? Let’s talk! "*" indicates required fields

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Tempted to jump straight to a new tool to solve your content problems? In this episode, Alan Pringle and Bill Swallow share real-world stories that show how premature solutioning without proper analysis can lead to costly misalignment, poor adoption, and missed opportunities for company-wide operational improvement.

Bill Swallow: On paper, it looked like a perfect solution. But everyone, including the people who greenlit the project, hated it. Absolutely hated it. Why? It was difficult to use, very slow, and very buggy. Sometimes it would crash and leave processes running, so you couldn’t relaunch it. There was no easy way to use it. So everyone bypassed using it at every opportunity.

Alan Pringle: It sounds to me like there was a bit of a fixation. This product checked all the boxes without actually doing any in-depth analysis of what was needed, much less actually thinking about what users needed and how that product could fill those needs.

Related links:

How humans drive content operations (recorded webinar & transcript)
Brewing a better content strategy through single sourcing (podcast)
The Scriptorium approach to content strategy
Get monthly insights on structured content, futureproof content operations, and more with our Illuminations newsletter

LinkedIn:

Alan Pringle
Bill Swallow

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

End of introduction

Bill Swallow: Hi, I’m Bill Swallow

Alan Pringle: And I’m Alan Pringle.

BS: And in this episode we’re going to talk about the pitfalls of putting solutioning before doing proper analysis. And Alan, I’m going to kick this right off to you. Why should you not put solutioning before doing proper analysis?

AP: Well, it’s very shortsighted and oftentimes it means you’re not going to get the funding that you need to do the project to solve the problems that you have. And with that, we can wrap this podcast up because there’s not a whole lot more to talk about here, really. But no, seriously, we do need to dive into this. It is very easy to fall into the trap of taking a tool’s first point of view. You’ve got a problem, it’s really weighing on you. So it’s not unusual for a mind to go, this tool will fix this problem, but it’s really not the way to go. You need to go back many steps, shut that part of your brain off and start doing analysis. And Bill, you’ve got an example, I believe, of how taking a tool’s first point of view didn’t help back in a previous job you had.

BS: I do, and I’m not going to bury the lead here, but they didn’t do their homework upfront to see how people would use the system. So I worked for a company many, many, many years ago that decided to roll out and I will name the product. They rolled out Lotus Notes.

AP: You’re killing me. That’s also very old, but we won’t discuss that angle.

BS: But they did so because it checked every single box, every single box on the needs list, it did email, it had calendar entries, it did messaging, notes, documents, linking, sharing, robust permissions, and you even had the ability to create mini portals for different departments and projects. So on paper, it looked like a perfect solution. And everyone, including the people who greenlit the implementation of Lotus Notes, hated it. Absolutely hated it. Why did they hate it? It was difficult to use. It was very slow. It was very buggy. Sometimes it would crash and leave processes running, so you couldn’t relaunch it. There was no easy way to use it. Back at that point, we had PDAs, personal digital assistants, and very soon after that we had the birth of the smartphone. There was no easy way to use it in these mobile devices except for maybe hooking up to email. It didn’t fit how we were working at all. While it shouldn’t count, it really wasn’t very pretty to look at either. So everyone bypassed using it at every opportunity. They would set up a Wiki instead of using the Lotus Notes document or notes portal that they had. They would use other messaging services. This is back during Yahoo Messenger and ICQ. But yes, we had that going on and in the end it was discontinued after its initial three-year maintenance period ended because nobody liked it.

AP: Yeah, so sounds to me like there was a bit of a fixation. This product checks all the boxes without actually doing any in-depth analysis of what you needed, much less actually thinking about what users needed and how that product could fill those needs. And I think it’s worth noting too, think about this from an IT department point of view, because they’re often a partner on any kind of technology project, especially if new software is going to be involved because they’re going to be the ones a lot of times that say yay or nay, this tool is a duplicate of what we already have. Or no, you have some special requirements and we do need to buy a new system. So if I as an IT person, the person who vets tools hears from someone, and let’s get back into the content world, I need a way to do content management and I need to have a single source of truth and I need to be able to take the content that is my single source of truth and then publish to a bunch of different formats. This is a very common use case. I would be more interested as an IT person in hearing that than hearing I have to have a component content management system. There’s a subtle difference there. And I think, and this is possibly unfair and grouchy of me, but that is me, grouchy and unfair. If I hear someone come to me, I need this tool instead of I have these issues and I have these requirements. It sounds selfish and half-baked.

BS: It does.

AP: And again, I am thinking about this from the receiving end of these queries, of these requests, but I also want to step back into the shoes of the person making a request. You can be so frustrated by your inefficiency and your problems, you latch onto the tools. So I completely understand why you want to do that, but you are basically punching yourself in the face when you go and make a request that is, I need this tool instead of I have these issues, these requirements, and I need to address these things. It’s subtle, but it’s different.

BS: It’s very different. And also if you do take that approach of looking at your needs, you find that there’s more to uncover than just fixing the technological problem itself.

AP: Yes.

BS: There might be a workflow problem in your company that you may acknowledge, you may not know it’s quite there. Once you start looking at the requirements and looking at the flow of how you need to work, and how you need any type of new system to work, you start seeing where the holes are in your organization. Who does what? What does a handoff look like? Is it recorded? What does the review process look like? When does it go out for formal review? What does the translation workflow look like? And you start seeing that there may be a lot of ad hoc processes in place currently that could be fixed as well.

AP: True. And I also think when you’re talking about solving problems and developing your requirements from that problem solving, you are potentially opening up the solution to more than just your department, your group. It can possibly be a wider situation there, too. And also by presenting it as a set of problems and requirements to address those problems, there may be already a tool in-house at your company that you don’t know about or there may be part of a suite of tools, and if you add another component to it will address your problem instead of just buying something completely outright. And we’ve seen this before, where it turned out there was an incumbent vendor that had some related tools already at the company, and that company also had a tool that could solve the problems that our client had or our prospect had. We’ve had both prospects and clients have this issue, so it doesn’t make sense, therefore, to go and say, I need this tool, which is essentially a competitor of what’s already in place. You’re going to have a very uphill battle trying to get that in place. It is also very easy, as someone who has already done a content ops improvement project, to understand this tool is good. It saves me at this company, but you’ve got to be careful of thinking just because it helped you over at company A. Now you’re at company B, it may not be a fit for company B culturally, there may be already something in-house. So you’ve got to let go of those preconceived notions. I am not saying that the tool you used before was bad. It may be the greatest thing ever, but there may be cultural issues, political issues, and even IT tech issues that mean you cannot pick that tool. So why are you pushing on it when you have got all of these things against you? Again, it is easy to fall into these traps. Don’t do it.

BS: Yep. On the flip side of that, we had a situation where a customer of ours years ago was looking for a particular system, a CCMS, component content management system, and they had what they perceived to be a very hard requirement of being able to connect to another very specific system.

AP: Yes, I remember this. It was about 10 or 11 years ago.

BS: And it was such a hard requirement that it basically threw out all of their options except for one. And we got the system working the way they needed it to. It needed quite a bit of customization, especially over the years as their requirements grew. But in the end, they never connected to that requirement system. The one that everyone said this would be a showstopper. They never connected to it because they just decided it wasn’t a requirement after X many years. And that just kills me because there could have been three or four other candidate systems that would’ve easily have fit the bill for them as well and probably would’ve cost them a little bit less money. But there we are.

AP: In fairness, all parties involved, including us, we’re working on the information that we had at the time. And I think this is a case where a requirement that we thought was a hard requirement turned out not to be. However, just because this happened in this case, folks out there listening to us, that does not mean that if a particular requirement points at a particular system that it could be not a real requirement because you want another system really badly. So you want to ignore that really hard, not how that works. It’s not how that should work. So I think there is a balance here that needs to be struck, and I think this is probably a good closing message. Don’t follow your knee-jerk instinct in regard to, I need this tool. Really look at the requirements, do an analysis. And because we’re humans, sometimes that analysis is not going to catch other things that it should have. Or you may end up having, like you just mentioned, a requirement that that’s not necessarily as real as you thought that it was. But I think your chance at project success and getting a tool purchased can configure and up and running are much higher when you start with those requirements than you start off with, I need tool Y.

BS: Well said. Do the homework before the test.

AP: And don’t put the cart before the horse.

BS: Well, thank you, Alan.

AP: Thank you. This was shorter, but it’s an important thing, and I think, again, this points to any kind of operational change being a human problem and dealing with people’s emotions and their instincts as much or more than an actual technological issue.

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

Need to talk about content solutioning? Contact us!The post Tool or trap? Find the problem, then the platform appeared first on Scriptorium.

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Struggling to get the right content to the right people, exactly when and where they need it? In this podcast, Scriptorium CEO Sarah O’Keefe and Fluid Topics CEO Fabrice Lacroix explore dynamic content delivery—pushing content beyond static PDFs into flexible platforms that power search, personalization, and multi-channel distribution.

When we deliver the content, whether it’s through the APIs or the portal that you’ve built that is served by the platform, we render the content in a way that we can dynamically remove or hide parts of the content that would not apply to the context, the profile of the user. That’s the magic of a CDP. It’s delivering that content dynamically.

— Fabrice Lacroix

Related links:

Scriptorium: Personalized content: Steps to success (white paper)
Scriptorium: AI in the content lifecycle (white paper)
Fluid Topics, an AI-powered content delivery platform
Fluid Topics: What is Content Operations and Why is it Important?
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LinkedIn:

Sarah O’Keefe
Fabrice Lacroix

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

End of introduction

Sarah O’Keefe: Hi everyone, I’m Sarah O’Keefe and I’m here today with the CEO of Fluid Topics. Fabrice, Lacroix. Fabrice, welcome.

Fabrice Lacroix: Hey. Hi Sarah. Nice being with you today. Thanks for welcoming me.

SO: It’s nice to see you. So as many of you probably know, Fluid Topics is a content delivery portal or possibly a content delivery platform. And we’re going to talk about the difference between those two things as we get into this. So Fabrice, tell us a little bit about Fluid Topics and what that content delivery portal or maybe platform. Which one is it? What do you prefer?

FL: For us, it’s platform definitely. But you’re right, depends on where people are in this evolution process, on how they deliver content. And for many, many customers, the piece stands for a portal. You’re right, because that is the first need. That’s how they come to us, because they need a portal.

SO: Okay, so in your view, the portal is a front end, an access point for content, and then what makes it a platform rather than a portal?

FL: Probably because the goal that many companies have to achieve is delivering that content where it’s needed. It’s many places most of the time. So it’s not just the portal itself, and that’s where solving the problem of being able to disseminate this content to many touch points, you need a platform for that. The portal is one touch point only, but when you start having multiple touch points like doing in-product help or you want to feed your helpdesk tool or field service application or whatever sort of chatbot somewhere else, whatever use case you have that is not just the portal itself, then that becomes a platform thing.

SO: So looking at this from our point of view, so many of our projects start with component content management systems, CCMSs, which are the back end. This is where you’re authoring and managing and taking care of all your information, and then you have to deliver it. And one of the ways that you could solve your delivery front-end would be with a content delivery platform such as Fluid Topics. Okay. So then, what are the prerequisites, when you start thinking about this? So our hypothetical customer has content obviously, and they have, we’re going to say probably a back-end content management system of some sort, probably.

FL: Most of the time.

SO: Most of the time.

FL: Depends where you go, depends on the maturity and the industry. If you go to some manufacturing somewhere, they mostly still are maybe on the word and FrameMaker or something like that in design, and then they generate PDFs.

SO: So maybe we have a backend authoring, well, we have an authoring environment of some sort on the back-end. Maybe it’s a CCMS, maybe it’s something not like that. And now we’re going to say, all right, we’re going to take all this content that we’ve created and we’re going to put it into the CDP, the content delivery platform. Now, what does success look like? What do you need from that content or from the project to make sure that your CDP can succeed in doing what it needs to do?

FL: The first answer to that question that comes to my mind is no PDFs. I mean, if you look at it, don’t laugh at me. If you look at it from an evolutionary perspective, it’s like regardless how people were writing before, it was not CCMS, mostly unstructured. And at the end of the day, people were pressing a button and generating PDFs and putting the PDF somewhere, CRM, USB key, website for download. But managing the content unstructured was painful. That’s where you start working with the CCMS, because you have multiple versions, variants, you want to work in parallel, you want to avoid copy paste, translation, so the story around that. So then companies start and they start moving their content into CCMS. All of the content, part of the content, but they start investing in a modern way of managing, creating their content. But again, if you look at it once they have made that move, most of those companies 10, 15 years ago probably were still pressing a button and still generating PDFs. And then they realized that they had solved one problem for themselves, which is streamlining the production capability and managing the content in a better way. But from a conception perspective, regardless whether you work with word FrameMaker or in DITA with the most advanced CCMS of the market, if you still deliver PDF, you are not improving the life of your customers. And then people started realizing that, oh yeah, so we should do better. So let’s try to output that content in another way than PDFs. And then say, “What else than PDF, do we have? HTML.” And was like, okay, and let’s output HTML. But HTML that is pretty much the same as the PDF. You see what I mean? It’s like static document. Each document was a set of HTML pages. And then they started realizing that they need to reassemble the set of HTML pages into a website, which is even more painful than just putting PDFs on the website is reassembling zip files of HTML pages on the website, and then it’s like static HTML. And then you have to put a search on top and have to create consistency. And that’s why CDP have emerged. That’s solving this need, which is, how do we transition from PDF to static HTML to something that is easier, that ingest all this content, comes with search capabilities, comes with configuration capabilities, and as well at the same time as API, so that back to the platform thing, it’s not just a portal, but can serve other touch points. So that’s really because we are in the detail world, DITA is the Darwin Information Typing Architecture. So that’s a very Darwinian process that led to this creation of the CDP and the need of a CDP is the next step in the process. And many companies really follow that process of, I have to go from my old ways of writing, which are not working painful, move to a CCMS, but in fact realize that they don’t solve the real problem of the company, which is how can I help my customer, my support agent, my field technicians better find the content better use my content? And that’s where this T, oh, okay. That’s where we need a CDP.

SO: Yeah, and I think, I mean, we’ve talked for 20 years about PDFs and all the issues around them, but it’s probably worth remembering that PDF in the beginning was a replacement for a shelf of books, paper books that went out the door. And the improvement was that, instead of shipping 10 pounds, or I’m sorry, what four kilos of books you were shipping as you said, a CD-ROM or this was before USB, a zip drive. Remember those?

FL: Zip drive.

SO: A zip drive. But you were shipping electronic copies of your books and all you were really doing was shifting the process of printing from the creator, the software, hardware, the product company to the consumer. So the consumer gets a PDF, they print it, and then that’s what they use. Then we evolved into, oh, we can use the PDF online, we can do full-text search, that’s kind of cool, that was a big step forward. But now to your point, the way that we consume that information is not printed and it’s for the most part, and it’s not big PDFs, but rather small chunks of information like a website. So how do we evolve our content into those websites? So then what does it look like to have a, and I think here we’re talking about the portal specifically, but what does it look like to have a portal for the end user that allows them to get a really good experience in accessing and using and consuming the content that they need to use the product, whatever it may be. What are some of the key things that you need to do or that you can do?

FL: Yeah. I would say that the main thing that a CDP is achieving compared to static HTML, because now we have to compare not with PDFs that are probably still needed if you want to print as well, I’m not saying that PDF is dead and we should get rid of all PDFs. Just said that it’s just when you need to print, then you can get the PDF version of a document. But if we compare static HTML with what a CDP brings, we’re trying to make content personalized and contextual. If you pre-generate static HTML pages, it’s one size fits all. It’s the same HTML pages for everyone. And if you have two versions of your product and one variant, and then you translate the same zip file exists in 20 versions, so to say, and you have to assemble that and let people understand how to navigate that and that should become super complex. What a CDP solves is like, give me everything, and I will sort out this notion of I understand the fact that the same document can exist in 20 variants, whether it’s product version, document version, capabilities of the product version A, version, B, Asian market, European market, American market. And then you have subtilities and some paragraphs are here, some paragraphs are removed, added. And so we are adapting the content so that it fits the profile of the user. And if you ask me what’s needed to make a CDP work, it’s mostly metadata, metadata, metadata. And I can tell you a story, what was fun? It’s like, few years ago, some years ago, more than few, we had customers reaching out or expecting customers to reach out and say, “Oh, show me three topics.” And then we’re showing the capability and say, “Oh my God, it’s exactly what we need.” And then those guys disappeared for two years. And in fact, what they did during these two years is like adding metadata to the content. It was not about the product, but through this discussion we had with them and showing that you can put facets for the search and then varianting content and let people switch between variants and versions of the content through metadata and all that, and they realized that, oh my God, that’s exactly what we need. And then through their questions, they understood that they needed to have those metadata on the content and those metadata were not existing and still they were working with the CCMS. But if your output channel are PDFs, if you don’t put PDFs, you don’t care about putting this metadata on the content inside the CCMS. That’s a lot of work to do to maintain those metadata. But if at the end of the day you print a button and you generate a PDF, those metadata are lost, they are not used, they’re not leveraged by the PDF. So that becomes flat pages of content. So they had transitioned to a CCMS but never made this investment of tagging content. And when I mean tagging content, it’s not just the map, it’s like the section, the chapter, this is for installing, this is for removing, this is for configuring, this is for troubleshooting, this chapter is about this, this topic is about that for this version of the products. You know what I mean? Fine-grained tagging at different level of the documents. And because they were generating PDFs, they didn’t see the need of making that tagging at the right level, and they realized that suddenly the sheer value they could get from PDF is when the content is tagged because that’s using those tags and those metadata schemes that the CDP can adapt the content to the context profile of the user. So I would say, what’s needed to leverage the capabilities of a CDP? It’s mostly granularity of content and tags, metadata that let people, and you can design your metadata from a user perspective. As an end user, how would I like to filter the content? What are the tags I need for filtering the content? It’s like, if I run a search, I have these facets on the left side of the search result page, what would I like to click on to refine my search and spot the content that fits my needs?

SO: And I think, going back to our flat file PDF or static HTML, if we need to do this kind of thing, if you need context in a flat file, what you have to do is say something like, if you have product variant A, do this. And if you have product variant B, do this. Or if you are installing and the temperature, the ambient local temperature is greater than X, then do these extra steps. If you are baking and you are at high altitude, you have to adjust your recipe in these ways. So you end up with all these sort of if statements that are, hey, if this is you do these things, but it’s all in the text, because I have no way, maybe I can do two variants of the PDF like variant A for regular altitude and variant B for high altitude. But I can’t do one per country, right? I mean, I guess I could, but ultimately, what you’re describing is that instead of putting it into the text explicitly, “Hey Fabrice, if you meet these conditions, do these things or don’t do these things or do these extra things,” the delivery portal, platform is going to say, “Okay, what do I know about this end user? What do I know about Fabrice? I know he is in a certain location with a certain preferred language and a certain product. I know which products you bought.” So therefore you don’t get an if, if, if, if, you just get, here’s what you need to do in your context with your product.

FL: Exactly. When we deliver the content, whether it’s through the APIs or the portal that you’ve built and that is served by the platform, we render the content in a way that we can remove or hide dynamically parts of the content that would not apply to the context, the profile of the user. And that’s the magic of CDP. It’s making that content dynamically. It’s also called dynamic content delivery. You remember we had this concept, the dynamic part is, how can I dynamically leverage the metadata on the content side or the conditions that I adapted, read through metadata schemes and make that applicable to the situation and the user profile? So that’s the magic part of it, and that’s a huge improvement compared to a static document that lists all the conditions and then you put the burden on the reader to figure out, sort out inside the document what should be skipped and what to do depending on the product configuration.

SO: Which can of course get very complicated. Now you mentioned product help, in-app help, context sensitive help. So what does it look like to use a Fluid Topics or this class of tool to deliver context sensitive help or in-app help?

FL: We are back again to this granularity and the metadata. So imagine you are a software vendor, you design a web application that you have created and you want to do the inline help for your application, your web product. What would you do? You would say in that page, when people click on that question mark or help button, we should open a pane and display that information. That information needs to be a topic, it needs to be written, and the granularity should be a topic because that’s what you pull from the system. So that’s where we need the granularity that’s matching what you want to display inside your app, whether it’s a tool tip, maybe a small tool tip when you move something in the app and then that becomes some fragment of content you need to get from the CDP dynamically. That can be one page of explanation that you display in a pane that opens in your app, but you need to pull that content. So the same way that that’s how you would do it, you were embedding the content inside the application itself. You would write each part of the explanation, the help that you want to display as fragments of information. If you are doing it statically inside the application, but the problem is that if you want to fix something or enhance the content, you have to edit the application, change the… So it’s part of the development. Here, you want the app to pull the content dynamically because the same content can be not only used to be displayed live in the screen, real time. But can be the same content that is used on the doc portal or then you print a PDF on how to do this. That’s the same. You don’t want to maintain the same explanation, in the application, in the portal, in PDFs. So one source. So it’s exactly that. And then you’re pulling through metadata. The app will say, “Oh, give me what goes into that page.” So it’s metadata-driven as well.

SO: Right? So there’s an ID on the software or something like that, and it says, “Give me the content that belongs with this unique label.”

FL: Exactly. Behind each button you give an ID to that button, which is the question mark in that page. When people click pull content, inline content help, ID number 1, 2, 3, 4. And on your CCMS, you have a metadata, which is called content ID for inline help, whatever. And then you tag that piece of content, 1, 2, 3, 4, and then that’s it. Magic is done. So it’s that simple.

SO: So what I’m hearing, and this is in fairness, exactly what you started with is, you have to have metadata, right? On the content.

FL: You have to have metadata.

SO: And without the metadata there is, well, let’s talk about magic. So if you have a front end that is some sort of a large language model that bought something, what does that mean in terms of this content delivery platform? I mean, can’t you just use ChatGPT and call today?

FL: Yes, that’s a good one. I think most of the project AI project we’ve seen in large companies when they started to do, oh, let’s build a chatbot. That’s the magic dream of any company like building the chatbot that replies to any question. Okay, so how does the project start usually? You have the IT, some people in the IT team or the IT team is hiring external people specialized in AI and they realize that they need content. So the first thing they do is they come usually to the TechDoc team and say, “Give me all the content that you have.” And the TechDoc team says, “Okay, we have all these DITA contents.” You say, “No, I don’t want DITA, I want PDFs.” That’s huge to see that. Why? Because they use technology like something from Microsoft, you can build your chatbot in five minutes, but then the only content types you can fit this ready to use platform is with PDFs and Word. So all the magic you’ve put in your content and the tags are lost and you see people getting PDFs out of you wanting PDFs from your content, which is the exact opposite of the investment you’ve made. Putting PDFs somewhere on the storage place and say to Microsoft Chatbot, blah, blah, this is the content, this is the knowledge of the company. And then when you have 20 variants of the same product, then no metadata anymore. Then the chatbot is always mixing all the content. And when you start asking real questions about how to do this, how to do that with this version of the product, everything is lost. And then the chatbot start hallucinating, not because the LLM is hallucinating, because the LLM just the system, the chatbot does not know what PDF to use because it’s implicit to know that this PDF applies to that version of the product or that version. It’s even worse if you say, “If you have product A, do this, if you have product B, do that and start mixing conditions and then just the knowledge becomes barely readable by humans that make mistake reading it. So can you imagine how an LLM can make sure that it’s putting the right information from that complex text structure?

SO: Okay, so make PDFs out of DITA, dumb it down, send it to the chatbot, that’s bad.

FL: And then it’s guaranteed failure.

SO: So what’s the good version of this?

FL: But that’s how it works. I guess, I write that you’ve seen this sort of projects where people were asking for the content, thinking that the more they have, the better it’s going to be. And suddenly they realize that, that chatbot is not working and doing many mistakes. And they call that hallucination, because if the LLM was hallucinating, but it’s not, it’s just able to feed the LLM dynamically with the right retrieval, augmented generation scheme to dynamically provide the information for replying to the question because it’s difficult to pull from the PDF the right information that applies to the context. And we are back to, what is the context? What is the machine? What is the profile of the user? What is the variant, the version, the whatever you have in front of you? So that’s the complex part. So what’s the relationship? What is the successful AI? What’s the relationship between CDP and AI? All AI projects I’ve seen start regardless of us, regardless of Fluid Topics, start with we need to gather content. We need to take the content that we have, put it in one place, create this sort of unified repository of content. The promise that usually, as I said, they do it using static document, PDFs, to analyze blah blah. If you look at what a CDP is, that’s exactly what it is. It’s already your repository of content. At least everything around the product, because we’ve been talking about CCMS published to CDP. What also makes a CDP very special is that, not only can we ingest this DITA content, but also this legacy PDF and markdown content, API documentation knowledge bases. So the CDP is here to ingest all the knowledge that you have around your product, not just necessarily the formal techdoc, the proper techdoc that has been well written and validated. So we have already, well, the CDP is exactly that. It’s building, that’s the purpose of it. It’s building that unified repository and that’s where you should start from. And it’s fine grained, and we have the metadata and we have everything, so we know how to feed the LLM. So there are two things in an AI project. One is the LLM, but now people use generic LLM, you don’t fine tune, train an LLM anymore for this sort of use case that is just a chatbot for replying to questions and solving cases automatically. You use a generic LLM and you feed the LLM dynamically with the fragments of content of knowledge that you have in your repository. And that’s where just as a human, when you run a search, you look for content, you know what part of content, what are the fragments, the topics, the chapters that contain the knowledge for replying to that question? The tough part is, extracting that from the repository. Am I extracting the 2, 3, 4 pages around the question that are matching the version, the situation that I’m in? So that I can then feed the LLM and say, “This is the 10 pages of knowledge that we have, or 20 or 50 pages of knowledge. This is the question replied to the question using that knowledge.” That’s exactly what a chatbot does. You’re giving the question of the user, you give 5, 10, 20, whatever number of pages of knowledge that you have in your repository and you ask the LLM say, “This is the question, this is the knowledge, please reply.” So the test part is extracting the 5, 10, 20 pages that are really adapted to the situation, to the context.

SO: And the metadata helps you do that.

FL: And the metadata. Nothing else than metadata for doing that.

SO: Right. Okay. So we’ve talked a lot about metadata as I guess a precondition, right? A prerequisite. Yeah, it is. If you don’t have metadata, none of these other things are going to work. And I wanted to ask you about other, maybe, challenges or prerequisites. So other than people coming in and saying, oh, right, we need metadata, and then they go away for two years and then they come back and they have some metadata, what are the other issues that you run into when you’re trying to build out a CDP like this? What are some of the other… What are the top challenges that you run into other than clearly metadata? So we’ll put that one at number one.

FL: Oh yeah, clearly number one. I would say the second one now is the UX UI people want to design. Because modern platform have unlimited capabilities in designing the front end, the UI that you want. It’s like what do you want? What makes sense for regarding, based on your product types, the user that you have, the content that you have, what is the UX you want to build? That’s interesting, because probably five, no, let’s say 10 years ago, we were providing default interfaces out of the box with the product, with three topics to build your portal. And you could just brand that, put your colors, logo, tweak it a bit, and everybody was happy with that. And then we’ve seen a big evolution because now for many companies, marketing everywhere to say on UX, you have now UX director of VP of user experience that were not existing five years ago, 10 years ago. See what I mean, everybody was working is on swim lane. The techdoc department was in charge of writing the content and probably generating the PDFs and then setting up a doc portal. But many companies have realized that this tech doc portal is instrumental to the performance of the company. And now it says, “Oh, we need to have a look at that.” So it becomes a shared place. See, you’ve seen that I guess in your project.

SO: Yeah. Yeah.

FL: Five years ago, 10 years ago, the only people you had to work with and educate and discuss with were probably the tech dog team. And now you’ve got marketing and you’ve got customer support, and you’ve got customer experience people. And because they’ve realized the value there is in this content, but as well as how important it is to design the writer’s experience that fits with the other touch points of the company to create a seamless journey when you go from the corporate website to the documentation website to the help desk tool to the LMS. And you need some consistency around that, not only in terms of just branding colors and logos, but you go beyond that. And we see this as a new place where people struggle a bit. Our customers struggle is what do we want? In fact, they know that marketing says we need something that is more modern, more like this, more like that. But we start opening the discussion, what is it really that you want? Some companies are very mature, they got the Figma mockups and they come to us, “This is what we need to implement. We’ve spent two years with UX designer crafting the UX of our portal.” And some come and say, “Oh my God, you’re right. We don’t know what you need. Give us a default, something to start with and we’ll see.”

SO: Well, you’ll appreciate this. I had a call not too long ago with a very, very, very, very large company, very large. And they said, “We need a front end for our content, this tech content that needs to go out into the world, we need a design for it.” And because it’s a very large company, I said, “Great, where’s your UX team? And do you have a design system?” Because, I mean presumably they do. And the person I was talking to said, “I don’t know. I don’t think so.” And so I consulted the almighty search engine and discovered that not only did this particular company have a design system, they had something that is publicly available, that is their design system that you can go get all the pieces and parts and all the logos and all the behaviors and everything. It is all out there in the world. And yet, the people that work at this organization and in their defense, there are many, many tens of thousands of them did not know that this thing existed. And so all of their requirements in terms of what they had to do for their portal design were right out there in the world accessible to me.

FL: They didn’t even know about it.

SO: And they had no idea that it existed. And so we had to be the ones to make that connection and say, okay, we have to talk to the people or at least download all these assets and then figure out what to do with them and then make sure that we’re following the rules and all the rest of it. So to your point, the enterprise issues, and we also run out into this with metadata and taxonomy, that that is typically an enterprise problem, not a departmental problem. And actually making those connections across the departments for the first time is a task that very often falls to us as the consultants on the outside who are asking, “Do you have a taxonomy project? Do you have design systems? Do you have these enterprise assets that we need to align with and be consistent with?” And they’re not ready for that question, because it was until recently, put a pile of PDFs somewhere.

FL: That’s just a known and you don’t know what you don’t know. And when they start moving up to more capable tools, they discover that it comes with more capabilities, but they have to make choices, they have to invest in metadata, UX design and all that. And it’s probably some of those companies are not ready yet. I mean, they didn’t foresee that coming. And that’s where the project lag a bit in terms of complexity as well, because they realize that it’s not just buying the tool as well, making the investment on their content, their UX strategy, their design system and all that. That may be missing in some cases.

SO: And I think that probably saying it’s not just about buying the tool is really a good summary of this whole situation. Because we started with you’re really going to need metadata, and if you don’t have metadata, that’s a huge problem. And we’ve landed on, and there are all these other connections and pieces and parts that you have to think about. So Fabrice, thank you very much. This was a great discussion and I appreciate all your information and we will wrap this up there. Are there any parting thoughts that you want to leave people with?

FL: It was an absolute pleasure having this discussion with you, Sarah. I think it could have last another hour easily, so we need to stop somewhere. Maybe we’ll have another opportunities to keep on chatting about some of the subjects.

SO: Yep. Sounds good. And thank you again, and we will see you soon.

Christine Cuellar: Thank you for listening to Content Operations by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Deliver content dynamically with a content delivery platform appeared first on Scriptorium.

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Are you considering a structured approach to creating your learning content? We built LearningDITA.com as an example of what DITA and structured learning content can do! In this episode, Sarah O’Keefe and Allison Beatty unpack the architecture of LearningDITA to provide a pattern for other learning content initiatives.

Because we used DITA XML for the content instead of the actual authoring in Moodle, we actually saved a lot of pain for ourselves. With Moodle, the name of the game is low-code/no-code. They want you to manually build out these courses, but we wanted to automate that for obvious reasons. SCORM allowed us to do that by having a transform that would take our DITA XML, put it in SCORM, and then we just upload the SCORM package to Moodle and don’t have to do all the painful things of, you know, “Let’s put a heading two here with this little piece of content.” And the key thing is that allowed us to reuse content.

— Allison Beatty

Related links:

Self-paced, online DITA training with LearningDITA.com
Structured authoring and XML (white paper), which is also included in our book, Content Transformation
Confronting the horror of modernizing content
The benefits of structured content for learning & development content
Get monthly insights on structured learning content, content operations, and more with our Illuminations newsletter

LinkedIn:

Sarah O’Keefe
Allison Beatty

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

End of introduction

Sarah O’Keefe: Hi everyone, I’m Sarah O’Keefe.

Allison Beatty: And I’m Allison Beatty.

SO: And in this episode, we’re focusing in on the LearningDITA architecture and how it might provide a pattern for other learning content initiatives, including maybe the one that you, the listener, are working on. We have a couple of major components in the learningDITA.com site architecture. We have learner records for the users. We have e-commerce, the way we actually sell the courses and monetize them. That is my personal favorite. And then we have the content itself and assorted relationships and connectors amongst all those pieces. So I’m here with Allison Beatty today, and her job is to explain all those things to us because Allison did all the actual work. So Allison, talk us through these things. Let’s start with Moodle. What is Moodle and what’s it doing in the site architecture?

AB: Okay. So Moodle is an open-source LMS that we-

SO: What’s an LMS?

AB: Learning management system, Sarah.

SO: Thank you.

AB: And we installed Moodle, our own instance of Moodle and customized it as we saw fit for our needs. And that is the component that acts as the layer between the content and the learning experience. So without the Moodle part, it’s just a big chunk of content that you can’t really interact with. And Moodle gives that a place to live.

SO: And then Moodle has the learner records, right?

AB: Yes.

SO: And what about groups? What does that look like?

AB: In Moodle, there’s a cohort functionality which allows us to use groups so that a manager can buy multiple seats and assign them to individuals and keep track of their course progress through group registration rather than individual self-service signups.

SO: So if I were a manager of a group that needs to learn DITA, instead of having to send five or 10 or 50 people individually to our site, I could just sign up once and buy five or 10 or 50 seats in a given course and then assign those via email addresses to all of my people, right?

AB: Exactly.

SO: Okay. So then speaking of buying things, we had to build out this e-commerce layer, which I was apparently traveling the entire time that this was going on, but I heard a lot of discussion about this in our Slack. So what does it look like? What does the commerce piece look like?

AB: Yeah. So it is a site outside of the actual learningDITA.com Moodle site that has a connector into Moodle so that you can buy a course or a group registration in the store, and then you get access to that content in Moodle.

SO: So we have this site, this actually separate site, and if you’re in there, you can do things like buy a course or buy a collection of courses or a number of seats. And then what were some of the fun complications that we ran into there?

AB: Oh yeah. So the fun complications there were figuring out how to set up an commerce site that A, connected to Moodle so that we could sell the courses, and B was able to process taxes and payments and all of that fun stuff. So Moodle has PayPal as a feature just out of the box and the base Moodle source code. But we wanted to accept credit cards directly and so that meant some additional layers, which is how we ended up with the store.scriptorium.com site, which is built on WordPress and uses a connector, the aforementioned connector, to make those two sites talk to each other. So they’re actually, the LMS and the e-commerce piece are totally separate websites, but exist within the same system environment.

SO: And most of you listening to this probably don’t care, but one of the things we learned was that digital training, downloadable training content is sometimes subject to sales tax and sometimes not, depending on the particular state or the particular jurisdiction. So it’s not just, what is sales tax in North Carolina versus what is sales tax in Washington state versus what is it in Oregon? But additionally, in each jurisdiction is this type of training subject to sales tax or not. So we spent a more than optimal amount of time on figuring out all of those things and making sure we get it right, because I’m extremely interested in making sure that those taxes are done correctly and keep us out of trouble.

AB: And the basic PayPal and Moodle wasn’t going to give us that level of granular control and specification.

SO: And typically our customers are looking to pay via credit card. So we’ve got the LMS piece with the learner experience, the actual learning platform. We’ve got the e-commerce piece with the Let’s Take Money piece. And then finally we have the content piece. So what does it look like to actually create these courses and create and manage the content that then eventually goes into Moodle?

AB: Yeah. So the content does have a single source of truth. It is all authored in DITA XML and stored in a central repository. You can see that content in GitHub. It’s open source. We took the DIT XML and we developed a SCORM transform that we could use to hook the content up into Moodle and be able to use all of the grading and progress and prerequisite type things that we needed to flush out the actual learning platform. We had learned a fun lesson along the way that Moodle does not support SCORM 2004. So that required a little bit of backtracking to make sure that we were getting the data into the correct SCORM to get into Moodle. And so because we used it XML for the content instead of the actual authoring in Moodle, we actually saved a lot of pain for ourselves with Moodle. The name of the game with Moodle is low-code/no-code, and they want you to manually build out these courses. But we wanted to automate that for obvious reasons, and SCORM allowed us to do that by having a transform that would take our DITA XML, put it in SCORM, and then we just upload the SCORM package to Moodle and don’t have to do all the painful things of let’s put a heading to here with this little piece of content. And the key thing is that allowed us to reuse content as well. And then if we need to update the content, all we have to do is replace the SCORM package in Moodle.

SO: So currently we have DITA 1.3 content out there. The DITA 2.0 content is under development, and I would say mostly done. We’re mainly waiting for the actual release of the those two chunks of content, although those courses are going to be in GitHub in the DITA training, or I think it’s called Learning DITA now, the Learning DITA project.

AB: Yep.

SO: Separately from that, we’re working on some new courses which are not going to be open sourced, but will be available on Moodle or… Sorry, on learningDITA.com. And so for those of you that are wondering, we’ve got a number of things on our roadmap. I’d love to hear more from people listening to this about what they need out of this. What more advanced courses are you looking for? One thing that we’ve heard a lot of requests for is a DITA open toolkit plugins 101.

How do I build a plugin? How do I use best practices? How do I make this all happen? So we have this, I don’t know, DITA inception thing happening because we’re training people on how to do DITA using DITA inside DITA, building out the stuff.

AB: It’s all very meta.

SO: It’s extremely meta. Hypothetically, what would it look like to localize this? So what we’ve delivered right now is in English, and in the past we have had people put together both, let’s see, German, Chinese, and I think French versions of the Learning DITA content. But what does it look like in this new architecture to localize?

AB: Yeah. So much like the tool chain for this new architecture, there are a couple of different components, and if you would like to localize the Learning DITA content, what you’ll want to look at is the content itself, translating and localizing the source content, but you’ll also need to localize Moodle some. So what you would do is make a, basically clone the Moodle site, and you’ll have to, not to go too into the Moodle weeds, but you’ll need to reconfigure the initializing PHP file a little bit. And then you would take your translated localized content and prep that up into your new Moodle for whichever language you’re localizing into.

SO: So it looks as though, you mentioned maintenance and this idea that Moodle by design wants you to make updates inside Moodle, and we pulled the content out of there. We’re basically saying Moodle is for learners and learning management and course records and sequencing and those kinds of things, and grading, I suppose, but the DITA back end is for content. So we’re putting all the content in DITA and then we push it over to SCORM, which then goes into learningDITA.com into the Moodle site. It sounds like more work, right? We had to build a SCORM transform. We had to put all this stuff in… We didn’t just go into Moodle and start authoring, which would be a lot faster on day one. So what’s the rationale for that? What does it look like in the long term to maintain something in Moodle versus to maintain something in the system that we’re describing?

AB: Yeah. It may seem easier on day one to manually put the content in, but when you need to make an update or change something, or particularly if you want to change something about a piece of content that is reused and repeated throughout the courses, you have to manually trawl through every single course page and make those updates, whereas with the SCORM package, once you have the SCORM transform set up and running to your liking, you can run your DITA content through there and then replace the SCORM package in Moodle instead of having to manually trawl through page by page. And maybe there is some content that is duplicated, but you mess it up because you were manually trawling through page by page. So it also, having DITA as the single source of truth helps you with maintenance, even if it seems scary at first.

SO: And I expect one of the things we’re looking at is CCMS courses, and the concept of what is a CCMS is going to be the same for all of them. The process of how do I check out files is going to be a little different for each of them. So if you think about that from a course material point of view, you would have that conceptual overview of, what is the component content management system and why do I care? And then there’s, how do I do the thing in specific component content management system? That would probably be unique, but the conceptual overview would be probably the same. So we might have two or five or 15 different courses, one for each CCMS, but you could see where the conceptual stuff would overlap.

AB: Exactly.

SO: Okay. Everyone, I hope this glimpse into content operations for structured learning content was useful. Of course, the learningDITA.com site is much smaller than what we typically do with our customers at scale, but we are getting more and more requests for learning content and structured content options for learning content. If you’re interested in learning more about learningDITA.com, would suggest you go there and check it out. Check out the DITA training, which has eight or nine courses on DITA stuff from what is structured authoring, all the way to tell me about the learning and training specialization. Allison, thank you so much for all your input.

AB: Thank you.

SO: And we’ll see you on the next one.

Christine Cuellar: Thank you for listening to Content Operations by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post LearningDITA: DITA-based structured learning content in action appeared first on Scriptorium.

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In this episode, Alan Pringle, Bill Swallow, and Christine Cuellar explore how structured learning content supports the learning experience. They also discuss the similarities and differences between structured content for learning content and technical (techcomm) content.

Even if you are significantly reusing your learning content, you’re not just putting the same text everywhere. You can add personalization layers to the content and tailor certain parts of the content that are specific to your audience’s needs. If you were in a copy-and-paste scenario, you’d have to manually update it every single time you want to make a change. That scenario also makes it a lot more difficult to update content as you modify it for specific audiences over time, because you may not find everywhere a piece of information has been used and modified when you need to update it.

— Bill Swallow

Related links:

Structured authoring and XML (white paper), which is also included in our book, Content Transformation
Confronting the horror of modernizing content
The challenges of structured learning content (podcast)
Self-paced, online DITA training with LearningDITA.com
Get monthly insights on structured learning content, content operations, and more with our Illuminations newsletter

LinkedIn:

Alan Pringle
Bill Swallow
Christine Cuellar

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

End of introduction

Christine Cuellar: Hey, everybody, and welcome to today’s show. I’m Christine Cuellar, and with me today I have Alan Pringle and Bill Swallow. Alan and Bill, thanks for being here.

Alan Pringle: Sure. Hello, everybody.

Bill Swallow: Hey, there.

CC: Today, Alan, Bill, and I are going to be talking about structured content for learning content. Before we get too far in the weeds, let’s kick it off with a intro question.

Alan, what is structured content?

AP: Structured content is a content workflow that lets you define and enforce consistent organization of your information. Let’s give a quick example in the learning space. For example, you could say that all learning overviews contain information about the audience for that content, the duration, prerequisites, and the learning objectives for that lesson or learning module. And by the way, that structure that I just mentioned … It actually comes from a structured content standard called the Darwin Information Typing Architecture, DITA for short. That is an open-source standard that has a set of elements that are expressly for learning content, including lessons and assessments. And I think it’s also worth noting, another big part of the whole idea of structured content is that you are creating content in a format agnostic way. You are not formatting your content specifically for, let’s say, a study guide, a lesson that’s in a learning management system, or even a slide deck. Instead, what a content creator instructional designer does … They are going to develop content that follows the predefined structure, and then an automated publishing process is going to apply the correct kind of formatting depending on how you’re delivering the content. That way, as a content creator and instructional designer, you’re not having to copy and paste your learning content into a bunch of different tools. And I know for a fact a lot of instructional designers are doing that right now. Instead of doing all that copying and pasting, you write it one time, and then you say, “I want to deliver it for these different delivery targets, whether it’s for online purposes, whether it’s for in-person training or maybe a combination of both.” You set up publishing processes to apply the formatting for whatever your delivery targets are so you, as a human being, don’t have to mess with that.

CC: Which is awesome. Part of the reason that we’re talking about this today is that structured content has been a part of the techcomm world for over 30 years, for a really long time, and now we’re starting to see it make inroads in the learning and development space. We’ve been doing a lot of work for structured content in the learning space, but how is it different from the techcomm space? And Bill, I’m going to kick this over to you for that.

BS: I think I’m going to take a higher-level view on this because there is a lot of overlap between techcomm and learning content. Where they really start to diverge is in delivery. Techcomm is pretty uniform in how it delivers content to people. There’s personalization involved and so forth, but essentially everyone’s getting the same thing. The experience is going to be the same. Everyone’s going to get a manual. Everyone’s going to get online help. Everyone’s going to get a web resource, what have you. It might be tailored to their specific needs, but it’s a pretty candid delivery experience. For training, the focus is on the learning experience itself, and it’s usually tailored to a very specific need, whether it’s a very specific type of audience that needs information, or it’s very specific information that needs to be delivered in a very specific way for those people. Beyond that, we start looking at the content itself under the hood, and the information starts to, I would say, broaden with learning content because it can consume all the different types of information you have with technical content. And generally in a structured world, we think of that as conceptual information, how-to information, and reference information, for the most part. With learning content, now you have a completely new set of content in addition to that where you have learning objectives. You have assessments. You have overviews, reviews, all sorts of different content that essentially expands on the wealth of information you have from your technical resources.

CC: That’s great. Typically, the arguments for structured content, and the reason it’s really valuable for organizations, is it introduces consistency in your content, consistency for your brand across wherever you’re delivering content. It also helps you build some scalable content processes, that kind of thing. What are some of the arguments for structured content for the learning environment specifically, if there are any other new ones?

AP: Some of the reasons that you want to do structured content for learning content are really similar to other types of content. We’ve already talked about one of them. I touched on this earlier in regard to automated formatting. You are not having to do all of the work as a human being, applying formatting to ever how many delivery formats that you have. That is a huge win that you’re not having to do that. And especially in the training space, I have seen so many organizations copying content from one platform to another because the platforms don’t play well together, so you’ve got multiple versions of what should be the same exact content to maintain. That is another huge reason to consider structure. You want a single source of truth for your content regardless of where that information is being delivered because if you’re looking at the overall learning experience and the excellence and quality of that learning experience, if you were telling learners slightly different things in different places in your content, you are not providing an optimal learning experience. Therefore, having that single source of truth for a particular bit of information gives your learners a consistent piece of information regardless of what channel they consume it for. That’s a really important win for a solid, dependable learning experience.

CC: Gotcha. No, that definitely makes sense. It sounds like it would take some of the effort off of the subject-matter experts who are creating these trainings so that they can … They, I’m assuming, would rather focus on the work of helping train people. Getting some of the manual formatting and copy and pasting off of their workload sounds pretty nice. What are the complications that it might introduce or the change management issues that might need to be tackled when you’re bringing structured content into a learning environment?

AP: It’s true anytime you bring in structure. When people are used to working in an environment where you are doing manual formatting, and you’re seeing what things look like as you kind of develop the content, the idea of developing content in a format agnostic way where you’re not thinking about what does this slide look like, or how is this assessment going to work in the learning management system, it’s very easy to get focused on the delivery angle because you want it to be good, and you want it to be done in a way that makes that learning experience useful for the people who are trying to learn whatever it is they’re trying to learn. You don’t want those impediments of bad formatting or a not great way that your assessments behave in your learning management system, but you kind of get to offload all of those concerns, which are very valid. I’m not saying they’re not valid. They are, but you want an automated process. Basically, you want computers to do that work for you. You want programming to apply that formatting so you can really focus on getting that information as solid as it can be, and you let technology handle the rest. You do set up the standards for how you deliver that content, whether it’s in print, online, in person, whatever. However you’re delivering your learning and training content, you set the standards. “This is how I need this to behave. This is how I need it to look. This is how I need it to interact.” Once you set those standards, then you turn around and have someone who has this programmatic skill set, like we do at Scriptorium, to come in and develop the transformations that take your content and deliver it in the ways you need it delivered so you, as, like you were saying, the subject-matter expert, the instruction designer, or whatever content creator we’re talking about here … You are not doing that for every single delivery type that you are putting out for your learners.

BS: And it’s not to say that the experience isn’t tailored because it still can be tailored. Even if you are significantly reusing your content, you’re not just taking the same text everywhere. You can add personalization layers to that content and tailor certain parts of the content specific to what that specific audience needs rather than having to retype it all every single time you want to make a change if you were in a copy-paste scenario. And that also would make it a lot more difficult to update all that content as you modify it for specific audiences over time because you may not find everywhere where a piece of information has been used and modified if you need to update it. It does take a little bit of … Well, it takes a lot of the work off of those developing the content because they don’t have to worry about exactly what it looks like for every single target that they’re producing. It does require a little bit of, I would say, faith in the system that it will work. It really comes down to how you’re architecting this in the first place to make sure you understand who your varied audiences are, what the look and feel needs to be, what the delivery points are, and making sure that you are authoring within the scope of those things. And once you get that down, as Alan mentioned, it becomes a push-button operation to produce all of your various outputs.

AP: I think, too, from a change management point of view, one thing that I have heard from lots of content creators in the learning space is the burden they have, for example, if a program or the company changes names, changes logos, changes branding, if you have that built in to the formatting in a way where you’re having to go into, say, a bunch of Microsoft Word or PowerPoint files and manually change those out, and I am sure I am talking to people out there in the ether who know exactly what I’m talking about, it is extremely painful. And when you have automated the application of formatting, what you can do is change those processes to update them to include the latest corporate colors, the latest taglines, the latest fonts, the latest logos, whatever has changed so you, as a human being, again, do not have to go in there and touch all of those files yourselves because that is a burden you don’t need when you were trying to quote do your real work, which is help people learn, not apply formatting to a zillion Microsoft Word documents. Nobody wants to do that, at least nobody I know anyway.

CC: No. That’s a very good example of how the structure can just take that part of the workload off of you so you can get to focus on what you want to do. But I like, Bill, how you put it that you have to trust the process because it is an adjustment to go from authoring your content in a specific PowerPoint or in a specific Word doc to authoring it in a way that it can be reused. But ultimately what I’m hearing both of you say is that, even though it’s a valid concern that you might worry about your ability to personalize and your ability to control the user experience, once structured content is implemented correctly, and everyone is adjusted to the system, it sounds to me like you’re saying that your opportunities for personalizing at scale are actually going to be bigger than when everyone’s doing it individually, and at least it introduces consistency across those personalized experiences. Do you think that’s fair to say, either of you? Do you think that’s a fair statement, or is that too optimistic-

AP: That is an incredibly loaded question the only answer to which is … No, you were correct. That is, structure does enable all the things that you just ask in that very leading, but good, question.

CC: It is very leading.

BS: It removes the visual context of where the content is going, but it doesn’t remove … In fact, it enhances the context of what the content is about.

AP: Right.

CC: That’s a good way to say it. I like that. Looking at structured content within the learning space itself, how does it … I know, Bill, you had mentioned that, within the techcomm space, it’s fairly uniform in how content is delivered and who it’s delivered to. Not that it’s always the same. How about in the learning space? How does that vary? And how does the structure approach vary?

BS: Well, this might contradict what I said before, but it’s a slightly different look on it in that, really, the learning clients that we’ve had … They kind of mirror a lot of the techcomm clients we had in that everyone is producing roughly … If you look at it from a high enough altitude, it all looks the same. They’re all producing manuals. They’re all producing e-learning. They’re all producing whatever. When you get down into the nuts and bolts, that’s when you start finding that every single implementation is going to look a little bit different. In techcomm, you might have completely different types of content that you need to be able to handle. The same thing is with the learning space. Every single group is going to have different needs, and they’re going to have very specialized needs based on the content that they’re producing and who they’re producing it for. The learning space, unlike techcomm where they’ve basically been going down the structured path for 20, 30 years … The learning space has really been a sea of black boxes where every single system has its own way of doing things. It does about 90%, 95% of the same stuff that every other system out there does, but there is something special, something canned, something within the system that allows it to do the one thing that no other system does. And all of these technologies historically have really been locked down tight where your content goes in, and it lives and thrives in that box that you’re developing it in. But if you need to take that content out and change systems and put it somewhere else, there’s a lot of rework that potentially needs to be done depending on how customized that system you were using was. And let’s face it. You can structure content. You can centralize it. You can componentize it all you want. It’s not going to change the fact that learning content is going to have these many varied endpoints for how it’s being delivered. Even though you are consolidating and structuring in a central repository to maximize your reuse, to not worry about the formatting, you may still have three or four different learning management systems that you are pushing that content into. Each one of those systems has different requirements. The type of content that gets consumed. What it does. How it reacts. What it expects. The order it needs that information in per lesson, per page. E-page. It gets a little more complicated in the delivery of the learning content because we need to be able to tailor to not only the needs of the particular client in the content that they’re producing but the needs of the systems that need to ingest it.

AP: One other thing I would mention here is the level of interactivity, I think, is higher with learning and training content than the techcomm world. Now, I realize there are documentation portals and things like that that do provide some levels of interactivity. However, I think you are going to see much more of that kind of thing on the learning and training side, especially in regard to assessments when you are trying to have people do little, basically, mini exercises to prove that they have learned what they need to learn and that they are graded, and then those scores are recorded. That is the kind of thing you don’t see in techcomm. That is a whole, very specific thing to the learning and training world. Therefore, the structure that you choose needs to accommodate that, and your delivery targets in particular need to accommodate that very high level of interactivity with, for example, like Bill was saying, a learning management system.

BS: You have quite a variety of needs out there from basic, true/false, multiple choice, or matching all the way down to simulations, doing interactive exercises, and so forth all within a learning management system. And you need to be able to account for that. And as I mentioned, not all of those systems function in the exact same way, so it needs to be tailored.

CC: For any listeners that are listening to this episode right now, and they are in the learning content space, and they’re interested in getting started with structured content, Alan, where would you recommend they start?

AP: Well, our website, scriptorium.com, has lots–very self-serving. Very self-serving. We have a lot of resources, and we will put them in the show notes so you can get to them. We also are the creator and maintainer of a site called learningdita.com that teaches people about one way to do structured content, which is DITA, which I mentioned earlier in the show. And there is a free Introduction to DITA course that you can take. Between some links that we’ll include in the show notes in regard to what is structured content, how it applies to the learning and training space, and learning DITA, those are all good starting points for people who are considering going on the structured content journey for their learning content.

CC: That’s great. And the only thing I’ll add to that is that, if you’re interested in learning more about learning content and structured content, this is something that we talk about a lot. I would recommend also subscribing to our Illuminations newsletter which, like Alan said, that’s also going to be linked in the show notes. But every month, we send out a recap of the topics we talked about, and learning content is very often in there because we talk about it a lot.

This final question is for both of you. Is there anything else that you want to leave our listeners with about structured content in the learning content space before we wrap up today?

BS: I’d say, if you’re looking at structured content, it’s not going to on its face be a savior solution. But if with enough thought, it can really make a difference in your content development workflow, and it can save you a lot of time in producing content that is targeted to very specific people and delivery points.

AP: For me, my final suggestion here is think about your pain points. What are the things that are keeping you up at night as you develop your learning and training content? What are the continual issues you are battling, especially your content creators? What are they battling? Is it they’re having to format for umpteen different platforms? Is it that they’re needing to personalize things for different locations? For different levels of service that you were training people about? What are the things that are causing you problems? Basically, compile a list of those. And then from there, figure out, could structured content, solve any of these problems? Don’t put the cart before the horse, is the best way to put it, really. Think about your pain points in your processes and then see if structure might be the thing to solve them.

CC: That’s great. And on that, Alan, Bill, thank you very much for being here and recording this with me today.

BS: Thank you.

AP: Absolutely. We like to talk about this stuff probably too much.

CC: Thank you for listening to Content Operations by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

Get monthly insights on structured learning content, content operations, and more with our Illuminations newsletter. * Name First Last * Email * Data collection + I consent to my submitted data being collected and stored.Review our privacy policy * Consent to subscribe + I consent to the use of my submitted data for marketing emails. I understand that I can unsubscribe at any time.Review our privacy policy The post The benefits of structured content for learning & development content appeared first on Scriptorium.

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In this episode, Alan Pringle, Gretyl Kinsey, and Allison Beatty discuss LearningDITA, a hub for training on the Darwin Information Typing Architecture (DITA). They dive into the story behind LearningDITA, explore our course topics, and more.

Gretyl Kinsey: Over time that user base grew and grew. And now it boggles my mind that it got all the way up to 16,000 users. I never expected it to grow to that size.

Alan Pringle: Well, we didn’t really either, nor did our infrastructure. Because as of late 2024, things started to go a little sideways, and it became clear our tech stack was not going to be able to sustain more students. It was very creaky. The site wasn’t performing well. So we made a decision that we needed to take the site offline, and we did, to basically redo it on a new platform.

Related links:

Check out our self-paced online DITA 1.3 training.
Open-source DITA training project GitHub files

LinkedIn:

Alan Pringle
Gretyl Kinsey
Allison Beatty

Transcript:

Introduction with ambient background music

Christine Cuellar: From Scriptorium, this is Content Operations, a show that delivers industry-leading insights for global organizations.

Bill Swallow: In the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

Sarah O’Keefe: Change is perceived as being risky, you have to convince me that making the change is less risky than not making the change.

End of introduction

Alan Pringle: Hey, everyone, I am Alan Pringle, and today I am here with Gretyl Kinsey and Allison Beatty. Say hello, you two.

Gretyl Kinsey: Hello.

Allison Beatty: Hello.

AP: We are together here today because we want to talk about LearningDITA, our e-learning site for the DITA specification because we have just moved it to a new platform. So we want to give you a little background on what went on with that decision. So first of all, Gretyl, you and I were at Scriptorium when we kicked off this site, and I just went back and looked at blog posts. We announced it via blog post I wrote in July of 2015. So we have had this site up and running for 10 years, which absolutely blows my mind.

GK: It blows my mind too. It’s hard to believe that it’s been that long because it does seem like it got launched pretty recently in my memory, but it has been through a lot of changes and so has the entire landscape of content creation as well. So yeah, it’s really cool that now we can look back and say it has been 10 years of LearningDITA being on the web.

AP: For those who may not be familiar with the site, give us a little summary of what it is.

GK: Sure. So LearningDITA is a training resource on DITA XML and it’s developed by Scriptorium, and it covers a lot of the main fundamentals of DITA. So we have some courses on basic authoring and publishing. We also have a couple of courses on reuse and one course on the DITA learning and training specialization. So you get a good overview of a lot of different areas of DITA XML. And all of the courses are self-guided e-learning. So you can go through and take them at your own pace. You can go back and take the courses again if you want a memory refresher. And they all come with a lot of examples and exercises. So you get a download of sample files that you can work your way through. There’s some of that practice that’s guided, and then there’s others that you do on your own. And then there are also assessments throughout each course that help you test your knowledge. So you get a really nice hands-on approach to LearningDITA. So that’s why we called the site that in the first place. And it really helps to get those basics, those fundamentals in place if you are coming at it as a beginner who is unfamiliar with DITA or maybe you have some familiarity, but you want to just reinforce what you know.

AP: So we went along with this site and kept adding courses over the years. I think we got to nine, is that right? I think it’s nine.

GK: That’s right. So we really started this out, like I was mentioning earlier, that we needed something that was beginner-friendly, something for people who were unfamiliar with DITA because we saw a gap in the information that was available at the time 10 years ago. A lot of the DITA resources, documentation, guides and things like that out there were something that assumed some prior knowledge or prior expertise, and there wasn’t really anything that filled that gap. So we came up with these courses. And the nine courses that we have, the first one is just an introduction to DITA. So that was the first one that launched back in July of 2015. And then shortly after that, we added a few courses on topic authoring. So that covers the main topic types, concept, task reference and glossary entry. And then we just added more courses over time. So we’ve got one that covers the use of maps and book maps. We’ve got one that covers publishing basics. We have, like I mentioned, the two courses on reuse. So there’s a more introductory basic reuse course and then a more advanced reuse course, and then learning and training. So those are the nine courses that we have, and they’ve been up there pretty much the entire time. The earliest ones where that introduction, the authoring, and then we added the others as the demand increased over time.

AP: And that demand, I’m glad you mentioned that, really did increase because as of late 2024, we had over 16,000 students in the database for LearningDITA, which also completely blows my mind.

GK: Yeah, it does for me too, because I think in the early days we saw a lot more individuals using it, and then over time we would see more large groups of users sign up. So an entire class whose professor might’ve recommended taking the LearningDITA courses or sometimes an organization, whether it was one of our clients or just another organization, would have a lot of employees sign up all at once. And so yeah, over time that user base grew and grew. And now it does boggle my mind as well that it got all the way up to 16,000 users. I never expected it to grow to that size.

AP: Well, we didn’t really either, nor did our infrastructure. Because as of late last year, things started to go a little sideways and it became clear our tech stack was not going to be able to sustain more students. It was very creaky. The site wasn’t performing well. So we made a decision that we needed to take the site offline and we did to basically redo it on a new platform. And Allison, this is where I want you to come in because you are one of the, shall we say, victims on the Scriptorium side who got to dive into what our requirements were, what we needed to do. Essentially, I mean, we really became consultants for ourselves and turned our consultant eye at our problem to figure out what it was. And Allison, if you don’t mind, tell us a little bit about that process and where we landed.

AB: Yeah, so the platform was the first big choice that we knew we had to make, and things started out pretty fuzzy because we didn’t really know what we were doing and just had to figure out what was going to work to solve these pain points. And so as a starting place, we knew we needed a new LMS, learning management system. And so we did some research on what learning management systems were out there and thought about what we could use that would fit our needs. And we ended up choosing Moodle, which is an open source LMS that is very widely used within colleges and universities and higher education settings. And we knew it could be very powerful and probably suit our needs with some custom work. But the thing about Moodle is it’s known for having a high barrier to entry in terms of the installation, and that made us a little nervous. But the more we kept looking at LMS options, both open source and commercial, we realized that Moodle is so popular and industry standard almost for a reason and that it was worth taking on that challenge.

AP: And I even had someone in the learning space because I asked her advice, what LMS would you use? She pretty much said run away from Moodle because for a lot of the reasons that you just mentioned. But I think it’s worth noting, it does have… There are a lot of people using it, especially in educational settings, schools, universities. It’s also the open source angle was appealing because that way it didn’t look like we were picking “favorites” by picking a particular proprietary LMS.

AB: Yeah, definitely. And then the other piece of the puzzle there as far as how we’re going to display and host the learning content was the DITA transform for the content itself and how we were going to get the LearningDITA content into our LMS. And so we knew that Moodle is compatible with both SCORM and xAPI and we ended up deciding that we wanted to develop a DITA to SCORM transform because SCORM is something that we have discussed and worked on with other clients as we’ve been seeing this trend in learning and training content pickup.

I don’t know if Gretyl wants to talk a little bit about how she’s seen SCORM throughout various projects and why we decided it was something we wanted to pursue and learn more about ourselves.

AP: And what is it while you’re at it? That too.

AB: That’s a good question. I’ll just go ahead and talk a little about what it is without getting too deep technically. Basically it’s a standard for e-learning content and it provides communication that can do things like track grades within your LMS. In the LearningDITA, the previous site and the current site, you had to pass assessments to get to the next lesson. And so SCORM can handle things like tracking assessment completion and scores. It’s pretty flexible and widely used. It’s more or less just a standard, but it requires a pretty specific data structure for it to function because it’s expecting certain data structures that are defined in the standard for it to work in different environments. And Gretyl, would you like to talk a little bit about how we’ve seen the SCORM standard pop up through various client projects?

GK: Sure. So we have seen I think over especially these last 10 years since LearningDITA launched an increase or a bit of an uptick in clients who come to us with e-learning content specifically. Some of them, that’s the only content they have. For others, they are trying to get some sort of a process for developing both e-learning content and then other kinds like technical documentation, marketing content. But a lot of them end up going down this path where they realize DITA XML is going to be helpful for content creation, especially if they do have that cross-department collaboration or reuse that needs to happen. And SCORM has been something that we’ve seen crop up with a lot of these projects. Because like you mentioned, Allison, it offers all that flexibility around things like scoring the assessments, keeping that student data that’s needed. And we’ve also seen how it’s really good when you’ve got an organization that has to deliver e-learning content to multiple different LMSs. So let’s say they’ve got students in a lot of different geographical areas or different industries and they all use different LMSs. That SCORM package can be delivered into all of them and used. And so they get that flexibility. So we’ve seen this crop up in a lot of different client projects. And the more we saw it pop up in these different projects, the more we said this might be beneficial for us too. And we’ve seen all the different ways that these organizations have made use of SCORM packages and why not give it a try for our LearningDITA content. And which by the way, I just wanted to mention, I don’t think we explicitly said this, but all of the LearningDITA courses themselves are authored in DITA XML. So kind of meta layer there to think about. But because of that, we have to think about how are we going to publish this information, get these e-learning courses out onto the web. And so a DITA to SCORM transform, as Allison said, is the approach that we decided on.

AP: And those source files, by the way, are part of this open source project that’s out in GitHub. And we’ll put some links in the show notes about it. But you can look at the source files that we used and download them for free. They’re open source. You can look at them and even use them for your own purposes if you like.

GK: And one question I had there, so you mentioned that all of those files are free and LearningDITA itself, the website, the platform has always been free, but now we are introducing a new pricing model. And so Alan, I wanted to ask you about that, how that change came about, why we made that decision to go from an entirely free resource to something with a new pricing model?

AP: Yeah, that’s a hard one and it was not a fun discussion. It wasn’t. But basically considering we’ve got 10 years of work invested in this, we had both hundreds of hours invested in developing and maintaining the site and all the courses. We also have hosting costs involved. So it got to the point to where especially with those 16,000 students, things were just not sustainable. And the tech model, the tech stack was not working anymore. So we knew we had to do something and invest more time into the platform or frankly abandon it. And when you look at the choices, completely shut down the site and get rid of that resource or decide to charge very small amounts. The intro course will always be free. That was the decision that we made. And there will be coupon codes. There will be discounts for courses and other things. So we realize we are changing from the free model. Wish we didn’t have to do it. But looking at the reality of the time that we’ve invested in it and to keep it running in the future, that was a decision that we made to keep this running for the long haul.

GK: And I think, like we’ve said, we’ve seen so many changes in the content space, the industry itself over these years. And I think evolving and making sure that we are keeping track of the value that we add by having this resource makes sense to go to that pricing model.

AP: And I want to talk a little more about the Moodle part of this equation, because the way that it works is different than what we had before. And I think it’s worth noting the user experience is a little different. Because when you open up a course, it essentially opens up in a SCORM package viewer. Allison, could you talk just a little bit about how that experience is different?

AB: Yeah. So something that we noticed about Moodle is that it’s a very low-code, no-code type of platform. And so part of that SCORM decision was we wanted to be able to single source the content that lives in that repo or repository. We didn’t want to manually insert all that content. And so the way that SCORM ends up interacting with the Moodle site is that instead of having the content baked into webpages, it launches equivalent to an iframe, but it launches a second window where you take the course. And then when you close out that window, it ends your session. So don’t freak out if a second window pops up when you go to take your course. That’s the way that it is designed to work with the SCORM transform.

AP: And then Moodle records your activity, how well you’ve done with the quizzes, and all of that kind of information.

AB: And on the technical back end, all of that grade recording and assessment tracking is something that is handled because of the SCORM transform and how we built the Moodle site.

AP: And I think it is time for us to mention the people who really helped build that Moodle transform. Let’s call them out by name. Thank you to Jake Campbell, Simon Bate, and Melissa Kershes. Thanks to all of them for getting in there and helping us get that done.

GK: And I can just say after doing a lot of end user testing to make sure this works, I actually think it is easier to keep track of where you are than it was in our previous platform. I like that it pops things out into a new window. It really helps you, guide you along as you go through each part of the course. And it pops up with notifications about saving your progress if you need to stop and start a course at any point. And it does make it very clear where you are in the course and whether you have passed those assessments. And so the entire package does work really well. I think it’s really intuitive as an end user. And hopefully for all of you who go and take the courses on the new platform, you will see the same thing.

AP: I think it’s worth mentioning too, moving to this new platform, it’s going to give us opportunities to do more things in the future. We will be adding new content, especially as the DITA 2.0 standard comes out. So when that is released by the committee that controls the standard, we will do some updates to our courses. And I think we’re going to maybe do some micro learning perhaps, some live e-learning. We’ve got lots of choices here, so stay tuned for that.

And with that, Allison and Gretyl, I want to thank you very much for your work on the site and for talking with us today.

GK: Absolutely. Thank you.

AB: Thank you.

The post LearningDITA: What’s new and how it enhances your learning experience appeared first on Scriptorium.

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In our last episode, you learned how a taxonomy helps you simplify search, create consistency, and deliver personalized learning experiences at scale. In part two of this two-part series, Gretyl... Read more »

The post Building your futureproof taxonomy for learning content (podcast, part 2) appeared first on Scriptorium.

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Can your learners find critical content when they need it? How do you deliver personalized learning experiences at scale? A learning content taxonomy might be your solution! In part one... Read more »

The post Taxonomy: Simplify search, create consistency, and more (podcast, part 1) appeared first on Scriptorium.

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Ready to deliver consistent and personalized learning content at scale for your learners? In this episode of the Content Operations podcast, Alan Pringle and Bill Swallow share how structured content... Read more »

The post Transform L&D experiences at scale with structured learning content appeared first on Scriptorium.

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In episode 179 of the Content Strategy Experts podcast, Sarah O’Keefe and Alan Pringle share the inside scoop on how to write an effective request for a proposal (RFP) for... Read more »

The post Creating content ops RFPs: Strategies for success appeared first on Scriptorium.

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In episode 178 of the Content Strategy Experts podcast, Sarah O’Keefe and Christine Cuellar perform a pulse check on the state of AI as of December 2024. They discuss unresolved... Read more »

The post Pulse check on AI: December, 2024 (podcast) appeared first on Scriptorium.

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Is it really possible to configure enterprise content—technical, support, learning & training, marketing, and more—to create a seamless experience for your end users? In episode 177 of the Content Strategy Experts podcast, Sarah O’Keefe and Bill Swallow discuss the reality of enterprise content operations: do they truly exist in the current content landscape? What obstacles hold the industry back? How can organizations move forward?

Sarah: You’ve got to get your terminology and your taxonomy in alignment. Most of the industry I am confident in saying have gone with option D, which is give up. “We have silos. Our silos are great. We’re going to be in our silos, and I don’t like those people over in learning content anyway. I don’t like those people in techcomm anyway. They’re weird. They’re focused on the wrong things,” says everybody, and so they’re just not doing it. I think that does a great disservice to the end users, but that’s the reality of where most people are right now.

Bill: Right, because the end user is left holding the bag trying to find information using terminology from one set of content and not finding it in another and just having a completely different experience.

Related links:

The business case for content operations (white paper)
Replatforming an early DITA implementation (case study)
Hear Sarah speak about The reality of enterprise customer content at tcworld 2024!
Hear Bill speak about the The challenges of replatforming, also at tcworld 2024.

LinkedIn:

Sarah O’Keefe
Bill Swallow

Transcript:

Bill Swallow: Welcome to The Content Strategy Experts podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about enterprise content operations. Does it actually exist? And if so, what does it look like? And if not, how can we get there? Hi, everyone. I’m Bill Swallow.

Sarah O’Keefe: And I’m Sarah O’Keefe.

BS: And Sarah, they let us do another podcast together.

SO: Mistakes were made.

BS: So today we’re talking a little bit about enterprise content operations. If it exists, what it looks like. If it doesn’t, why doesn’t it exist? What can people do to get there?

SO: So enterprise content ops, I guess first we have to define our terms a little bit. Content operations, content ops is the system that you use to manage your content. And manage not the software, but how do you develop it, how do you author it, how do you control it, how do you deliver it, how do you retire it, all that stuff. So content ops is the overarching system that manages your content lifecycle. And when we look at content ops from that perspective, and of course we’re generally focused on technical content, but when we talk enterprise content ops, it’s customer-facing content, which includes techcomm, but also learning content, support content, product data potentially, and some other things like that. And ultimately, when I look at this, again bringing the lens back or going back to the 10,000-foot view, we have some enterprise solutions but only on the delivery side. The authoring side of this is basically a wasteland. So I have the capability of creating technical content, learning content, support content, and putting them all into what appears to be some sort of a unified delivery system. But what I don’t really have is the ability to manage them on the back end in a unified way, and that’s what I want to talk about today.

BS: So those who are delivering in that fashion, so being able to provide customer-facing information in a unified way, as far as their system for content ops goes, it’s more, I would say, human-based. So it’s a lot of workflow. It’s a lot of actual management of content and management of content processes outside of a unified system.

SO: So almost certainly they don’t have a unified system for all the content, and we’ll talk about why that is I think in a minute. It’s not necessarily human-based, it’s more that it’s fragmented. So the techcomm group has their system, and the learning group has their system, and the support team has their system, et cetera. And then what we’re doing is we’re saying, okay, well once you’ve authored all this stuff in your Snowflake system, then we’ll bring it over to the delivery side where we have some sort of a portal, website portal, content delivery CDP that puts it all together and makes it appear to the end user that those things are all in some sort of a, it puts it in a unified presentation. But they’re not coming from the same place, and that causes some problems on the backend.

BS: Right, and ultimately the user of that content doesn’t really care if it’s a unified presentation. They just want their stuff. They don’t want to have a disjointed experience, and they want to be able to find what they’re looking for regardless of what type of content it is.

SO: Right, and the cliche is “don’t ship your org chart,” which is 100% what we’re doing. And so let’s talk a little bit about what does that mean, what are the pre-reqs? So in order to have something that appears to me as the content consumer to be unified, well for starters, you mentioned search. I have to have search that performs across all the different content types and returns the relevant information. And what that usually means is that I have to have unified terminology. I’m using the same words for the same things in all the different systems. And I need unified taxonomy, classification system metadata so that when I do a search, everything, and maybe I’m categorizing or I’m classifying things down and filtering, that when I do that filtering, that the filtering works the same way across all the content that I’ve put into the magic portal. So taxonomy and terminology are the things that’ll make your search, relatively speaking, perform better. So we have this on the delivery side and that’s okay-ish, or it can be, but then let’s look at what we’re doing on the authoring side of things because that’s where these problems start.

BS: So what do they start looking like?

SO: Well, maybe let’s focus in on techcomm and learning content specifically. We’ll just take those two because if I try and talk about all of them, we’re going to be here for days and nobody wants that. All right, so I have technical content, user guides, online help, quick snippets, how-tos. And I have learning, training content, e-learning, which is enabling content, I’m going to try and teach you how to do the thing in the system so that you can get your job done. Now, let’s go all the way back to the world where we have an instructional designer or a learning content developer and a technical content developer. So for starters, almost always those are two different people, just right off the bat. And instructional designers tend to be more concerned with the learning experience, how am I going to deliver learning and performance support to the learner? And the technical writers, technical content people tend to be more interested in how do I cover the universe of what’s in this tool set, or this product, and cover all the possible reasonable tasks that you might need to perform, the reference information you need, the concepts that you need? It’s a lot of the same information. It’s there’s a slightly different lens on it. And in the big picture, we should be able to take a procedure out of the technical content, step one, step two, step three, step four, and pretty much use that in a learning context. In a learning context, it’s going to be, hey, when you arrive for your job at the bank every morning you need to do things with cash that I don’t understand. And here’s a procedure, and this is what you’re going to do, steps 1, 2, 3, 4, 5, and you need to do them this way and you need to write them down, and it tends to be a little more policy and governance focused, but broadly it’s the same procedure. So there should be the opportunity to reuse that content. And big picture, high-level estimate is probably something like 50% content overlap. So 50% of the learning content can or should be sourced from the technical content. The technical content is probably a superset in the sense that the technical content covers, or should cover, all the things you can do, and training covers the most common things or the most important things that you need to do. It probably doesn’t cover a hundred percent of your use cases. Okay, so now let’s talk about tools.

BS: Right because I was going to say these two people, the technical writer and the training developer, they are using, at least historically, two very different sets of tools to get their job done.

SO: Right. So unified content solutions, without getting into too many of the specifics, which will get me in big trouble, basically the vendors are working on it, but they’re not there yet. There’s a lot of point solutions. There’s a lot of, oh yes, we have a solution for techcomm and we have a solution for learning and we have a delivery solution, but there’s not a unified back end where you can do all this work.

And some of the vendors have some of these tools in their stable, some of them don’t. But from my point of view, it doesn’t really make a whole lot of difference whether you buy two-point solutions from separate vendors or from the same vendor because right now they’re disconnected.

| | |

BS: They’re two-point solutions.

SO: Yeah, they’re all point solutions. So it’s not good. And then that brings us to how can we unify this today? What can we do and what kind of solutions are our customers building or are we building with our customers? So a couple of things here. Option A is you take your structured content solution and you say, “Okay, learning content people, we’re going to put you in structured content. We’re going to move you into the component content management system. We’re going to topicify all your content, and we’re basically going to align you with the techcomm toolset and make that work.” We have a few customers doing that. It works well for learning content developers that are willing to prioritize the document structure and process over the flexibility in the downstream learning experience.

BS: Right.

SO: That’s a small set of people. Most learning content developers are not willing to prioritize efficiency and structure over delivery, which I think is actually the root cause.

BS: Right. Now, those who are doing this, they are seeing some benefit in being able to produce a wide variety of their training deliverables from that unified source. But again, it comes back to how willing people are to give up the flexibility that they have in developing course content.

SO: We can talk about big picture and we can talk about all the things, but this decision, this approach 100% of the time comes down to how badly do you want to be able to flail around in PowerPoint. And if having the ability to put random things in random places on random slides is critical, then this solution will not work.

BS: So on the flip side, you would then look to maybe somehow connect your technical communication system to your learning repository.

SO: Right. So you take your techcomm content and you treat it as a data source essentially for your learning content, and you just flow it into the learning authoring environment. It turns out that’s hard.

BS: It’s very hard.

SO: Super difficult. It’s difficult to get your structured content out into a format that the learning content system can accept in a reasonable manner.

BS: And if your content is highly structured, you’re likely losing a lot of semantic data along the way to get it there.

SO: Yeah, you lose a lot, but it’s just bad. And ultimately, this almost always lands, I mean we talk about flow it in there, but ultimately this almost always means that you’re going to be copying and pasting and reformatting and re-reformatting, and it’s just terrible.

BS: So more often than not, we’re not seeing this level of unification then.

SO: Yeah, I mean, are you connecting your techcomm and you’re learning in a structured environment? A few people, yes. And for the right use case, it’s great. Or flow the techcomm content down into the learning environment, but ultimately not worth it, we’ll just copy and paste. So in terms of unification, basically none of the above, right?

BS: Mm-hmm. So how would people get there?

SO: So there’s a couple of options. The probably most common one is some sort of a DIY solution. We’re going to find a way to glue these systems together. We’re going to find a workflow that involves converting the techcomm content, which usually is created first and move it into the learning content. Again, for the right group, for the right environment, unifying everything in a structured authoring environment makes a lot of sense. I think ultimately that’s where it’s going to land, but the structured content systems need to do some work to make themselves into what amounts to a reasonable viable authoring solution for the learning content people. Basically the learning content people are not willing to put up with the shenanigans that ensue in order to use a structured content system. And I’m not even sure they’re wrong, right?

BS: Yeah.

SO: They’re just saying, “No, this is terrible and we’re not doing it.” Okay, well, that’s fair. So either you tinker and put it all together in some way. Option B is wait for the vendors, wait for the vendors to fix this problem, fix this requirement, and deliver some systems that have a solution here. And it’ll be a year or two or five or 20, and eventually they’ll get to it. You can go with a delivery-only solution, so we’re only going to solve this on the delivery side. If you do that, you really, really, really, really need an enterprise-level taxonomy and terminology project group.

BS: Absolutely.

SO: You’ve got to get that aligned. You cannot go around having half your text say entryway, and half your text say hallway, half your text says study, and half your text says den. And I’m halfway down a clue reference, was it the wrench or the outlet? No, no, no, okay. You have to get your terminology in alignment. You must because otherwise people search on oven and it doesn’t return range because those are in fact… Well, okay, they’re not exactly the same thing, but close enough, so those types of things. So you’ve got to get your terminology and your taxonomy in alignment. Most of the industry, like most of the people out there that are doing techcomm and learning content, I am confident in saying have gone with option D, which is give up. Just don’t do it. Just don’t bother. We have silos. Our silos are great. We’re going to be in our silos, and I don’t like those people over in learning content anyway. I don’t like those people in techcomm anyway. They’re weird. They’re focused on the wrong things, says everybody, and so they’re just not doing it. I think that does a great disservice to the end users, but that’s the reality of where most people are right now.

BS: Right, because the end user is left holding the bag there trying to be able to find information using terminology from one set of content and not finding it in another and just having a completely different experience.

SO: They make it a you problem.

BS: Yeah. So if you’re seeing opportunities to unify content operations in your organization, what are some key ways of communicating that up so that you can begin to get some funding, some support, some executive level buy-in to do these things?

SO: The technology problem is hard. Putting everybody in an actual unified authoring environment is a really hard problem. So I think what you want to do is go for the easier solutions where you can get some wins. And the easier solutions where you can get some wins are consistent terminology across the enterprise. So we’re going to have some conversations about terminology and what we need to do in terms of terminology, and everybody’s going to agree on the words we’re going to use. Taxonomy, what does our classification system look like? What are the names for our products and how do we label things so that when we deliver all these different content chunks, they’re coming from all these different systems, we can bring them into alignment? I mean, you can do the work on the back end to align taxonomy or you can do it on the delivery side to say these things are synonyms. So there are some ways of addressing this even when you get down into the delivery end of things. But I think what you want to do is start thinking about the things… Oh, and translation management, which ties into both terminology and taxonomy. I think you want to start maybe with those things and then slowly work your way upstream, like a salmon, avoiding the bears on the… Okay, you’re going to try and work your way upstream towards the authoring. Because ultimately if you look at this from an efficiency point of view, it would be much, much more efficient to have unified authoring and put it all together. It’s just that right now today, that’s a heavy lift and it only makes sense in certain environments. So what can we do to prepare for that so that when we do get to that point and those tools do start to unify a little bit better, we’ve done the legwork that’ll make it easier to make that transition as we go?

BS: Right. So it’s spending the effort to unify as much as you can the content and the language and the organization, as well as trying to keep pace with where I guess all of these different industry tools are going and making sure that you are making improvements in the right direction. So if you’re thinking about structured content, that you are keeping an open mind as to where and how I guess these other groups can start leveraging what you’re using and vice versa. And I guess talking with the other groups in your organization. So if you’re in techcomm, then talk to the training group, see what they’re doing, see what their plan is, what’s their five-year roadmap? Are they looking at certain technologies? How might that play into your development, and vice versa, being able to share that information.

SO: And I know, Bill, you’re doing a session on re-platforming at tcworld this November 2024. And when you’re thinking about re-platforming, what are some of the factors that you should be looking at there that tie into this?

BS: Well, it directly plays into that next step of we have a platform on the techcomm side, we bought it 12 years ago, it served our needs. But the training group, let’s say, has been talking and they have this other system that they’re not too happy with, and they want to see if they can start sharing our content.

Well, then you have an open conversation to say, “Okay, how can we get to a shared solution, what do these requirements look like,” and go ahead and pick a system that kind of meets both requirements. But then you have that heavy lift of just saying, “Okay, so now we have these two different old systems and we need to dump our content, and I use that very generally, into the new system, so that everyone from those two groups can now author in the same place.

SO: And I’m thinking as you’re evaluating these systems, all other things being equal, which they are not, but all other things being equal, you would look for the one that’s more open, that is more flexible knowing that things are going to change because they always do. What’s available to us that’ll give us maximum flexibility in a year or two or five when these new requirements come in that we have not anticipated at this point?

BS: Right, because you’re exiting your old systems because they are potentially inflexible. We cannot accommodate anything new. We can sustain what we’re doing indefinitely, but we can’t accommodate this new thing that we need to do.

SO: Yeah, it’s interesting because looking at the the techcomm landscape, we have a lot of customers and a lot of just generalized ecosystem that has moved into structured content, and starting as early as the late nineties or maybe even the early nineties in Germany, people were moving into structured content at scale. And now we’re looking at it and saying, “Okay, well there’s all this other content out there and we need to look at that and we need to look at whether we can bring that into the structured content offerings.” But not unreasonably, those other groups are looking at it and pushing back and saying, “This isn’t optimized for the kind of work that I do. It’s optimized for the kind of work that you people do. So how can we improve this and bring it into alignment with what the new and additional stakeholders need?” And it’s a hard problem, I really feel for the software vendors. It’s easy for us sitting here on the services side to say, “Hey, do better,” because we’re not doing the work.

BS: Very, very true. And at that point, you have a winner and a loser, and I hate to say it that way, but you have a winner and a loser on the system side at that point. Where you’re pulling one other group in because you have an established structural approach and they could benefit from it, but basically they have to absorb the brunt of the change that’s going to happen, and it’s not necessarily fair.

SO: Well, yeah. I mean, life isn’t fair. But also I’ll say that that pain that you’re talking about, the people that are now in structured content, they had that pain. It was just 10 years ago-

BS: Very true.

SO: …and they’ve forgotten. For those of you that were around and in this industry 10 years ago, or 20 years ago, or 25, I mean, remember what it was like trying to get people to move from you will pry unstructured FrameMaker from my cold, dead hands. You’ll pry Microsoft Word from my cold, dead hands. You will pry PageMaker, Interleaf, Ventura Publisher from my cold, dead hands.

BS: WordStar.

SO: Okay. So tools come and go, and the tool that is the state-of-the-art, BookMaster, for today is not necessarily the tool that’s going to be state-of-the-art for tomorrow or yesterday. I mean, basically this stuff evolves and we have to evolve with it, and we have to understand what are the best and most reasonable solutions that we can offer to a customer or to a content operations group in order to deliver on the things that they need to deliver on.

BS: Very true. So there are no unicorns.

SO: No unicorns, or maybe more accurately you can construct your own unicorn and it might be awesome, but it’s going to be a lot of work.

BS: So I think we could probably talk about this for hours because there are so many different facets that we can touch upon, but I think we’ll call it done for now, and maybe we’ll see you soon in a new episode?

SO: Yeah, if this speaks to you, call us because we’ve barely scratched the surface.

BS: All right. Thanks, Sarah.

SO: Thanks.

BS: And thank you for listening to The Content Strategy Experts podcast brought to you by Scriptorium. For more information, visit Scriptorium.com or check the show notes for relevant links.

The post Do enterprise content operations exist? appeared first on Scriptorium.

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Whether you’re surviving a content operations project or a journey through treacherous caverns, it’s crucial to plan your way out before you begin. In episode 176 of the Content Strategy Experts podcast, Alan Pringle and Christine Cuellar unpack the parallels between navigating horror-filled caves and building a content ops exit strategy.

Alan Pringle: When you’re choosing tools, if you end up something that is super proprietary, has its own file formats, and so on, that means it’s probably gonna be harder to extract your content from that system. A good example of this is those of you with Samsung Android phones. You have got this proprietary layer where it may even insert things into your source code that is very particular to that product line. So look at how proprietary your tool or toolchain is and how hard it’s going to be to export. That should be an early question you ask during even the RFP process. How do people get out of your system? I realize that sounds absolutely bat-you-know-what to be telling people to be thinking about something like that when you’re just getting rolling–

Christine Cuellar: Appropriate for a cave analogy, right?

Alan Pringle: Yes, true. But you should be, you absolutely should be.

Related links:

Nightmare on ContentOps Street (podcast)
Enterprise content operations in action at NetApp (podcast)
Content creature feature
Hear Alan Pringle speak about the Horrors of modernizing content operations at LavaCon 2024!

LinkedIn:

Alan Pringle
Christine Cuellar

Transcript:

Christine Cuellar: Welcome to the content strategy experts podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize and distribute content in an efficient way. this episode, we’re talking about setting your ContentOps project up for success by starting with the end in mind, or in other words, planning your exit strategy at the beginning of your project. So I’m Christine Cuellar, with me today is Alan Pringle. Hey, Alan.

Alan Pringle: Hey there.

CC: And I know it can probably sound a bit defeatist to start a project by thinking about the end of the project and getting out of a new process that maybe you’re building from the beginning. So let’s talk a little bit more about that. Why are we talking about exit strategy today?

AP: Because everything comes to an end. Every technology, every tool, and we as human beings, we all come to an end. And at some point, you are going to have tools, you’re gonna have technology and process that no longer supports your needs. So if you think about that ahead of time, and you’re ready for that inevitable thing, which will happen, you’re gonna be much better off.

CC: Yeah. So this conversation started around the news of the DocBook Technical Committee closing, and that’s kind of a big deal for a lot of people, and it kind of sparked this internal conversation about like, you know, what if that happened to you? How can people avoid getting caught by surprise? And of course, as Alan just mentioned, the answer to that is really to begin with the end in mind, to have an exit strategy because everything does end at some point. So this got me thinking about, you know, I don’t know, Alan, you’ve seen the horror movie The Descent, right? You’ve seen that movie? Yes, because it’s amazing and it’s a horror movie and it’s awesome. So it me kind of think of that because, you know, this group, and I’m not going to spoil it, no spoilers for people who haven’t seen it yet, but, if you haven’t, go watch it. The first one’s my favorite. I haven’t seen the second one, so I’m biased. Anyways, that’s not the point. This group plans to go along one path, you know, down these caves which are definitely in North Carolina, right Alan? That’s definitely where they take place.

AP: Well, they say it is in North Carolina, but it is quite clearly not filmed in North Carolina. As someone who is familiar with Western North Carolina, I had to laugh at this movie trying to pass off somewhere in the UK as like the Appalachian Mountains, but that’s just a quibble. So go ahead with your story.

CC: Anyways, yeah, they got a mountain in there, right? And then there’s a path into the mountain. Of course, they’re going to explore this deep, dark cave. So they’re descending as the name implies. And so they’re planning to go along one path. think someone maybe tricked someone else along the way. I can’t remember. But they’re planning on going down one path. And there’s a lot of things that begin to happen that they didn’t plan on. And one scene in particular, there’s a cave that collapses and of course that means they have to pivot, right.

AP: Yeah.

CC: So when you’re thinking about building an exit strategy and trying to plan for things that you can’t anticipate, how do you anticipate things you can’t anticipate?

AP: Well, first of all, let’s be clear. All the things that happened in that movie happened in a period of like two hours or an hour and a half. And part of the issue with any kind of process and operations is things can slowly start to go badly and you just kind of keep on trucking and really don’t pay attention to it. But…

CC: Yes.

AP: It’s not just about fine tuning your operations. That’s a whole other conversation. You your process is going to require updating every once in a while. There going to be new requirements and you need to address them in your content ops by changing your process, updating your tools, maybe adding something new. What we’re talking about here is when those tools and that process, they’re coming to an end, for example, because a particular piece of software is being defecated. It is end of life. What are you going to do?

CC: Mm-hmm.

AP: What if there is a merger? You have a merger and there are two systems doing the same thing. One of those systems is going to lose and go away. Why are you going to maintain two of the same systems? So you’re going to have to figure out how to pivot to get to that.

CC: Mm-hmm.

AP: So there are all of these things that can happen that mean you have got to exit whatever you were doing and move into something new, something different. And the reasons are many, like I just mentioned, but the end result is, are you ready for when that happens? In a lot of cases, frankly, people aren’t.

CC: Yeah. So if you could give listeners three pieces of advice on how to be less dependent on a particular system, if you had to narrow it down to three, what would you suggest to help them not be just dependent on one particular system or maybe a set of systems?

AP: One thing is when you’re choosing tools, if you end up something that is super proprietary, has its own file formats, et cetera, that means it’s probably gonna be harder to extract your content from that system because it is proprietary. Even if your content is in a standard, and in a lot of cases, of course, I’m talking about DITA, the Darwin Information Typing Architecture and XML standard. Even with DITA, even though it’s open source and a standard, some of the systems that can manage DITA content put their own proprietary layer on top. A good example of this is, for example, those of you with Samsung Android phones. I’ve had one in the past.

CC: Yeah, that’s me.

AP: Samsung puts their own proprietary layer on top of the Android operating system and a lot of that stuff frankly I hate, but that’s not the point of this conversation, but it’s the same issue. You have got this proprietary layer where it may even insert things into your source code that is very particular to that product line. So look at how proprietary your tool is or your toolchain is and how hard is it going to be to export? That should be an early question you ask during even the RFP process. How do people get out of your system? And I realize that sounds absolutely bat, you know what, to be telling people to be thinking about something like that when you’re just getting rolling–

CC: Appropriate for a cave analogy, right?

AP: Yes, true. But you should be, you absolutely should be.

CC: And how do you know you are going to get onto the other two things to think about in just a second, but question there, how do, what are some maybe green flags for how that question should be received or how you want that question to be received if it’s going to maybe be the right fit?

AP: I would hope some variation of the answer would be you can export to this standard, although that often is probably not the answer that you’re going to get.

CC: Okay, as standard. What are some other things people need to keep in mind in order to not be system-dependent?

AP: I don’t know if it’s so much system-dependent, but you need to think culturally about what this means. People become very attached to their tools because they become very adept. They become experts in how to manipulate and do whatever with a certain tool set. And they feel like, you know, I am in total control here. I know what I’m doing. Things are running well.

CC: Yeah.

AP: And when it turns out that tool is going to have to go away, their entire process and their focus on being an expert, it’s blown. It’s just blown away. And that can be very hard to deal with from a person level, a people level, having to tell people, yeah, this is a shock to your system. You’ve been using this tool forever. You’re really good at it. Unfortunately, that tool is being discontinued. We’re gonna have to move to something else. That can be very hard for people to swallow and it’s understandable.

CC: Mm-hmm.

AP: It’s completely understandable. One other thing that I will mention is if you can get your source content, not the actual delivery points I’m talking about here, but wherever you’re storing your source in some kind of format neutral, file format and again, talking mostly about XML content, extensible markup language, because when you create that content, you are not building in the formatting. You were creating it as a markup language. And the minute your content is in a markup language, it becomes easy to easier. I shouldn’t say easy because nothing here is easier. There is a better path to moving that content, possibly to another standard, for example, because you can set up a transformation process that’s very programmatic.

CC: Mm. Yeah.

AP: This particular element in this model becomes this. And when you hit this particular element in this model, you start a new file. If you see this particular attribute, it needs to be moved over here to this attribute.

CC: Hmm.

AP: So it’s a matching process that you have to do so it can be programmatic. So anytime you get into something that’s XML and what does that X stands for? And what does that X stand for? It stands for extensible. That gives you a little more control because it gives you more flexibility. And that’s weird to think more flexibility gives you more control. That almost seems kind of diametrically opposed, but that’s true.

CC: Yeah.

AP: Because you can move something out more easily because it is something that can be sliced, diced, transformed. So there’s that angle.

CC: Yeah. Yeah. So, okay. So as a non-technical person myself, I’m gonna see if I can summarize this and you tell me whether or not this is accurate. So from a very high level view of this, it’s almost like, you know, rather than keeping all of your content in one particular content management system or something like that, you’re keeping it in a, it’s all stored in a separate box or a separate repository. And then whatever system you’re going to use is your delivery output. It’s almost like a, is that accurate to say? Okay.

AP: Because when you are in a format that is not, doesn’t have the, if you’re in a file format that does not have the formatting of your content built in, that means you can deliver to a bunch of different presentation layers. You can automatically apply it.

CC: Okay.

AP: And that’s really, I was kind of headed that way. You can even see your new system as almost a delivery target, I need to figure out how to transform my source content in a way that a new tool, a new system can understand. And so basically you’re saying, okay, let’s export it, let’s clean it up, maybe do some automated transformations and programming on it to make it more ingestible by the other system.

CC: Mm-hmm.

AP: So you could even look at this process of moving from one system to another as being really your final destination, another horror movie, your final delivery target, moving that source content into another system that you’re about to use.

CC: Yeah. Thank you also for unpacking that because that was much more clear than my example, but that was really helpful. So since people are planning with the end in mind, how far out are we thinking this exit strategy would typically be implemented? How far down the road is this?

AP: And that’s the thing, I can’t answer that question because you never know what is going to happen. you, right, mean, it’s like the cave collapse analogy like you mentioned, sometimes you have to take a detour, not of your own choice or of your own making. And again, mergers, tools being discontinued, companies that go under, all of these things can happen. And you need to have a contingency.

CC: Mm. Never know. So it’s a contingency plan, really. Yeah.

AP: And you need to have a contingency plan in place to get ready to exit. It’s just like during natural disaster season, you hear people say, do you have your emergency preparedness kit ready? It’s a very similar thing, but it’s in the corporate world. This is as much about risk reduction as it is about smooth content operations, at least from my point of view.

CC: Yeah. Yeah. And you mentioned several like big things that happen that can trigger the need to, you know, it’s time to exit and move on. Are there any scenarios where there isn’t a big thing that happens like a merger or a business closing or different things like that? Are there more quiet ways where you realize you may not realize that it’s time to exit? But it’s more the need to exit is more subtle.

AP: If your content process, your content operations cannot support new business requirements, for example, you need to connect to a new system, you need to deliver your content in another format. If your current system and tools can’t do that, that is a sign you’re probably going to have to find the exit door and find something that will support whatever it is that you cannot do.

CC: Mm-hmm.

AP: It’s usually you just hit this wall where you realize we have taken this tool and this process as far as it can go. It is time to move on. And here I am going to toot the consultant horn again. But that is when you start getting that uneasy feeling, that’s when you can talk to a consultant who can help you unpack it to see if it’s really a sign that the tool is no longer going to fit you or if there’s something you can do within your current system to make things work. That’s when a third-party point of view can be very valuable.

CC: Question for you on that third party perspective, since you’ve seen companies make these transitions many times and exit something and go into a new one, what’s one thing or pitfall that companies need to be aware of that maybe isn’t included in their exit strategy that should be?

AP: Something that’s very common is to frame everything you want from your new system from the perspective of what your current system is doing. Even though your current system is not going to do something that you need it to do, you still are so fixated on how it is doing things and you can’t get beyond that. That can be a huge problem. Being able to step back and objectively look. This system can’t do this.

CC: Mmm.

AP: We need it to do that. And this is how we need to get there. People can get so mired in the, this is how we’re doing things. And we’re going to move over to this new system and do the same exact thing, just in new tools. That’s not a reason to move. There’s some compelling thing that’s forcing you out of that other tool. So now is the time to change things, update things, make some nips and tucks. Maybe undo some things. Don’t just wholesale move over into a new system and keep things status quo. Otherwise, why bother?

CC: Yeah, yeah. Is there anything else you can think of when you get to when it’s time to start the exiting process? Anything else that you can think of that companies need to have at the forefront of their mind?

AP: It’s the communication. And that includes the vendors and it includes with the people inside the company who are using the tools. And I would also mention it includes procurement. They need to understand the wins, the whys, why you’re having problems, all that, because there can be contractual obligations about when a license ends and another one begins. So you’ve got to keep that information flowing to all kinds of parties to make this exit, this transition work well.

CC: Yeah, you want it to end like the American version of The Descent where the hero actually gets out and drives away in the car, not like the UK version where the person is still stuck in the cave, which is the better ending for a horror movie, I will say, but not for your content ops project. Definitely.

AP: Yeah, but at least in a content ops project, you’re not going to get eaten by some humanoid blind thing living at a cave.

CC: Hopefully, right? That’s ideal. That’s the best case scenario.

AP: Hopefully not. Yeah.

CC: Well, Alan, is there any other parting advice you can think of before we wrap up today’s topic?

AP: Don’t go into a cave unprepared. Okay? Just don’t. How’s that?

CC: Yeah, don’t yeah that that is actually good advice. Yeah, don’t go unprepared. That’s really helpful. And like Alan mentioned earlier a third party perspective. I know it’s very biased to be saying it but a third party perspective when it’s time to either make the exit transition or plan for the exit transition. Content strategists can really help with that because we’ve seen we’ve seen a lot of things a lot of caves. Yes. Yeah.

AP: A lot. Maybe not cave dwellers, but a lot.

CC: Hopefully, hopefully no one has actually seen those. Yeah, well, thank you so much for being here, Alan. I really appreciate you talking about this with me today. And thank you for listening to the Content Strategy Experts Podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

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Are you looking for real-world examples of enterprise content operations in action? Join Sarah O’Keefe and special guest Adam Newton, Senior Director of Globalization, Product Documentation, & Business Process Automation at NetApp for episode 175 of The Content Strategy Experts podcast. Hear insights from NetApp’s journey to enterprise-level publishing, lessons learned from leading-edge GenAI tool development, and more.

We have writers in our authoring environment who are not writers by nature or bias. They’re subject matter experts. And they’re in our system and generating content. That was about joining us in our environment, reap the benefits of multi-language output, reap the benefits of fast updates, reap the benefits of being able to deliver a web-like experience as opposed to a PDF. But what I think we’ve found now is that this is a data project. This generative AI assistant has changed my thinking about what my team does. Yes, on one level, we have a team of writers devoted to producing the docs. But in another way, you can look at it and say, well, we’re a data engine.

— Adam Newton

Related links:

NetApp Product Documentation featuring Doc, NetApp’s GenAI-powered assistant
AI in the content lifecycle
Technical debt in content operations
The business case for content operations

LinkedIn:

Adam Newton
Sarah O’Keefe

Transcript:

Sarah O’Keefe: Welcome to the content strategy experts podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage structure, organize and distribute content in an efficient way. In this episode, we talk about content operations with Adam Newton. Adam is the senior director of global content experience services at NetApp. Hi everyone, I’m Sarah O ‘Keefe. Adam, welcome.

Adam Newton: Hey there, how are you doing, Sarah?

SO: It’s good to see and/or hear you.

AN: Good to hear your voice.

SO: Yeah, Adam and I go way back, which you may discover as we go through this podcast. And as those of you that listen to the podcast know, we talk a lot about content ops. So what I wanted to do was bring somebody in that is doing content ops in the real world, as opposed to as a consultant.and ask you, Adam, about your perspective as the director of a pretty good-sized group that’s doing content and content operations and content strategy and all the rest of us. So tell us a little bit about NetApp and your role there.

AN: Sure. So NetApp is a Fortune 500 company. We have probably close to 11,000 or more global employees. Our business is primarily data infrastructure, storage management, both on-prem. We sell storage operating system called ONTAP. We sell hardware storage devices, and we are most importantly, think, at this day and age, integrating with Azure, Google Cloud Platform, and AWS on first -party hyperscaler partnerships. My team at DENAP is… I actually have three teams under me. The largest of those three teams is the technical publications team. The other two teams globalization responsible for localization translation of both collateral and product. And then finally, and most new to my team is our digital content science team, which is our data science wing. Have about 50 to 53, think, employees at this point in my organization and all told probably about a hundred with our vendor partners.

SO: And so I think we all have a decent idea of what the technical publications team and the globalization teams do. Can you talk a little bit about the data science side? What does that team up to?

AN: Yeah, that’s a thank you for asking that question. So about two years ago, I was faced with an opportunity to hire. And maybe some of your listeners who are managers are familiar with that situation, right? I hope they are, rather than not being able to hire. I took a moment and thought a little bit more about what I needed in the future. And I thought a little bit differently about roles and responsibilities, opportunities inside NetApp and the broader content world and decided to bring in a data scientist. And then I thought a little bit more about, well, there are other data scientists at NetApp. Why would I need one? And I thought a little bit about the typical profile of the data scientists at that time at NetApp, mostly in IT and other product teams. Those data scientists were primarily quantitative data scientists coming from computer science backgrounds. And I thought, well, you know, we’re in the content business. I want to find a data scientist who is a content specialist and who has a background in the humanities and who also has skills in core data science skills, emphasizing, for example, NLP. And so that was my quest. And I was very, very fortunate to find a PhD candidate in English who wanted to get out of the academy and who had these skills. And it’s been an incredible boon to our organization. We’ve even hired a second PhD in English recently. And Sarah, since you and I are friends, I’ll say one was from UNC and one was from Duke. Okay. So we don’t have to have that discussion here. I’m an equal opportunity person. Although I did hire the UNC one first, Sarah.

SO: I see, I see. So for those of you that don’t live in North Carolina, this is… I’m not sure there is a comparison, but it is important to have both on your team. And I appreciate your inclusion of everybody. It is kind of like… I’ve got nothing.

AN: Yes.

SO: Okay, so you hired some data scientists from a couple of good universities. Or do they get along? Do they talk to each other?

AN: Fabulously, yes. No petty grievances.

SO: Okay, just checking. All right. So how do you, in this context then, what does your environment look like? What kinds of things are you doing with the docs team? And what’s the news from NetApp docs?

AN: So maybe a little bit of background actually, and you and I have talked about this previously, but we used to be a data shop. And then as things sped up inside our business with the adoption and development of cloud services at NetApp, we found that some of the apparatus of our data infrastructure, our past practices weren’t able to keep up to speed of the cloud services that were being developed. I think this is actually, I’ve talked to other people in our business, this is a very common situation. We handled it in one way. There are many ways to handle it, but the way we chose to handle it was to exit data and to move in our source format anyway to a format called ASCII doc, which I always frequently describe as a dialect of markdown. And we went from being a closed system of technical writers working inside a closed CMS to adopting open source. We now work in GitHub. Our pipeline is all open source and we have now contributors to our content that are not technical writers. In some cases, they’re technical marketing engineers, solution architects, and so forth as well as a pipeline of docs that we build through automations where we, for example, transform API specifications or reference docs that are maintained by developers and output those into our own website docs.netapp.com. In addition to just the docs part, my globalization team has been using for many years, machine translation. So speaking to one particular opportunity of being in one organization, when we output our docs and whenever we update our docs in English, they’re automagically updated in eight other languages and published to docs.netapp.com. So we roughly maintain 150,000 English files and you can times those by eight. Is that right? Did I do the math right? Yeah.

SO: Or nine, depending.

AN: Nine. Yeah. Is English the language? Yeah, sure. Let’s count it.

SO: Depends on how we use it. Okay, so you have an ASCII doc, you know, Markdown-ish. Is it fair to call it Docs as Code environment?

AN: So we often describe it as a content ops, environment. I’m not sure if that is, different from Docs as Code, but I think maybe I will accept that as a reasonable description in the sense that, we have asked our team members to think about the content that they’re writing as highly structured, semantically meaningful units of information. I think in the same way I think a developer can be asked to think of their code being that way and the systems in which we write in VS code, many engineers are writing in that.

SO: Mm-hmm.

AN: And of course our source files, as I mentioned, all in our automation and our pipelines are all based on being in GitHub.

SO: And so then you’ve got docs.netapp.com as a portal or a platform where a lot of this content goes. And what’s happening over there? Do you have any news on new things you’ve done there?

AN: Yeah. I mean, very recently, you know, the timing of this is really interesting. We, have been working on a generative AI solution, for a year, Sarah. you’ll recall the, the hype, right? When, when chat GPT exploded onto the, the, into the public consciousness, right? Through the media and, shortly thereafter, we began imagining what it might look like to leverage that technology, those types of technologies to deliver a different customer experience. And we identified a chatbot as being something we thought could add to the browse and search experiences on docs .netapp .com. And we just released that on the 20th of August announced it here internally inside of NetApp on the 27th. So we are literally like 48, 72 hours into a public adventure here.

SO: I take full credit for planning it, even though I knew nothing about any of this.

AN: Yeah. And that was a long time. I think it’s worth noting too. It was a long time. And I think it’s beyond the full dimensions of this, this discussion to talk about why it took so long. But I will say maybe to, you know, the, were early adopters and we felt, we felt the pain and the benefit of being that, you know, it was like, you know, changing the tires on a, on a race car, right? That was speeding around the track. So we had to learn and be responsive and also humble in the sense that there were some missteps that we had to recover from and some magical thinking, I think, at the beginning of the project that was qualified more over the course of the project.

SO: And so what does that GenAI solution sitting in or over the top of the docs content set, what does that do in terms of your authoring process? Do you have any, are there any changes on the backend as you’re creating this content that is then consumed by the AI?

AN: I would say we’re in the process of understanding the full implications of having this new output surface, this generative AI assistant, and fully grappling with what the implications are for the writers. We find ourselves frequently in discussions about audience. And audience is all those humans that we have been writing for and a whole bunch of machines that we now need to think more consciously about, you know, and it’s, we find ourselves often talking about standards and style, but not just from the perspective of, you know, writing the docs in a consistently patterned way for humans to be able to consume well, but also because patterns and machines are a marriage made in heaven. And we see actually opportunities to begin to think of the content we’re writing as a data set that needs to be more highly patterned and predictable so that a machine can consume it and algorithmically and probabilistically decide how to generate content from the content we’re creating.

SO: And where is this going in terms of what’s next as you’re looking at this? I think you mentioned that there’s other opportunities potentially to add more data slash content.

AN: Yeah, actually, if I back up to a detail and I shared, but maybe quickly, you know, we do have writers in our authoring environment who are not writers. They are by nature and by bias sort of, they’re, people who have their subject matter experts, right? And they’re in our system and they’re generating content. But I think that some of the opportunities that, so that was about join us in our environment, right? Join us in our environment, reap the benefits of multi-language output, reap the benefits of fast updates, reap the benefits of being able to deliver a web-like experience as opposed to a PDF. But what I think we’ve found now is that this is a data project. This generative AI assistant has changed my thinking about what my team does. And I think, yes, on one level, true. Yes, we have a team of writers and there’s a big factory devoted to producing the docs. But in another way, you can look at it and say, well, we’re a data engine. We own a large, own, maintain a large data set and the GenAI is one consumer of that data set. But we’re also thinking about our data set as being joinable to other data sets inside of NetApp. And in particular, I work inside the chief design office at NetApp, along with UX researchers and designers. And we’re also more broadly part of our platform team at NetApp, shared platform team. So we’re thinking about how might we join our data with other teams’ data to create in-product experiences that are data-led or data-driven in combination with curated experience. So if your viewers were to be able to see me, I am waving my hand a little bit, not because I’m dissembling, but more because I’m aspiring. And I think there’s a really, really cool future ahead for, a way, Sarah, that I think is super energizing for the writers, right? To see that their work is being reframed, not replaced or changed, right? The fear of writers with GenAI, right, of being replaced. Well, I would offer this as an example of, you know, maybe it’s not such a dismal view and maybe in fact there’s a very interesting future if you reframe your thinking about what you do and the opportunities to join what you do to create different experiences.

SO: And I think it’s an interesting perspective to look at GenAI as being a consumer of the content slash data that you’re putting out. A lot of the initial stuff was, this is great. GenAI will just replace all the tech writers. You’re talking about something entirely different.

AN: I guess I wanted to expand on that because I think we’re actually now hovering on a really important point. You know, what is your mindset? You know, what what how are you thinking about this moment in time? The broad we write you or the broader you us generally write who are in this industry. And, you know, I think we don’t see a great indication that GenAI can create net new content and do it well, honestly. I think you can write it summarizing, it can make your day-to-day, your meeting notes and so forth, Microsoft Co-pilot, right? There are some great uses, but I have not seen convincing, compelling indicators that docs can be written by, at least at the enterprise level, right? Our products are complex. We often talk about our writers as sense makers, right? And I think that we can take advantage of GenAI in the right ways. And I think this is one of the ways that we’re taking advantage of it, which is to give customers another experience. And frankly, also for us to learn a lot about what people are asking and assuming and we can learn a lot and continuously improve.

SO: So what’s happening on the delivery side? Somebody asks for some sort of information and it gives either, it says it doesn’t exist or it gives an incorrect response. Are you seeing any patterns there? What are you doing with that?

AN: Yeah, many of your listeners might have produced products themselves, right, or delivered products themselves and remembered what happens in the first day or two of releasing a product, right? So the timing of this chat is really good. Yeah, in the last couple days we’ve seen I was just talking to a data scientist on my team and I was saying, you know, what I think I see here emerging as a possible pattern is that people don’t actually know how to use these things effectively. That, you know, they ask of it questions that it really could never answer, or they don’t fully understand the constraints of the system, meaning that, well, it’s only based on a certain data set. you know, they don’t know that the data set doesn’t include the data they’re looking for, right? Because it sits somewhere else. You know, we’re modifying our processes to intake feedback. I think there’s a real interesting nexus is, is it the AI or is it the content? That’s the really interesting one, right? You know, was the content ambiguous, deficient, duplicitous, whatever, you know, is that a word?

SO: It is now.

AN: At UNC we use that word, not at Duke. But it is an interesting discussion inside our organization when we receive a piece of feedback, what’s causing it? Is it the interpretive engine or is it our source? And so we’re seeing a lot of gaps in our content, it’s exposing a lot of gaps or other suboptimal implementations.

SO: I mean, we’ve said that in a sort of glib manner, because of course you’re living this day to day and hour by hour, but we’ve said that, know, GenAI sitting over the top of a content set is going to uncover all your inconsistencies, all your missing pieces, all your, you know, over here you said update and over here you said upgrade. That was an example I heard from someone else. And so it basically uncovers your technical debt.

AN: Yeah, beautiful. Yeah, bingo. Yeah. Yeah. Yeah. You’re so right there. Terminology, right? my God. Can you believe how many things, how many ways we’ve talked to, talked about X, right?

SO: Right, and the GenAI thinks they’re different because, or it doesn’t think anything right, but the pattern isn’t there and so it doesn’t associate those things necessarily.

AN: Yeah, your listeners may commiserate with this, or the use of words as verbs and nouns, like cable. We often in our documentation talk about cabling devices. How would a GenAI know that the writer of the question is using cable as a verb or noun?

SO: Mm-hmm. So as you’re working through this and with your, you know, it sounds like two days of go live plus a year or two or three of suffering and a year and two days.

AN: Well, a year and two days, a year and two days.

SO: You know, I think you’re further along than lot of other organizations. Do you have any advice for those that are just beginning this journey and just looking at these kinds of issues? What are the things you did best or maybe worst or would do the same way or not? What’s out there that you can tell people that’ll maybe keep them from, you know, get them, get them or help them as they move forward?

AN: Yeah, but maybe think of it in the old people process systems dimensions. Actually, taking that latter one, systems, I would say beware the fascination of the system without thinking more about the processes and people that are going to be involved in the creation of some kind of generative AI solution. I think, you know, this is as much of an adaptive people process as it is a problem as it is a technical problem. Probably more frankly on the adaptive. And from a process perspective, I’d say, be curious about what you learn. Be attentive to the specifics, but look for the broad patterns in the feedback or what you’re seeing as you develop these solutions, you know, for me, I think I hinted at this before and I think it for me has been frankly, the epiphany of the project. There have been many, but I’d say I I would really highlight this one, which is what does my team do? What is the value of what they generate? And for me, yes, we are, you know, primarily a team that creates documentation, but you know, holy smokes, you know, the, the idea that we are data owners, and we govern a massive, semantically rich, non-determinant, fast-changing data set, that is super, super interesting. Even here inside NetApp, Sarah, we have teams reaching out to us who frankly before probably never thought about the docs. And all of a sudden, because we have this huge data set, they’re like, wow, we can, you know stress test our system or our new technologies using what they have. That’s a super cool moment for our team.

SO: Yeah, I think you’re the first person that I’ve heard describe this sort of context shift from this is content to this is data or this content is also data or however you want to phrase that. But I think that’s a really interesting point and opens up a lot of fascinating possibilities, not least for the English PhDs of the world. That’s super helpful.

AN: Is this where I confessed at one time trying to think I was going to be one of those and I got out because I realized I was terrible at it?

SO: No, no, no, that goes in the non-recorded part of the podcast. Yeah, I’m going to wrap it up there before Adam spills all of the dirt.

AN: Yeah, what am I compensating for, right?

SO: But thank you, because this is really, really interesting. And I think it will be helpful to the people listening to this podcast, because it’s so rare to get that inside view of what it really looks like and what’s really going on inside some of these bigger organizations as you move towards AI, GenAI strategies and figure out how best to leverage that. So thank you, Adam. And it’s great to see you.

AN: No, Sarah, thank you. And actually, I would like to thank my team. I mean, it has been an incredible adventure, and I think the team is really amazing.

SO: Yeah, and I know a few of them and they are great. So with that, thank you for listening to the Content Strategy Experts Podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Enterprise content operations in action at NetApp (podcast) appeared first on Scriptorium.

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In episode 174 of The Content Strategy Experts podcast, Sarah O’Keefe and Alan Pringle explore the mindset shifts that are needed to elevate your organization’s content operations to the enterprise level.

If you’re in a desktop tool and everything’s working and you’re happy and you’re delivering what you’re supposed to deliver and basically it ain’t broken, then don’t fix it. You are done. What we’re talking about here is, okay, for those of you that are not in a good place, you need to level up. You need to move into structured content. You need to have a content ops organization that’s going to support that. What’s your next step to deliver at the enterprise level?

— Sarah O’Keefe

Related links:

The business case for content operations
Do you have efficient content ops?
Technical debt in content operations
Content Ops Forecast: Mostly Sunny With A Chance Of Chaos (webinar)

LinkedIn:

Sarah O’Keefe
Alan Pringle

Transcript:

Alan Pringle: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about setting up your content operations for success. Hey everyone, I am Alan Pringle and I am back here with Sarah O ‘Keefe in yet another podcast episode today. Hello, Sarah.

Sarah O’Keefe: Hey there.

AP: Sarah and I have been chatting about this issue. It’s kind of been this nebulous thing floating around and we’re gonna try to nail it down a little bit more in this conversation today. This idea of setting up your organization for success and their content operations. And to start the conversation, let’s just put it out there. Let’s define content ops. What are content operations, Sarah?

SO: Content strategy is the plan. What are we going to do, how do we want to approach it? Content ops is the system that puts all of that in place. And the reason that content ops these days is a big topic of conversation is because content ops in sort of a desktop world is, well, we’re going to buy this tool, and then we’re going to build some templates, and then we’re going to use them consistently. And the end, right? That’s pretty straightforward. But content operations in a modern content production environment means that we’re talking about lot of different kinds of automation and integration. So the tools are getting bigger, they’re scarier, they’re more enterprise level as opposed to a little desktop thing. And configuring a component content management system, connecting it to your web CMS and feeding the content that you’re generating in your CCMS, your component content management system, into other systems via some sort of an API is a whole different kettle of fish than dealing with, you know, your basic old school unstructured authoring tool. So yeah.

AP: Right. But in their defense, for the people who are using desktop publishing, that is still content operations.

SO: Sure, it is.

AP: It’s just a different flavor of content operations. And frankly, a lot of people, a lot of companies and organizations outgrow it, which is why they’re going to this next level that you’re talking about.

SO: Right. So if you’re in a desktop tool and everything’s working and you’re happy and you’re delivering what you’re supposed to deliver and basically it ain’t broken, then don’t fix it. You are done. You should shut off this podcast and go do something more fun with your time. Right? What we’re talking about here is, okay, for those of you that are not in a good place, you need to level up. You need to move into structured content. You need to have a content ops organization that’s going to support that. What do you do? What’s your, you know, what’s your next step and what does it look like to organize this project in such a way that you move into, you know, that next level up and you can deliver all the things that you’re required to deliver in the bigger enterprise, whatever you want to call that level of things. So desktop people, I’m slightly jealous of you because it’s all working and you’re in great shape and good for you. I’m happy for you.

AP: So making this shift from content operations and desktop publishing to something more enterprise level like you’re talking about, that is a huge mind shift. is also technically something that can be quite the shock to the system. How do you go about making that leap?

SO: Well, I’m reminded of a safety announcement I heard on a plane one time where they were talking about how, you know, when you open the overhead bins after landing, you want to be careful. And the flight attendant said, shift happens. And we all just looked at her like, did you actually just say that? And she sort of smirked. So making this shift can be, it’s can be, it’s difficult, right? And what we’re usually looking at is, okay, you’ve been using, you know, Word for the past 10, 15, 20, 57 years. And now we need to move out of that into, you know, something structured XML, maybe it’s DITA, and then get that all up and running. And so what’s going to happen is that you have to think pretty carefully about what does it look like to build the system and what does it look like to sustain it? Now here I’m talking particularly to large companies because what we find is the outcome in the end, right, when this is all said and done and everything’s up and running and working, what you’re probably going to have is some sort of an organization that’s responsible for sustainment of your content ops. So you’re to have a content ops group of some sort, and they’re going to do things like run the CCMS and build new publishing pipelines and keep the integrations moving and help train the authors. And in some cases, they’re kind of a services organization in the sense that you have an extended group of maybe hundreds of authors who are never going to move into structured content. So you’re taking on the, again, word content that they are producing, but you’re moving it into the structured content system as a service, like an ingestion or migration service to your larger staff or employee population. Okay, so in the future world, you have this group that knows all the things and knows how to keep everything running and knows how to kind of manage that and maintain it and do that work. And probably in there, you have an information architect who’s thinking about how to organize content, how to classify and label things, how to make sure the semantics, you know, the actual element tags are good and all that stuff. But right now, you’re sitting in desktop authoring land with a bunch of people that are really good at using whatever your desktop authoring tool may be. And you have to sort of cross that chasm over to, now we’re this content ops organization with structured content, probably a component content management system. So what I would probably look at here is, you know, what is the outcome? You know, thinking about the system has stood up, we’ve made our tool selection, everything’s working, everything’s configured, everything’s great. What does it look like to have an organization that’s responsible for sustaining that? And that could be, you know, two or three or 10 people, depending on the size, again, the size and scope of your organization and the content that you’re supporting. But in order to get there, you first have to get it all set up. You have to do the work to get it all up and running. Our job typically is that we get brought in to make that transition. Right? So we’re not going to be for a large organization, we’re not going to be your permanent content ops organization. We might provide some support on the side, but you’re going to have people in-house that are going to do that. They’re going to be presumably full-time permanent kind of staff members. They know your content and your domain and they have expertise in, you know, whatever your industry may be.

AP: Right.

SO: Our job is to get you there as fast as possible. So we get brought in to do that setting up piece, right? What are the best systems? What are the things you need to be evaluating? What are the weird requirements that you have that other organizations don’t have that are going to affect your decisions around systems and for that matter, people, right? Are you regulated? What is the risk level of this content? How many languages are you translating into? What kind of deliverables do you have? What kind of integration requirements do you have? And when I say integration, to be more specific, maybe you’re an industrial company and so you have tasks, service, maintenance kinds of things, and you need those tasks like how to replace a battery or how to swap out breaks to be in your service management system so that a field service tech can look at their assignments for the day, which are, you know, go here and do this repair and go here and do this maintenance. And then it gets connected to, and here’s the task you need and here’s the list of tools you need. And here are all the pieces and parts you need in order to do that job correctly. Diagnostic troubleshooting systems. You might have a chat bot and you want to feed all your content into the chat bot so that it can interact with customers. You may have a tech support organization that needs all this content and they want it in their system and not in whatever system you’re delivering. So we get into all these questions around where does this content go? You know, where does it have tentacles into your organization and what other things do we need to connect it to and how are we going to do that? So I think it’s very helpful to look at the upfront effort of configure or, you know, making decisions, deciding on designing your system and setting up your system versus sustaining, enabling, and supporting the system.

AP: There are lots of layers that you just talked about and lots of steps. It is very unusual, at least in my experience, to find someone, some kind of personnel resource, either within or hiring, who is going to have all of the things that you just mentioned because it is a lot to expect one person to have all of that knowledge, especially if you are moving to a new system, and you’ve got a situation where the current people are well versed in what is happening right now in that infrastructure, that ecosystem. To expect them to magically shift their brain and figure out new things, that’s a lot to ask for. And I think that’s where having this third-party consultant person, voice, is very helpful because we can help you narrow in on the things that are better fits for what you’ve got going on now and what you anticipate coming in the future.

SO: Yeah, I mean, the thing is that what you want from your internal organization is the sustainability. But in order to get there, you have to actually build the system, right? And nearly always when people reach out to us and say, we’re making this transition, we’re interested, we’re thinking about it, et cetera, they’re doing it because they have a serious problem of some sort. We are going into Europe and we have no localization capabilities or we have them, but we’ve been doing, you know, a little bit of French for Canada and a tiny bit of Spanish for Mexico. And now we’re being told about all these languages that we have to support for the European Union. And we can’t possibly scale our, you know, 2 .5 languages up to 28. It just, it just can’t be done. We’ll, we’ll drown. Or people say, We have all these new requirements and we can’t get there. We’ve been told to take our content that’s locked into, you know, page based PDF, whatever, and we’re being required to deliver it, not just onto the website and not just into HTML, as you know, content as a service, as an API deliverable, as micro content, all this stuff. And they just, they just can’t, you can’t get there from here. And so you have people on the inside who understand, as you said, the current system really well, and understand the needs of the organization in the sense of these things that they’re being asked to do and they understand the domain. They understand their particular product set internally. But it’s just completely unreasonable to ask them to stand up, support and sustain a new system with new technology while still delivering the existing content because, you know, that doesn’t go away. You can’t just push the pause button for five months.

AP: No, the real world does not stop when you are going on some kind of huge digital transformation project like one of these content ops projects. So basically what we’re talking about here, especially on the front end, the planning discovery side, is we can help augment, help you focus. And then once you kind of picked your tools and you start setting things up, there’s some choices there that sometimes have to do with like the size of an organization about how to proceed with implementation and then maintenance beyond that. Let’s focus on that a little bit.

SO: Most of the organizations we deal with are quite large. Actually, all of the organizations we deal with are quite large compared to us, right? It’s just a matter of are they a lot bigger or are they a lot, a lot, a lot, lot bigger?

AP: Correct.

SO: Within that, the question becomes how much help do you want from us and how much help do your people need in order to level up and get to the point where they can be self-sufficient? We have a lot of projects we do where we come in and we help with that sort of big hump of work, that big implementation push, and help get it done. And then once you go into sustainment or maintenance mode, it’s 10% of the effort or something like that. And so either you staff that internally as you’re building out your organization internally, or we stick around in sort of a fractional, smaller role to help with that. The pendulum kind of shifted on this for a while, or way back, way back when it was get in, do the work and get out. We rarely had ongoing maintenance support. Then for a bit, we were doing a lot of maintenance relative to the prior efforts. And now it feels as though we’re seeing a shift in a little bit of a shift back to doing this internally. Organizations that are big enough to have staff like a content ops group or a content ops person are bringing it back in-house instead of offloading it onto somebody like us. We’re happy to do whatever makes the most sense for the organization. At a certain size, my advice is always to bring this in-house because ultimately, your long-term staff member who has domain expertise on your products and your world and your corporate culture and has social capital within your organization will be more effective than offloading it onto an external organization, no matter how great we are.

AP: To wrap up, think I want to touch on one last thing here, and that’s change management. And yes, we beat that drum all the time in these conversations on this podcast, but I don’t think we can overstate how important it is to keep those communication channels open and be sure everyone understands what’s going on and why you’re doing what you’re doing. What we’ve talked about so far is very much, okay, we’ve come up with a technical plan, we’ve done a technical implementation, and now we’re going to set it up for success and maintain it for the long haul and adjust it as we need to as things change. But there are still a group of people who have to use those tools, your content creators, your reviewers, all of those people, your subject matter experts, I mean, I can go on and on here, they are still part of this equation here and we can’t forget about them while we’re so focused on the technical aspects of things.

SO: I would say this and directly to the people that are doing the work, know, the authors, the subject matter experts, the people operating within the system. I would look at this as an opportunity. It is an opportunity for you to pick up a whole bunch of new skills, new tools, new technologies, new ways of working. And while I know it’s going to be uncomfortable and difficult and occasionally very annoying as you discover that the new tools do some things really well, but the things that were easy in the old tools are now difficult, right? There’s just going to be that thing where the expertise you had in old tool A is no longer relevant and you have to sort of learn everything all over again, which is super, super annoying. But it’s fodder for your resume, right? I mean, if it comes to it, you’re going to have better skills and you’re going to have another set of tools and you’re going to be able to say, yes, I do know how to do that. So I think that just from a self-preservation point of view, it makes a whole lot of sense to get involved in some of these projects and move them forward because it’s going to help you in the long run, whether you stay at that organization or whether you move on to somewhere else, you know, at some point in the future. That’s one of the ways I would look at this. It is certainly true that the change falls on the authors, right?

AP: Correct.

SO: They all have to change how they work and learn new ways of working and there’s a lot there and I don’t want to you know sort of sweep that aside because it can be very painful. We try to advocate for making sure that authors have time to learn the new thing that people acknowledge that they’re not going to be as productive day one in the new system as they were in the old system that they know inside out and upside down that they get training and knowledge transfer and just, you a little bit of space to take on this new thing and understand it and get to a point where they use it well. So I think there’s a, you know, there’s a combination of things there. For those of you that are leading these projects, it is not reasonable, again, to stand the thing up and say, go live is Monday. So, you know, I expect deliverables on Tuesday. That is not okay.

AP: Yeah. And you’ve just wasted a ton of money and effort because you’ve thrown a tool at people who don’t know how to use it. So all of your beautiful setup kind of goes to waste. So there are lot of options here as far as making sure that your content ops do succeed. And I don’t think it’s like pretty much everything else in consulting land. It is not one size fits all.

SO: It depends, as always. We should just generate one podcast and put different titles on it and just say it depends over and over again.

AP: Pretty much, we’d probably just get an MP3 of us saying that phrase over and over again and just loop it and that will be a podcast episode. And on that not-great suggestion for our next episode, I’m gonna wrap this up. So thank you, Sarah.

SO: Thank you.

AP: I think she just choked on her tea, everyone.

SO: I did.

AP: Thank you for listening to the Content Strategy Experts Podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Position enterprise content operations for success (podcast) appeared first on Scriptorium.

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Translation troubles? This podcast is for you! In episode 173 of The Content Strategy Experts podcast, Bill Swallow and special guest Mike McDermott, Director of Language Services at MadTranslations, share strategies for overcoming common content localization challenges and unlocking new market opportunities.

Mike McDermott: It gets very cumbersome to continually do these manual steps to get to a translation update. Once the authoring is done, ideally you just send it right through translation and the process starts.

Bill Swallow: So from an agile point of view, I am assuming that you’re talking about not necessarily translating an entire publication from page one to page 300, but you’re saying as soon as a particular chunk of content is done and “blessed,” let’s say, by reviewers in the native language, then it can immediately go off to translation even if other portions are still in progress.

Mike McDermott: Exactly. That’s what working in this semantic content and these types of environments will do for a content creator. You don’t need to wait for the final piece of content to be finalized to get things into translation.

Related links:

MadCap Software
MadTranslations
Accelerate global growth with a content localization strategy (podcast)
Lost in translation? Create scalable content localization processes

LinkedIn:

Bill Swallow
Mike McDermott

Transcript:

Bill Swallow: Welcome to the Content Strategy Experts podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we explore strategies for conquering localization challenges, and unlocking new market opportunities. Hi everybody. I’m Bill Swallow, and with me today is Mike McDermott from MadCap Software. Hey Mike.

Mike McDermott: Hi Bill.

BS: So before we jump in, Mike, would you like to provide a little background information about you, who you are, what you do at MadCap?

MM: Sure. My name is Mike McDermott. I am the director of language services at MadCap Software working with our MadTranslation Group. And we support companies that work in single source authoring in multichannel publishing tools like those offered from MadCap Software for IXIA and MadCap Flare and Xyleme and other tools.

BS: So Mike, what are some of the challenges you’ve seen and what works for overcoming some of these localization challenges?

MM: One of the main challenges I see with companies that come to us, and they typically come to us because they’re looking at working in an XML-based authoring tool and they’re curious about the advantages it has for translation. And one of the biggest challenges I see initially with these companies is just figuring out what content needs to go into translation when you’re working in different types of tools. And one of the ways I see to solve that problem is working in a tool where you have the ability to tag certain content and identify content for different audiences or different purposes. It just makes it simpler to identify that content and get it straight into translation and removes a lot of the human error around packaging up content and trying to figure out yourself what files, house texts that might be translatable for whatever the output is that you’re looking to build. So just working in those tools I see inherently helps with translation because it helps you identify exactly what needs to be translated and it gets it into translation much quicker.

BS: So I think we’re talking about semantic content there and making sure that you have all the right metadata in place so that you can identify the correct audience, the correct, let’s say versions of the product, whether to translate or not, and any other relevant information about the content. So you’re able to isolate the very specific bits of content that need to be translated and omit a lot of the content that necessarily isn’t needed for that deliverable.

MM: Exactly, Bill. It lets the technology tell you what needs to be translated in what houses text versus you trying to go through a file list and determine what do I need to send out to a translator to translate. The flip side of that is to just send everything for translation, but it’s very rare that anything in any given project for any type of system is going to need to be translated. So by tagging it in that way, you can quickly get into the translation and get things moving. And what I see happening at the end of these projects, oftentimes when you’re not working in those types of systems is you end up finding bits and pieces of content or different files that ended up needing to be translated that missed that initial pass. Now they have to go back through translation and you’re delayed. So just getting everything right the first time and relying on the tools to tell you exactly what needs to be translated by looking up metadata or different tags just simplifies the process and speeds everything up, helps translation get done quicker and just improves time to market for the end user to get their content out.

BS: So it sounds like it reduces a good amount of friction, especially with regard to finding missing bits and pieces that should have been translated and weren’t, and then needing to go back and make sure that’s done in time. What are some other ways that people can reduce friction in their translation workflow?

MM: Well, a big emphasis for us over the past few years around removing friction is working with connectors and different technologies that can orchestrate the translation process. So we can automate a lot of this and remove the bottlenecks around someone having to, like I said before, manually go into a set of files and package things up for a translator, zip up files, upload them to different locations, and they just get passed around and things can happen when working that way, even outside of just missing files. So working with connectors and these technologies that can connect directly into these systems and get the text right into translation, removing all those friction points just eliminates a lot of room for error in project delays, bottlenecks for tasks that can be easily handled by modern technology.

BS: And I assume that there’s probably some technology there as well that kind of govern other things, other parts of the workflow, like review, content validation, that type of thing?

MM: Exactly, exactly. So we’re trying to automate the flow of data into the different points in translation and then get the content ready. For example, for reviewers, you mentioned reviewers. So once content gets into translation, we can get it right into the translation system from the authoring environment that the customer’s working in, get it into translation. And as soon as the translation is done, a human reviewer on the client side or on our side or whoever can be notified that this content is ready for translation and it just helps keep things moving. So now it’s on them to complete their translation. And once that’s done, the process can continue on and the automated QA checks, the human QA checks can be done at that point, and then the project can be pushed back to wherever it needs to go and put into publication. But by automating the steps and plugging in the humans where they provide the most value, it just removes the time costs in error-prone steps that don’t need to be there.

BS: So it sounds like a lot of it does come down to saving a good deal of time. I would also imagine that these types of workflows, they also help streamline a lot of the publishing needs that come after the translation as well.

MM: Correct. And that’s kind of why we started MadTranslation when we did, was to provide our customers a place to go to work with the translation agency that understood these tools and understand how these bits and pieces come together to build an output. We put it together to provide our customers a turnkey solution where they can get a working project back where they can quickly get into publication. By removing the friction points and using modern technology to automate a lot of these processes, we’re able to get things into translation and add a translation into the final deliverable much faster. So once that happens, we can build the outputs and we can check if it requires a human check on it, things can get to that point much quicker, and we’re not waiting for somebody to manually pull down files and putting them into another location so the next actually take place. We want to automate that part of it so we can get to that final output into a project file where a customer can plug it into their publishing environment and get it out as quickly as possible. A lot of the wasted time is around those manual steps, and when it comes to validation and review, it’s just the reviewers and validators maybe not being ready for the validation or not being educated on how it will work. So it’s important to make sure that everyone in that process knows how it’s going to be done, when things are going to be ready for the review or the QA checks. And then the idea from there is to just feed the content in via connectors, removing the friction point and just send it through. And this is necessary, especially when you’re doing very frequent updates and kind of a more of an agile translation workflow. It gets very cumbersome to continually do these manual steps to get to a translation update. Once the authoring is done, ideally you just send it right through translation and the process starts.

BS: So from an agile point of view, I am assuming then that you’re talking about not necessarily translating an entire publication from page one to page 300, but you’re talking about as soon as a particular chunk of content is done and it’s “blessed,” let’s say, by reviewers in the native language, then it can immediately go off to translation even if other portions are still in progress.

MM: Exactly. Exactly. And that’s what working in this semantic content and these types of environments will do for a content creator is you don’t need to wait for the final piece of content to be finalized to get things into translation. So as you said, it becomes even more important when you’re doing updates because you don’t want to have to send over the entire file set every time you’re doing an update. Whereas when you’re working in a more linear format like Word, you end up having to send that full file every time, and the translation agency is likely reprocessing it using translation memory. But all that stuff still takes time and working in these types of tools, you can very quickly identify those new parts or those bits that you know are ready for translation, tag them or mark them in some way and send them through the translation process.

BS: Very cool. So a lot of the work that we’re seeing now on the Scriptorium side of things is in re-platforming. So people have content in an old system or they have, say a directory full of decaying word files, and they want to bring it into some other new system. They want to modernize, they want to centralize everything, basically have a situation where they’re working in data or some other structured content, bring it into semantic content. What are some of, I guess, the benefits of doing that give you as far as translation goes when you’re looking at content portability? So being able to jump ship from one system to another.

MM: I think working in those systems where the text or the content is stored away from the output that you’re building has a lot of benefits to not only translation being able to just get the text that needs to be translated, exported out of the system and then put back where it needs to go. But it really future-proofs you and gives you the portability that you talk about to make changes because the text is stored in a standard format that can be ported versus you see some organizations getting locked into a closed environment to where when it goes to make a change, it requires certain types of exports to other type of file types that other tools can then import. But by storing them in a standard way in XML, for example, it gives you that flexibility in a future proves you from being locked into any one scenario.

BS: Excellent. So I have to ask, since I’ve come from a localization background as well, what’s one of the hairier projects that you’ve seen or one of the hairier problems that people can run into and in a localization workflow?

MM: One of the challenges we run into sometimes around client review, when you start incorporating validators into the translation system and include them as part of the process, when you get multiple reviewers. Sometimes that will happen where a company will assign a reviewer for every language, but you might have different people reviewing the same set of content. I mean, that’s the biggest delay that we see with projects is translations delivered and then the translation is dumped on a native speaker within the company’s desk and they’re asked to review it and they’re not ready to do the review, it’s not scheduled and it can delay the project. That’s one of the biggest delays we see. So that’s why we try at the front end of a project to figure out on the client side, what’s going to happen after we deliver this project, after we send the files, is the content going to be reviewed or validated? If so, let’s figure out a way to incorporate them into our translation system where they can review the translations before we build the outputs and do all the QA checks. So that’s one of the hairier situations in terms of time delays. Expectations around just time in general have always been a thing in localization. As you know, people can be surprised as to how long it can take for a translator to get through content. I mean, the technology is there certainly to speed it up. Since we’ve started MadTranslations a little over 10 years ago, we’ve seen the translation speed increase quite a bit, but it still takes time for a good translator to get through that content and know when to stop and do the research that’s needed to get a technical term right. So that’s one of the surprise moments I think for new buyers of localization is the time that it can take and there’s solutions in place, like I said, to make it go faster. But if you want that human review and that expertise and the cognitive ability to know when to stop and figure out what this term is or what the client wants or doesn’t want around certain terminology, and then to database it and then include that as part of the translation asset so it stays consistent every time. That takes time versus just sending something through a machine translation, doing a quick spot check and sending it back to the customer.

BS: So it sounds like having that workflow defined and setting those expectations that certain things need to happen at each point of that workflow. Some of it might be automated, some of it does require a person, and that person I guess should probably be identified ahead of time and given a heads-up that, “Hey, something’s going to be coming at you in three weeks. Be ready for it.”

MM: Be ready for it. And also, what are you ready for? So it’s kind of training a reviewer, what are you looking for here? Are we looking for key terms? Are we looking for style preferences? Everyone kind of understanding what it is that a reviewer is going to be looking for, and they might be looking for different things when it comes to technical documentation versus a website, for example. So just having everyone communicate and understand what the intended purpose of the final output is and where everyone fits in the process and defining a schedule around that process definitely helps.

BS: Definitely. I know myself, I’ve seen cases where working for a translation agency, having a client come to me and basically say, “I need this done as soon as possible. What can you do?” And it was a highly technical manual, and we said, “Well, we have an expert in these different languages. This person is available now. This one won’t be available until next month. And this person really only works nights and weekends because they are a professional engineer in their day job.” So turnaround is going to be a little slow, and the client persisted that we just need it as soon as possible. We need to get it out the door in a couple of weeks, and I’m thinking to myself in the back of my head, why are you coming to us now when you need this in a couple of weeks? You shouldn’t just be throwing it over the fence at the last possible minute and expecting it to come back tomorrow. So there was that education. Unfortunately, they decided that they didn’t care. They wanted us to use as many translators as possible and get it done as quick as possible. And we had them sign documents that basically said that we are not liable for the quality of the translation since the client is basically looking to get this done as quickly and cheaply and dirty as possible. It was a nightmare, and I think it took one round of review on the client side for them to basically circle back and say, “Okay, I get what you were saying now.” None of these translations work at all together, because we were literally sending out a chapter to a different translator and there was no style guide because the client hadn’t provided anything. There was no terminology set because the client didn’t provide anything and everything came back different. And they said, “Okay, we get it. We get it. We’ll revise our schedules, get it done the right way. I don’t care how long it takes.”

MM: I’ve run into something very, very similar to what you described, and it was put disclaimers in the documents to where this is going to be poor quality. We’re admitting it right now. This is the only way we’re going to get it back within a week, and we do not recommend publishing. And as soon as the files come back and so on, looks at it and says, “Okay, let’s back up and do it the right way.”

BS: Yes. I guess the biggest takeaway there is plan ahead and plan for quality and not just try to get it done as fast as possible.

MM: And that’s one of the benefits to where we sit at MadTranslations with MadCap Software companies, companies coming into these types of environments. They’re typically at the front end, the planning stages on trying to figure out how all this is going to work. So we have an ability to help them understand what the process looks like and then define it in combination with our tooling and their needs and come up with a workflow that’s going to keep things moving fast, but gives you that human level quality that everyone needs at the end.

BS: Being able to size up exactly what the process needs to look like before you’re in the thick of it definitely helps. And having that opportunity to coach someone through setting up the process for the first time, I’d say that’s definitely priceless because so many mistakes can happen out of the gate between how people are authoring content, what their workflow looks like.

MM: And it’s even more important for companies to have to maintain the content. So it’s one thing to just take a PDF and say, “Hey, I need to translate this file and I’m never going to have to update it again. I just need a quick translation.” It’s another to have a team of authors dispersed around the globe working on the same set of content that then needs to be translated continuously.

So different needs, but like you said, planning, defining the steps and knowing what the requirements of the content are from authoring to time to publication in each language, and how to fit the steps and to meet that as best as possible is best done, like you said, upfront versus when it needs to be published in a week.

BS: Planning, planning, planning. I think that sounds like a good place to leave it. Mike, thank you very much.

MM: Thank you, Bill. Thanks for having me on.

BS: Thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Conquering content localization: strategies for success (podcast) appeared first on Scriptorium.

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When organizations replatform from one content management system to another, unchecked technical debt can weigh down the new system. In contrast, strategic replatforming can be a tool for reducing technical debt. In episode 172 of The Content Strategy Experts podcast, Sarah O’Keefe and Bill Swallow share how to set your replatforming project up for success.

Here’s the real question I think you have to ask before replatforming—is the platform actually the problem? Is it legitimately broken? As Bill said, has it evolved away from the business requirements to a point where it no longer meet your needs? Or there are some other questions to ask, such as, what are your processes around that platform? Do you have weird, annoying, and inefficient processes?

— Sarah O’Keefe

Related links:

The true cost of quick fixes (podcast, part 1), where Gretyl Kinsey discusses, “spaghetti reuse”
Technical debt in content operations
Renovation revelations: Managing technical debt (podcast)
Replatforming an early DITA implementation (case study)

LinkedIn:

Sarah O’Keefe
Bill Swallow

Transcript:

Sarah O’Keefe: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about replatforming and its relationship to technical debt. Hi, everyone. I’m Sarah O ‘Keefe. And the two of us rarely do podcasts together for reasons that will become apparent as we get into this.

Bill Swallow: And I’m Bill Swallow.

SO: What we wanted to talk about today was some more discussion of technical debt, but this time with a focus on a question of whether you can use replatforming and new software systems to get rid of technical debt. I think we start there with the understanding that no platform is actually perfect.

BS: Mm-hmm.

SO: Sorry, vendors. It’s about finding the best fit for your organization’s requirements and then those requirements change over time. Now Bill, a lot of times when we talk about replatforming, you hear people referring to the burning platform problem. So what’s that?

BS: Yeah, it’s well, it may actually be on fire, but likely not. What we’re really talking about is, you know, a platform that was chosen many years ago. Perhaps it’s approaching end-of-life. Perhaps your business needs have taken a, you know, a left or sharp left or right turn and it no longer, you know, the platform no longer supports those business needs or, you know, it really could be just a matter of cost. You know, the, platform you bought 10 years ago was, was built upon a very specific cost structure and model. And you know, the world is different now, and there are different pricing schemes and whatnot. And you may just want to, you know, replatform to recoup some of that cost.

SO: So does that, I mean, does that work? mean, if you exit platform A and move on to platform B, are you necessarily gonna save money? So no.

BS: In a perfect world, yes, but we don’t live in a perfect world. Yeah. I mean, I hate to be the bearer of bad news, you know, if you’re looking to switch from one, you know, from one platform to another to save costs, there is a cost in making that switch. And, you know, at that point, you need to look at, weighing the benefits and drawbacks, you know, is the cost to move to a new system going to be worth the cheaper solution in the long run. I mean, it’s a very, very basic model to look at. And there’s a lot of other costs and benefits and drawbacks to making a replatforming platform switch. But it’s one thing to consider there.

SO: Yeah, I think additionally, it’s really common to have people come to us and say, you know, our platform is burning. We’re unhappy with platform X and we want to replatform into platform Y. Now, what’s funnier is that usually we have some other customer that’s saying, I’m unhappy with platform Y and I need to go to platform X, right? So it’s just like a conveyor belt of sorts.

BS: You can’t please everybody.

SO: But the real question I think you have to ask before replatforming is, is the platform actually the problem here? Is it legitimately broken? And as you said, it’s evolved away from the business requirements to a point where they no longer meet your needs. And or there are some other questions to ask, like, what are your processes around that platform look like? Do you have weird, annoying, and inefficient processes?

BS: Mm-hmm.

SO: Do you have constraints that are going to force you in a direction that isn’t maybe from a technology point of view the best one? Have you made some old decisions that are now non -negotiable? So you’ll see people saying, well, we have this particular kind of construct in our content and we’re not giving it up ever.

BS: Mh-hmm.

SO: And you look at it and you think, well, it’s very unusual and is it really adding value, but it’s hard to get rid of it because it’s so established within that particular organization. So the worst scenario here is to move from A to B and repeat all the same mistakes that were made in the previous platform.

BS: Yeah, you don’t necessarily want to carry, well, you don’t want to carry that debt over, certainly. You know, so anything that you have established that worked well, but doesn’t meet your current or future needs. mean, absolutely. You do not want to move that forward. That being said, you have a wealth of content, a wealth of technology that you have built over the years and you want to make sure that you can use as much of that as possible to at least give yourself a leg up in the new system. So that you don’t have to rewrite everything from scratch, that you don’t have to completely rebuild your publishing pipelines. You might be able to move them over and change them and you might be able to move and refactor your content so that it better meets your needs. But I guess it’s a long way of saying that not only are you looking at a burning platform problem, but you’re also looking at a futureproofing opportunity. And you want to make sure that if you are going to do that lift and shift to another platform, that you, you take a few steps back and you look at what your current and future requirements are or will be and you make the necessary changes during the replatforming effort before you get into the new system and then start having to essentially deal with the same problems all over again.

SO: Yeah, I mean, to give a slightly more concrete example of what we’re talking about, relative to 10 years ago, PDF output is relatively less important. 10 years ago, we were getting a lot of, need PDF, we have to output it, and it has to meet these very, very high standards. People are still doing PDF, and clients are still doing PDF, but relatively, it is less of a like showstopper, primary requirement. It’s more, yes, we still have to do PDF, but we’re willing to negotiate on what that PDF is going to look like. Instead of saying it has to be this pristine and very complex output, they’re willing to drop that down a few notches. Conversely, the importance of HTML website alignment has gotten much, much higher. And we have a lot of requirements around Content as a Service and API connectors and those kinds of things. So if you just look at all your different publishing output connection pipelines 10 years ago PDF was really still unquestionably the most important thing and that’s not necessarily the case anymore.

BS: And on the HTML side, there’s also, could be HTML, could be JSON, but you do have a wealth of apps, whether it be a phone app or an app in your car or an app on your fridge that needs to be supported as well where your PDF certainly isn’t going to cut it. And a PDF approach to content design in general is not going to fly.

SO: So when we talk about replatforming, we tend to, in many cases, I look at this through the lens of, okay, we have, you know, DITA content in a CCMS and we’re gonna move it to another DITA CCMS. But in fact, it goes way, way beyond that, right? What are some of the, I guess, input or I’ll say legacy, but what are some of the formats that we’re seeing that are on the inbound side of a replatforming?

BS: Let’s see, on the inbound side, we certainly have maybe old models of DITA. So maybe something that was developed in DITA 1.1, 1.2, pre 1.0, something that’s heavily specialized. We have things like unstructured content, like Word files, InDesign, unstructured FrameMaker, and what have you. We’re also seeing that there’s an opportunity there as well to move a lot of developer content into something that is more centrally managed. In that case, we’ve got Markdown and other lightweight formats that need to be considered and migrated appropriately. And then, of course, all of your structured content. So we mentioned DITA. There’s DocBook out there. There are other XML formats and whatnot. And potentially, you have other things that you’re you’ve been maintaining over the years that now is a good opportunity to migrate that over into a system, centralize it, and get it aligned with all your other content.

SO: Yeah, and looking at this, I think it’s safe to say that we see people entering and exiting Markdown, like people saying we’re going to go from DITA to Markdown, but also Markdown to DITA. We’re seeing a lot of going into structured content in various flavors. Unstructured content, we largely are seeing as an exit format, right? We don’t see a lot of people saying, “Put us in Word, please.”

BS: No, no one’s going from something like DITA into Word.

SO: So they might go from DITA to Markdown, which is an interesting one. Okay, so I guess then that’s the entry format. That’s where you’re starting. What’s the outcome format? Where are people going for the most part?

BS: For the most part, there are essentially two winners. There are the XML-based formats, and then there is the Markdown-based formats. And I’m lumping DITA, DocBook, and other proprietary XML models all into XML. But generally, people are migrating more toward that direction than to Markdown. And there’s really a division there. It’s whether you want the semantics ingrained in an XML format and the ability to apply or heavily apply metadata. Or if you want something lightweight, that’s easy to author and is relatively, I don’t want to say single purpose, but it’s not as easily multi-channel as you can get with XML.

SO: Yeah, I mean the big advantage to Markdown is that it aligns you with the developer workflows, right? You get into Git, you’re aligned with all the source control and everything else that’s being done for the actual software code. And if that is a need that you have, then that is, you know, that’s the direction to go in. There are some, as Bill said, some really big scalability issues with that. And that can be a problem down the line, but Markdown generally, you know, okay, so we pick a fundamental content model of some sort, and then we have to think about software. So what does that look like? What are the buckets that we’re looking at there?

BS: For software, we’ve got a lot of things. First and foremost, there’s the platform that you’re moving to. What does that look like? What does it support? You have certainly authoring tools that are there. You also have all of your publishing pipelines. All of that’s going to require software to some degree. Some of it’s third party. Some of it’s embedded in the platform itself. And then you have all of your extended platforms that you are connecting to. Those might change. Those might stay the same. You might not change your knowledge base, for example, but you still need to publish content from the new system. The new system doesn’t quite work the way the old system did. So your connector needs to change. Things like that. I would also say that, you know, with regard to software, there’s also a hit. It’ll be a temporary blip, but it will be a costly blip in the localization space because when you are replatforming, especially if you are migrating formats to a new format, you’re going to take a hit on your 100% matches in your translation memory. So anything that you’ve translated previously, you’ll still have those translations, but how they are segmented will look very different in your localization software.

SO: Yeah, and there are some weird technical things you can do under the covers to potentially mitigate that, but it’s definitely an issue.

BS: And it’s still costly.

SO: OK, so we’ve decided that we need to replatform and we’ve done the business requirements and we picked a tool and we’re ready to go from A to B, which we are carefully not identifying because some of you are going from A to B and some of you are going from B to A. And it’s not wrong, right? There’s not a single, you know, one CCMS to rule them all.

BS: Mh-hmm.

SO: They’re all different and they all have different pros and cons. So depending on your organization and your requirements, what looks good for you could be bad for this other company. But within that context, what are some of the things to consider as you’re going through this? So you need to exit platform A and migrate to platform B.

BS: Mm-hmm. I think the number one thing you should not do is expect to be able to pick up your content from platform A and just drop it in platform B. Yeah, it’s never going to be that easy and it shouldn’t be something that you really are considering because not only are you replatforming, but you’re aligning with a new way of working with your content. So just picking it up and dropping it in a new system is not going to help you at all with in that regard. And given that you need to get the content out of the system, that’s the best time to look at your content and say, how do we clean this up? What mistakes do we try to erase with a migration project on this content before we put it in the new system?

SO: Yeah, I think the decisions that were made that tend to take on a life of their own, like this is how we do things. And much, much, much later you find out that it was done that way because of a limitation on the old software. This is like that dumb old story about, you know, cutting the end off the pot roast. And it turned out that Grandma did that because the roasting pan wasn’t big enough to hold the entire pot roast. It’s exactly that, but software, right? So bad decisions or constraints, you need to test your constraints to see whether your new CCMS, in fact, is a bigger roasting pan that does not require you to cut the end off the pot roast. What about customization?

BS: Customization is a good one. And what we’re finding is that a lot of the old systems or people who are exiting an older system for a newer system, they have a lot of heavy customization because there wasn’t a, in many regards, there wasn’t a robust content model available at the time. So they had to heavily specialize their content model and make it tailored to the type of content that they were developing. And now, you know, something that was built 10, 15 years ago that is using highly structured, specialized structured content. If you look at what’s available now, a lot of those specializations have been built into the standard in some way. So you can unwind a lot of that. It’s a great opportunity to unwind a lot of it and use the standard rather than your customization. That helps you move forward as the specifications for the content model change, you will be aligned with that change a lot better than if you had used a customization along the way. Specialization or any kind of customizations for that matter, you know, they’re expensive. They’re expensive to build. They’re expensive to maintain. They’re expensive to train people on. You know, they affect every aspect of your content production from authoring to publishing. There’s, something that needs to be specifically tailored, whether it’s training for the writers, whether it’s a training, you know, designing your publishing pipelines to understand and be able to render those customers, customized models, the translators that are involved, making sure that, you know, their systems can understand your tags if they’re custom so that they know whether, you know, that they can show and hide them from the translators and you don’t get translations back that contain translated tags, which we’ve seen. There’s a lot going on there. So the more that you can unwind, if you have heavily customized in the past, the better off you will be.

SO: Yeah, I think, mean, and here we’re talking, I think specifically about some of the DITA stuff. So if you’re in DITA 1.0 or 1.1 with your older legacy content, they added a lot of tags and did a 1.3 and they’re adding more and did a 2.0 that might address some of the things like you added a specialization because there was a gap or a deficiency in the DITA standard. So you could probably take that away and just use the standard tag that got added later. Now, I want to be clear that, I mean, we’re not anti-specialization. I think specialization is great and it’s a powerful tool to align the content that you have and your content model with your business requirements. And you have to make sure that when you specialize, all the things that Bill’s talking about, all those costs that you incur are matched by the value that you get out of having the specialization.

BS: Mm-hmm.

SO: So, you’re going to specialize because it makes your content better and you have to make sure that it makes it enough better to make it worthwhile to do all these things. Very, very broadly, metadata customization nearly always makes sense because that is a straight-up, we have these kinds of business divisions or variants that we need because of the way our products operate. And those nearly always make sense. And element specialization tends to be a bigger lift because now you’re looking at getting better semantics into your content. And you have to ask the question, do I really need custom things, or is this out of the box, did a doc book, custom XML content model good enough for my purposes? That’s kind of where you land on that. And then reuse, I did want to touch on reuse briefly because, you know, we can do a lot of things with reuse from reusing entire, you know, chunks, topics, paragraph sequences, list of steps, that kind of thing, all the way down to individual words or phrases. And the more creative you get with your reuse and the more complex it is, the more difficult it’s going to be to move it from system A to system B.

BS: Absolutely. It’ll be a lot more difficult to train people on as well. And we’ve seen it more times than not that even with the best reuse plan in mind, we still see, you know, what we call spaghetti reuse in the wild, where, know, someone has a topic or a phrase or something in one publication and they just reference it into another publication rather, you know, from one to the other. And it doesn’t necessarily, some systems will allow that. I’ll just put that out there. Other systems will absolutely say, absolutely not. You cannot do this. And you have to, you know, make sure that whatever you’re referencing exists in the same publication that, you know, that, that you’re publishing. so we’ve had to do a lot of unwinding there, you know, with regard to this spaghetti reuse and we’ve, we’ve had a podcast in the past with Gretel Kinsey on our side who I believe she talked extensively about spaghetti reuse. What it is what it isn’t and why you should avoid it. But yes as you’re replatforming if you know you have cases like this It’s best to get your arms around it before you put your content in the new system.

SO: Yeah, and we’ll see if we can dig it out and get it into the show notes. What about connectors?

BS: Connectors are interesting. And by that, we’re talking about either webhooks or API calls from one system to another to enable automation of publishing or sharing of content and what have you. For the most part, if you’re not changing one of the two systems, managing that connector can be a little bit easier, especially if it’s your target or the receiving end of the content is reaching out and looking for something else in like a shared folder using the webhook or using an FTP server, what have you. But generally, know, those webhooks can or sorry, those connectors can get a little sketchy. You know, it might be that your new platform doesn’t have canned connectors for the other systems that you have always connected to and need to connect to. So then you need to start looking at, well, do we need to build something new? we find a way of, find some kind of creative midpoint for this? They can get a little dicey. So I think it’s important to, before you re -platform, before you even choose your new content management system, that you look at where your content needs to go. And if you have support from that system to get you there.

SO: So a simple example of this is localization. If you have a component content management system of some sort, you’ve stashed all your content in, and then you have a translation management system. And the old legacy system, the platform you’re trying to get off of, has or maybe doesn’t have, but you need a connector from the component content management system over to the TMS, the translation management system, and back so that you can feed it your content and have the content returned to you.

BS: Mm-hmm.

SO: Well, if that connector exists in the legacy platform, but not in the new platform, you’re gonna have to either lean on the vendors to produce a new connector or go back to the old zip and ship model, which nobody wants, or conversely, you were doing a zip and ship in the old version, but the new version has a connector, which is gonna give you a huge amount of efficiency.

BS: Mm-hmm.

SO: The connectors tend to be expensive and also they add a lot of value, right? Because if you can automate those systems, those transfer systems, then that’s going to eliminate a lot of manual overhead, which is of course why we’re here.

BS: Mm hmm. Human error as well.

SO: So they’re worth looking at, you know, pretty carefully to see what that connector, as you said, Bill, you know, what’s out there, what already exists. Does the new platform have the connectors I need? And if not, who do I lean on to make that happen so that I don’t go backwards, essentially, in my processes? Okay, anything else or should we leave it there?

BS: I think this might be a good place to leave it. We could talk for hours on this.

SO: Be good place to leave it. Let’s not and say we did. OK, so with that, thank you for listening to the Content Strategy Experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Cutting technical debt with replatforming (podcast) appeared first on Scriptorium.

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Just like discovering faulty wiring during a home renovation, technical debt in content operations leads to unexpected complications and costs. In episode 171 of The Content Strategy Experts podcast, Sarah O’Keefe and Alan Pringle explore the concept of technical debt, strategies for navigating it, and more.

In many cases, you can get away with the easy button, the quick-and-dirty approach when you have a relatively smaller volume of content. Then as you expand, bad, bad things happen, right? It just balloons to a point where you can’t keep up.

— Sarah O’Keefe

Related links:

Technical debt in content operations
AI in the content lifecycle (white paper)
Collaborate with a content strategist to transform content operations
Accelerate global growth with a content localization strategy

LinkedIn:

Sarah O’Keefe
Alan Pringle

Transcript:

Alan Pringle: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about technical debt and content operations. What is technical debt and can you avoid it? Hey everybody, I am Alan Pringle and I’ve got Sarah O’Keefe here today.

Sarah O’Keefe: Hey everybody.

AP: And we want to talk about technical debt, especially in the context of content operations. And to start off, we should probably have you define what technical debt is, Sarah. I think this is something most people run into during their careers, but they may not have had a label to apply to what they were dealing with. So what is technical debt?

SO: We usually hear about technical debt in the context of software projects. And it is something along the lines of taking the quick-and-dirty solution, which then causes long-term effects, causes long-term costs. So Wikipedia says it’s the implied cost of future reworking because a solution prioritizes expedience over long-term design. And that’s really it. You know, I have this thing, I need to deliver it this week. I’m going to get it done as fast as possible. But then later, I’m going to run into all these problems because I took the easy road instead of the sustainable

AP: So it’s basically when the easy button bites you in the backside weeks, months, years later.

SO: Yeah, and with any luck you are aware that you’re incurring technical debt. The one that’s really painful is when you don’t realize you’re doing it.

AP: Right, or you didn’t know you weren’t part of the process when it happened. And I think this is kind of moving into where I want to go next. Let’s talk about some examples, especially in the context of content of where you can incur or stumble upon technical debt.

SO: So right now, the example that we hear actually most often is that any inconsistencies and problems in the quality of your content, the organization of your content, and the structure of your content lead to a large learning model or AI misinterpreting information and therefore your generative AI strategy fails. So essentially, because the content isn’t good enough, genAI you know, tries to see patterns where there are none and then produces some stuff that’s just complete and utter junk. Now, the interesting thing about this is that probably you are aware, at least at a high level, that your content wasn’t perfect. But the LLM highlights that it’s like, it’s like a technical debt detector. It will show that, look at you, you took a shortcut and it didn’t work or you didn’t fix this and it didn’t. And so here we are. Another good example of this is any sort of manual formatting that you’re doing. So you’re producing a bunch of content, a bunch of docs, a bunch of HTML pages, PDF, whatever. And in the context of that, you’ve got some step in there that involves cleaning it up by hand. So I get it sort of 90—95% is I just apply the template and it all just works. But then I’ve got this last step where I’m doing a couple of little finicky cleanup things and that’s okay because it’s just an hour or two and all I’m delivering is English. Okay, well along comes localization and suddenly you’re delivering in not just one language but two or three or a dozen or 27 and what looked like one hour in English is now 28 hours, you know, once time for English and 27 times again where you’re having to do this cleanup. And so all of a sudden your technical debt balloons into something that’s basically unsustainable because that choice that you made to not automate that last 5% suddenly becomes a problem.

AP: It’s a scalability issue, really, at the core.

SO: Yeah, in many cases, you can get away with the sort of, as you said, the easy button, the quick-and-dirty approach when you have a relatively smaller volume of content. And then as you expand, bad, bad things happen, right? It just balloons to a point where you can’t keep up.

AP: Yeah, and I have recently run into some technical debt, not in the content world, but in the homeownership world. And I’m sure this painful story will resonate with many people and not in a good way. But how many times have you gone to update a kitchen, update a bathroom, only to discover that there was some weird stuff done with the wiring? The plumbing is not like it really should have been. And basically you want to jump into a time machine, go back to when your house was built to have either a gently corrective conversation with the people who are building your house or just murder them outright because you are now having to pay to untangle the mess that was made 30, 40, 50 years ago. I am there right now and it is not a happy place.

SO: And it would have been, whatever it was they did was presumably cheaper than doing it right. But what they actually paid to do it the cheap way, plus what it would have cost to do it right, you know, would have been an extra 5 % or whatever at the time. But now it’s compounded because you’re having to, you know, in the case of plumbing, you know, tear out walls and go back and replace all these pipes instead. So you have to essentially start over instead of just do it. Another great example of this is accessibility. So when you start thinking about a house that has grab bars or wide doorways that wheelchairs will fit through, right? If the house was built with it, it costs a little bit more, not a lot, but a little. But when you go back to retrofit a house with that stuff, it is stupidly expensive.

AP: Exactly. And really, these things that we’re talking about in the physical world very much apply when you’re talking about software infrastructure, tool infrastructure as it can be bad.

SO: Yeah, I mean, there’s a perception of it’s just software, right? We’re not doing a physical build. We’re not using two by fours. So how bad could it be? It can be real bad. But that is the perception, right? That we’re not building a physical object so we can always go back and fix it. And I mean, you can always go back and fix everything. It’s just how much is it going to cost?

AP: Right, how much time and money and effort is it going to suck up to get you to where you need to be so you can then do the next thing that you intended to actually do in the first place? So yeah, I think this is something where this technical debt, sometimes there is no way around it. You inherit a project, you’ve got some older processes in place and you’re gonna have to deal with it. Are there some strategies that people can rely on to kind of mitigate and make it less painful?

SO: Well, first I’ll say that not all technical debt is bad or destructive in a way. And the canonical example of this is if you’re trying to figure out is this thing gonna work, I wanna do a proof of concept, I don’t wanna see if the strategy that I’m considering is even feasible. So you go in and you take a small amount of content and you build out a proof of concept or a prototype, proof of concept like, look, we were able to generate this PDF over here and this HTML over here, and we fed it into the chat bot and everything kind of worked. And you look at it and you say, okay, so that was good enough. And because it was a proof of concept, you maybe didn’t sort of harden it from a design point of view. You just did what was expedient and you got it done. That’s fine, provided that you go into this with your eyes open, knowing where you cut the corners, recognizing that later we’re going to have to do this really well and we probably can’t use the proof of concept as a starting point, or it’s good enough and we can use it as a starting point, but here’s where we cut all the corners. You have this list of like, we didn’t put in translational localization support, we didn’t put all the different output formats we’re going to need, we just put in two to prove that it would more or less work. But I think you made a really good point earlier. So often you inherit these things. So you walk into an organization and you’re brand new to that organization and you get handed a content ops environment. This is how we do things. Great. And then the next thing that happens is that genAI comes along or a new output format comes along or, we’ve decided we want to connect it to this other software system over here that we’ve never thought about before, or, hey, we’re bringing in a new enterprise resource planning system and we need to connect to it, which was never on the requirements day one. And now you realize, looking at your environment, that what’s there won’t, you can’t get from what you have to where you need to be because the requirements shifted underneath you. Or you came in and you just didn’t have a good understanding of how and when these decisions were made because it was five or 10 years ago with your predecessor kind of thing. So. So how do we deal with this? It’s I mean, it just sounds awful, but it’s like you have to manage your debt just like actual debt.

AP: All right, sure.

SO: Right, so understand what you have and haven’t done. We have not accounted for localization. We’re pretty concerned about that if and when we get to a point where we’re doing localization. Scalability. We are only going to be able to scale to maybe 10 authors and if we end up with 20, we’re going to have a big problem. So let’s just be aware of that when we get to eight or nine. But the thing is you always have technical debt that you identify that you know about this is hopefully unlike personal finance, you always have more debt than you think you have, right? Because in the content world, things change. Or in your housing example, like the building code changes. So they built the thing, umpteen years ago, and it was okay in the sense that it conformed with the requirements of the building code at the time, I assume.

AP: Of course.

SO: And now you’re going in and you’re making updates and suddenly the new building code is in play and you’re faced with the technical debt that accrued as the building code changed, but your house, your physical infrastructure did not change. And so there’s a gap between where you need to end up and where you are, part of which is just time has elapsed and things have changed.

AP: Right, and that is very true of some of the requirements you mentioned in regard to content operations. Generative AI, that’s what, the past two years, if that, that wasn’t on the horizon five years ago when some decisions were made. it absolutely is very much parallels. And when it comes to personal finance, sometimes things get so bad, you have to declare bankruptcy. And I think that can also apply to technical debt as well.

SO: Yeah, it’s a, you know, it’s an unhappy day when you look at, you know, a two-story house and you’ve been told to build a 50-story skyscraper. It just can’t be done, right? You cannot take a, you know, a sort of a stick-boiled house made of wood and put 50 stories on top of it. At least I don’t think so. We’ve now hit the edges of what I know about construction. So sorry to all the construction people, you build differently if you know that it’s going to be required to be 50 stories. Even if you only build the initial two, so either you build two knowing that eventually you’ll scrape it and start over with a new foundation or you build what amounts to a two-story skyscraper, right, that you can then expand on as you go up. So you overbuild, mean, completely overbuild for two stories knowing you’re going forward.

AP: Scalability.

SO: But yeah, we have a lot, a lot of clients who come in and say, you know, we’re in unstructured content, know, word unstructured frame maker, InDesign, basically a PDF-only workflow. And now we need a website or we need all of our content in like a content as a service API kind of scenario. And they just can’t get there from a document page-based, print-based, PDF-targeted workflow, you can’t get to, and also I wanna load it into an app in nifty ways. I mean, you could load the PDF in, but let’s not. So you end up having to say, this isn’t gonna work. This is the, I have a two-story suburban house and I’ve been told to build a 50-story skyscraper. Languages, localization are really, really common causes of this. So separately from the, “I need website, in addition to PDF,” the, “We’re only going to one or two languages, but now we’re going to 30 because we’re going into the European Union,” is a really, really common scenario where suddenly your technical debt is just daunting.

AP: So basically you’re in a burn it all down situation. Just stop and start all over again.

SO: Yeah, I mean, your requirements, it’s not that you did it wrong. It’s that your requirements changed and evolved and your current tools can’t do it. So it’s a burning platform problem, right? The platform I’m on isn’t isn’t going to work anymore. And so I have to get to that other place. It’s really unpleasant. Nobody likes landing there because now you have to make big changes. And so I think ideally, what you want to do is evolve over time, evolve slowly, keep adding, keep improving, keep refactoring as you go so that you’re not faced with this just crushing task one day. But with that said, most of the time, at least the people we hear from have gotten to the crushing horror part of the world because it’s good enough. It’s good enough. It’s not great. We have some workarounds. We do our thing until one day it’s not good enough.

AP: And it’s very easy to get used to those workarounds. That is just part of my job. I will deal with it. You kind of get a thick skin and just kind of accept that’s the way that it is. While you’re doing that, however, that technical debt in the background, it’s accruing interest, it’s creeping up on you, but you may not really be that aware of.

SO: Right. Yeah, I’ve heard this called the missing stair problem. So it’s a metaphor for the scenario where, again, in your house or in your life, there’s a staircase and there’s a stair missing and you just get used to it, right? You just climb the steps and you hop over the missing stair and you keep going. But you bring a guest to your house and they keep tripping on the stairs because they’re not used to it, at which point they say, what is the deal with the step? And you’re like, yeah, well, you just have to jump over stair three because it’s not there or it’s got a, you know, missing whatever. So missing stair is this idea that you can get, you can get used to nearly anything and the workaround just becomes, “Get used to jumping.”

AP: And it ties into again, there’s technical debt there, but you have kind of almost put a bandaid on it. You’re ignoring it. You’ve just gotten used to it. Yeah, you do. So really, there’s no way to prevent this? Is it preventable?

SO: I mean, if you staffed up your content ops organization to something like 130% of what you need for day-to-day ops and dedicated the extra 30 or maybe 10%, but you know the extra percentage to keeping things up to date and constantly cleaning up and updating and refactoring and looking at new and yeah so no there’s no way to do it and everybody is running so lean.

AP: I’m gonna translate that to a no. That is a long no. So yeah.

SO: And as a result, you make decisions and you make trade-offs and that’s just kind of how it is. I think that it’s important to understand the debt that you’re incurring, to understand what you’re getting yourself into. And, you know, I don’t want to, you know, beat this financial metaphor to death, but like, did you take out like a reasonable loan or are you with the loan sharks? Like how bad is this and how bad is the interest going to be?

AP: Yeah, so there’s a lot to ponder here and I’m sure a lot of people are listening to this and thinking, I have technical debt and I’ve never even thought about it that way. it is a topic that is unpleasant, but it is something that needs to be discussed, especially if you’re a person coming into an organization and inheriting something you may not have had any say in the decisions that were made 10 years ago, five years ago, and things have changed so much that might be why they’ve brought you in. So it is something that you’re gonna have to untangle.

SO: Yeah, sounds about right. So good luck with that. Call us if you need help, but sorry.

AP: Yeah, so if you do need help digging out of the pit of technical debt, you know where to find us. And with that, I’m going to wrap up. Thank you, Sarah. And thank you for listening to the Content Strategy Experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

SO: Thank you.

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In episode 170 of The Content Strategy Experts podcast, Bill Swallow and Christine Cuellar dive into the world of content localization strategy. Learn about the obstacles organizations face from initial planning to implementation, when and how organizations should consider localization, localization trends, and more.

Localization is generally a key business driver. Are you positioning your products, services, what have you for one market, one language, and that’s all? Are you looking at diversifying that? Are you looking to expand into foreign markets? Are you looking to hit multilingual people in the same market? All of those factors. Ideally as a company, you’re looking at this from the beginning as part of your business strategy.

— Bill Swallow

Related links:

Strategien für KI in der technischen Dokumentation, (original German version)
Strategies for AI in technical documentation (English version with synthetic audio)
Lost in translation? Create scalable content localization processes
What does it all mean?! Foundations of an enterprise content strategy
AI in the content lifecycle (white paper)

LinkedIn:

Bill Swallow
Christine Cuellar

Transcript:

Christine Cuellar: Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we are talking about content localization strategy. So maybe you’re starting to think about introducing a localization strategy. Maybe you’re hitting some pain points in your localization processes, all that good stuff we’re going to be talking about today. Hi, I’m Christine Cuellar.

Bill Swallow: And I’m Bill Swallow.

CC: Bill, thanks for being here today to talk about localization. Bill is our go-to localization expert, and localization has been coming up a lot. So I noticed for me, on the marketing side of things, there’s been a lot of, you know, SEO stuff coming up for localization. People seem to be searching about it, asking questions at a more beginning to thinking about the whole localization process level. So that’s what we wanted to talk about today. Give you the chance to have some upfront knowledge about what you could be getting into with introducing localization in your content strategy. And yeah, let’s talk about it with an expert. So thanks, Bill.

BS: Thank you.

CC: First things first, the most basic question, what is content localization strategy? So what do we mean by that?

BS: Okay, so I can kind of frame this in, I guess the same point of view as a content strategy, but basically you’re taking a look at your entire localization process from start to finish. Plus you’re looking at what are the systems that are involved? How are authors prepping the content for localization? Are they writing well upfront? What does the publishing preparation look like? How are you choosing your translators? Are you going to pure machine translation? Are you using live people to do the translation? Are you using people who are content experts? Are you using people who are market experts? So there are a lot of different factors there that all kind of get balled up into this grander strategy of how are you going to approach getting your content authored and translated appropriately in other regional markets.

CC: Yeah, okay. That makes sense. And taking a step back even further, can you walk me through the difference between localization and localization strategy?

BS: Sure. Localization itself is kind of more of an action, and whereas strategy is more planning around that action, I think that’s the best way to put it. So localization involves a bunch of different things. It involves the act of internationalization. So that’s prepping your content, your code, your product, whatever it is to be delivered for multiple regional and language markets. And then you have the translation component of localization, which is actually getting things written, spoken however, in other languages. And the strategy piece is more bridging both of those and adding additional components so that you have a solid plan for every step in that process.

CC: Okay, yeah, that makes sense. And where do we step in? We here at Scriptorium, where do we sit?

BS: Generally we at Scriptorium, we sit on the source content authoring side. And we look at the overall content strategy, and we do look at a localization strategy as a component of that. They’re not separate. They’re very intertwined and we need to take a look at really both of them. So a lot of our clients do come to us because they have localization requirements.

And we have to account for those in the content strategy that we build for them. So we’re looking not only at the source content authoring process and what needs to happen in that to get the job done, but we also have to look at where are they going with their content, how are they going to localize it, what do they need to localize, what processes do they have in place now? Are they working? Are they not looking at systems? Are they adequate? Are they not? And look at the markets. Are they already reaching those markets? Do they need to do something different? How do we need to position the content as it moves through that funnel of production so that when it comes out the other side, it is ready for those markets. So they’re kind of intertwined there.

CC: Okay. Yeah. So when are organizations typically thinking about a content localization strategy?

BS: Well, localization generally it’s a key business driver. Are you positioning your content for one market, one language, and that’s all? Or are you positioning… I shouldn’t say just product because product services, what have you. Are you looking at diversifying that? Are you looking to expand into foreign markets? Are you looking to hit multilingual people in the same market? All of those factors. So ideally as a company, you’re looking at this from the beginning as part of your business strategy. And what are you doing to… What are you producing? Who are you producing it for? How do they need to consume it? So as soon as you catch a whiff of those multilingual requirements, bells should be going off saying, “Hey, we need a plan for this.” More commonly, an organization might be producing for one market or producing for several markets. They’re kind of doing things ad hoc, producing content, then sending it out to a translator. They’re getting something back, they may be polishing it up or it’s a finished product and then they send it out. It’s a very time-consuming process. It’s a very costly process, and it’s very difficult to kind of juggle when things will be done. Because if you don’t have a set process around things and you don’t have an idea of how long things will take, what efficiencies you’re able to build up front and so forth, you’re throwing caution to the wind and just putting stuff out there and hoping that it comes back in time so that you can go to market with it. We’ve worked with clients who have said that generally it takes about nine months or so to get their localized product out the door and into the market after the English is done. And for a lot of those, we’ve brought that number into three months, one month, depending on exactly what they’re producing and how they need to produce it, so-

CC: Yeah, it’s a huge difference.

BS: Looking at that… Oh, huge difference. And looking at that time to market, that’s perhaps more valuable than the cost that you’re dumping into putting a localization strategy or a content strategy together because you’re able to sell quicker into those markets. You’re not waiting for the opportunity to start seeing revenue come back from the initiatives that you’re taking to get stuff out there.

CC: Yeah. Yeah, that makes sense. And I feel like… So correct me if I’m wrong here, but in the global world that we live in, it feels like localizing products and getting them ready for new regions is a very… I think that would be something that executives think about from the get-go like, yes, of course we want our product ready for new regions and locations. But why is the… It sounds like maybe the content piece of that is not thought about or maybe left behind until it’s an absolute emergency. Would you say that that’s… First of all, is that accurate?

BS: Sadly, I’d say yes.

CC: Okay.

BS: Content is often an afterthought in general, whether we’re talking about producing stuff just in your native language for a native market. Localization is usually even more of an afterthought because it’s like, oh, well, we wrote it in English, we’ll just have someone translate it. And by then you’re waiting until that product is done and then sending it to somebody else who’s looking at it going, “I can’t make sense of this. It’s not written well. And I’m going to take my best guess at how to translate this.” It could take months to get that back.

CC: So maybe organizations see the value in having their products and services available in other markets, but they don’t necessarily think of all of the content localization pieces that are involved in getting that out the door.

BS: No, and it’s similar for pretty much anyone trying to get anything done that you want to do something. But for example, I really want to put a new patio in the back of my house. I know exactly… I even have an idea of exactly how that should go in. I don’t have the time. I don’t have the materials needed to do it. And I’d much rely on somebody else who knows what they’re doing to put it in the correct way so it’s not graded improperly, so that there aren’t uneven portions that people will trip over and so forth. So looking at it that way, the same thing with localization. People who are running a company or starting a company, they may have an idea that yes, they need to get from point A to point B to point C to point D. They don’t know those steps along that path, and they need some help figuring out, okay, it’s not that you just write your English content, you throw it over to somebody else and they send it back. It’s a more intricate process. You have some systems in place that we’ll manage that handoff that will allow people to gate the content and proof it and make sure it’s correct before it goes anywhere. And you may have some other efficiencies built in that allow you to automatically format things when the time comes to actually produce. So there are a lot of bits and pieces that people just generally don’t think about because it’s not in their wheelhouse.

CC: Yeah, they can’t know what they don’t know.

BS: Exactly.

CC: Okay. So it sounds like most organizations realize that this is a problem once they’re actually trying to get their product out the door and into a new market, into a new region. What are some obstacles to getting a content localization strategy set up? I’m sure that one issue is probably like, oh, you’re in emergency mode and we just need to get this product out the door. That might present a challenge in and of itself.

BS: Absolutely.

CC: Yeah. Are there other obstacles as well to getting a more future-focused strategy in place?

BS: Oh, that one is a good one. That is the first hurdle to get over.

CC: Is the emergency mode.

BS: So being able to recognize or realize that you’re in emergency mode and getting out of that mindset and saying, okay, it’s not just that this will be a forever problem of just waiting and hoping for good quality coming out in the end. Once you’re able to realize that you need to break that mindset and start looking forward, then we start hitting other obstacles. One of them is going to be funding because there will be systems involved, there will be personnel required, there will be processes that need to change and so forth. And that will certainly cost a lot upfront. You’re going to basically see that return on investment in a pretty quick amount of time. We’ve seen one company make their investment back within a year, but they were producing an insane amount of languages already, and they just needed to tidy up their process. And again, by bringing that window in from nine months to about a month and a half or so, to be able to get their localized stuff out, they were able to quickly realize that return on investment there. But another one is buy-in, because you have a lot of people who are busy doing their job and you’re suddenly telling them that they need to change how they do their job, and it might be abandoning the tools that they like to use. Writing in a different way, looking at publishing in a different way and interacting with people who they normally don’t interact with on a day-to-day basis. So your source author’s interacting with a localization manager internally who needs to send stuff out to translators or your writer’s interacting with translators to explain what they had written so that the translator has a definitive idea of what it is and how to translate it for the market that they’re translating for. And then of course, you have the obstacle of governance and change management comes along with that. You need to be able to make sure that any of the changes that you introduce, that people are following the new way of doing things and aren’t falling back to old bad habits or even old good habits at the time. And you need to make sure that you have these gating processes so that once something is written in English, you have a formal review on that to make sure it’s correct, to make sure it’s written appropriately. That goes out to translation. They have their own gating process of making sure they receive all the files, that they understand the content that they have, all the supporting information that they need to help them translate and localize this information for that market. Then of course, they do their own quality checks. It comes back, you make sure that there’s a final review on the company side to make sure the translation seems good. And then you’re able to publish and deliver. So it still sounds like a lot of gating factors, but once you kind of get things going and figuring out where you can expedite and make things a lot easier, you start to bring in that entire timeline.

CC: Yeah, that makes sense. You mentioned buy-in, and so I could see how if people feel like their workload’s being increased by suddenly needing to talk to more people, coordinate between more departments or even just have more things on their radar, I could see how that could create a lot of, oh, I don’t know if I want to go in this direction. What are some ways… And that’s probably one of the… As you mentioned, that’s just one of a few buy-in challenges. What are some of the ways that you maybe win people over or show people how this can benefit their work life versus just make it harder?

BS: That’s a good question. I think that authors in general to understand where their content is going and who is consuming it. And even though it’s… We’re talking about corporate content, we’re talking about everything from website content to product manuals to troubleshooting tips and all that stuff and training materials. So it’s not really… Even though it belongs to the company, a lot of authors tend to have a kind of, I guess, personal pride built around what they write.

CC: Yeah, okay. Yeah, that makes sense.

BS: So knowing who is consuming it down the road and the reason why you have these additional checkpoints and processes in place will kind of help, I think get a lot of them around the idea of, yeah, this is a good thing and I’m looking forward to helping any way I can. Because the last thing they want is to have something written completely correctly in English and have it go out to, I guess let’s say a market in Denmark. And the content was translated incorrectly because the translator maybe didn’t understand what something meant, and they gave it a different term, which had a different meaning in that market.

CC: Yeah. And I could also see from a safety standpoint, that could be really dangerous too, if you’re not properly translating instructions for high stakes content, medical devices, stuff like that. Just like you do in English, you want that content to be accurate and understandable. Because if it’s not accurate, of course it’s wrong and people could get hurt also if people don’t understand it, even if it’s totally accurate. But it’s just hard to understand. That presents, I’m sure, a lot of dangerous situations where your people could get hurt and your company is liable. So yeah, it makes sense that you would really want to have a good process in place.

BS: Oh, absolutely. And even more along those lines, the regulations that we have to adhere to here in the US are somewhat different to… Very different to anywhere else in the world. There are different directives in place depending on where you are regionally, things that have to be included that have to be said a very specific way. So I guess the easiest way to look at it is that there are more legal ramifications in the US. So you could get sued if something is wrong, whereas opposed to if you go over to the UK, it’s generally more that there’s a directive you have to follow and you simply cannot release in that market if your, for example, machinery content does not meet that specific directive’s requirements. So there’s a slightly different approach. So it might be… There’s still a legal ramification if things go wrong, but there’s also another set of requirements that need to be met before you even start worrying about the legal stuff.

CC: And are most organizations aware of those kind of requirements when they start trying to get into a new market?

BS: Some of them might be, but again, if you’re in one particular region, chances are that’s the region you’ve grown up with and that’s the region you understand. And there’s been very little attention paid to what are their requirements in other geographic regions, other countries and so forth. So I can’t say is it common, is it not common? But in general, you know what? And when you’re looking to move to a foreign market, there’s the foreign context. You’re going to have very little insight into what that foreign market demands by its very nature. As a company moves into a new language market, new geographic market, they’re going to learn things as they go, and they’re going to bring that knowledge back and refine how things are being done currently so that it also satisfies that new requirement. And it’s going to be an iterative process until they really get their arms around it. And again, going back to a localization strategy for your content, you can kind of start putting those feelers out. Because if one market has one set of requirements, it’s like, wait a minute, now we want to go to three. What are the requirements for the other two before we even start thinking in that direction? So you’re able to start building upon that strategy that you’re developing. I mean, we’re not experts in all the requirements for every single market on the face of the earth. I can say that outright, but we can help companies start to identify what they need to start looking into before they start running.

CC: So since we mentioned one of the reasons this topic came about was seeing some SEO search trends, people trying to get more information on localization. What other trends are you seeing in localization right now?

BS: I think the big one is still going to be machine translation. It’s continually evolving and it’s getting smarter, still not, I would say, better than a human. It’s certainly quicker, but we’re getting there. And a lot of that… We talk about AI a lot. And obligatory nod to AI for this podcast, but when we talk about AI, and I think I mentioned this on another podcast already, that when you look at machine translation, that was really like AI Alpha or AI Beta where it was already using an algorithm to start putting together translations for written text. So with AI in the mix now, we’re getting a lot more, I guess, interesting results, a lot more targeted results with machine translation. I still don’t think it’s a perfect solution, and we’ll certainly need some proofreading, but it’s come a long way. And I think that that trend is certainly not going to fall off the radar anytime soon. In fact, recently Sarah O’Keefe had a podcast with Sebastian Göttel about strategies for AI and technical documentation, and they actually recorded that podcast in German. And they used AI to translate and voice augment into English. So not only were things machine translated from German into English, but the German speaking was then synthetically reproduced in English, which just is really cool.

CC: Yeah, it’s super cool to listen to, and we’ll link those in the show notes as well. There’s two versions, the German version and the English version. But yeah, you’re right. It was a super cool process, but you had mentioned earlier there was a human piece to it that was still needed because when it was originally recorded in German, then we got the German transcript, translated that into English. And when we translated that, at first it was Google Translate just to get it all done, but then Sarah needed to go and check it because she speaks both English and German. And we needed that human element to make sure that the translation was correct. Because like you were saying, you can’t just necessarily put it into a machine and cool, yay, it’s done. We need the human to make sure that it was actually translated properly and the things make sense. And we did notice once Sebastian’s synthetic audio was created in English, a lot of the prompts or the questions just were different lengths. The English version sometimes was shorter or sometimes longer of just the exact same question. It’s just the languages are different. So it’s really cool. It was a really cool experiment and does open up some interesting possibilities, would you say, for localization. And we’ve never been able to have a German and English podcast before, so that’s kind of cool.

BS: Yeah, no, it was very cool. I sat in the back of the room just watching the entire process, but it was definitely something I was quite interested in seeing. Yeah, there was a lot of editing of the English translation because again, it was pure machine translation and it needed some help. But once that was done, the synthetic audio really came right together, and I was impressed in how that happened.

CC: Yeah. And it’s so interesting because it’s definitely… It sounds like Sebastian, but then also it sounds not quite human, but it’s really close. It’s really interesting. But it did-

BS: Very uncanny valley.

CC: Yeah, it was, and I only speak English. I don’t speak German, so it made that podcast accessible to me. I was able to listen to it, and it does present some interesting opportunities, but as always with AI, the human element was definitely needed. It was very important to make sure that the humans at the other end of the screen could eventually consume it.

BS: Oh, yeah.

CC: Awesome. Well, bill, thank you so much. We covered a lot of ground today, and we really appreciate it. This was really helpful, and yeah, thanks for being on the show.

BS: Yeah, thanks.

CC: And thank you for listening to the Content Strategy Experts podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Accelerate global growth with a content localization strategy appeared first on Scriptorium.

View Details

In episode 169 of The Content Strategy Experts podcast, Sarah O’Keefe and special guest Sebastian Göttel of Quanos engage in a captivating conversation on generative AI and its impact on technical documentation. To bring these concepts to life, this English version of the podcast was created with the support of AI transcription and translation tools!

Sarah O’Keefe: So what does AI have to do with poems?

Sebastian Göttel: You often have the impression that AI creates knowledge; that is, creates information out of nothing. And the question is, is that really the case? I think it is quite normal for German scholars to not only look at the text at hand, but also to read between the lines and allow the cultural subtext to flow. From the perspective of scholars of German literature, generative AI actually only interprets or reconstructs information that already exists. Maybe it’s hidden, only implicitly hinted at. But this then becomes visible through the AI.

How this podcast was produced:

This podcast was originally recorded in German by Sarah and Sebastian, then Sarah edited the audio. Sebastian used Whisper, Open AI’s speech-to-text tool to transcribe the German recording, followed by necessary revisions. The revised German transcript was machine translated into English via Google Translate and then we cleaned up the English transcription.

Sebastian used ElevenLabs to generate a synthetic audio track from the English transcript. Sarah re-recorded her responses in English and then we combined the two recordings to produce the composite English podcast.

Related links:

Strategien für KI in der technischen Dokumentation, (original German version)
Scriptorium: AI in the content lifecycle (white paper)
Quanos
Quanos: AI-based meta data assignment in ST4
Quanos: An example of a real English talk of Sebastian

LinkedIn:

Sebastian Göttel
Sarah O’Keefe

Transcript:

Sarah O’Keefe: Today’s episode is available in English and German. Since our guest works with AI in German-speaking countries, we had the idea to create this podcast in German. The English version was then put together with AI support, particularly synthetic audio. So welcome to the Content Strategy Experts Podcast, today offered for the first time in German and English. Our topic today is Information compression instead of knowledge creation: Strategies for AI in technical documentation. In the German version, we tried to put it all together in one nice long word, but it didn’t quite work. Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about best practices for AI and tech comm with our guest Sebastian Göttel of Quanos. Hello everyone, my name is Sarah O’Keefe. I am the CEO here at Scriptorium. My guest is Sebastian Göttel. Sebastian Göttel has been working in the area of XML and editorial CCMS systems in technical documentation for over 25 years. He originally studied computer science with a focus on AI. Currently, he is Product Manager for Schema ST4 at Quanos, one of the most used editorial systems in machinery and industrial engineering in the German-speaking regions. He is also active in Tekom and, among other things, contributed to version 1 of the iiRDS standard. Sebastian lives with his wife and daughter, three cats, and two mice just outside Nuremberg. Sebastian, welcome. I look forward to our discussion. In English, we say create once, publish everywhere. This is about recording once and outputting multiple times. So, off we go. Sebastian, our topic today is, as I said, information consolidation instead of knowledge creation and how this strategy could be used for AI in technical documentation. So please, explain.

Sebastian Göttel: Yes, first of all thank you for inviting me to the podcast. It’s not that easy to impress a 14-year-old daughter. And I thought, with this podcast I have a chance. So I told her that I would be talking about AI on an American podcast soon. And the reaction was a little different than I expected. Youuuuu will you speak English? You can put quite a lot of meaning into a single “uuuu” like that. And that’s why I’m glad that I can speak German here. But, and this is now the transition to the topic, what will the AI make of the “You will speak English”? How does it want to pronounce that correctly in text-to-speech or translate it into another language? And that’s what I think our conversation will be about today. If we want to understand how AI understands us, but also how we can use it in technical documentation, then we have to talk about information compression, but also invisible information. “You will speak English?” Can the AI conceptualize that my daughter doesn’t trust me to do this or simply finds my German accent in English gross? Well, if the AI can understand that, then it is new information or actually information that was already there and that both father and daughter were actually aware of during the conversation. I find it quite exciting that German scholars have often dealt with this. Namely, what is in such a text, and what is meant in the text? What’s between the lines? And when you think back to your school days, these interpretations of poems immediately come to mind.

SO: So poems. And what does AI have to do with poems?

SG: Yes, well, you often have the impression that AI creates knowledge; that is, creates information out of nothing. And the question is, is that really the case? I think it is quite normal for German scholars to not only look at the text at hand, but also to read between the lines and allow the cultural subtext to flow. And from the perspective of scholars of German literature, generative AI actually only interprets or reconstructs information that already exists. Maybe it’s hidden, only implicitly hinted at. But this then becomes visible through the AI. Wow, I never thought I would refer to German literature scholarship in a technical podcast.

SO: Yes, and me neither. But the question remains, how does AI work and why does it work? And then why do these problems exist? What is our understanding of the situation today?

SG: Well, I think we’re still pretty impressed by generative AI, and we’re still trying to understand what we’re actually perceiving and what’s happening there. There are things that just make our jaws drop. And then there are those epic fails again, like this recent representation of World War II German soldiers by Gemini, Google’s generative AI. According to our current understanding, the soldiers were politically correct. And there were, among other things, Asian-looking women with steel helmets. I always like to compare this with the beginnings of navigation systems. There were always these anecdotes in the newspaper about someone driving into the river because their navigation system mistook the ferry line for a bridge. It was relatively easy to fix such an error in the navigation system. It was clear why the navigation system made the mistake. Unfortunately, with generative AI it’s not that easy. We don’t know, actually, we haven’t even really understood how these partially intelligent achievements come about. But the epic fails make us aware that it’s not an algorithm, but a phenomenon that seems to emerge if you pack many billions of text fragments into a matrix.

SO: And what do you mean here by “emerge”?

SG: That is a term from natural science. I once compared it to water molecules. A single water molecule isn’t particularly spectacular, but if, for example, you’re sailing in a storm on the Atlantic or hitting an iceberg, you get a different perspective. Because if you put many water molecules together, completely new behavior emerges. And it took physics and chemistry many centuries to partially unravel this. And I think we will, maybe not for quite as long, but we will have to do a lot more research into generative AI in order to understand a little more about what exactly is happening. And I think the epic fails should make us aware that we would currently do well not to blindly place our fate in the hands of a Large Language Model. I think the human-in-the-loop approach, where the AI makes a suggestion and then a human looks at it again, remains the best mode for the time being. The translation industry, which feels like it is a few years ahead of the world when it comes to generative AI or neural networks, has recognized this quite cleverly and implemented it profitably.

SO: And if translation is the model, what does this mean for generative AI and technical documentation?

SG: That’s a good question. Let’s take a step back. So at the beginning of my working life, there was a revolution in technical documentation, these were structured documents; SGML and XML. This has been known for several decades now, and it is still not used in every editorial team. And that means we now have these structured documents and the other thing, which are the nasty unstructured documents. I always thought that was a bit of a misnomer because unstructured documents are actually structured. Well, at least most of the time. There’s a macro level where I have a table of contents, a title page, and an index. There are chapters. Then there are paragraphs, lists, and tables and that goes down to the sentence level. I have lists, prompts, and so on. It’s not for nothing that some linguists call this text structure. And if I now approach XML, the beauty of XML is that I can now suddenly make this implicit structure explicit. And the computer can then calculate with our texts. Because if we’re being honest, in the end, XML is not for us, but for the machine.

SO: Is it possible then that AI can discover structures that, for us humans, have so far only been expressed through XML?

SG: Yes. Well, I recently looked into Invisible XML. There you can overlay patterns onto unstructured text and they become visible as XML. Very clever. I think generative AI is a kind of Invisible XML on steroids. The rules aren’t as strict as in Invisible XML, but genAI also understands linguistic nuances. I found it very exciting, a customer of ours fed unstructured PDF content into ChatGPT; that is unstructured content from the PDF, in order to then convert it to XML. The AI was surprisingly good at discovering the invisible structure that was hidden in the content and converted XML really well. So that was impressive. When AI now appears to create information out of nothing, I think it is more likely that it makes existing but hidden information visible.

SO: Yes, I think the problem is that this hidden structure, in some documents, it’s there, but in others, there’s what we call “crap on a page” in English. So that’s, there’s no structure. And from one document to another, there is no consistency, so they are completely different. Writer 1 and Writer 2, they write and they never talk. And so if the AI now creates an entire chapter and an outline from a few keywords, how does it work? How does that fit together?

SG: Yes, you’re right. So far we’ve been talking about we take PDF and then XML is added to it. But if I’m put on the spot, I’ll throw in a few keywords and ChatGPT suddenly writes something. But also, I think this idea also applies that this is actually hidden information. It might sound a bit daring at first, but there’s nothing new, nothing completely surprising. Now if I just ask, let’s say ChatGPT, give me an outline for documentation for a piece of machinery. And then something comes out. I think most of our listeners would say the same thing. This is nothing new. This is hidden information contained in the training data, which is easily made visible through the query. Because ultimately, generative AI creates this information from my query and this huge amount of training data. And the answer is chosen so that it fits my query and the training data well. It creates a synthetic layer over the top. And in the end, the result is not net new information, but hopefully, the necessary information delivered in a way that’s easier to process further. Either like the example with PDF, enriched with XML or I maybe now have an outline. And I imagine it’s a bit like a juicer. The juicer doesn’t invent juice, it just extracts it from the oranges.

SO: Making information easier to process sounds almost like a job description for technical writers. And what about other methods? So if we now have metadata or knowledge graphs, what does that look like?

SG: That’s right, in addition to XML, these are also really important. So metadata, knowledge graphs. I find that metadata condenses information into a few data points and the knowledge graphs then create the relationships among these data points. And this is precisely why knowledge graphs, but also metadata, make invisible information visible. Because the connections that were previously implicit can now be understood through the knowledge graphs. And that can be easily combined with generative AI. At the beginning, the knowledge graph experts were a bit nervous, as you could tell at conferences, but now they’re actually pretty happy that they’ve discovered that generative AI plus knowledge graphs is much better than generative AI without knowledge graphs. And of course, that’s great. By the way, this isn’t the only trick where we have something in the technical documentation that helps generative AI get going. If you want to make large knowledge bases searchable with Large Language Models, you can do that today with RAG, or Retrieval Augmented Generation. And this means you can combine your own documents with a pre-trained model like ChatGPT very cost-effectively. If you now combine RAG with a faceted search, as we usually have in the content delivery portals in technical documentation, then the results are much better than with the usual vector search, because in the end it is just a better full-text search. That’s another possibility where structured information that we have can help jump-start AI.

SO: Is it your opinion that structured information will not become obsolete through AI, but will actually become more important?

SG: My impression is that the belief has taken hold that structured information is better for AI. I think we’re all a bit biased, naturally. We have to believe that. These are the fruits of our labor. It’s a bit like apples. The apple from an organic farmer is obviously healthier than the conventional apple from the supermarket. I think this is scientific fact. But in the end, any apple is better than a pack of gummy bears. And that’s what can be so disruptive about AI for us. Because at the end of the day, we are providing information. And if users gets information that is sufficient, that is good enough, why should they go the extra mile to get even better information? I don’t know.

SO: Okay, so I’m really interested in this gummy bear career and I want to hear a little bit more about that. But why is your view on the tech comm team’s role so, let’s say, pessimistic?

SG: I think my focus has gotten a little wider recently. I think I’m not really just looking at technical documentation. When it comes to technical documentation, we are lost without structured data. It will not work. But if we take the bigger picture, at Quanos we not only have an CCMS, but we also create a digital twin for information. I’m in all these working groups as the guy from the tech doc area. And I always have to accept that our particularly well-structured information from tech doc, the one with extra vitamins and secondary nutrients, is actually the exception out there when we look at the data silos that we want to combine in the info twin. When I was young, I believed that we had to convince others to work the way we do in tech docs. That would have been really fantastic. But if we’re honest with ourselves, it just doesn’t work. The advantages that XML provides for technical documentation are too small in the other areas and for individuals to justify a switch. The exceptions prove the rule. As a result, tons of information is out there locked up in these unstructured formats. And it can only be made accessible with AI. That will be the key.

SO: And how do we do that? If XML isn’t the right strategy, what does that look like?

SG: Well, so let’s take an example. So many of our customers build machinery and let’s take a look at the documentation that they supply. There are several dozen PDFs for each order. And of course the editor has a checklist and knows what to look for in this pile of PDFs. The test certificate, the maintenance table, parts lists, and so on. And even though the PDFs are completely “unstructured” as compared to XML files, we humans are able to extract the necessary information. And the exciting thing about it is that anyone can actually do it. So you don’t have to be a specialist in bottling systems or industrial pumps or sorting machines. If you have an idea of what a test certificate, a maintenance table, a parts list is, then you can find it. And here’s the kicker: the AI can do that too.

SO: Ahh. And so in this case are you more concerned with metadata…or something else?

SG: No, you’re right. So this is in fact about metadata and links. I find it fascinating what this does to our language usage. Because we have gotten used to saying that we enrich the content with metadata. But in many cases we have simply made the invisible structure explicit. No information was added. Nothing has become richer, just clearer. But now imagine that your supplier didn’t provide a maintenance table. Then you need to start reading, understand the maintenance instructions, and extract the necessary information. And that’s tedious. Even here, AI can still provide support. But how well depends on the clarity of maintenance procedures. The more specific background knowledge is necessary, the more difficult it becomes for the AI to provide assistance.

SO: What does that look like? Do you have an example or use case where AI doesn’t help at all?

SG: It depends on contextual knowledge. I once received parts of a risk analysis from a customer. And her question was, “Can you use AI to create safety messages?” And I said, “Sure, look at the risk analysis and then look at what the technical writers made of it.” And they were exemplary safety messages. But there was so little content in the risk analysis that with the best intentions in the world you couldn’t do anything with artificial intelligence; that end result was only possible because the technical writers had an incredibly good understanding of the product and also had the industry standards. The information was not hidden in this input, but in the contextual knowledge. And that’s so specialized that it’s of course not available in the Large Language Model.

SO: In this use case, you don’t see any possibility for AI at all?

SG: Well, at least not for a generic Large Language Model. So something like ChatGPT or Claude, they have no chance. There is an opportunity in AI to specialize these models again. You can fine-tune this with context-specific content. But we don’t yet know at the moment whether we normally have enough content. There are some initial experiments. But let’s think back to the water molecules. We need quite a few of them to make an iceberg or even a snowman. Ultimately, you have to ask which supporting materials are needed from which point of view, and fine-tuning is really expensive. So there are costs. It takes a long time. Performance is also an issue. And how practical is this approach? Do we have training data? So, given all these aspects, it is still unclear what the gold standard is for making a generic large language model usable for content work in very specific contexts. We just don’t know today.

SO: Can you already see or predict how generative AI will change or must change technical documentation?

SG: I really think it’s more like looking into my crystal ball. So it’s not that easy to estimate which use cases are promising for the use of AI in technical documentation. As a rule, you have a task where a textual input needs to be transformed into a textual output according to a certain standard. And it used to be garbage in, garbage out. In my opinion, the Large Language Models change this equation permanently. Input that we were previously unable to process automatically due to a lack of information density, we can now enrich it with universal contextual knowledge in such a way that it becomes processable. Missing information cannot be added. We’ve discussed that now. But these unspoken assumptions, in fact, we can pack them in. And that helps us in many places in technical documentation, because one of the ways good technical documentation differs from bad documentation is that fewer assumptions are necessary in order to understand the text or if you want to process it automatically. And that’s why I find condensing information instead of creating knowledge to be a kind of Occam’s Razor. I look at the assignment. If it’s simply a matter of making hidden information visible or putting it into a different form, then this is a good candidate for generative AI. What if it’s more about refining the information by using other sources of information? Then it becomes more difficult. If I now have this information, this other information in a knowledge graph, if it is already broken down there, then I can explicitly enrich the information before handing it over to the Large Language Model. And then it works again. But if the information, for example, the inherent product knowledge, is in the editor’s head, as was the case with my client’s risk analysis, then the Large Language Model simply has no chance. It won’t generate any added value. Then you may have to rethink your approach. Can you divide the task somehow? Maybe there is a part where this knowledge is not necessary, and I have an upstream or downstream process where I can optimize something with AI. And I think that’s the mother lode of opportunities lies. This art of distinguishing what is possible from what is impossible, and this will be more of a kind of engineering art, will be the factor in the coming years that will decide whether generative AI is of use to me or not.

SO: And what do you think? Of use, or not of use?

SG: I think we’ll figure it out. But it will take much longer than we think.

SO: Yes, I think that’s true. And so thank you very much, Sebastian. These are really very interesting perspectives and I’m looking forward to our next discussion, when in two weeks or three months there will be something completely new in AI and we’ll have to talk about it again, yes, what can we do today or what new things are available? So thank you very much and see you soon!

SG: … soon somewhere on this planet.

SO: Somewhere.

SG: Thank you for the invitation. Take care, Sarah.

SO: Yes, thank you, and many thanks to those listening, especially for the first time in the German-speaking areas. Further information about how we produced this podcast is available at scriptorium.com. Thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Strategies for AI in technical documentation (podcast, English version) appeared first on Scriptorium.

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Folge 169 ist auf Englisch und Deutsch verfügbar. Da unser Gast Sebastian Göttel sich im deutschsprachigen Raum mit KI beschäftigt, kam die Idee, diesen Podcast auf Deutsch zu erstellen. Die englische Version wurde dann mit KI-Unterstützung zusammengebastelt.

Sarah O’Keefe: Was hat die generative KI mit Gedichtinterpretationen zu tun?

Sebastian Göttel: Ja, nun, also oft hat man da ja den Eindruck, dass KI das Wissen schöpft, also Informationen aus dem Nichts erschafft. Und da ist die Frage, ist das denn wirklich so? Denn für die Germanisten ist es, glaube ich, schon eher normal, nicht nur den vorliegenden Text anzuschauen, sondern auch zwischen den Zeilen zu lesen, den kulturellen Subtext einfließen zu lassen. Und aus dem Blickwinkel der Germanisten, interpretiert oder rekonstruiert generative KI eigentlich nur Informationen, die schon vorhanden ist. Möglicherweise ist die verborgen, nur implizit angedeutet. Aber die wird durch die KI dann sichtbar.

Related links:

Strategies for AI in technical documentation (Englische KI-Version)
Scriptorium: AI in the content lifecycle (white paper)
Quanos
Quanos: „Die Doku-Lounge“ (podcast)
Quanos: “ChatGPT – Evolution für die Technische Doku?“ (talk)
Quanos: „Zwischen Verstand und Verschlusssache – KI im Spannungsfeld von MI5 und ST4“ (talk)
Quanos: KI-basierte Metadatenvergabe in ST4

LinkedIn:

Sebastian Göttel
Sarah O’Keefe

Transcript:

Sarah O’Keefe: Die heutige Episode ist auf Englisch und Deutsch verfügbar. Da unser Gast sich im deutschsprachigen Raum mit KI beschäftigt, kam die Idee, diesen Podcast auf Deutsch zu erstellen. Die englische Version wurde dann mit KI-Unterstützung zusammengebastelt. Also herzlich willkommen zum Content Strategy Experts Podcast, heute zum ersten Mal auf Deutsch. Unser Thema ist heute Informationsverdichtung statt Wissensschöpfung. Strategien für KI in der technischen Dokumentation. Wir haben versucht, das alles in ein Wort zusammenzubringen, das hat aber nicht ganz geklappt. Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize and distribute content in an efficient way. In this episode, we talk about best practices for AI and TechCom with our guest Sebastian Göttel of Quanos. Hallo, ich heiße Sarah O’Keefe. Ich bin hier bei Scriptorium die Geschäftsführerin. Mein Gast ist Sebastian Göttel. Sebastian Göttel arbeitet seit über 25 Jahren im Bereich XML und Redaktionssysteme in der technischen Dokumentation. Ursprünglich hat er mal Informatik mit Schwerpunkt KI studiert. Aktuell ist er bei Quanos Product Manager für Schema ST4, einem der meistgenutzten Redaktionssysteme im Maschinen- und Anlagenbau in DACH. Er ist auch in der Tekom aktiv und hat unter anderem an der Version 1 des iiRDS-Standards mitgewirkt. Sebastian lebt mit Frau und Tochter, drei Katzen und zwei Mäusen vor den Toren von Nürnberg. Sebastian, herzlich willkommen. Ich freue mich auf diesen Austausch. Auf Englisch sagen wir ja create once, publish everywhere. Hier geht es um einmal aufnehmen und mehrfach ausgeben. Also, los geht’s. Sebastian, unser Thema ist heute, wie gesagt, die Informationsverdichtung anstatt von Wissensschöpfung. Und wie diese Strategie für KI in der technischen Dokumentation eingesetzt werden könnte. Also, bitte, erklär doch mal.

Sebastian Göttel: Ja, erstmal vielen Dank für die Einladung in den Podcast. Es ist ja gar nicht so einfach, eine 14-jährige Tochter zu beeindrucken. Und ich dachte mir, mit diesem Podcast habe ich eine Chance. Also habe ich ihr erzählt, dass ich demnächst in einem amerikanischen Podcast über KI sprechen werde. Und die Reaktion war ein bisschen anders, als ich mir das erwartet habe. Duuu wirst da Englisch sprechen? Man kann schon ziemlich viel Bedeutung in so ein einzelnes Duuu legen. Und von daher bin ich zum einen froh, dass ich hier Deutsch sprechen darf. Aber, und das ist jetzt die Überleitung zum Thema, was wird die KI aus dem “Duuu wirst da Englisch sprechen” machen? Wie will sie das beim Text-to-Speech korrekt aussprechen oder in eine andere Sprache übertragen? Und darum, glaube ich, wird es in unserem Gespräch heute gehen. Wenn wir verstehen wollen, wie KI uns versteht, aber auch wie wir sie in der technischen Dokumentation einsetzen können, dann müssen wir über Informationsverdichtung, aber auch unsichtbare Informationen sprechen. Duuu wirst da Englisch sprechen. Kann die KI rekonstruieren, dass meine Tochter mir das nicht zutraut beziehungsweise meinen deutschen Akzent im Englischen einfach grottig findet? Naja, also wenn die KI das rekonstruieren kann, ist es dann neue Information oder eigentlich eher Information, die schon da, war und die eigentlich im Gespräch sowohl Vater als auch Tochter bewusst war. Ich finde das ziemlich spannend, dass die Germanisten sich damit schon ganz häufig beschäftigt haben. Nämlich, was steht in so einem Text drin und was ist in dem Text gemeint? Was steht zwischen den Zeilen? Und wenn man so an seine Schulzeit zurückdenkt, dann fallen einem ja sofort diese Gedichtinterpretationen ein.

SO: Also Gedichte und was hat die generative KI mit Gedichtinterpretationen zu tun?

SG: Ja, nun, also oft hat man da ja den Eindruck, dass KI das Wissen schöpft, also Informationen aus dem Nichts erschafft. Und da ist die Frage, ist das denn wirklich so?

Denn für die Germanisten ist es, glaube ich, schon eher normal, nicht nur den vorliegenden Text anzuschauen, sondern auch zwischen den Zeilen zu lesen, den kulturellen Subtext einfließen zu lassen. Und aus dem Blickwinkel der Germanisten, interpretiert oder rekonstruiert generative KI eigentlich nur Informationen, die schon vorhanden ist. Möglicherweise ist die verborgen, nur implizit angedeutet. Aber die wird durch die KI dann sichtbar. Ui, hätte nie gedacht, dass ich mal in einem technischen Podcast mich auf Germanisten berufe.

SO: Ja, und ich auch nicht. Da bleibt aber doch die Frage, wie funktioniert das? Also wie funktioniert die KI und warum funktioniert das? Und wieso gibt es dann diese Probleme? Was ist denn heute unser Verständnis von der Lage?

SG: Also ich glaube, wir sind immer noch ziemlich beeindruckt von der generativen KI und wir versuchen noch zu begreifen, was wir da überhaupt wahrnehmen, was da passiert. Da gibt es Dinge, die lassen uns einfach den Kiefer runterklappen. Und dann gibt es wieder diese Epic Fails, wie vor kurzem diese Darstellung von Wehrmachtsoldaten von Gemini, der generativen KI von Google. Die Soldaten waren nämlich nach unserer heutigen Vorstellung politisch korrekt. Und da gab es dann unter anderem asiatisch aussehende Frauen mit Stahlhelm. Ich vergleiche das immer so ganz gern mit den Anfängen der Navigationssysteme. Da gab es ja auch immer diese Anekdoten in der Zeitung, dass wieder jemand in den Fluss gefahren ist, weil sein Navi die Fährlinie für eine Brücke gehalten hat. So einen Fehler konnte man im Navigationssystem relativ einfach fixen. Da war klar, warum das Navi den Fehler gemacht hat. Bei der generativen KI ist das leider nicht ganz so einfach. Wir wissen nicht, eigentlich, wir haben es noch nicht mal wirklich verstanden, wie diese teilweise intelligenten Leistungen zustande kommen.Die Epic Fails, die machen uns aber bewusst, dass es sich nicht um einen Algorithmus handelt, sondern um ein Phänomen, das scheinbar emergiert, wenn man viele Milliarden Texte in eine Matrix packt.

SO: Und was meinst du da mit emergiert? Was ist das denn?

SG: Das ist ein Begriff aus der Naturwissenschaft. Ich habe das mal mit Wassermolekülen verglichen. Ein einzelnes Wassermolekül ist nicht sonderlich spektakulär, aber wenn du zum Beispiel im Segelboot in einem Sturm auf dem Atlantik unterwegs bist oder auf einen Eisberg aufläufst, dann kriegst du eine andere Perspektive. Denn viele Wassermoleküle zusammengenommen zeigen ganz neues Verhalten. Und das nennt man Emersion. Und Physik und Chemie haben viele Jahrhunderte gebraucht, um das halbwegs zu enträtseln. Und ich denke, wir werden, vielleicht nicht ganz so lange, aber wir werden noch ein gutes Stück weiterforschen müssen bei der generativen KI, um auch da ein bisschen mehr zu verstehen, was da jetzt genau passiert. Und ich finde, die Epic Fails, die sollten uns bewusst machen, dass wir aktuell gut daran tun, unser Schicksal nicht blind in die Hände eines Large Language Models zu legen. Ich finde, der Ansatz Human in the Loop, wo die KI einen Vorschlag macht und dann ein Mensch nochmal drüber schaut, das bleibt bis auf weiteres der beste Modus. Und die Übersetzerbranche, die gefühlt der ganzen Welt ein paar Jahre voraus ist, wenn es um generative KI geht oder um neuronale Netze, die hat das ziemlich klug erkannt und gewinnbringend umgesetzt.

SO: Und wenn also jetzt die Übersetzung das Muster ist, was heißt das dann für generative KI und die technische Doku?

SG: Das ist eine gute Frage. Lass uns mal einen Schritt zurück machen. Also am Anfang meines Arbeitslebens, da war die Revolution in der technischen Dokumentation, das waren diese strukturierten Dokumente. SGML und XML. Und das kennt man jetzt also mittlerweile schon seit mehreren Jahrzehnten und es ist ja immer noch nicht in jeder Redaktion gebräuchlich. Und das heißt, wir haben jetzt diese strukturierten Dokumente und das andere, das sind die bösen unstrukturierten Dokumente. Und ich fand das schon immer so ein kleines bisschen einen Etikettenschwindel, denn unstrukturierte Dokumente sind ja in Wirklichkeit auch strukturiert. Also meistens zumindest. Da gibt es so eine Makro-Ebene, da habe ich ein Inhaltsverzeichnis, ein Titelblatt, ein Stichwortverzeichnis. Es gibt Kapitel. Dann gibt es Absätze, Listen und Tabellen und das geht dann runter bis auf die Satzebene. Da habe ich Aufzählungen, Aufforderungen und so weiter. Und nicht umsonst nennen das manche Linguisten ja Textstruktur. Und wenn ich jetzt mit XML rangehe, das Schöne daran an XML ist, dass ich diese implizite Struktur nun plötzlich explizit mache. Und damit kann dann der Computer mit unseren Texten rechnen. Denn wenn man ehrlich ist, am Ende ist XML nicht für uns, sondern für die Maschine.

SO: Kann es dann sein, dass die KI Strukturen entdecken kann, die für uns Menschen bis jetzt zwangsweise nur durch XML ausgedrückt wurden?

SG: Ja. Also ich habe mich da mal vor kurzem mit Invisible XML beschäftigt und da kann man über unstrukturierten Text Muster legen und die werden dann als XML sichtbar gemacht. Ganz clever. Und ich finde generative KI ist so eine Art Hochleistungs-Invisible XML. Also weil es zwar nicht so ganz strikt wie Invisible XML Regeln enthält, aber dafür auch sprachliche Nuancen versteht. Und ich fand es ganz spannend, ein Kunde von uns, der hat unstrukturierte PDF-Inhalte in Chat-GPT gefüttert, also unstrukturierte Inhalte aus dem PDF, um sie nach XML dann zu konvertieren. Und die KI hat erstaunlich gut die unsichtbare Struktur entdeckt, die in den Texten verborgen war und echt prima XML konvertiert. Also das war beeindruckend. Also wenn KI jetzt scheinbar Informationen aus dem Nichts schafft, dann ist es eben eher so, dass es existierende, aber verborgene Informationen sichtbar macht.

SO: Ja, ich glaube das Problem ist ja so, dass diese verborgene Struktur, also in manchen Dokumenten ist das da, aber in anderen da ist das, was wir auf Englisch, bei uns heißt das Crap on a Page. Das ist also, da gibt es keine Struktur. Und von einem Dokument zum anderen, da gibt es keine, also keine, die sind ganz anders. Also Redakteur 1 und Redakteur 2, die schreiben und die unterhalten sich niemals. Und also wenn die KI jetzt aus ein paar Stichworten ein ganzes Kapitel und eine Gliederung erstellt, wie geht das? Wie passt das zusammen?

SG: Ja, du hast recht. Jetzt haben wir die ganze Zeit drüber geredet: Wir nehmen PDF und dann wird da XML noch dazu gepackt. Aber wenn ich jetzt hier an der Stelle bin und sage, ich haue mal ein paar Stichworte rein und ChatGPT schreibt dann plötzlich etwas. Aber auch, ich finde auch da gilt dieser Gedanke, dass das eigentlich verborgene Information ist. Klingt vielleicht zuerst mal ein bisschen gewagt, aber da entsteht nichts Neues, nichts völlig Überraschendes. Wenn ich jetzt, sagen wir mal ChatGPT, einfach frage, gib mir mal eine Gliederung für eine Maschinen-Dokumentation. Und dann kommt da was raus. Ich denke, das würden die meisten von unseren Zuhörern genauso hinschreiben. Das ist nichts Neues. Das ist versteckte Information, die in den Trainingsdaten steckt, die durch die Anfrage einfach sichtbar gemacht werden. Denn letztendlich erstellt die generative KI diese Information aus meiner Anfrage und dieser riesigen Menge an Trainingsdaten. Und die Antwort, die ist so gewählt, dass sie gut zu meiner Anfrage und den Trainingsdaten passt. Die, ja, legt sich so ein bisschen wie so ein Layer da drüber, sodass das einfach gut das simuliert. Und am Ende habe ich damit dann keine neue Information, sondern hoffentlich die benötigte Information in einer besser verarbeitbaren Form. Entweder wie vorhin beim Beispiel mit dem PDF, mit XML angereichert oder ich habe jetzt eine Gliederung. Und ein bisschen stelle ich mir das vor wie so bei einer Saftpresse. Ja, die erfindet den Saft ja auch nicht, sondern die holt das aus den Orangen einfach raus.

SO: Informationen besser verarbeitbar zu machen, also das klingt doch fast schon wie eine Tätigkeitsbeschreibung für technische Redakteure. Und was ist mit anderen Methoden? Also wenn wir jetzt Metadaten oder Knowledge Graphs haben, wie sieht das denn da aus?

SG: Stimmt, das ist neben XML natürlich auch total wichtig. Also Metadaten, Knowledge Graphen. Ich finde Metadaten, die verdichten Informationen auf wenige Datenpunkte und die Knowledge Graphen, die machen dann die Beziehungen zwischen diesen Datenpunkten. Und gerade dadurch machen Knowledge Graphen, aber auch Metadaten ja unsichtbare Informationen sichtbar. Denn die Zusammenhänge, die vorher implizit wahr waren, die können jetzt durch die Knowledge Graphen nachvollzogen werden. Und das lässt sich prima mit generativer KI kombinieren. Am Anfang waren die Knowledge Graph Experten ein bisschen nervös, das konnte man merken auf Konferenzen, aber jetzt sind sie eigentlich ziemlich froh, dass sie festgestellt haben, generative KI plus Knowledge Graphen, das ist viel besser als generative KI ohne Knowledge Graphen. Und das ist natürlich prima. Das ist übrigens nicht der einzige Trick, wo wir in der technischen Dokumentation etwas haben, was der generativen KI auf die Sprünge hilft. Wenn man mit Large Language Models große Wissensbasen durchsuchbar machen will, dann macht man das ja heutzutage mit RAG, also Retrieval Augmented Generation. Und damit kann man sehr kostengünstig eigene Dokumente mit einem vortrainierten Modell wie ChatGPT kombinieren. Und kombiniert man jetzt RAG mit einer Facettensuche, so wie wir das in den Content Delivery Portalen in der TechDoc normalerweise haben, dann sind die Ergebnisse viel besser als mit der üblichen Vektorsuche, denn die ist am Ende ja nur eine bessere Volltextsuche. Und das ist dann auch wieder eine Möglichkeit, wo strukturierte Informationen, die wir eben haben, der KI auf die Sprünge hilft.

SO: Also bist du dann auch der Meinung, dass die strukturierte Information, durch KI nicht obsolet wird, sondern sogar noch wichtiger wird?

SG: Ich habe schon den Eindruck, dass sich so ein bisschen der Glaube durchgesetzt hat, strukturierte Informationen sind besser für KI. Ein bisschen sind wir dann natürlich, glaube ich, alle biased. Also wir müssen das glauben. Das sind ja die Früchte unserer Arbeit. Ein bisschen ist es auch so, also genauso wie der Apfel vom Biobauern natürlich gesünder ist, als der konventionelle Apfel aus dem Supermarkt. Ich denke, das ist wissenschaftlich klar erwiesen. Aber am Ende ist ein Apfel immer besser als eine Packung Gummibärchen. Und das ist es, was bei KI so disruptiv sein kann für uns. Denn am Ende machen wir Informationsvermittlung. Und wenn der Anwender Informationen bekommt, die ausreicht, die gut genug ist, warum sollte er dann noch die Extra-Meile gehen, um noch bessere Informationen zu bekommen? Ich weiß nicht.

SO: Ja, also ich interessiere mich wirklich an dieser, also Gummibärchen-Karriere. Da will ich mal ein bisschen mehr hören. Aber warum ist das denn so, sagen wir mal, pessimistisch für die Redaktion von dir?

SG: Ich glaube, mein Bild ist ein bisschen größer geworden in der letzten Zeit. Ich glaube, da geht es mir gar nicht so sehr um die technische Dokumentation. In der technischen Dokumentation sind wir ohne strukturierte Daten aufgeschmissen. Das wird nicht funktionieren.

Aber wenn wir das größere Bild machen, bei Quanos haben wir ja nicht nur ein Redaktionssystem, sondern wir machen auch so einen digitalen Informationszwilling. Und dann sitze ich immer in diesen Arbeitskreisen drin als der Typ aus dem Tech-Doc-Bereich. Und da muss ich immer hinnehmen, dass unsere besonders gut strukturierten Informationen aus der Tech-Doc, also die mit den besonders viel Vitaminen und sekundären Pflanzenstoffen, das ist halt doch in der Realität da draußen eher die Ausnahme, wenn wir uns die Datensilos angucken, die wir im Info-Twin zusammenfahren wollen. Und als ich jung war, da habe ich noch dran geglaubt, dass wir die anderen davon überzeugen müssen, auch so zu arbeiten wie in der technischen Dokumentation. Das wäre doch echt prima gewesen. Aber wenn wir ehrlich sind, es klappt halt nicht. Die Vorteile, die wir in der technischen Dokumentation dank XML haben, die sind in den anderen Bereichen für die einzelnen Kollegen zu klein, als dass sie umsteigen wollen. Also Ausnahmen bestätigen die Regel. Das bedeutet, da draußen gibt es Tonnen von Informationen, die in diesen unstrukturierten Formaten eingesperrt sind. Und die können nur mit KI zugänglich gemacht werden. Das wird der Schlüssel sein.

SO: Und wie machen wir das? Also wenn jetzt XML da nicht der richtige Pfad ist, dann wie sieht das aus?

SG: Naja, also nehmen wir ein Beispiel. Also viele unserer Kunden sind ja Maschinenanlagenbauer und gucken wir mal auf die Zulieferdokumentation. Da kommen für einen Auftrag, mehrere Dutzende PDF. Und natürlich hat die Redakteurin dann so eine Checkliste und sie weiß, was sie in diesem Haufen PDF suchen muss. Das Prüfzertifikat, die Wartungstabelle, Ersatzteillisten und so weiter. Und obwohl die PDFs ja komplett unstrukturiert sind, also dieses unstrukturiert, wie wir halt als XML-Leute das dann so nennen, sind wir Menschen in der Lage, diese Informationen zu extrahieren. Und das Spannende daran, eigentlich kann das jeder. Also dafür muss man kein Spezialist für Abfüllanlagen oder Industriepumpen oder Sortiermaschinen sein. Wenn du eine Vorstellung davon hast, was ein Prüfzertifikat, eine Wartungstabelle, eine Ersatzteilliste ist, dann findest du die. Und jetzt kommt’s. Dann kann die KI das nämlich auch.

SO: Aha. Und also geht es dir in diesem Fall eher um Metadaten oder um was anderes?

SG: Nee, du hast schon recht. Also es geht hier in der Tat um Metadaten und Verlinkungen.

Ich finde das spannend, was das mit unserem Sprachgebrauch macht. Denn wir haben uns ja so angewöhnt zu sagen, wir reichern die Inhalte mit Metadaten an. Aber in vielen Fällen haben wir einfach nur die unsichtbare Struktur explizit gemacht. Da ist gar keine Information dazugekommen. Da ist nichts reicher geworden, sondern einfach nur klarer. Aber jetzt stell dir mal vor, dein Zulieferer hat keine Wartungstabelle geliefert. Dann musst du anfangen, die Wartungsarbeiten zu lesen, zu verstehen und die notwendigen Informationen zu extrahieren. Und das ist ziemlich mühsam. Selbst hier kann dann die KI noch unterstützen. Aber wie gut, hängt dann schon davon ab, wie verständlich die Wartungstätigkeiten beschrieben sind. Und umso mehr spezifisches Hintergrundwissen notwendig ist, umso schwieriger wird es, für die KI hilfreich zuzuarbeiten.

SO: Und wie sieht das denn aus? Also hast du ein Beispiel oder ein Use Case, wo die KI gar nicht weiterhilft?

SG: Wie schon gesagt, das hängt natürlich dann vom Kontextwissen ab. Ich hatte von einer Kundin mal Teile der Risikoanalyse bekommen. Und da ging es darum, kann man daraus mit KI Sicherheitshinweise erstellen? Und ich habe dann gesagt, ja klar, guck mal die Risikoanalyse an und dann guck mal an, was die Redakteure daraus gemacht haben. Und es waren mustergültige Sicherheitshinweise. Aber es stand so wenig in der Risikoanalyse drin, dass beim besten Willen konnte man da nichts mit Künstlicher Intelligenz machen, sondern das ging nur, weil die Redakteure ein wahnsinnig gutes Produktverständnis hatten und auch noch die Normen im Hinterkopf hatten, die dafür notwendig waren. Da war eben die Information nicht in diesem Input versteckt, sondern im Kontextwissen. Und das ist so speziell, das ist natürlich auch nicht im Large Language Model vorhanden.

SO: In so einer Anwendung oder in so einem Anwendungsfall siehst du dann überhaupt keine Möglichkeit für KI?

SG: Also zumindest nicht für ein generisches Large Language Model. Also sowas wie ChatGPT oder Claude, die sind da chancenlos. Es gibt die Möglichkeit in der KI, diese Modelle nochmal zu spezialisieren. Man kann die ja mit kontextspezifischen Texten feintunen. Aber ob wir da im Normalfall ausreichend Texte haben, weiß man im Moment noch nicht so. Da gibt es die ersten Experimente. Aber denken wir nochmal zurück an die Wassermoleküle. Für einen Eisberg oder schon für einen Schneemann brauchen wir ziemlich viele davon. Also heute ist letztendlich so, welche Hilfsmittel unter den Gesichtspunkten dann auch, also Feintuning ist echt teuer. Also Kosten. Dauert lange. Also auch Performance ist ein Thema. Und wie praktikabel ist das? Haben wir Trainingsdaten? Also unter diesen ganzen Aspekten, was da jetzt wirklich der goldene Weg ist, um so ein generisches Large Language Model für die Textarbeit für sehr spezifische Kontexte brauchbar zu machen, ist einfach noch unklar. Weiß man heute einfach nicht.

SO: Kannst du denn heute schon sehen oder voraussehen, wie die generative KI die technische Dokumentation verändern wird oder muss?

SG: Ich finde das noch echt mehr so einen Blick in die Kristallkugel. Also das ist noch gar nicht so einfach einzuschätzen, welche Use Cases jetzt für den Einsatz von KI in der technischen Dokumentation vielversprechend sind. In der Regel hast du eine Aufgabenstellung, wo ein textueller Input nach einer bestimmten Maßgabe in einen textuellen Output transformiert werden soll. Und früher galt da Garbage in, Garbage out. Die Large Language Models nach meiner Meinung verändern diese Gleichung nachhaltig. Input, den wir mangels Informationsdichte früher nicht automatisch verarbeiten konnten, den können wir jetzt durch universelles Kontextwissen anreichern, so anreichern, dass er verarbeitbar wird. Fehlende Informationen können nicht ergänzt werden. Das haben wir ja jetzt besprochen. Aber diese unausgesprochenen Annahmen, in der Tat, die können wir mit reinpacken. 6Und das hilft uns in der technischen Dokumentation an vielen Stellen, weil sich eine gute technische Dokumentation ja unter anderem dadurch von einer schlechten unterscheidet, dass weniger Annahmen notwendig sind, um den Text zu verstehen, beziehungsweise auch, wenn man ihn maschinell verarbeiten will. Und deshalb finde ich Informationsverdichtung statt Wissenschöpfung für mich so eine Art Ockhamsches Messer. Ich betrachte mir die Ausgabenstellung. Geht es jetzt einfach nur darum, verborgene Informationen sichtbar zu machen oder sie in eine andere Form zu bringen, dann ist das einfach ein guter Kandidat für den Einsatz von generativer KI. Oder geht es jetzt eher darum, durch den Rückgriff auf andere Informationsquellen die Informationen zu veredeln? Dann wird es schon schwieriger. Wenn ich jetzt diese Informationen, diese anderen Informationen in einem Knowledge Graphen habe, wenn die dort schon aufgeschlüsselt sind, dann kann ich ja die Informationen explizit vor der Übergabe an das Large Language Model anreichern. Und dann geht das auch wieder. Wenn aber die Informationen, zum Beispiel das inhärente Produktwissen im Kopf des Redakteurs ist, wie bei der Risikoanalyse meiner Kundin, dann hat das Large Language Model einfach keine Chance. Das wird da keinen Mehrwert generieren. Dann muss man eventuell nochmal überlegen, kann man die Aufgabenstellung noch irgendwie aufteilen? Vielleicht gibt es einen Teil, wo dieses Wissen nicht notwendig ist und ich habe einen vor- oder nachgelagerten Prozessschritt, wo ich mit der KI was optimieren kann. Und ich finde, da wird in der Zukunft die Musik spielen. Diese Kunst, das Machbare vom Unmachbaren zu unterscheiden, und das wird eher so eine Art Ingenieurskunst sein, das wird in den kommenden Jahren der Faktor sein, der entscheidet, ob die generative KI mir einen Nutzen stiftet oder nicht.

SO: Und was glaubst du, mehr oder nicht?

SG: Ich glaube, wir werden das raustüfteln. Aber es wird viel länger dauern, als wir das glauben.

SO: Ja, also ich glaube, das stimmt.

Und also vielen Dank, Sebastian. Das sind wirklich ganz interessante Perspektiven und ich freue mich auf unsere nächste Diskussion, wenn in so zwei Wochen oder drei Monaten was ganz Neues da in der KI ist und wir uns noch mal darüber unterhalten müssen, ja, was können wir denn heute machen oder jetzt machen? Also vielen Dank und wir sehen uns …

SG: … demnächst irgendwo auf diesem Planeten.

SO: Irgendwo.

SG: Vielen Dank für die Einladung. Mach’s gut, Sarah.

SO: Ja, und vielen Dank an die Zuhörenden, besonders zum ersten Mal im deutschen Raum. Weitere Informationen sind bei scriptorium.com verfügbar. Thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links. Thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

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In episode 168 of The Content Strategy Experts podcast, Sarah O’Keefe and special guest Leslie Farinella, Chief Strategy Officer at Xyleme, discuss the challenges facing content operations for learning content, insights for navigating information silos, and recommendations for successful enterprise-wide collaboration.

Why do we still have these silos of content? Back to what you said, Sarah, if we’re thinking about the learner experience, the learner doesn’t distinguish between classroom, e-learning, looking something up, or going to technical documentation. They just know, “I gotta get my job done. I need to perform. I need to know what I’m doing.”

— Leslie Farinella

Related links:

Xyleme LCMS
MadCap CCMS-LCMS Guide (white paper)
So much waste, so little strategy: The reality of enterprise customer content
Rise of the learning content ecosystem with Phylise Banner (podcast)
Wrangling the Meg of learning content

LinkedIn:

Leslie Farinella
Sarah O’Keefe

Transcript:

Sarah O’Keefe: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about the challenges that organizations face with content operations for learning. Hey, everyone. I’m Sarah O ‘Keefe, and today I’m delighted to welcome Leslie Farinella of Xyleme to the podcast. Xyleme, as you may know, has recently been acquired by MadCap Software, which also owns Flare and IXIASOFT. So Leslie, welcome. Tell us about yourself and your role at Xyleme/MadCap.

Leslie Farinella: Hi, Sarah. I’m super excited to be here today. So I’ve been at Xyleme for over the last eight years. Actually, prior to that, I was in the learning content space, but on the business side, helping organizations to drive performance within their workforce. And I realized that, you know what, if we wanted to scale, we were going to have to bring technology to help solve this problem. So I got really excited. So I jumped over to the product side. And since I’ve been at Xyleme, I’ve pretty much covered almost all of the roles, ending up with my last role being the chief strategy officer.

SO: And so here we are. And I think you’re probably the perfect person to talk to about this topic where we’re getting a lot of interest all of a sudden. Well, from my point of view, maybe not from your point of view, but from my point of view, we’re getting a lot of interest in content operations for learning content.

LF: Yeah.

SO: So people are asking questions like, if I have overlapping content between my tech comm content and my learning content, why, you know, why can’t I combine those in some efficient way as opposed to what I’m doing now, which is this terrible copy and paste or worse rewrite without, you know, people ever talking to each other. But also we’re hearing from learning organizations that don’t actually have what I would consider to be tech comm content who need a more mature content workflow. So they’re asking questions like, “How can I develop learning better, faster, cheaper?” So what does that look like on your side of the fence?

LF: We absolutely hear the exact same thing, and I think it’s only gonna get worse because if we think about the root cause and think about what’s really driving this conversation and what’s making this conversation escalate is the speed of change and the need to drive agility within the organizations so organizations have to adapt faster than they have before which means people have to learn new skills new mindsets and new behaviors faster than before and which means inevitably they have to learn on the go, which means that performance support and tech comms is part of that learning. And as you and I know, cause I know you and I’ve had past conversations breaking down that silo between tech comm and learning is gonna be essential to driving that agility that organizations need to change. And that’s why they’re feeling the pressure.

SO: And so what does that look like? You know, Xyleme in particular is an enterprise learning content management system, which perhaps I should have said in the intro. What does it look like when people start considering something, you know, a solution like that? What’s the executive-level argument for that?

LF: Speed, agility, cohesiveness, learner experience. And I think that what we all have to remember is when you’re buying something like a CCMS or an LCMS, you know, component content management system or learning content management system, they’re kind of flip sides of the same coin, but they also need to work together. And I think that is the change in mindset we need in the industry is that if you think about learning, you have formal learning. I take a course. Usually, I’m a novice. I need some scaffolding. But the majority of the learning, once I kind of get my initial scaffolding happens by experience. It happens by solving problems. And inevitably that means looking stuff up. So it means going back to the documentation because no one’s going to go to the LMS to go flip to halfway through the e-learning course to look something up that’s just very painful. So what I hear from the top executive level is how do we make that whole system work together? How do we consider it from a job performance perspective and moving people from a novice to proficiency across that entire spectrum, which is learning and tech comm. And that’s where this idea that we have these separate systems and these separate processes really start to get in our way. And I think that’s where the opportunity is, is to see how do we break down that silo and how do we think about how these technologies can work better together or maybe even collapse into a single tech stack.

SO: Yeah, and I think that, you know, a big part of this is if you if you go back 20, 25, 30 years, we had classroom training, basically, and we had paper like books or maybe a cheat sheet or a job aid, but, you know, some sort of a printout. And so the distinction between I’m going to go to a class and learn the things and they’re going to give me a like a student guide or a textbook or, you know, but something, some sort of supporting material. And then there’s my reference library of books. And today, we still have that. I mean, we still have that distinction between class, e-learning, blended learning, and online, and all the rest of it. But there’s that bucket. And then there’s that bucket of, OK, there’s this other book adjacent or book-derived stuff. However, today, it’s all sitting on the same website. And so now as an end user, as a software user or learner, I show up on your website, your product website, and like, hey, I’m blocked on this task that I need to do. I’ve got a job I need to get done. I don’t know how to do it. And I just frankly don’t care. I just want you to give me the answer. Now, I don’t care where it lives. Not my problem. But give me the answer and give it to me better, faster, cheaper. And then, you know, infamously, we always say, “Don’t ship your org chart,” except we always do. So what does it look like to start to foster these connections and improve the integration or the interaction or the, I’m struggling for words, which is probably a symptom of this problem. What does it look like to start fostering those connections to improve the end-user experience?

LF: I think what you just said, end user experience. You know, we have to map that user experience. And I think that’s one thing that the learning side has done well is they’ve invested in the LMS, the learning experience platforms. Everybody still complains about them, but at least they were, you know, investing and trying and those experiences are getting better and better because there’s more competition in the market. People are coming up with other tools. They’re bringing, you know, more algorithms into play and then, you know, AI will play into that as well. But what they haven’t done well is content management and structured authoring. So Xyleme is an LCMS. So actually, you know, there obviously are people on the learning space that have bought into, we need to bring structured authoring into learning. But it’s not the majority. A lot of organizations still haven’t done that. And I think that once you start to bring what tech docs already knew is, you know, you’ve got to standardize to personalize. You’ve got to bring in, you know, you got to think modular. You’ve got to be able to standardize against your terminology. And then you can start to scale. That’s something that the learning side, you know, needs to learn and that’s something that the LCMS, which is the counterpart to component content management brings in and we’ve tailored it to the audience of instructional designers and learners to help with that transition. But the base ideas underneath the technology are the same. One of the interesting things in the acquisition with MadCap and the IXIA team when we started comparing products, we’re like, we do that, we do that too. yeah, we’ve always wanted to do that. You guys already have it, but we all, we realized very quickly we were solving the same problem and getting to the same result. We made them make different design decisions along the way, but we were solving the same problem and the fundamental premise underneath both technologies were the same, which then starts to beg the question, why aren’t they combined? Like, why are we still have these silos of content? If we’re thinking about back to what you said, Sarah, the learner experience, the learner doesn’t distinguish between classroom e-learning, looking something up, going to technical documentation. They just know, I gotta get my job done. I need to perform. I need to know what I’m doing. And I wanna, you know, ready myself for my next role in promotion within the organization. And they have expectations on their performance. And so how do we look at that and understand it needs to be more cohesive and how can we as both the tech docs and the learning industry break down that silo with the content but also the experience itself to make that more cohesive.

SO: Yeah, I think one thing that’s sometimes overlooked in this is that the default emotional state of a person who is looking for information is something like frustration and anger, right? Because they’re not reading for fun. They’re not going to class for fun. I mean, probably. They are doing it because this class or this learning piece or this piece of information that I don’t have, is standing between me and getting the job done. I need to generate a pivot table and I don’t know how, so show me how to do it. I need to do a thing and until I do the thing, I can’t progress in my tasks of the day and so I’m annoyed. And we’ve set aside knowledge base for the purpose of this conversation, but knowledge base usually is even worse because usually that’s something like my system crashed, why? So they’re not just annoyed, they’re like incandescently angry because something is not working. Okay, so, and I think you said something really interesting in there about how the learning experience, you know, the downstream user experience for learning, there’s been a lot of work put into that and comparatively less on the tech comm side. I’m not saying all tech comm is bad or anything like that, but when you look at some of the work that’s been done in producing really sophisticated e-learning and really interesting learning experiences on a platform of some sort, and then conversely on the back end, tech comm has done a huge amount of work around reuse and efficiency and automated formatting and automated delivery and multi-channel and all these things, which I think there’s some advantages there and there’s some things there that I think the learning world can can probably leverage and you know vice versa so, you know, while you and I are ruling the world and we’re fixing all of this, you know, we can’t fix the integration next week and I mean I’ve been complaining about that for a while, but you know that is a legitimately difficult hard problem. But what are some of the steps that we can take as content creators, whether learning or tech comm, to start thinking about this sort of more unified approach to enabling content? What can we do there? And what are some of those first steps?

LF: I think the first step is we have to collaborate. I think the first step is, do you even know the people in your tech comm team or your learning team? Like, do you even know who they are? So, you know, I think there’s a conversation. I think the second one is to have a shared goal of we want to create a better user experience. Like, you know, an agreement that that is a goal that’s worth, you know, pursuing. And I think your managers, your VPs, definitely your leadership would agree that is. and then I think mapping that out. Like what would that learning experience look like? What’s your utopia? And then break it down, right? You can’t boil the ocean. You have to kind of have a plan. You know, what does the vision look like? And then what’s the first step? Start small. Like what’s the first step in the vision? And I think you and I talked earlier, a procedure is a procedure. Like there’s no magic. There’s some obvious low hanging fruit here as far as, you know, where you can share content that drives efficiency and makes sense. And then to the learner, you’re not coming up with different terminology. We all know the brain loves consistency because it helps with retrieval within the brain. So when I see the same picture, when I see the same example, when I see the same terms, it unlocks memory within the brain. It helps with retrieval. So, you know, we can make it easier for people. But then also looking at, you know, can we put some of that technical documentation and embed it in the learning content in the LXP so it’s easy to find where are people going? Maybe it is to the tech doc portal. Maybe we put it in both places and we figure out single source, right? We can update it in both places. We can keep that in sync, but really understanding and mapping that learner, the end user experience for performance and working together and understanding that we both have something to contribute to the conversation. I think, you know, to your point, tech comms can learn a little bit about experience and how people, you know, retrieve information, but the learning team can definitely learn a lot about structured authoring content management from the tech comm team. So bring those expertise together, which is 80% business and 20% technology. I mean, the first part is, you know, you just got to agree and set your goals and then figure out what’s the best technical solution that will drive those goals. And I would even argue, take it small. Like, you know, do experiment, see what works, what doesn’t work, trial and error. Cause I wish I had the whole answer. I don’t. I think it definitely is a problem that we need to invest in solve. And the only way we’re going to solve is through experimentation. But I also don’t think there’s a one size fit all answer either. I think each organization has legacy tech stacks. We all know we can’t just throw out the tech stack we have, you know, we have different competing business priorities. We have different skills and capacity within our teams. So do what you can. And I think that sometimes people throw up their hands and they do nothing because they think it’s too big. But you got to start small and you got to start somewhere. And step one is go have lunch with the people, maybe a virtual lunch these days, but on the other side, like talk to them, share you guys. At the end of the day, you have a common goal of driving performance within your organization. You have a shared mission. That’s where I would start.

SO: Yeah, I like figure out who your counterpart is. That seems like a reasonable achievable goal. And then, yeah, and then back, you know, work from there. What can you, you know, can you reach consensus on shared terminology? Because, you know, I mean, never mind unified content authoring, that would be lovely but can we agree to call a car seat a car seat and not sometimes a safety seat and sometimes a baby seat and sometimes a something else? Because that would be like a really good start.

LF: Yeah. And the more things you can agree on, the more things you’ll find to agree on. So start with that. How do I share, you know, the procedures? How do I keep stuff in sync? You know, how do I even reduce the time between, you know, product release, the technical documentation and any formal training that needs to have? How do I make sure, you know, how can I generate FAQs? There’s a lot of things that you could brainstorm that you could do together, which then it fosters that collaboration.

SO: Mm-hmm.

LF: And then figure out what are the technical barriers I’m hitting. And I’ll say this as a vendor and then talk to the vendor and say, hey, here’s the business problem we need to solve. We think it’s a market problem. We think there’s value with you. We need you to fix this. Like we need you to be able to integrate these systems. And again, from the vendor side, if you make a good business case and you can show that the market in general, it’s good for the market, you can probably push their roadmap. But if you don’t speak up, if you haven’t tried, how do you know what those barriers are? So how do you know what to push? So just because it doesn’t do it today doesn’t mean you can’t get a solution.

SO: And the bigger you are, the more we would like you to kindly contact the vendors because…

LF: Yeah, the more money you have, the more clout you have. But I’ll be honest with you. As far as our roadmap on the vendor side, many times anyone who’s willing to experiment and to put some skin in the game as far as a real use case and to work together, I would rather build features and integrations based on real-world examples and real-world data than a theoretical PowerPoint we may put together from a nice product feature. And I know most product vendors are the same.

SO: I’ll have leverage.

LF: So partnering with your tech vendors and coming to them with, this is the business problem we want to solve. This is why we think it’s worth solving. And partnering with them to solve it is going to help to break down some of those technical silos. And the good news is on the MadCap side, because we do have the IXIA, we have the Flare, we have the Xyleme, that’s our vision is to how do we bring it together? It’s not gonna happen overnight because we all have. Like I said earlier, we all kind of made different design decisions which aren’t necessarily all compatible right this second, but we’re figuring out how do we make them more compatible? Like who’s got to kind of give up what and how can we make these work together? And because they’re all in our product stack, we have a vested interest in doing that. And honestly, we’re looking for customers, if there’s any MadCap customers out there listening, we’re looking for customers who want to partner with us on that journey and help us to figure out the answer because we know the problem pretty clear. We know some of the answer, but the only way you truly find the answer is by partnering with customers to figure it out.

SO: So I have to ask you about AI because we’re not allowed to do podcasts without asking about AI anymore. Tell me a little bit about your take on AI in the content universe that you live in.

LF: Yeah, I can, you know, there’s so much buzz about AI generation and the large language models and chat GPT. And I think because it kind of like wowed us all and it made the news and not that there’s not some efficiencies to be found there around summarization and descriptions. Cause one thing we know is that. The quality of the descriptions that go in the LMS and the LXP really drive retrieval or people being able to find something. And humans actually write really bad descriptions. AI does a better job of writing descriptions that search can find. So I think there’s something there there. But what really excites me is AI retrieval. Being able to match content to a person, like to me specifically based on my role context, where am I searching from? Am I searching from within Salesforce? Am I searching within my technical app? You know, what gives some idea of what I might be my problem that I’m having? Maybe even send error messages in what’s my region? What are my current skills? What are my skill gaps that would get me the information that I need faster and just the information that I need, not, you know, the 20 page document and now I’ve got to go find page five of 20. The great thing about AI retrieval is it can just bring me topic seven out of 70 and just bring that back to me. So I think that really solving that retrieval problem is huge, that time to an answer. The second one is AI data. AI’s been doing a lot with data. It’s not new news as far as data classification, looking at patterns. But if we think about if our common mission is performance and people being able to do their job, understanding holistically somebody’s journey from novice to proficiency and expert and what really drove those. And we might find out it’s all on the managers. And I argue a lot of it is their manager, you know, their manager and their coaching and had nothing to do, nothing against the audiences we’re talking to, but had very little to do with the learning team and the comp team. It had a lot to do with the managers, but understanding that and how we contribute into that journey will help us to understand what’s really important. And the nice thing about AI is it can bring in a lot more data and look at patterns that are much more sophisticated than us as humans can. We can’t hold that many variables in our head at one time. So I’m excited about AI to bring personalization of content, matching people to content, helping us better understand the value of the content we write and what drives that value of the content so that we can drive those best practices because I think we guess a lot and we have our ideas, we might be surprised at the answer. And then yeah, I mean, AI generation does definitely have a role. I don’t want to say it doesn’t have any, but honestly, it doesn’t excite me quite as much as the other two.

SO: Well, I, you know, I sort of lost interest early on when I asked chat GPT to generate a bio for me and it informed me that I had a PhD, which I mean, cool, but no. So, you know, it, it just, there were a couple of other things like that. It, and, and you said this earlier, you know, it is, it is important in our context to get the information right. And the thing that ChatGPT and the other generators don’t necessarily do is accuracy. They generate plausible content. But if we care about getting it right, cut the blue wire, then the red wire. no, wait, wrong. So it’s important to have this stuff be correct. And that’s the thing that GenAI really struggles with because it doesn’t really have a concept of correct.

LF: Yep. I think that’s where we are sitting on a gold mine with our content, because if you think of RAD, which is Retrieval Augmented Generation, which is the current, you know, leading answer as far as proprietary information that must be correct, it really is about retrieval. And what it does is it points to your vetted database of content. Well, where are those? By LCMS? CCMS? Gold mines of content, because, well, AI can do unstructured content. So not saying that you can’t give it a PDF or PowerPoint, whatever unstructured content. If you give it structured content, it’s like rocket fuel. It’s just easier, it’s better. And if you tagged that content, even if you use AI to help tag it, but if you’ve tagged that content, now that retrieval accuracy goes up exponentially, so we are sitting on rocket fuel. If you’ve already invested in an LCMS or a CCMS, you’re doing structured authoring, you have rocket fuel to drive your AI solution. And you don’t need AI to do it. It’s not that it has AI inherently in our databases. It’s just that we have the content that’s going to generate those AI agents and help to generate those answers and drive those right answers. And one of the key things when you think about proprietary content in these rag systems is the attribution. So it will provide a response. It’s not totally, it may summarize it, but it’s not rewriting it to the, it’s not just making it up like Jack GPT would, where it’s writing it from scratch. It is retrieving it. It may summarize it, but it gives an attribution. It tells me where it got that content from so as the person looking at it, I can decide whether I trust that source and I can verify it. So if it’s red wire versus blue wire and the wrong blue wire, something’s gonna blow up, I can go check the source and say, okay, yes, I trust that source and I’m gonna cut the blue wire.

SO: And on that cheery and I think hopefully explosive note, that seems like that sounds like a good place to wrap it up. Leslie, thank you so much for coming on. I hope we’ll continue this conversation and drive some positive change and some new cool integration and cooperation possibilities. And with that, thank you for listening to the content strategy experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

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In episode 167 of The Content Strategy Experts Podcast, Sarah O’Keefe, Alan Pringle, and Bill Swallow discuss the difficulties organizations encounter when they try to create a unified content experience for their end users.

AP: Technical content, your tech content or product content, wants to convey knowledge so the user or reader can do whatever thing that they need to do. Learning content is about improving performance. And with your knowledge base content, it’s when, “I need to solve this very specific problem.” So those are the distinctions that I see among those three types.

SO: Okay, and from a customer point of view, what does this mean?

AP: Well, in reality, I don’t think the customers care. They want the information available, and they want it in the formats they want it in. And also, they want the right information so they can either get that thing done, improve their performance, or solve a specific problem.

Related links:

So much waste, so little strategy: The reality of enterprise customer content
Pulse check on AI: May, 2024
New to tech comm? Expect the unexpected
Wrangling the Meg of learning content

LinkedIn:

Sarah O’Keefe
Alan Pringle
Bill Swallow

Transcript:

Sarah O’Keefe: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about the challenges of content operations across the enterprise. Hi, everyone. I’m Sarah O ‘Keefe. I’m here today with two partners in crime, Alan Pringle and Bill Swallow.

Alan Pringle: Hello.

Bill Swallow: Howdy.

SO: That first one was Alan, and the second one was Bill. Good luck with that everybody. So I have a big topic today. I want to focus on the intersection of technical content, learning content, and knowledge base content. And Alan, what’s the difference between the three?

AP: Okay, let me see if I can break this down, because I’m sure people have very strong opinions about this, and we may hear about them, but this is how I’m gonna break them down. Technical content, your tech content or product content, wants to convey knowledge so the user or reader can do whatever thing that they need to do. Learning content is about improving performance. And with your knowledge base content, it’s when, “I need to solve this very specific problem.” So those are the distinctions that I see among those three types.

SO: Okay, and from a customer point of view, what does this mean?

AP: Well, in reality, I don’t think the customers care. They want the information available, and they want it in the formats they want it in. And also, they want the right information so they can either get that thing done, improve their performance, or solve a specific problem.

At the end of the day, they don’t care what department or what group wrote it. They just want it, and they want it then and there.

SO: So this enabling content is like, here’s how you can get your job done. Here’s how you can do the thing you need to do and move on with your day so that you can generate the report or write the thing or do the code or whatever it is. They need this content so that they can do the thing. So then, we have all these silos, right? We have technical content in its silo, and we have learning content, and we have knowledge base content, and then we have tools optimized for each of those use cases or for each of those sets of authors. So, now, is this a bad thing from a content perspective?

AP: That is possibly the worst leading question I’ve ever heard on this podcast. The worst.

SO: Okay, I’ll rephrase.

AP: You don’t need to, but of course it’s bad. It is very, very bad. And the reason that it’s bad is because there is so much overlap in this content. Roughly half of technical content, there’s overlap because you’re both dealing with tasks. You’re dealing with tasks.

SO: Procedures, yeah.

AP: Yeah, step-by-step instructions. So you don’t need two sets, one for each group. Why are we doing this? And when I say we, I mean the entire content world because folks, we are. You’ve also got overlap between your technical/product content and your support content. Troubleshooting instructions, Q&A’s on avoiding very specific problems. Same exact stuff, yet again, we’re often maintaining two different versions of that information. So there you go.

SO: So what we want is shared content, right? But we can’t do it because the tools aren’t there. Is that right? It is right. I know it’s right.

AP: Well, yeah, I mean, but it’s not just the tools. It’s the people that write this content because they often have, shall we say, fairly strong opinions that they need a special flavor or they need a special twist on the content. So it’s tools, but they’re also these opinions that the content creators have that inform these problems as well, I think.

SO: Okay, and then Bill turning to infrastructure, what does this look like from an infrastructure point of view as opposed to a, I mean, shared content is kind of an infrastructure problem, but I think there’s additional ones. What does that look like?

BS: Goodie, it’s my turn. Yeah, so shared infrastructure is a big one, you know, getting everyone to kind of play in that, you know, that same sandbox. But there are other things that really need to be shared across the enterprise.

AP: Hmm.

BS: So things like taxonomy, you know, making sure everyone is aligning, you know, with the same terms, the same way of categorizing things, the same way of organizing information, their localization workflow, and even the vendors that they’re using, you know, that they’re all going under the same process so that they get a uniform result back. And then, you know, design systems, making sure that there’s a federated search in place, and making sure that anything that’s being produced for customer or reader consumption has the same unified experience might be a little bit different from content type to content type from delivery platform to platform, but in the end, you have a unified experience so that people aren’t relearning how to engage with your content in every context you produce it.

SO: So from an infrastructure point of view, what does it look like today to set up shared infrastructure? Can you tell us a little bit about the software tools that are available that allow you to do all of this in a unified way?

BS: You know, it’s too big of a list. And that list is basically consumed with things like duct tape, string, Bondo, you name it. There is nothing out there that will give you a unified experience across the enterprise for every content type out there. Right now, it does not exist.

SO: So on the authoring side, I think there’s some unified delivery kinds of integrations. But I think we’re talking about the back end.

BS: We’re starting to see a lot with portals that are starting to collect a lot of information and present them all in one unified space, or at least provide one universal point of access for that content. And we are seeing some tools start to reach out and kind of embrace other traditional content silos. So things like, for example, being able to do develop all of your content in one single place and be able to push to a same branded let’s say knowledge base and documentation portal But I don’t think that there’s anything out there that really grabs everything and says okay. We’re going to do you know manuals We’re going to do other tech content. We’re gonna do web-based references we’re going to do knowledge base articles and tech support guides and training materials, you name it, and produce it all from one source to all these different things. So we have a lot of duct tape and string in place at the moment.

SO: And point solutions like, hey, we’re optimized for learning. Hey, we’re optimized for KB. We’re optimized for tech com. And I mean, it does seem to me that there’s a really big disconnect between what our clients are asking for and what the market has available because our clients are asking for slash demanding unified authoring solutions. And like you said, we have duct tape and string to offer them.

BS: Mm-hmm.

SO: So, okay, so if let’s step back a little bit and say you don’t do this. So you take the departmental approach and you push your tech com content through your tech com solution to the web and you push your KB to a KB article database thing and you have learning content which goes to a learning management system and therefore some sort of a learning platform. What happens when those are not unified? And I’ll, Alan, I’ll start with you. What happens with that if they’re not unified from a content point of view?

AP: Well, the terminology you’re using is not gonna be consistent or often is not consistent across your content types. For example, you go to your knowledge base, and you find a support article that uses a certain term for some widget. And then later on, when you try to search for the name of that widget and some other content, like on the product side of the content, and that product side uses a slightly different term, you’re not gonna get a search result because they’re using different terminology for what is really the same exact thing. So you have that lack of alignment. And the same thing is true, for example, with your product content and your training content. You may have slightly different how-tos or tasks to accomplish the same exact thing. So you’ve got those contradictions there in how to do things, in terminology, and you’re not getting a consistent voice at all in what you are presenting to your customers because of these departmental silos that we were talking about.

SO: And then Bill, on the infrastructure side, what do you see there in terms of problems that surface?

BS: A lot of it comes around or comes back to user experience, you know, because all these tools have very, I guess, a targeted focus. They have a lot of custom feature sets that are built just for that type of content. And a lot of the more generalized features are built out in slightly different ways. And you don’t have a lot of, or you may have a lot of ability to customize, but generally they’re not customized for whatever reason. Either it’s too difficult, no time, one group likes it one way, one group likes it another way. So you have these disjointed user experiences, just going from one area of the website to another. So being able to navigate manuals online to going over to a knowledge base and seeing a completely different interface and not knowing how to navigate it out of the box. So you’re now asking your customers to learn how to use your content in addition to having to use your content to find information in the first place.

SO: So we’re, I mean, we’re doing a lot of complaining, right?

BS: It’s fun to complain.

SO: It is fun to complain. But I guess as consultants, our job is, in fact, to take on the complaints and then come up with a solution. So in the absence of the magic system that does all the things, you know, one thing we’ve seen a lot of customers do is make that compromise where they say, okay, we’re gonna take the thing that’s optimized for A, but we’re gonna use it for A and B even though it’s suboptimal for B. And of course, then the B people feel like B-class citizens, which isn’t great, but enterprise-wide, it’s very, very helpful. On the taxonomy side of things and some of these others, it does feel as though you can build that over the top and then just integrate it into all the other tools and push it down onto those. So I guess that part’s okay-ish. But I mean, what does this look like? And I guess my question to both of you is what’s the solution here? I mean, what’s the path forward and where do we want this to land? I mean, for our personal gratification, but mostly for our customers. What do our customers need the solution to look like so that this is, infamously, the line is you don’t want to ship your org chart, right? You don’t want your website to be a reflection of your org chart at a level that is recognizable to the end customer because, again, they don’t care. So what are some of the solutions here? What are some of the options that people have?

AP: Well, I think one thing you’ve got to do and step back and realize this is not just a tech problem. Now, the tech problem is very real in regard to the silos because you’re using different sets of tools, especially on the authoring side and the content creation side to get things done. But I think all of those content creators need to step back and think a little more globally across the company and not just about this is just for my people, this is just for me. Need to take a bigger step back and think, how can other departments potentially use this information? And then you start getting into tech, how can they actually reuse it? And that’s where you slip away from more culture to tech and how it can enable that sharing and that reuse.

BS: Mm-hmm.

SO: And some of the things like terminology is a good example. If you standardize terminology, you can ask people to follow that across all their systems, right? Like use this term and not that term does not require a unified, you know, content management solution. It’s just a writing practice. And you could layer the terminology management over the top of multiple systems. I mean, it’s more expensive, but you could. Bill, do you have any hope?

BS: Mm-hmm. There’s always hope. You know, we’re starting to get there and especially as, you know, at least systems are starting to be able to somewhat talk to each other via API. So there is a way to share information across. It’s not a, it’s not what I would call anything remotely close to, you know, intelligent reuse, because you’re still duplicating content from one system to another. But at least if you’re consistent about writing in one place, and pushing it out where it needs to go via those hooks, then it’s better than authoring everything separately.

AP: You still have a single source of truth in what you’re talking about and that’s the end goal or it should be the end goal for this problem.

BS: Exactly.

SO: And it might be helpful to look at single source of truth less as the process of doing a task, like how do I change my password in a database, right? There’s a four-step or a two-step or one-step procedure, but there’s a procedure and there’s only one way of doing it. And I think a lot of times the ultimate solution to this is to do some, essentially, forensics on where does that information originate. And if it originates here and I am a downstream user of that information, that’s fine. Just don’t ever modify it. Always go back to the source of the information and modify it at the beginning and then flow it back through. The problem that arises is that in a scenario where flow it back through involves manual processes or copy and pasting, it’s always going to fail because people fail, right? People don’t do the thing. And so you get those inconsistencies and now there’s four different ways of changing your password. One in the tech docs, one in the learning and like two in the knowledge base. And now what do you do with it?

AP: And you’ve got frustration among your users because they’re getting inconsistent information. And then you’ve got frustration with your content creators because they constantly feel like they’re having to go hunt for something or it is not worth my time to go find it.

BS: Mm-hmm.

AP: I’m just gonna copy and paste and then they forget to update one of the umpteen versions they have. And then they’re stuck in this constant go go go process so it’s bad on both sides of the content equation for your content creators and the people who were consuming that content as well.

SO: Okay, well, this is super encouraging. And with those helpful words from Bill and Alan and maybe me, but mostly them, I will leave you to it. And so with that, thank you for listening to the Content Strategy Experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

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In episode 166 of The Content Strategy Experts Podcast, Sarah O’Keefe and Alan Pringle check in on the current state of AI as of May 2024. The landscape is evolving rapidly, so in this episode, they share predictions, cautions, and insights for what to expect in the upcoming months.

We’ve seen this before, right? It’s the gold rush. There’s a new opportunity. There’s a new possibility. There’s a new frontier of business. And typically, the people who make money in the gold rush are the ones selling the picks and shovels and other ancillary services to the “gold rushees.”

— Sarah O’Keefe

Related links:

“Put an AI on it” meme
AI business viability (gift link)
AI and GDPR
AI and mushrooms (gift link)
AI in the content lifecycle (white paper)

LinkedIn:

Sarah O’Keefe
Alan Pringle

Transcript:

Alan Pringle: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we’re checking in on the state of artificial intelligence. Things are moving really fast in the AI space, so we want to let you know we recorded this podcast in May of 2024. Hey everyone, I’m Alan Pringle.

Sarah O’Keefe: And I’m Sarah O’Keefe, hi.

AP: And we’re going to talk about AI yet again, but we need to circle back to it because it’s been a while and kind of assess the space right now. Last week I saw a really great meme. It was a still of Carrie Brownstein and Fred Armisen from the Put a Bird On It sketch from Portlandia. And it said, “Put an AI on it!” And that’s kind of where we are now.

SO: Yay.

AP: So many companies, so many services, so many products look at this AI thing that we’ve got now. And a lot of these AI birds, if you will, have landed on content creation, kind of our wheelhouse. So let’s pick that apart for a minute.

SO: So I guess we can start with generative AI, GenAI, which is a ChatGPT and all of its general ilk, right? The chat interfaces. And generally speaking, at least for technical content. There does seem to be an emerging consensus that this is not where you go for content creation. You’re not going to start from scratch. Now, maybe you get it to throw out some ideas. Maybe you can do a first draft, but overall, the idea that, you know, ChatGPT or generative AI is just going to generate your docs for you is not the case. So there’s a big nope on content creation, but there’s also a big yes for productivity enhancement. I wrote a draft, but did I write it at the appropriate seventh or eighth grade level? Can I run it through the AI and let it clean it up? I need a summary. I need this cleaned up. I need my XML tag set corrected. I need a proposal for keywords that metadata that I haven’t put in yet, those kinds of things. So there does seem to be a rising level of capabilities in that space, in that productivity enhancement, how can I take this thing that I wrote or that I created and refine it further to get to where I need to be.

AP: Yeah, I was at a conference a few weeks ago, and in the expo hall, so many of the vendors were selling an AI service or some kind of AI add-on. And my thought was, how can the market possibly sustain all of these new products and new services? And I know there was an article in the New York Times last week that was talking about the business viability of AI. And it really doesn’t matter how cool or neat what your AI tool does. If there’s not business viability behind it, you’re going to have a really hard time in the marketplace, because you’ve got so many established players like the likes of Google and Microsoft who are really starting to dig into AI, and does it leave room for anyone else? So part of me wonders, is this going to help some vendors, hurt some vendors, or some vendors just going to go away at some point because of this tussle with AI features?

SO: Well, I mean, we’ve seen this before, right? And it’s the gold rush. There’s a new opportunity. There’s a new possibility. There’s a new frontier of business. And typically, the people who make money in the gold rush are the ones selling the picks and shovels and other ancillary services to the “gold rushees.”

AP: Exactly.

SO: And so to me, I’m starting to think about this as it’s going to fade into the background eventually in the sense that it would not occur to me at least to write a document without a spell checker and/or, you know, some sort of built-in grammar checker. They’re super useful, but I don’t necessarily do exactly what they tell me at all times. I look at what they tell me and then I use my own judgment. So I think that’s where we’re going to land where AI is going to be this useful tool that sort of a little bit fades into the background and that has human review. And we’re starting to see people refer to human in the loop, just as we did with machine translation, which is another place where you can look for patterns. What is AI adoption gonna look like? Go look at machine translation. Sometimes it’s good enough, sometimes it needs a human in the loop. Sometimes if you’re translating, let’s say, literary fiction, it’s maybe not that well suited, because it’s just not going to pick up on the kinds of things you need to pick up as a literary translator.

AP: Yeah, yeah, I agree. Is this going to be a feature that you accept as part of whatever suite of tools that you’re using? It’s just built in and there it is. So let’s talk now about something a little more complicated and I think maybe a little more dangerous with AI and that’s intellectual property. It has always been a problem, and there are all kinds of lawsuits flying about with different content creators claiming that different AI engines are stealing their copyrighted content, that sort of thing. And I don’t think that haze, that cloud has really been removed at this point. It’s still a problem that we need to address.

SO: Yeah, it’s a huge question mark. And, you know, it’s terrifying from the point of view of if I use AI and the AI injects something into my content or into my code that is that belongs to somebody else that’s copyrighted by somebody else. What’s that going to look like? What’s going to happen? And I have seen, you know, differing opinions on this from all sorts of people in our industry, in adjacent industries, from attorneys, non-attorneys, everybody has an opinion on this. And the thing is that the responses are, they just run the gamut from, do not use under any circumstances because we could get ourselves in trouble to eh, whatever, YOLO, it’ll be fine. I saw a comment just the other day along the lines of, well, I can’t believe that people would get sued for this because everybody’s doing it essentially. And I mean, they might be right. I’m not saying they’re wrong, but remember Napster? I mean, they got taken down.

AP: Yes, they did.

SO: We now have streaming and those kinds of things, but the original one that was kind of the unlicensed in a pirate version, really, did get taken out. And I haven’t the slightest idea whether the regime that we’re under right now is going to end up like, you know, a Napster or like a Spotify. Not a clue.

AP: Yeah, yeah. And this conversation on IP intellectual property kind of ties into something else I’m going to talk about too. And that’s the regulatory angle. Different governments are taking a look at this. And I think that’s absolutely worth discussing as well.

SO: Yeah, again, I think more questions than answers, but just in the last, say, two months, the European Union has passed an AI act, which divides AI into risk categories based on what kinds of things it is doing. And so they’re banning certain kinds of AI, they are regulating certain kinds of AI, and then they’re allowing certain other kinds, you know, but they’ve basically said, if it’s in the highest risk category, then you have to follow these kinds of rules, or maybe it’s not allowed at all. China has taken a different approach. The US has so far done nothing in terms of regulations.

AP: Nothing.

SO: We’ve talked about it, but we haven’t done anything. So it’s quite likely that at least in the short term, the regulatory schemes will be different in different locations, in different countries. And then just in the past week or so, I bumped into a pretty interesting article that was talking about GDPR, the European Privacy Regulation. And basically, under GDPR, you have certain kinds of rights. You have the right to be forgotten. You have the right to be taken out of a database, and somebody has anonymously sued OpenAI because when they go into OpenAI and they say more or less, “What is my birthday?” It gives them the wrong answer. So this is apparently a, again, anonymous but public figure, and we’ll put the article in the show notes. So this anonymous public figure is suing AI on the grounds that it reports an incorrect birthdate for that person and you have the right to have your data be correct under GDPR. Well, OpenAI’s response to this lawsuit is along the lines of it is impossible for us to correct that, right? Because there’s not an underlying database that says John Smith date of birth X. It’s just generative, which is sort of the crux of the whole issue here. But the legal footing, the legal argument appears to be that under GDPR you can’t say, oh, I’m sorry, it’s impossible for me to correct that fact. So you’re just gonna have to deal with it. And so we’re gonna have a really interesting collision between the content that generative AI creates, which may or may not be factual. That’s not a thing, right? And GDPR, which is an established law. And I have the slightest idea where that’s going.

AP: Yeah. And I think too, in this vacuum or with this absence of regulations in some countries, you’re going to see companies then make their own rules. And a lot of them have telling employees when they, what they can and cannot do with AI, which really, like I said, in the absence of there being any kind of rules to help kind of create a baseline, it makes sense, especially if you’re trying to be very careful about liability, putting out incorrect information or using copyrighted information that you shouldn’t be, it would make sense for you to protect your bottom line by basically instituting your own guidelines for how you can and cannot use AI.

SO: And if you look at social media where the platform is basically not responsible for the content that people are putting on it, right? So if I’m on LinkedIn, let’s say, and I put something on LinkedIn and then somebody else reads it, if what I’ve said is problematic, they’re gonna sue me, not LinkedIn, right? LinkedIn is not responsible. And with AI right now and generative AI, who’s responsible? If I go and I generate something using generative AI, and then I publish it in some way, and then I guess I assert copyright on it, which is a whole other can of worms because I can’t right now under current law. But if I do that, then if what I post is wrong and legally problematic, so it’s, I don’t know, defamatory or something, then like who gets sued? Do you sue OpenAI for being incorrect? Do you sue me? Do you sue the platform I put it on? Like who is responsible when the AI gets the content wrong? Is it me because I didn’t validate it or correct it or clean it up? If we build out a chatbot that’s AI-driven, that’s generating information and you know, we’ve already seen this use case legally. You know, the company is going to be responsible for the information that the chatbot is putting out if the chatbot is sitting on the company website. But if it’s impossible to be sure that the chatbot’s gonna be right, what do you do with that?

AP: Yeah. And it’s been established as of last night before we recorded this, the big Met Gala happened. And apparently there were two quite realistic photos or images of Katy Perry in two different dresses. How she pulled that off, I don’t know, at on the steps at the Met Gala. So and the problem is a lot of the social media platforms absolutely could not, they just didn’t do anything. These photos just exploded.

SO: Right. Because they were fake, right?

AP: They were fake. 100% generative AI fake. And even her mother was fooled by it, apparently. And Katy Perry’s response was, “I was working, so no, I was not there.” But it just goes to show you that you’re right. Once these images got out there, they exploded on social media, and those platforms really are not equipped to handle flagging of that or even removing it at this point.

SO: “I didn’t know you were going to the Met Gala.”

AP: Exactly.

SO: Yeah, I’ve seen a decent number of it largely in AI news coverage where, you know, a New York Times or Washington Post will put up an image and they’ll put a slug on it or a caption that says this is AI-generated. And usually, they watermark it. So it’ll be actually in the image, not on a caption below, but in coverage of AI itself. And for example, talking about this deep fake or, you know, the one where the Photoshop UK princes, princesses, that one. They carefully labeled the photo itself as altered on the photo so that people would know when they were reading the news story what they were dealing with. But of course, you know, that’s not going to happen on social media, where it’s just going to fly around the world faster than anything. And so, yeah, I think I don’t know. I mean, I’m saying I don’t know a lot. That’s where we are. We don’t know.

AP: We don’t. Yeah.

SO: We don’t know what’s going to happen. Things are changing very quickly. The legal and regulatory and risk scenarios are completely unclear. I did want to touch on one other sort of more practical matter. We’ve seen a lot of complaints recently, and I think I’ve experienced this personally, and I think you have as well, that search, like Google search, Bing search, all the traditional search is actually getting worse.

AP: Oh, 100%. Yeah.

SO: You search and you get bad, you know, just junky results, and you can’t find the thing you’re actually looking for. And the basic reason that that’s happening is that the internet, the worldwide web has been flooded with AI-generated content at a scale that has completely overwhelmed the search algorithms, such that they are unable to sort through all this stuff and actually give you good information. I mean, we did at one point, a year ago, have a scenario where if you had a pretty good idea of what you were looking for and you typed in the right search phrase, you would get some pretty decent results and you could find what you were looking for. And now it’s just junk, which has to do with AI-generated content that is micro-targeting SEO phrases. And ultimately, I think this means, well, it’s going to be a war between the search engine algorithms and the AI-generated content. But I suspect that search and SEO as we know it today is done because it won’t win this. And then people are like, “Oh, I like it a lot better when I go to ChatGPT, and it gives me this nice conversational paragraph of response,” notwithstanding the fact that that paragraph of response probably isn’t super accurate.

AP: But it’s so chatty and friendly.

SO: Uh-huh. So I’m not terribly optimistic about that one either. And so what does this mean if you are a company that produces important and high-stakes content, like all of our clients, basically? What does that mean to you? And I think it means that you’re going to be looking hard at a walled garden approach, right? To say, if you are on our site, and you are behind a login on our site, we have curated that information, we have vetted it, we have approved it, and you can rely on it. If you go out there, you know, in the big wide world, there’s no telling what you’re gonna find out there. And that implies that I have to know who I’m buying from so that I can go to the right place and get the right information. And I’ve already found myself doing this. Instead of going to a big general purpose, e-commerce buy things site, such as the one I’m carefully not mentioning, I find myself saying, oh, I need a new stand mixer. I like KitchenAids. I’ll go to their site and buy it there. And so I’m buying direct from brands that I’m familiar with and that I know because that feels safer than going to the great big site that has a little bit of everything, including a stunning array of what seems to be problematic counterfeit and or knockoff kinds of things. So instead, yeah, but so if I don’t know the brand, if I don’t know the brand, then what? Like, how do I find the right thing if I don’t know where to start already?

AP: The same as true of information. Right. Yeah, I don’t think that’s going to be fixed anytime soon and it’s probably going to get worse after this podcast, in fact.

SO: So I’m concerned. Yeah, and you know, as a parting gift of, I guess, fear, we will put it in the show notes using a gift link. But there was an article that appeared in the Washington Post about a month ago, maybe two, having to do with apps for identifying wild mushrooms when you’re foraging. So this already seems kind of like a high-risk activity to me, just generally going out in the forest and looking for mushrooms that you’re going to forage and hope you get it right and you pick the really delicious one and not the one that’s gonna kill you. And Alan’s making faces at me because he hates mushrooms.

AP: I have the solution for this problem. Don’t eat them. But that’s not helpful. Yeah.

SO: Yes, you have a really simple solution. But for those of us who do like mushrooms and don’t want to die, there are a whole bunch of apps out there. And so there was some research done in apparently Australia on mushroom identification apps, which are apparently AI-driven, which seems like kind of not a good idea. However, what they found was that the best of the AI-driven apps was 44% accurate. And I wish for my mushroom identification app to be a whole lot more than 44% accurate, especially in Australia where everything kills you!

AP: So a 56% chance of poisoning yourself. That’s excellent. Great.

SO: Yeah, or at least of getting it wrong. But again, it’s Australia. And so if it’s wrong, it’s probably going to kill you because that’s Australia. So yeah, that’s not good. And that feels like a not acceptable outcome here. So I don’t know where this is going, but I am pretty concerned.

AP: Yeah. So as we wrap up, there are some good things to talk about, especially, there are a few. Sarah was whispering, “Are there? Are there?” Or made a face. There are, I mean, on the content-creation side, I think there have been some tools that have added some useful features, much like the spell-checker analogy that you talked about. But there are still so many unanswered questions in regard to intellectual property and legal risk. All of those things are still way up in the air. A lot of countries are trying to adjust by taking a look at regulations, but you know, those aren’t in place yet. So we’re in, we’re at a crossroads, I think, and we’ve still got to pay a lot of attention to what’s going on with AI right now.

SO: Yeah, you know, there’s some really, there’s some really nifty tools out there. It’s also worth pointing out that there have been tools that use machine learning and AI that are already out there. They just weren’t, it wasn’t AI front and center. Now everything, as you said, put an AI on it because you can get sales that way, and you can get attention. But there are a lot of companies that are doing some really interesting and really difficult work with this. And I want to, you know, I’m not against any of this stuff. I just want to make sure that we use these tools in a way that, you know, maximizes the good outcomes and minimizes the, “Oops, I ate the wrong mushroom.”

AP: Yeah. Fatal mistakes. Not a fan. Not a fan at all. Well, I think we’ll wrap it up on that cheery note about eating poisonous mushrooms on the Content Strategy Experts podcast. We go places, folks. We will talk about almost anything on this, not just content. So thank you for listening to the Content Strategy Experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Pulse check on AI: May, 2024 appeared first on Scriptorium.

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In episode 165 of The Content Strategy Experts Podcast, Sarah O’Keefe and guest Patrick Bosek of Heretto discuss how the role of customer self service is evolving in the age of AI.

I think that this comes back to the same thing that it came back to at every technological shift, which is more about being ready with your content than it is about having your content in the perfect format, system, set of technologies, or whatever it may be. The first thing that I think either of us will say, and a lot of people in the industry will tell you, is that you need to structure your content.

— Patrick Bosek

Related links:

Heretto
Content Components podcast by Heretto
AI in the content lifecycle (white paper)
Content paradox: Standardization = personalization

LinkedIn:

Patrick Bosek, Heretto
Sarah O’Keefe, Scriptorium

Transcript:

Sarah O’Keefe: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk with Patrick Bosek about the changing role of content in self service and whatever the opposite of self service is, maybe just service. Hi, everyone. I’m Sarah O ‘Keefe, and I’ve got Patrick Bosek, the CEO of Heretto with me today. Hey, Patrick!

Patrick Bosek: Hey Sarah, it’s good to be here. I guess to be back, technically.

SO: Yeah, you’ve been here one or two times before, so I’m going to cut to the chase here. And our topic today is self-service content and how things are changing in self-service content. So talk a little bit about that. What’s going on?

PB: Well, I think to talk about self-service content, we have to talk about what’s changing in, I think, self service more generally, which you kind of alluded to in the idea of, you what is the opposite of self service, right? So the landscape is, as I see it, is very interesting today, because historically we had what was very obviously self service, and then what we had was very obviously not self service. So I guess just people or service or something—people service maybe. And for the most part, self service was content, right? So if you went someplace and you read something and you figured it out on your own, over the last decade or so, self services started to involve a little more action. You can go to a McDonald’s and self-service order a coffee today. We can talk about it in a minute whether or not we think that’s a good idea or a bad idea. But now as we’re getting into the age of true…intelligent, if you want to call them, virtual assistants, AI, those types of things. Now we’re in a place where the things that were very traditionally handled by humans. So helping you figure out what you really mean, helping you dig through something when you’re not exactly sure where you’re finding, finding it, or if it is possible, those types of questions are actually performing actions. Some of those are going to continue to bleed over into systems. So now self service isn’t just content anymore that you go and look up and then you yourself go and figure it out and do something. There’s going to be this mixing between these two things where the service that’s provided by automated systems is going to perform some of the things that humans were performing. They’re going to need a bunch of content in order to be able to do this properly. And probably also as instructions, you’ve got to teach these things what to do somehow. And as we all see with the way that we interact with them, you use words, you don’t use programming languages as much. So content plays a role in its traditional form. It continues to play a role in training people. It also plays a role in establishing what this new generation of systems that are going to help us perform actions and learn things and answer questions, what those things are going to do.

SO: So it feels like we’re adding another dimension to this, because when mobile apps first came out, the big development there was that they were contextually aware. So you can get your app to tell you what the weather is at your location because it knows where you are or it can know where you are. And it feels like this is a similar kind of thing that some of this is more a matter of not just, “Hey, here’s a page with some instructions,” but rather, you know, let me, let the system do some work around what your context is and what some of your knowledge is and adapt accordingly.

PB: I think there’s absolutely an aspect. So I would actually put that in the category of just like maybe even traditional personalization. You know, feed metadata in those are things about yourself and then you perform some type of a matching or a computation. And then you feed content back. So that’s, that’s effectively personalization out of its core. Like here’s some things about me. Okay. Then those match to some things about the content. Give me just the content that matters to me. I think where this starts to become new and really interesting is where you start to have systems, so probably, you know, AI-based systems that are actually not just like filtering or personalizing content, they’re actually manipulated in content or they’re manipulating your journey with the content. And one of the places that, you know, we are seeing more of that I think is an interesting place for this is in learning. So you start to think about how learning systems and self service have worked for a long time. And as much as there’s been like micro learning content, and then there’s been more organic things like that kind of stuff, by and large learning has been linear when it comes to self service. Here’s a guide, here’s a course, whatever it may be. And it didn’t matter if you didn’t need to know a good chunk of it or if you already knew a good chunk of it or whatever it may be. Like you went through that, right? That’s how that works. So that, I mean, it’s how colleges, college courses work. It’s how, it’s how learning works in general. Like unless you’re sitting across from a tutor, like learning is linear by and large, when it’s being taught. Well, with AI, all of a sudden we can deploy systems at scale potentially where you can always be sitting across from a tutor. The entire paradigm around how it is that we, you know, air quotes here, “self service,” if we still want to call it that, the things that we need to learn can fundamentally change.

SO: So what does it look like for us sitting in the content universe when customer experience is moving in this direction towards this, I guess, more sophisticated self service? Not just here’s what we have, deal with it, but rather here is information or learning or a chunk of content or whatever that is adapting to that person’s requirements. I think it is, right?

PB: In certain circumstances, it certainly has the ability to be adapting to people’s requirements. I think that’s the thing that we will absolutely be seeing. But more generally, what does content need to look like to give you the range of things you might want to do as an organization in this new paradigm? And I think that this comes back to the same thing that it came back to at every technological shift, which is more about being ready with your content than it is about having your content in the perfect format or the perfect system or the perfect set of technologies or whatever it may be. So the first thing that I think either of us will say, a lot of people in the industry will tell you is like, you need to structure your content. And I do think that the story for this on the learning side, on the traditional self service side, on the AI-agent side, and I think even on the people service side of things still does start there. But I don’t think it’s because self service is intrinsically something which is powered by structured content. What I think is that structured content really just gives you, the organization, you, the content creator, a lot more control over what goes into these systems no matter the range of intelligence that they have. And that means that you have input control on the experiences. And as we all know, LLMs, even when they’re backed by like RAG, retrieval augmented generation, or other systems that are meant to kind of keep these things fenced in, they’re black boxes. And the bigger the box, the blacker the box. So, the strategy, if you look out over the industry, there’s a lot of very sophisticated stuff, but some of the stuff that works the best is input control. And that’s where I think that structured content is really gonna be a key element of this, no matter how far in the future you look.

SO: Yeah, and I mean, my explanation of this to people, which I’m sure makes the actual AI experts cry, is AI likes patterns. And so if you feed it content that follows consistently the same pattern, you greatly improve your odds of getting good output from what you’re putting into the system. When you have stuff that’s not well organized or structured or anything else, you know, garbage in, garbage out—you’re gonna get a mess.

PB: So I think there’s that is true. There are caveats, but the thing that remains true at the center of that is that if you don’t have very precise control over what goes in, you lose an enormous amount of control over what comes out. So even there’s, there’s such things like overtraining, right? Where you can actually get AI that will produce, less high-quality results with certain quantities or certain types of training. And what you end up with in those circumstances is that like, okay, well, if your stuff is just a bunch of stuff and you stuff it all into an AI system.

SO: That was excellent.

PB: It’s good, right? I gotta have some fun. So you don’t have any ability to say, okay, well, these pieces really, these are the ones that are impacting our outputs. Let’s pull this out, or even just iterate in an intelligent way. So, which part of the corpus, which part of the things that we put into this system are the ones that are having the negative impact? Retraining becomes a much more complicated process. And at the same time, when we’re looking out over deploying across multiple experiences, right? So, you know, let’s take the learning and reference. So, you know, probably speaking documentation portals, whatever they may be. Some people call them knowledge bases in certain circumstances. Those are the two obvious things, because in the past they’ve been highly bifurcated, even though they use a lot of the similar information underneath the hood. Well, if you’re trying to build AI-backed much more like personalized learning systems. Well, you can’t have the content in those systems being different than the reference content, because when you go and you look at the stretch of things that go into that stuff, well, if you have the AI system telling your, user something which is wholly inaccurate. And you can’t pull it back to the rest of the stuff that’s published on the internet, you can get highly divergent results, and you could end up in a circumstance where you have no ability to actually deploy these things properly. So you can’t have one set, which is very cottage based, like, you know, we will go in and we craft these things and one set, which is highly structured. And then you power all of the learning, the intelligent learning systems of the structured stuff, because it’s going to be easier. So you have to find a way to pull these things together, and then use the mechanisms underneath the content to put the right inputs into the right places.

SO: And we’ve been talking for years and years and years about problems with silos and how they’re an outgrowth of the organization itself, right? You’ve got a learning organization and a documentation organization and a tech support organization. They’re all producing content into their respective silos. And the question becomes, if organizationally that’s what the company looks like, then it is almost impossible to rip those silos apart or put them together, destroy them to collaborate across them because the org chart doesn’t encourage it or even makes it impossible potentially. And so then you’ve got different terminology being used by the same company but in different departments, which is really common. And then what? So we’re back to, you know, the fundamental truth that when you have a website as a company, even if you segment that website into like, oh, learning.xyz.com and docs.xyz.com and KB or support.xyz.com, your customers don’t care, right? I mean, they’re not interested in the fact that you have three separate organizations that all hate each other. That’s just not on their list of things they care about.

PB: So I mean, this goes back to the classic, like don’t ship your org chart, which is, yeah, obviously, right. So obviously we’ve been doing this in content for ever, basically. I do think that it’s gonna be, we’re gonna be forced to change because, you know, again, you go back to the idea of like, if you contradict yourself in your learning content and your docs content and it’s being read as written or as built and presented to a human being. Human beings are incredibly flexible creatures. We can go in and be like, oh, well, okay, fine. So like they didn’t update that piece, those dummies, they should have done this, but I understand what’s going on. But when you put an abstraction layer over that, now you have a system that just basically does what it’s told, you know, by and large, or understands what it’s, what it’s educated in, and what it’s told, it’s not going to have that same intuition. That’s a very human thing, even at this point in time. I don’t, I don’t really see the current generation of LLMs getting to a point of having that style of intuition. I mean, the thing that just happened with the ASCII art is a great example, right? And it’s a little bit divergent here, but bear with me. So people figured out how to hack these AI systems by going and asking them questions with ASCII art, which in one sense shows their brilliance because they’re able to understand it. But in the other sense, it shows their lack of intuition because they were like, oh, well, this doesn’t apply to my rules. Who cares? Right? And whereas a human being would have been like, oh, I’m still not allowed to talk about bombs. Right? It doesn’t matter if you’re in a theater, if you write, don’t yell bomb in ASCII or in Sans Serif, people understand that it’s still talking about the same general concept. So this is the same thing that you run into where you can’t have these discrepancies and stretch a single system over the top of these. And you can’t have a really strong customer experience that properly educates people, properly answers questions, and all those types of things, unless they’re joined together.

SO: Yeah, apparently in addition to ASCII art, if you use Morse code, that will also work around all the guardrails, which sounds fun. So, okay, so in our couple of minutes that are left here, how does Heretto and CCMSs in general, but Heretto specifically, how do they play into this?

PB: Yeah, sure. So that’s a great question and one I appreciate you asking it for obvious reasons. I’m going to answer the CCMS part first, then I’m going to answer the Heretto part. So CCMSs as platforms, and I think this is probably true for pretty much every major CCMS in the industry or in the space. They’re going to give you the ability to manage more structured content at a higher velocity and a higher level of governance. Now they’re all going to be able to do this, you know, to different efficacies, right? So some are going to do it better or worse for your particular circumstance. But broadly speaking, that’s why you buy a CCMS. A bunch of content, you want to be able to have your per author or per information developer content be higher than it is, and you wanna make sure that you have the proper amount of governance so that what you deploy is what should be deployed, right? It has to be good enough, it has to meet the criteria, especially today. So those are the things that you build into the process in the CCMS. And then, obviously, they help you track things like localizations as well, but I would broadly put that in the same bucket. So as we’re looking at, how does this relate to the future of the customer experience, you know, be it directly with the content or be it derived from the content through some intermediary system like AI. It’s the governance piece, and it’s also the quantity piece. You have to have enough to be able to answer all the cases to be able to touch all the learning points to be able to educate and guide these systems in all the proper ways. And now, because you don’t have that human intuition as your last fail save, the level of governance has gone up a bar. You have to be able to have much better governance on your content to be able to control inputs. So I think that this is a new age of CCMS. And it’s funny because we have seen an acceleration in interest from people and an acceleration in interest that’s educated where people are coming. And they’re like, we have to get this in order, because we realize that if we don’t have our hands around this, we’re gonna have a huge mess at the end of the toolchain. So I do think that people are more aware today, you know, it’s probably still relatively niche in the grand scheme of things, but there’s a growing awareness that the having the right systems in your content operations ecosystem to produce the right outcomes down the chain is gonna be critical. And CCMS for this style of content is 90% of the time gonna be the best place to start. Not to say there’s not other ways to get there. On the Heretto question, Heretto does all that stuff like the other CCMSs. Obviously there’s some aspects of collaboration and things like that that we think we do better. But I think the key thing as it relates to the future of these technologies that Heretto provides that you don’t really get in other CCMS technologies is our ability to efficiently and agilely deploy content into specific pods. So we have static publishing, we have the ability to generate HTML, PDF, all that kind of stuff, like all the other CCMSs. But we also have the ability to dynamically deploy content into an API layer where the content is in its own little pod. So you can kind of deploy as many little content APIs as you want. Most organizations have one big API that they deploy that powers an entire doc site. It can be tens of thousands or more, you know, topics. But you also have the ability to say, all right, I want to just deploy this here, and this API is only going to have this content in it. And that comes back to the critical aspect of the bigger the block box, the blacker the box as it relates to AI systems. So you don’t go hook your AI system up to the totality of, you know, your large API that serves your web experience or general web experience. You hook your AI up to this specific pod that only has these specific things in it. And therefore, you know exactly what’s going into that AI system, you know, be it for something that’s more like RAG-based, which is really just like search and summarize, I think it’s a much better name for it. Or BSL which is more training-based. So I think that’s kind of the critical piece that Heretto offers right now that is not present in other systems that, you know, relates to what we’re talking to today anyways.

SO: Alright, I mean, that seems like a good place to leave it, because basically you’re saying, hey, this stuff is coming. All these things are changing, and here’s a helpful roadmap for how to get there. Any closing words before I wrap this up?

PB: No, other than this is a really exciting time to be part of content. You know, we’ve both been here for a little while, and we’ve seen a lot of changes in this industry. But this is certainly unique. There is no doubt that the acceleration understanding and the change in the landscape over the last, you know, year, 18 months, I would say has been unprecedented. You know, I think you see that all the way from, you know, the types of experiences that we want to start deploying that we believe are possible, but we’re not totally sure based on new technologies. And then also the change in approach to things like learning content, seeing organizations suddenly starting to say, okay, so like PowerPoint is not our primary method of training people. Like our primary method of training people is going to be dynamic digital experiences. And we need to be prepared for that. And then whatever comes after that, you know, I think that this is a shift that, I’ve been waiting for, you’ve been waiting for, for a long time. I mean, like, for gosh sake, like we implemented the experience for DITA learning and training. What is it? One dot one or something like that, like 10 years ago. And we’ve had a couple of customers that have used it across that time, but it’s just been recently that we’ve had more and more people coming in and starting to use it. And there has, there seemed to be a bit of a Renaissance in the understanding around these things. So, I don’t know, this is just, it feels very new. It feels very fresh again, which I think is part of the structured content cycle. And this is the fun part of the cycle. So I’m enjoying it.

SO: Yeah, I would I would agree with that. So I’ll leave it there. Patrick, thanks for being here. Always good to see you. And with that, thank you for listening to the content strategy experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes.

The post Self-service content in the age of AI with Patrick Bosek appeared first on Scriptorium.

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In episode 164 of The Content Strategy Experts Podcast, Alan Pringle and special guest Chris Hill of DCL talk about where you can find redundancy in your learning content, what causes it, and how a single source reuse strategy can eliminate duplication.

You really start to run into trouble when you need to make version two, and you discover a problem with version one. If I’m making some marketing materials, maybe I need to use some information from the engineering team or from the manuals for whatever product I’m marketing. I might just copy that information over and put it into my marketing materials. Then, when we go to produce our training for that particular product, we might say, “Okay, I need that stuff. I’m gonna copy that from wherever I can find it,” which might be from marketing or engineering depending on where I look and who I know better or which repository is easier for me to get to. The problem here is that if anybody has made any edits along the way, they have to ensure that those edits are propagated through all these departments. And that doesn’t always happen.

— Chris Hill

Related links:

Data Conversion Laboratory (DCL)
Harmonizer by DCL
Confronting the horror of modernizing content (case study)
Training content paradox: Standardization = personalization

LinkedIn:

Chris Hill, DCL
Alan Pringle, Scriptorium

Transcript:

Alan Pringle: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk with guest Chris Hill of DCL about learning content and where you can find redundant duplicated content, what causes it, and how a reuse strategy can eliminate that duplication. Hey everyone, I am Alan Pringle and we have a guest here today, Chris Hill of DCL. Hey Chris, how are you doing?

Chris Hill: Doing well, thank you, Alan. It’s nice talking to you.

AP: Great, yes as always. Chris, tell folks out there a little bit about yourself, DCL, and your role there if you would.

CH: Sure. DCL stands for Data Conversion Laboratory. And so we got our start doing data conversion, which is moving content between formats. And over the last, let’s see, that started in the 80s, if you can imagine a tech company starting in the 80s.

AP: Yes, I can. I am of an age, yes.

CH: So since then, we’ve expanded out into lots of areas, but basically any kind of content transformation, workflows, content enrichment, all sorts of activities around content. So that’s our key theme. I joined DCL about four years ago, and I’ve actually been in the content management space for a good more than 20 years now, and have a lot of experience with both migrating from, you know, using tools like Word and such, and then moving into a content management system. I actually managed, product managed a content management system and then got into conversion. And as part of my job here, I oversee a product called Harmonizer, which is our tool for doing content analysis and specifically reuse analysis to find places where content is redundant, duplicated, and help users figure out what they need to do to improve that situation.

AP: Well, in this conversation today, I think we’re going to tap into all the wisdom that you bring to the table with your background and content and your experience at DCL identifying reuse. And let’s start with just the concept of redundant content. And there are lots of ways to describe this. And I’ve heard it referred to several different ways. Redundant content, duplicated content, overlapping content. If you would kind of give people a bird’s eye view of what we’re talking about here.

CH: So we’re really talking about any place where you’ve got similar or exactly the same content reproduced. And you usually know you’re doing this because anytime you hit that Control C and Control V or choose the copy paste menu, if you’re a menu person, anytime you’re doing that, you’re creating redundant content. And, you know, it’s usually the easiest way to get it done if you’re working in a tool like Microsoft Word or a word processor or a desktop publishing environment or something like that. Generally, you copy stuff from one document to another. And that can be fine for version one of those documents. Where you start to really run into trouble is when you need to make version two, and you discover a problem with version one. So if I’m making some marketing materials, maybe I need to use some information from the actual engineering team or from the manuals for whatever product I’m marketing. I might just copy that engineering data or whatever information over and put it into my marketing materials. And then when we go to produce our training for that particular product, we might say, okay, I need that stuff. I’m gonna copy that from wherever I can find it, which might be their marketing or it might be engineering depending on where I look and who I know better or which repository is easier for me to get to. And the problem with that is that if anybody’s made any edits along the way, they have to ensure that those edits are propagated through all these departments. And that doesn’t always happen.

AP: It usually does not happen. You’re being kind.

CH: Yes, I am. So when the engineers find out, oops, we made an error here in the technical manual, we better fix that or somebody is gonna do the wrong procedure or come out with a bad result, they might fix their manual, but. Are they aware that there’s all this marketing material with that stuff in it? Are they aware that the education team actually copied the stuff from marketing? They may not have even talked to the engineers to tell them they were using that content. And so what happens is you pretty soon have a sort of information entropy where things start to go fall apart and the information gets out of sync and you may have inaccurate information through various departments that no one can really trace. So that’s kind of where I see this grow and it’s pretty much a natural feature of using computers and the more traditional desktop application approach to creating content.

AP: Absolutely, and you’ve really kind of covered the big picture here really well. And what I want to do is kind of move just a little bit away from that and talk now about, especially for people in the learning and training space, where they might see some of that content overlap. And you’ve kind of touched on one. Anytime that you have a new version of the product or service that you are creating content for, it’s very common to just copy and paste the previous version, create a new file set, and then make your edits and updates in there. There’s one scenario right there where you have used copy and paste, and there’s a very good chance there’s a lot of overlapping information between those two versions that probably really should be maybe one set of files instead of duplicated content. So that’s one example I can think of immediately off the top of my head. Where are some other places where learning and training people might see this duplication of content?

CH: Yeah, so, well, the copy and paste happens for a lot of different reasons. Sometimes you’ll have product diagrams that somebody has or engineering schematics or something like that that need to be part of multiple divisions. And you’ll see that stuff sort of get copied around, if you will. I think you make a very good point about new versions of the product or because even, even in the case where you wrote perfect content the first time, if you ever could do that. And I wrote it perfectly well for the current release of the product. When the product is upgraded or changed in some way or a new revision is released. When you make those changes, that doesn’t mean all the old product disappears. People are still accessing that older content.

And if you start to find issues in the older content that get addressed maybe through your user support, is that getting pushed up to the newer stuff? Because if the newer stuff did what you described, which is I copied it, I may not even know that that’s now inaccurate in the new release of the manual. Or vice versa, it could be someone using the new product who identifies a problem with our documentation, and we go back and we neglect to fix the old ones, well then all the users of the older product are going to run into that issue sooner or later.

AP: Yeah, and then you’ve got this whole layer too. What if you were delivering to all of these different delivery targets, different delivery formats, you’re using Microsoft Word over here to create perhaps more study guides or scripts or something like that. Then you’re also using PowerPoint over here to create slides. You are copying and pasting perhaps into some kind of software. That will help you with simulations or more audio video kinds of things. So in addition to what you and I’ve just talked about with the different versions, how those are out of sync, if you were copying and pasting content into all of these different tools that create these different delivery types, then this problem is multiplying rapidly because you’re gonna have to go in and touch all of that source for all of those different delivery targets; your Word files, your PowerPoint files, your Articulate content, whatever else. So it kind of can explode pretty quickly in your face.

CH: It sure does. And we haven’t even touched on if you’re in different countries translating to different languages, what do you do about all the translated content? And that can quickly overwhelm you as well.

AP: Exactly. Yeah, so basically this problem becomes exponential, both from say, the versions of your product to service, across the different delivery targets that you’re dealing with. And then if you have to localize that content, all of the, shall we say, bad behaviors that are in your, or let’s call them inefficient behaviors, that’s less judgmental.

CH: There you are.

AP: Yeah, less judgy. These inefficient, behaviors are then duplicated in every single language that you crank out. So yeah, it’s very ripe for inefficiency. It’s very ripe for errors because it is unfair to expect a human being to go through and keep track of all of this. So things go sideways and you even touched on something else a little earlier.

CH: For sure, yes.

AP: And then in some cases, you are pulling content from other departments, other content creating groups. And then that’s another layer of this exponential explosion where if you’ve changed something and someone quote, borrowed that from your group, are you sure they’re gonna know that you changed that? Or you fixed it when they copied and pasted it into their version? And then think about the poor end users, the content consumers who were getting this information they’re probably not getting a consistent picture at all about what you’re talking about because of all this copy and paste all over the place. It’s a mess. Yeah. So let’s go on and try and put a more positive spin on this mess and start talking about the process for identifying this duplicated content.

CH: That’s good.

AP: So what can people do to start kind of taking the pulse of this problem?

CH: I think a lot of it depends on your resources and your organization’s commitment, but there’s always things you can do, whether they’re smaller efforts or larger efforts. So, you know, at the very BMW view or let’s say Cadillac view, if you’re from the 80s like me. You would probably have a huge budget to be able to implement a whole new set of tools and workflows that allowed you to use all sorts of technologies to do what’s called single-source publishing. And that’s where you author in a format neutral format. And then you take those pieces and really you’re creating sort of Legos of content, you could imagine.

AP: I call them puzzle pieces, so yeah. Yep.

CH: There you go, puzzle pieces, Legos. And they fit together in lots of different ways. You can put them together for training. You can put the little pieces together for your user manuals. You can put some of the pieces together for your marketing materials. But the key is that you’re using the same piece in all of those places. And what these sort of advanced tools allow you to do is keep track of all those pieces. Use those pieces in all those multiple places and then still create your deliverables out of those pieces. So instead of authoring directly in PowerPoint when you’re writing a course or writing in Word when you’re writing a manual or maybe working on HTML when you’re creating your website instead of creating content in those sort of single-use formats you create your content in a neutral format and then you have it output to those formats.

AP: Exactly.

CH: And so you still can deliver those end formats that you need to actually put out in the world, but you’re doing it from a single source of truth. And that’s that single content repository. Now that’s the ideal, that’s the perfect one.

AP: Yeah, and you’re not, and you are not going to get to what you just described overnight. You are not going to snap your fingers and that’s going to happen. So yeah, I think you’re headed kind of where my brain was. And that is you can start small with this and you don’t even have to think about tools. You can start very small and start thinking about, you know, where is this duplicated information? Just trying to ferret it out. And one way you can do that, you as a content creator have a very good idea of what is in your set of training content. You’re the people who are creating it. You know where the bodies are buried, where things are going wrong, where you’ve noticed that there’s this duplication. You could also work with a consultant like me who has been doing this kind of stuff for years and can help you by asking the right questions and maybe trigger some things in your brain. Oh yeah, I didn’t think about that. But there is also technology out there like your Harmonizer tool that can help people start to identify that reuse. And I think it’s worth noting it doesn’t have to be things that are exactly the same. Your tool can help find things that are fuzzy matches that are sort of the same because that’s equally valuable as well. And I want you to talk a little bit about how that process works because I think that’s important.

CH: Sure. So the tool we developed, which was actually kind of a companion to our conversion work, is we had the same problems. People come to us and bring those content reuse problems, and they would ask us if we could help them in some way, because when they’re converting content, even if they’re going to move to some neutral format or they’re just moving from, say, Word to FrameMaker or FrameMaker to something else. That was a lot of the work we were doing, but they would bring us lots of duplicated content. And sometimes at that conversion stage is a good time to nip that a little bit or make some headway against those duplications. So we developed Harmonizer as a tool that was very format neutral. It just basically extracts all the text from whatever content you have and puts those into blocks and then it compares every single text block to every other text block and it’ll tell you which ones are all the same, which ones are close and that close can be pretty far apart actually. So I could do things like if I had a sentence and I told you when you go to the store pick up some milk and then somewhere else I tell you to pick up some milk when you are at the store. Those aren’t exactly the same. And in fact, if you do a word-by-word analysis, they’re completely different. But if you do a harmonizer style analysis, we use some linguistic algorithms to be able to tell that linguistically, those are essentially the same thing, or at least very close in what they’re describing, even though the words and the letters are all in a different order.

AP: It’s the intent of that sentence, basically. Yeah. Yeah.

CH: Very much, yeah. So we detect that as well and put that into groups. So then you can look and you can say, okay, I’ve got this block of text. It says this. Here’s all the places Harmonizer will highlight where they’re different, sort of like a diff tool so that you can see, oh, I use the word or here and I use the word and in this other place. Or maybe I used one version of our product name, in some of the content and I am using a different version of the product name in another part of the content. Or maybe I’m comparing two products and their manuals are 75 % the same content just every now and then the product name is mentioned and that has to be different. All of those things can really illuminate why you have duplication. It can also help you find those places where maybe you’ve made corrections in one place and haven’t got to those other places because you might see, oh, this paragraph is the same except we added a warning at the bottom, do not do something. We better tell everyone else that warning in all the other formats that we’ve created. So that’s kind of what Harmonizer does. It’s not a magic bullet. It gives you a very large, well, if you have a lot of content, it’ll give you a large report if you’ve got a modest amount, you’ll get a modestly sized report. It’ll scale to whatever amount of content you want to feed it. What we do is we use it very strategically. And for instance, we can use it to identify just why you have maybe close but not matching content. So maybe you’re using inconsistent wording in different places. We can identify maybe if you have already some standard content, we can identify if there are places where maybe it varies in ways you didn’t expect. So you can check your standard content libraries if you need to. There’s all kinds of ways it can be used, but at its core, it’s again, just giving you those matches and helping you see, really shining a light on where your content is as far as redundancy.

AP: And one thing point I want to make here is it really doesn’t matter what tools you’re using to create content. This work you can do is not dependent necessarily on those tools. Like I said, you yourself can kind of do a self-service thing where you start to think more deliberately about where you think content is. You can work with a consultant who can help you figure this out. You can use a tool like Harmonizer to help dive deeper and really find this content. So there are all these layers that you can do. And the first layer is you can start thinking about that yourself. So there’s a lot of options there. So once you have started to identify this duplicated content through whatever those methods are that we just talked about, it’s time to get into a reuse strategy. And you’ve already touched on this really well. The core of that reuse strategy is you have a single source of truth for every piece of content, every piece of information, there is one version, one format-neutral version that you can then pull into all your different delivery targets and all your different types of content. So that’s kind of the core of that. Once you know where that duplication is, you can start coming up with this more formal reuse strategy. And I think you also pointed out to the copy and paste that is like the morning light going off, you’ve got duplicated content. There’s copying and pasting going on. That’s what you want to try to eliminate with the single source of truth. Give people a little idea of the benefit of the single source of truth. And I’m talking about both for content creators and for the content consumers because it falls on both sides, the benefit of that single source of truth.

CH: For sure it does. Content creators know this. We’ve already touched on when there’s a problem found or a change needed in the documentation. Maybe the product’s changing or was updated. If it’s software, who knows? Maybe we’ve added a new menu item. So we need to add that to the documentation. Well, if we’ve got a single source for everything and everyone draws from that source, we update that source and it will flow out into all the other channels without any real effort. Now, you can simulate this with your copy-paste activities, but you have to really formalize how you do copy-paste. So you’ve got to only copy from say the source of truth, not from each other or something like that as a starting point. If you can’t actually implement true, single source tool chain. Another area though where this really impacts is on the quality of the content you’re delivering to your readers and your consumers. We all know and I deal with this all of the time and this should be make everyone feel a little bit better that even a giant company like Microsoft has this problem. I work in SharePoint quite a lot. And SharePoint has a lot of different versions. It’s been around forever. One of the biggest challenges I have is when I go look for answers, and this isn’t to pick on Microsoft, by the way. Every software company, you could probably find some of this.

AP: Absolutely.

CH: But I go looking in the content for something, I’ll read it one way in one place. I’ll read something a little bit different about the same feature in another place and Sometimes they’re just describing them in two different ways Because maybe one was written by the engineering team and one was written by the marketing department Maybe another version was written by the training department. So that’s going to happen. But then I also run into a lot of places where it’s not easy to tell when this stuff was even created. So it might be very old stuff that I’m looking at that no longer is even applicable. All these issues become simplified if you’re doing that single source of truth because you can start tying together a strategy to deal with that. When you just publish stuff out there and it all gets sort of thrown out in a fire hose to your consumers, that can become a very big challenge for them when there are all these inconsistencies in different language styles or different ways of writing the information.

AP: And if people are using all the different content that’s available out on your website to make a purchasing decision, and it doesn’t just have to be the marketing content, they can be looking at the product content. They can be looking at the publicly available training content. If they are getting mixed messages, different information that should be talking basically about the same thing, that can be a huge turnoff and it can hurt you financially because people will be like, I’m not comfortable buying this product or service because I’m getting mixed messages in the content that’s available out here. The bottom line is people don’t care what department or what your organization is like, what your hierarchy is, what your tree is, whatever you want to call it for your different departments and your management. They don’t care about that. They just want a consistent message, consistent information and they want to get it from wherever they find it and they want to be sure that it’s the same message they get regardless of what quote, department’s content that they’re touching.

CH: Yeah, when I’m working with your product, your product is really what I, how I see you. I see you through the product. I don’t see you through your departments and your channels and whatever organizational structure you’ve created to manage your company. So I think that’s a really important point you make to really make sure that that product experience is consistent and clean. And doing this, you know, even if all you’re doing is just trying to make things more consistent than addressing the redundancy issue can help just in ensuring that we’re presenting that unified view of our product to the world.

AP: This conversation really has probably given people a lot of food for thought. There’s a lot to think about when we’re talking about this duplicated content, redundant content. If we want to kind of back up a little bit and give people maybe one or two pieces of advice on where to get started, even if it’s starting small, what are some things that people can start to do now to start thinking about this bigger picture of duplication, reuse, single source of truth? Any recommendations there?

CH: For sure. So the first thing is you’ve got to tame a little bit of your Wild West if you’ve got that of content. So if I can just go on the corporate network and start willy-nilly looking around and copying and pasting stuff out of anywhere I can find it, which is sometimes the case, that’s probably a big area where you’re creating a lot of content entropy. So you need to think about that. And it may just be even a training issue. It may be a network organization issue. But you should start considering how you can make the authoritative repository accessible to everyone and then limit where they’re getting stuff to that authoritative repository. You don’t have to implement a whole new content management system and tool chain to do that. You can do that using permissions, using training, and having regular contact between the groups that create the content that’s getting copied around. So making sure there’s some interface between them so that they can coordinate and know that they need to coordinate these content activities. A lot of times that simple piece just gets overlooked because a lot of companies really treat content as kind of the afterthought. I’ve built the product, okay, hurry up, make a manual, do some training, do whatever, because we’re product-focused. And so it’s kind of natural, but you really need to see your content as an integral part of that product that you’re delivering so you can get started with just using the tools that you have and working on the processes and the consistency with which you apply those tools. You can also start strategizing for the future. So you can look at, okay, maybe we need to figure out, first of all, how much money is it costing us to copy and paste a lot? Again, knowing how much duplication you have, and then you can put estimates on, okay, if I’ve got all this amount of duplication, how much does it cost to make a change to this manual if we are to ensure that it gets to all the delivery channels, including marketing, training, all the languages, all the manuals? How much does a change cost? Once you start quantifying that, you might find out there’s a better budget than you think for working on this problem.

Again, you’re going to have to look at your content itself and figure out how much redundancy there is. So planning that strategy, figuring out how much it’s costing you, all of that can be very helpful, I think. And then ongoing maintenance. How are we going to maintain it? I’ve been to a lot of organizations where they’ll do a big push to clean things up and they’ll say, okay, we’re going to hire someone, we’re gonna get some new tools going and man, we’ve fixed it, right? And so they fix it. And then three years later, they’re in the same boat they were in because they didn’t really follow up on that. They didn’t plan to maintain the content. Nobody was charged with the duty to ensure that we were adhering to the strategies that the tools were providing and nobody really had the responsibility to look at that stuff. So if you’re going to make the investment, you have to also have the follow-through. And a lot of times that involves consultants, because let’s be honest, if this is the first time I ever do this, I’m not going to do it very well. And I usually don’t get a chance to do this 100 times. I’m not going to do this over and over in my organization.

AP: Yeah.

CH: But if you find a consultant, you can find someone that’s done this 100 times for a lot of different organizations. And they already know where all the pitfalls are and where all the trouble is. And they’ll help steer you in the right direction the first time. Because you don’t get a lot of bites at this apple. Like, your company’s not going to say, oh, just keep working on content reuse for the rest of time. They’re going to want to see some progress.

AP: Exactly. Yeah, and it comes down to return on investment. You do not do these kinds of things for fun. You’re doing them for business reasons, and business reasons include making money and getting a return on investment on any kind of investment in technology, and that includes content technology.

CH: Absolutely.

AP: Chris, this has been very helpful. I think this is a good place to wrap up. Thank you so much for your insights. I think you’ve given people a whole lot to think about.

CH: Well, I appreciate the conversation.

AP: Thank you for listening to the Content Strategy Experts Podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post How reuse eliminates redundant learning content with Chris Hill (podcast) appeared first on Scriptorium.

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If you’ve taken the courses at LearningDITA.com and you’re interested in starting a DITA project, check out episode 163 of The Content Strategy Experts Podcast where Bill Swallow and Sarah O’Keefe talk about the steps you can take to get funding.

“Showing up with cookies never hurts, but what is your executive’s motivation from a business point of view? What are they trying to accomplish in their goals for this next quarter or month or year, and so on? You need to show them, assuming that you can, that moving to structured content, moving to DITA, and changing tools is going to help achieve those business goals.”

— Sarah O’Keefe

Related links:

Content operations ROI calculator
The business case for content operations
Content operations from start to scale
LearningDITA

LinkedIn:

Bill Swallow
Sarah O’Keefe

Transcript:

Bill Swallow: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk to you about next steps after LearningDITA, how to get your boss to sign off on a DITA project. Hey everybody, I’m Bill Swallow.

Sarah O’Keefe: And I’m Sarah O ‘Keefe, hi.

BS: So yeah, we’re going to talk a little bit about what to do after you’ve completed your learningDITA.com courses and you have some DITA knowledge under your belt. So I guess we’ll start off with completing the courses. You pretty much have a working DITA environment then after you complete all of the courses on learningDITA .com, you have a batch of topics, a batch of tasks, a batch of other types of files, a map, you have a publishing scenario, you have some reuse going on. So it kind of makes for a neat little proof of concept package. But now that you’ve got that, how do you bring it to management? How do you sell it as we want to move forward in this direction?

SO: We’re assuming, of course, that I think a lot of the people that do LearningDITA, they come for different reasons. And a big chunk of it is just, I need to learn this because I want to be more marketable. I want to get a new job. I want to have a chance at the jobs that require DITA information or DITA knowledge.

BS: Right.

SO: But I guess what we’re focused on here today is this question of, all right, so you’ve run through the courses and you’ve decided that this is potentially a good idea for your company, for your employer. You really want to advocate for “we need to move our content into DITA because it feels like this is a good idea for this particular organization.” So what do you do next? And at that point, you’re right, you’ve got a proof of concept and that may be enough to show to your peers and maybe your immediate manager just to let them look at that. Almost certainly the next thing they’re gonna ask you for though is to take some of your content because the learning ditto ducklings are only gonna get you so far. They’re gonna say, well, how does this apply to our content? So probably you’re gonna have to go off and do some…

BS: Haha.

SO: …test topics or some test content using your actual live content. I think that’s probably step one. The key thing though, I think to recognize is that DITA and structured content is not just a tool. You’re not going to your manager and saying, hey, I need $500 for a piece of software or even a thousand.

BS: Mm-hmm.

SO: You can of course do this potentially with source control, which is at least free in theory, free but not cheap, right?

BS: Haha.

SO: And, but the effort of, for example, taking five or 10 or 50,000 pages of word content and moving it into DITA is really significant. And so you’re talking about a big, you know, departmental or even enterprise effort to make this happen. And so the bottom line is that somebody needs to agree that this is a good use of your time and or resources, which means you need an executive sponsor.

BS: Right. So how would you start moving up the chain to have those discussions in order to, I guess, get to an executive sponsor or how would you frame a pitch to an executive sponsor then? If you are convinced this is the right direction to move in, you have your proof of concept, you are hopefully moving some of your actual real-world content into DITA to beef up that proof of concept to pitch. What are the things we need to start thinking about?

SO: I think that many of us that live in this technical writing, technical communication world tend to be really interested in new technology. Something new comes along, we’re like, oh, this is so cool and I can’t wait to use it and I can’t wait to apply it and it is delightful and fun and new and different and nerdy. That pitch, you know, look at this, this is so cool. That doesn’t work unless you’re selling AI, then it pretty much works. But the question you have to ask is who is the person that’s going to fund this project? And the more money you need, the higher up the chain you’re going to have to go. And what motivates that person from a business point of view?

BS: Haha.

SO: Right? I mean, showing up with cookies and things never hurts, but what is their motivation from a business point of view? What are they trying to accomplish in their goals for this next quarter or month or year or whatever? And you need to show them, assuming that you can, that moving to structured content, moving to DITA, changing tools is going to help achieve those business goals.

BS: Mm-hmm.

SO: So the number one most obvious way to do this is to show cost avoidance, right? There’s a decent amount of research that says that if you’re using desktop publishing tools, you’re probably spending something like 50% of your time doing formatting work as opposed to content work. And the formatting automation that you have with structured content, gets you out of that formatting work. So you can basically say, hey, we were spending 50% of our time on formatting. Instead, we’re going to write some transforms, and then we’ll be done. We’ll have push-button processing, which is a pretty clear cost avoidance and a pretty clear gain. And we have a calculator for this that addresses looking at those issues, which we’ll make sure to put in the show notes.

BS: Mm-hmm.

SO: But there are other levers that may matter more to your executives and to your leaders than cost avoidance. Time to market is a big one.

BS: Mm-hmm.

SO: Can we get this stuff done faster? Not necessarily cheaper, but can we get it out the door faster? Or do you have these delays of, oh, I still have to reformat it, and oh, now all my numbering is wrong, and I have to go back through and fix everything, and it’s just a nightmare. Can we get a competitive advantage? Can we do a better job of supporting the brand? Can we do a better job of translation localization and expanding what we’re doing? You need to really understand where’s the business going and why? What direction is it going in? It is really, really common after a merger to have a situation where you have two or three or 15 mutually incompatible content development systems. And what you really need to do is bring them all together in the same way that the products are being brought together and the company is being brought together into one unified thing so that you can sell, you know, products A, B, and C, which used to belong to different companies as a unified set. Well, you need the content to also be a unified set, which pushes you towards a unified approach. And if that’s, you know, if DIDA can solve that for you, then that’s a story that’s gonna be compelling to a leader who’s dealing with merger headaches.

BS: Mm-hmm.

BS: So finding a way to kind of translate what you need to do to expedite and streamline your work to align with the company goals, or at least the goals of essentially the person with the money who’s going to make this effort happen.

SO: Yeah, and know, expedite and streamline is really useful and in and of itself doing your job more efficiently as opposed to less efficiently is generally a good idea. I think it goes beyond that into additional factors. When we talk about, so did a reuse is a great example, right? You walk into this presentation and you’re like, Conrefs are the coolest thing ever and look at these keys and look at what I can do with scope, right? And you’re…

BS: Haha.

SO: …you’re the people you’re presenting to are like what what what they have no context they don’t care if they’re software engineers you can maybe talk to them about like object-oriented things and how you can you know whatever but no you walk in there and you say okay um you know how we have this problem where your content over in this bucket contradicts the content over in this other bucket. And the reason is that we copy and paste from A to B, and then we update A, but we don’t update B. And they’re like, oh, yes. And then if right now you’re going to bring up that Air Canada issue with their chatbot that had incorrect information, which is a great example of this, where almost certainly what happened was that the chatbot was fed a bunch of information that wasn’t kept up to date.

BS: Mm-hmm. Yeah, they have no context for what you’re talking about.

SO: Or they were fed the incorrect information to begin with, well, that shouldn’t happen. You should have a single place where you stash all of that information and then you just push it to all of your endpoints, such as a chat bot. And, you know, solving those kinds of problems so that the company doesn’t get embarrassed slash sued slash held liable for making mistakes with their content is valuable. And that is you know, different and arguably more important than we can do it better, faster, cheaper.

BS: Mm-hmm. So yeah, it’s really avoiding those risks that you have in producing content where you can have inconsistencies. If you’re doing things right, you will write once, use everywhere by reference so that the same copy goes out in every place it needs to go. Are there any other things that we should really start looking at with regard to risk management there?

SO: One of the biggest challenges with making a change in tools, whether DITA or anything else at all, is that people, people who are not consultants really hate change. Actually, we hate change too. We’re just in the business of inflicting it on other people, but when the shoe is on the other foot and somebody’s advising us, we’re just as bad as all of you. Hi, everyone. Yeah. It’s pretty bad.

BS: Mm-hmm.

BS: That is true. That is entirely true.

SO: So, okay, so we all hate change, right? Change is bad. And change is perceived as being risky, right? Because there’s the thing I’m doing right now, which I know how to do, and I know where the problems are, and I know it’s inefficient, but I know how to get around it. It’s all known.

BS: Mm-hmm.

SO: And when you walk up to me and say, hey, I found this cool new way of doing content and it’s gonna be awesome and we’re gonna solve all these problems and it’s gonna be so great. My reaction as a human is A, I don’t believe you and B, this sounds like change and change is bad. So what you have to do is you have to convince me that making the change is less risky than not making the change.

BS: Mm-hmm. Yep.

SO: And, there’s a lot of things you can do to mitigate that, but probably the biggest one is to start small and do like a proof of concept and show some stuff and say, look, you know, we have this ongoing problem and I’ve solved it over here and look at how this just works. And I made this little update and look, it percolated into five different locations automagically and isn’t this cool. So to start to build that confidence and that trust and that knowledge, that understanding of the techniques or the technology or you know the thing that you’re trying to convince people to use to switch to. But the unknown, whatever that unknown is, is always going to be perceived as being riskier than the known, even when the known is bad. Like known bad is actually easier than unknown good.

BS: Mm-hmm.

BS: Mm-hmm, right, because you’re asking people to take a step forward in the dark.

SO: Right. And, you know, the dark is bad and I don’t like it. So now there you get into other issues. We’re talking here mostly about how do you deal with leadership and leadership is looking at it and saying, you know, is the risk worth it? Is the funding worth it? They have X amount of funding, some number. They have one hundred dollars and you’re asking for 50. But there’s eight other people also asking for fifty dollars and they have to pick.

BS: Mm-hmm.

SO: You know, two that are going to get $50 a piece out of their eight projects. So your pitch has to be, you know, you’re competing almost certainly for limited resources within your organization. So it has to be a good pitch. I mean, you have to make a compelling argument and, you know, con -KeyRefs are really cool is not actually a compelling argument.

BS: Yeah, how does it impact the bottom line of the company?

SO: Yeah, how can I fix these issues that we are wrestling with as an organization? We have localization problems, stuff we don’t, you know, we’re not managing our content properly and we get all these problems in localization. We’ve got writing issues, our warnings are not standardized and that’s gotten us into trouble because, you know, we got sued and these two documents didn’t agree with each other and they pointed out the discrepancy and that had real-world implications. We’re having trouble delivering content that complies with the EU directives, the machiner directive or the product documentation directives, because we don’t have enough control over the content that we’re delivering. Those are conversations that need to happen, and underlying that is, and so if we use DITA and we redo reuse and we do this and this and this and we automate our formatting,

BS: Mm-hmm.

SO: We can address these issues, but you have to start with the business problem and not with the feature.

BS: Mm-hmm. Right. Yeah, Conrefs are cool is definitely not a selling point out of the gate.

SO: I mean, it works for me, but you know.

BS: Well, but if you frame it the right way and get the executives on board with the business reasons for moving, you might actually get the executives saying, hey, con refs are cool.

SO: Right, now the big challenge here is that, you know, we’re talking about leadership as this amorphous thing, but it turns out that what’s gonna happen almost certainly is that the priorities change as you go up the line. So your tech com manager has one set of priorities and a vision or a, you know, amount of stuff that they’re looking at.

BS: Mm-hmm.

SO: And the director above that is looking at something different because tech com is just a part of their responsibilities. And the VP above that, again, so you have to understand what messaging is going to work at every level in the organization. And accordingly, provide the proper message or a message that is going to work.

BS: Mm-hmm.

SO: So ultimately, this comes down to know your audience, know who you’re talking to and what their priorities are and figure out how, whether and how. I mean, we should start with, does this actually fit into the game plan? I mean, is this the right solution for your organization? If you’re convinced it is, then how do you communicate that in a way that is understandable to your non-interested in content leadership?

BS: And then magic happens.

SO: And then magic happens.

BS: So that’s a big leap from doing a LearningDITA proof of concept course, more or less, to doing an executive pitch. And I know we covered a lot of ground here, and there are a lot of things that we still have not even discussed. But I guess in the interest of time, we do have a lot of resources available to you to start thinking in this direction, being able to put that pitch together, get the data that backs up your position that you do need to move if you are looking for a move into DITA. So we will put a bunch of these resources in the show notes. Sarah, do you have any particular ones in mind you’d want to share?

SO: So I mentioned the Content Ops ROI Calculator, and we’ll get that in there. There’s also a chapter that I wrote called the Business Case for Content Ops, which sort of goes through all of these different factors and the risk management issues. We haven’t really touched on compliance, but that’s another key factor that tends to play into this. That is available both on our site and then, you know, the larger Content Ops book is out there now and available for free. So there’s a whole bunch of interesting stuff in there that might be of use. So we’ll post all of that and links to some of the white papers that are floating around that may be of use to our listeners. And beyond that, if you’re, you know, working on building this case out, I would say feel free to reach out to us and we’ll do the best we can to help.

BS: And that sounds like a good place to close. Thank you, Sarah. And thank you for listening to the content strategy experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post What’s next after LearningDITA? (podcast) appeared first on Scriptorium.

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In episode 162 of The Content Strategy Experts Podcast, Bill Swallow and Christine Cuellar discuss the benefits of single sourcing as part of your content strategy through the example of two things they love: coffee and beer.

“We know companies that have moved away from a do-it-yourself approach because they had maybe two or three different people putting in half to almost full-time work on the publishing system and not on other facets of the company’s core business or the writing. They were simply there to keep everything working. It just blows my mind that on a scale where you have hundreds of writers contributing content, you are saying, Okay, you three people are going to be solely responsible for keeping this thing up and running so that they can produce their content, rather than having a system that’s designed to keep itself up and running.”

— Bill Swallow

Related links:

The truth is out there
Content as a service (white paper)
Prerequisites for efficient content operations (podcast)

LinkedIn:

Bill Swallow
Christine Cuellar

Transcript:

Christine Cuellar: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we’re talking about how you can brew a better content strategy through single sourcing. Hi, I’m Christine Cuellar.

Bill Swallow: and I’m Bill Swallow.

CC: Hey, Bill, thanks for being here today.

BS: Hey, thanks.

CC: So what I mean by brewing a better content strategy is that both Bill and I really love coffee. Right now for both of us, we’re recording it fairly early times in the morning. So actually we’re heavily reliant on coffee and other caffeinated sources to enable this conversation. Also, Bill, I know you like homebrewing beer. I like drinking beer. I have no idea how to homebrew, but I do enjoy beer as well. So we just thought that beer, coffee, drinks in general actually have some good analogies for single sourcing, which can be part of your content strategy. And it’s something that’s been coming up more and more in a lot of conversations with clients and people that are interested in content strategy so we thought this would be a good topic for today. So Bill I’m gonna kick it over to you for our first really big-picture question. First of all what is single sourcing? What do we mean when we say that? Let’s kick it off there.

BS: All right, so in a nutshell, single sourcing is writing content once for multiple purposes. It’s about as simple as you can get. It could be authoring centrally, it could be authoring collectively in a group or centrally as a single person for a wide variety of publishing needs, whether it be for different audiences, different output types, or what have you.

CC: Okay, yeah, that’s great. So how does, what are some ways that single sourcing can start to mimic drinks? Coffee, beer, any of that?

BS: We could take the example of multiple output formats. So traditionally with single sourcing, we’ve been doing that since I think the mid-90s. I remember working in. Oh, that’s based in the name. I remember working in Doc to help back in, I think it was 1996, to produce online help and written manuals from the same source using a very high-tech convention called RTF, which is basically the backbone of Microsoft Word at the time.

CC: Ooh.

BS: So that was fun. I had many nightmares about RTF coding. I solved problems in my dreams using RTF. It was a scary time. Yeah, I was essentially fully immersed, let’s say that. But in many ways, to take the same analogy, you’re producing a wide variety of, or you’re producing a core set.

CC: That’s when you know it’s really stressful. Yeah, that’s not good.

BS: of stuff that needs to go to many different places. And it’s a lot like, let’s say a coffee roaster since it’s early in the morning and we want to talk about coffee. A coffee roaster is going not going to sit there and roast a pound of beans, put it in a bag, and then send it off, and then roast a pound of beans, put it in a bag, send it off. You know, they’re going to roast, you know, a ton of beans, 10 tons of beans, however, you know, many that they can fit into their roaster.

CC: Yep.

BS: and do it all at once. A couple of things that allow them to do, one, it streamlines the process and speeds things up because now they have a wealth of products that they can then put in large bags for distribution to restaurants or cafes or what have you. They can put it in smaller bags and send it out to the grocery stores. They can do their online mail orders for coffee that way. Five-pound bags, one-pound bags what have you or they can even grind it up themselves put it in k-pods and people can destroy the planet with those I’m not a big fan of those the k-cups and pods but It also helps them create a more homogenous product because they’re working at a very large scale So and they’re they’re producing things in very large batches So with all their beans together in one roaster, they are able to produce a very consistent product that way.

CC: Yeah, that’s great. That’s a great analogy and that definitely makes a lot of sense. So when it comes to both coffee and beer, there’s a, you know, the commercial option that you just outlined, which is really helpful. And there’s also usually a DIY component. I mean, you can home brew beer, you can home brew coffee, of course, and do that in a bunch of different ways. Like it can just be your coffee pot or you can get all fancy and do, you know, all the little like other fancy things you can do with it, all of which I’ve done and they’re all leaving my brain at this moment. French roast, okay, that’s one. Anyways, it should have been more top of mind. But is that also an option for content?

BS: It can be. Looking at a commercial solution versus a DIY or DIY approach, it’s not so much a question of which approach do you prefer to take. Because I mean, yes, I’m a hobbyist when it comes to brewing beer. But I still, and really for the past 10 years, I stopped brewing because there were just so many high-quality

CC: Okay.

BS: Options on the market at that point. I’m like, why am I spending my time doing this when I can just go to the store and pick up? one of a thousand different types of beer but you really need to look at it from the standpoint of how much money do you have to spend on a commercial product versus how much time and commitment do you have to doing it yourself if you do it yourself.

CC: Yeah.

BS: The results can vary, but if you put the time and energy into it, you can produce some amazing results, but there is always a hidden cost of time and labor. When I used to actively brew, I brewed with a buddy of mine and we would do it every Monday night. So he would either come to my place with his equipment or I would go to his place with my equipment. And from like six o ‘clock until about midnight, we would be either brewing beer, cleaning equipment, bottling beer, doing whatever. It was a commitment. I mean, it was six hours a week, and literally it was every week. Unless we had something going on and we took a bye week, we were doing that every single week because there is always something that needs to be done in the process.

CC: Hmm. Yeah. Yeah, that’s a big time commitment. And I like that you mentioned that not only was there a big time commitment in actually brewing the beer, but also the cleanup, also the prep work. Yeah, I like that there’s this there’s other factors that you don’t think about that also are involved in doing it yourself? Is that also something that applies to, you know, single sourcing and content strategy? Are there a lot of factors that can come into play?

BS: Oh, absolutely. I mean, if you’re a homebrewer, you have to enjoy the monotony of cleaning. And it’s the same thing if you’re doing it yourself with putting together a publishing system and an authoring system that relies on, let’s say, open source tools and a lot of human care and feeding. You have to really enjoy the monotonous.

CC: Hmm.

BS: Droning kind of day-to-day maintenance work. You know, when you’re brewing, it’s, it literally is 90% cleaning, 10% brewing. Because I mean, you start, you know, you have to have everything completely sanitized. And once you get the pot boiling, you know, it’s, it’s doing its thing for about an hour. You know, you might be adding, you know, some hops here and there, or some other flavoring agents, depending on the type of beer you’re producing.

CC: Wow.

BS: But, largely, you’re just waiting for an hour. So while you’re waiting, you’re cleaning other stuff that you’re gonna need later in the process. And then you take five minutes to move to that next step, and then you have to wait for the beer to cool down. So then there’s another round of cleaning. Okay, all the stuff that I used to make this batch of beer now needs to get cleaned. And then you go to put it into the fermenter, and now you have to clean everything else. And the cycle just continues.

CC: Yeah, oh wow.

BS: It’s the same thing with these with, you know, with a do-it-yourself approach. And it’s not to say that it’s wrong or that it’s not ideal, because you can learn quite a lot in a do-it-yourself environment. But it does come at a cost. You know, you’re going to spend I actually we know companies that have, you know, moved away from a do-it-yourself response, because they had, you know, maybe two or three different people putting in half to almost full-time work on the publishing system and not on other facets of the company’s core business or the writing or what have you. They were simply there to kind of keep everything working. And it just blows my mind that on a scale where you have hundreds of writers contributing content that you are saying, okay, you three people are going to be solely responsible for keeping this thing up and running so that they can produce their content rather than having a system that’s designed to keep itself up and running.

CC: Yeah. Would you say that because it sounds like with a DIY approach, it can work, but it has to be very intentional and you have to be very realistic, like you said, about the cost and the time that’s involved. And I can see from like a coffee analogy. Do companies, I guess, default or kind of slide into a DIY approach without really thinking about it. Because I could see with like coffee, I do love enjoy, okay, with coffee, I do enjoy attempting to make lattes and, you fun stuff with my espresso machine, which I have like a really crappy one right now, but it’s really fun to play with. And I’ve practiced a lot with it. But still, the best cup that I make does not compare to like, basically every one of our local coffee shops here, I would 100 %… enjoy their stuff more than what I make. It’s just fun to play with. But it’s not realistic for me to go and buy, you know, the best coffee from one of the local places every single day. So instead, I have a coffee machine and instead I brew stuff here at home, you know, every day for my regular coffee addiction. And then when I want to be fancy, I go to a coffee shop. But just, you know, I don’t have the capacity to go somewhere else every single day. So that’s kind of why I’ve just

BS: Yeah.

CC: Not really thinking about it, slid into a DIY approach. Is that also something that happens with companies that they kind of DIY until they realize there is a different way to do it? Is it kind of a default method if that makes sense?

BS: Yes and no. And the decision as to why a company might choose to do it themselves rather than purchase a more packaged or commercial solution. It really varies. You know, you have some companies that, yes, they started out small. They hired someone perhaps who had some serious technical chops and was able to put together something very, very, very slick.

CC: Okay.

BS: But you know, they were the only ones who really knew how it worked. And as they hired more writers, you have varying degrees of varying degrees of, I guess, capability and willingness to learn how this thing works.

CC: Mmm.

BS: You know, so if, you know, for example, let’s say that they’re doing Markdown and they have all of these, you know, different scripts that run and fire off and they produce, you know, all these different outputs. It’s very, very slick. I’ve seen lots of implementations like that and that, you know, they’re actually pretty cool. But, you know, as you hire more people,

CC: Hmm. Oh yeah, that’s true.

BS: You start getting into, why do I have to write and mark down? I always keep forgetting to use this character instead of this character when starting a bulleted list. Or I always forget to, you know, close off the end of my, you know, my title or what have you, anything like that. You know, why can’t I use Microsoft Word? Why can’t we move to just using HTML? Why can’t we move to XML? Like, you know, you start getting a lot of that pushback and the pushback may not be direct.

CC: Mm.

BS: So you have cases at that point where you have quality slips starting to make their way into the core content set. And that’s where things get a little hairy. But to go back to your analogy, making coffee at home, you can have, there are plenty of really, really good espresso machines out there that you can buy for home, but it will never compete with that $8,000 Italian espresso maker that your cafe, you know, your choice, you know, the cafe has in town. You know that they, you know, they paid a ton of money for and they’ve spent hours and hours and dollars and dollars to train their staff on how to appropriately use it and clean it to produce that same, you know, questionably but perfect cup of coffee every single time.

CC: Yeah.

BS: You know, same thing with buying coffee, you know, buying beans or buying grounds. You know, these companies you buy and you know, people will laugh. I make the same comments about, you know, certain beer manufacturers. But, you know, you buy something like Folgers. It’s not, you know, in my opinion, it’s not the world’s best coffee. You know, I just don’t like, you know, what it tastes like.

CC: Yes.

BS: But every single time you buy a, they’re not tins anymore, are they? I think they’re more like plastic jugs of coffee. But you buy a jug of coffee and it’s always gonna be the same every single time. And you can say the same thing about Budweiser. People may say, oh, Budweiser, why would you ever drink that? It’s horrible. It’s like, yes, but it is absolutely consistent. You can buy a Budweiser anywhere in the United States, in the world.

CC: They’ve evolved. Yeah, yeah, yeah.

BS: Open it up and it will taste exactly the same.

CC: That’s true. Yeah, that’s true.

BS: You know, there are really no differences there. And they spend quite a lot of time and energy into ensuring that that product is consistent from every single batch that’s made in every single location across the world because they have breweries all across the world that produce this stuff because shipping it from one location around the world is just not gonna work. So all of these different locations have their equipment set up just the right way. Their chemists work, yes chemists, their chemists are working to make sure that the pH balance is perfect every step along the way as that beer is being produced. So otherwise, if you’re brewing yourself at home, your equipment may vary. I’ve put stuff together literally with duct tape and string.

CC: Hmm.

BS: I made it, I made a shower head out of a nine-inch tin foil pie pan

CC: Hahaha! Wow. Yeah, that’s a DIY way.

BS: Because, it was available, you know, to sparge or to clean my grain as it was, being run off as the beer was being run through. Or, you know, even if you roast your own beans at home, you know, the level of quality is going to vary, you know, because you are likely using your, your oven to do that roasting. And if you step away for a minute too long, or if you didn’t get the temperature setting quite right, so if you don’t have a digital temperature setting, or maybe your heating element is a little futsy, so sometimes it might be 310 degrees, sometimes it might be 332, who knows? There are lots of elements that can go wrong in a do-it-yourself environment.

CC: Yeah, that’s true. And like you mentioned earlier that a lot of that comes down to the people, not only the equipment that you’re using, but also the people. Like, do they know what they’re doing? Do they know why they’re doing it? And especially as you introduce more people, like you mentioned, if it’s you and your buddy that are brewing beer together, that’s another person that’s been added. And, you know, in a scenario where one person’s not as interested or, you know, just doesn’t know as much about the process that can really change things and vice versa. Like if you have two people that both really know what they’re doing and both really enjoy it, that can lead to a really good output.

BS: It can vary because yes, we both knew exactly what we were doing and But you know you start biting heads. I want to do it this way No, I want to do it this way if we do it this way. You’re gonna get this result I don’t believe you I think if we do it this way, we’ll get this result and yeah, we’ve had You know, we actually tried it and tried two different techniques of brewing the same beer and they came out very very different so

CC: That’s true, yeah.

BS: You know, it is what it is. But yeah, it all comes down to that quality control element, you know, and, you know, generally when you have a bigger commercial system, you can kind of get there a lot quicker. Now, it’s not going to do everything for you, but it’s got the pieces already laid out and it’s got some recommended workflows and processes for using that system to produce consistent results. Whereas with a do-it-yourself, you’re kind of left at your own devices and how well you document your stuff and how well you regulate it.

CC: Absolutely. Yeah, which can is it in and of itself is another time commitment. Yeah. So we’ve talked a lot about consistency, which is a really important element of this, but also personalization is another important value that you can get out of single sourcing. How does that? So let’s say if we put it in our coffee or beer analogy, let’s say you’re personalizing your packaging for, you know, different restaurants and different cafes or whatever. How does single sourcing make that more effective or what does that look like?

BS: Well, at the core of it, like for example, if you’re putting stuff out to cafes and restaurants, you’re typically not going to use the same level of pomp and flash on your branding packaging that you would if it was going to a grocery store. Because you want that product to pop off the shelf in the grocery store and catch people’s eyes, whereas at the restaurants and so forth, as long as the logo’s on the bag so they know they got the right thing.

CC: Yeah.

BS: It’s usually just a pretty nondescript bag with a description of what’s inside it. But in the end of the day, you’re not producing different product for these different groups. You’re producing the same product that’s going out to many different people, depending on who it needs to go to. So you may have one conveyor belt that takes the beans down to where they dump them into 25-pound bags or 50-pound bags. And then you have this other conveyor belt that goes off and does the one-pounders.

CC: Mm-hmm.

BS: And so it’s really streamlining from that. You’ve spent the time to build this, I guess, storage heap of beans that you then are distributing to many different people. So at that point, you’re taking from that same source and you’re partitioning it off as you need to for multiple different consumers.

CC: Mm. That’s true.

BS: Same thing with single sourcing. I mean, you have a core collective of content that ideally is all written in the same tone and voice. Aside from all the mechanics of how content gets produced, it needs to be written in the same tone and voice for…

to be able to blend and remix and be able to send it out to different audiences so that it doesn’t sound like, you know, eight different people, even though eight different people may have written the content, it doesn’t sound like eight different people wrote different parts of whatever it is you’re delivering. It’s a little jarring to go from…

CC: Hmm. Yeah.

BS: You know, one style of writing to another within the same paragraph or within the same, you know, chapter of a book or, you know, series of topics in an online help system. It can get very distracting. So, you know, in that case, you do need some attention toward how all these people are developing the content and what tone and voice they’re using. But aside from that, with regard to packing your…

CC: Yeah.

BS: You know, packaging your output from a content standpoint, you have things like, you know, templates that drive the look and feel of what the various outputs are going to look like. So templates or, you know, style sheets or what have you to produce these things. But also behind the scenes, you have other conventions such as variables, conditions. Perhaps you’re leveraging some form of reuse. So that you can kind of mix and match your content, turn things on and off depending on, oh, this is going out to, you know, an advanced user or this is going out for our, this is going out for our premium product. And this one’s going out for our base-level product. And base level product has features A, B, and C, but our premium has features D and E also tacked on. That type of thing. So you’re not rewriting content for these.

CC: Mm.

BS: You know, very many different outputs, but rather you are pulling from a single, you know, managed source of content and, you know, mixing and remixing and turning things on and off to produce that desired result.

CC: Yeah, absolutely. And then so taking that a step further, when you when it’s time to start selling your coffee or selling your beer in a location in a different country or different region, what happens then in that localization process? I mean, I’m assuming all of that is involved plus more. Yeah.

BS: Oh, plus more, because then you have language on the packaging and so forth that needs to change. But more importantly, with any kind of food-based product, and particularly with alcohol, there are different rules that govern how things can be sold, what you can say, what you can’t say on the packaging. We’re pretty loosey-goosey here in the United States where you can say anything. You can put out a package that is the same size product and say now 20% more. And you look, it was a 16-ounce box before, it’s a 16-ounce box now, but now it says 20% more.

CC: What? Maybe they meant air, 20% more air in the package.

BS: I guess, I guess, but you start going overseas and the nutrition labels need to change. You have to take very different stances when you’re listing ingredients. There are certain claims you can and cannot make on the packaging and in the advertising. And when it comes to alcohol, particularly, there are different rules that govern what can go into it that can be then passed off to a consumer and what you have to disclose and what you can’t disclose. And I go back to one of these things, and it’s not so much a governing rule anymore as far as you know how strict it is but there’s the Reinheitsgebot I hope I am pronouncing that right but it’s basically the German purity rule for beer and it basically governs and says that beer can only be made of three components water barley and hops and they omitted yeast even though yeast is what does the fermenting process because at the time they created the law, they didn’t really know about it. But yeah, essentially those four ingredients are the only things that can go into beer for Germany Not so much a rule anymore, but it’s it’s it’s an example of you know, if you were to produce something And call it something. Yes, if you were to produce beer and call it beer, but you’re making beer with Barley and corn and rice, you know, so something that let’s say Budweiser does. Would that technically be beer? Maybe not in Germany. So what do you call it? How do you package it? Can you sell it? Again, it’s not so much a thing anymore. It’s more of a historic note, but it kind of shows the differences in what you can do and what you can say in different countries.

CC: Oh, okay, interesting.

BS: Likewise, when you go to different, when you publish for different locales, you have not only different languages, but you have different fonts that you have to consider. You have different complete character sets, you know, so, you know, there’s, you know, the more the Latin character set that we use throughout the United States and throughout Western Europe. We start going more into Eastern Europe and you start getting into needing to use a Cyrillic alphabet.

CC: Mm-hmm.

BS: Certainly you move into Asia and now you’re starting to look into, oh, I’m going to need you know a completely different character set a double bite character set to put these things together and You know in some places you’re gonna have to change the complete layout of your content as it as it gets published because you know certain languages they go from right to left, not left to right, so that’s a completely different change and you know a lot of that you bake you hopefully are baking into the infrastructure that you are driving your content production with and not doing this by hand every time you need to send something out.

CC: Yeah, I can’t even imagine. Yeah, that would be a lot. Well, so for organizations that may not have adopted this single-sourcing approach yet, what are some factors? I mean, we’ve talked about a lot of them, but what are some either factors or like pain points or experiences they may be having that signal, hey, maybe it’s time to start thinking about this? How would you sum up those indicators?

BS: I think the biggest indicator is that you have a very overworked team of people who are spending their time on everything but their core job. So their core job should be producing content, developing content. It should not be formatting and reformatting content to produce it.

CC: Hmm. Yeah.

BS: You know, it certainly should not be copying and pasting content from one place to another and then making sure that any change to that copy and pasted content is reflected in the two or eight or 16 or 150 different places they pasted it into last time. You know, that’s a lot of busy work and you know, a lot of things that I hear, especially from small teams, is that they reach a point where they are so busy.

CC: Yeah.

BS: And making so little progress on new content development because they are spending all their time, you know, prepping for publishing, prepping for publishing, you know, prepping for publishing literally should be content is done. And that should be your prep for publishing. It shouldn’t be, okay, now let’s apply this template and let’s reformat everything. And now let’s send it off to the translator and oh, we got it back. Okay, now we have to reformat it so that it fits in this language because German is now, you know, eight pages instead of five. You know, it shouldn’t be fixing these things. Those are things that really should be handled automatically and, you know, allow the content developers to do what they were hired to do, which is develop the content.

CC: Yeah, exactly. Yeah, allow them to be able to do what not only you hire them to do, but I’m thinking that they’re more passionate about. That’s where their passion is. That’s why they’re here. I could see that being very discouraging if you’re passionate about the content and you spend almost all your time on formatting and other stuff. That sounds awful. And it would be discouraging. And I’m assuming leads to burnout, lead to, you know, high turnover.

BS: Yeah.

CC: Because you’re not getting to do what you want. You want to write content.

BS: True, although some people do thrive in that environment and they love that they love the fiddly bits, you know, and, you know, you’re not going to make them happy by taking that away. But then again, it’s like, you know, as you know, your company is growing, you’re producing more stuff, you need to produce more content, you need to do it quicker, you need to do it at a higher quality. You know, you’re you’re publishing at a higher volume, you’re adding more languages. You know, at that point, it’s like, do I keep that person happy?

CC: Oh, yeah.

BS: Or do I focus on what we need to get done?

CC: Yeah, fair. And maybe they can have some say or you can include them in what’s what the big vision is. But yeah, like you said, that you can’t always just make one person happy with the system. There’s all these other people that may also not be happy because of, you know, not having an efficient process and a way to pump out a lot of content at scale in a way that’s still quality.

BS: Mm-hmm.

CC: Still consistent. Yeah.

BS: Yeah, and there is a risk there as well because those who put together the DIY approach, they may love that. You know, I mean, that that’s something that they built from the ground up. That’s their baby, you know, and you’re taking their baby away. That can lead to some big problems.

CC: Yeah, makes sense.

BS: You know, either you lose that person who has all the publishing knowledge, even though you may be transitioning away from that system, they kind of know how it was set up and they know they know where the I hate to use the analogy, but they know where the bodies are buried in their infrastructure, and what made it tick. And you don’t want to lose that knowledge. Instead, you want to try to hopefully work with them to stand up the new one and give them some governance over how that runs. That might be an approach. But it does get tricky.

CC: Yeah, it makes sense because at the end of the day, it’s still about people. The people that you’re working with, you wanna make sure that they’re, the people on the team that are creating the content, it’s still about them, it’s still about the people at the other end of the screen or book or whatever, whatever kind of content you’re writing. Yeah, it’s still about people and people are complicated. We are.

BS: That’s putting it lightly.

CC: Yeah, that’s my deep wisdom for the day. That’s what comes from five cups of coffee in the morning. And on that note, I think we have exhausted every part of this beverage analogy for single sourcing and content strategy, but it was really helpful even for me to hear. I mean, I knew some of this, but there was a lot of this that I hadn’t thought of in terms of something very tangible like drinking coffee or drinking beer. So thanks Bill for exploring this with me. I also just love talking about coffee anytime it’s possible. So yeah, it’s great.

BS: It was fun.

CC: Well, yeah, thank you so much for being here and thank you for listening to the content strategy experts podcast brought to you by Scriptorium. For more information, visit scriptorium .com or check the show notes for relevant links.

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In episode 161 of The Content Strategy Experts Podcast, Sarah O’Keefe and Alan Pringle share their ideal world for enterprise content operations software, including specific requests for how content management software needs to evolve.

SO: “When I envision this in the ideal universe, it seems that the most efficient way to solve this from a technical point of view would be to take the DITA standard, extend it out so that it is underlying these various systems, and then build up on top of that. I don’t really care. What I do care about is that I need, and our clients need, the ability to move technical content into learning content in an efficient way. And right now that is harder than it should be.”

AP: “Oh, entirely. And I would even argue it should go the other way, because there is stuff possibly on the training side that the people in the product content side need. So both sides need that ability.”

SO: Right, so give us seamless content sharing, please. Pretty please.”

Related links:

The business case for content operations (white paper)
Ask Alan Anything: Resolving pain in content operations (podcast, part 1)
Developing a strategy for learning content
Prerequisites for efficient content operations (podcast)

LinkedIn:

Sarah O’Keefe
Alan Pringle

Transcript:

Sarah O’Keefe: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. You may have heard that Madcap has added a learning content management system called Xyleme to their portfolio. In this episode, we are providing an entirely unsolicited roadmap to the vendors in this space, including but not limited to MadCap, for enterprise content ops software as we move forward. Vendors, welcome to the show and think of this as your roadmap to success and call us if you need help. You totally do. Hi there. I’m Sarah O’Keefe and I’m here with Alan Pringle.

Alan Pringle: Hey there, I’m not sure this is the best idea, but we’re about to find out.

SO: Yes, it’s going to be great. We will totally not get in trouble. Alan, let’s dive in and maybe get in trouble as fast as possible. What is the number one item on our list of demands for content ops enterprise software?

AP: Going to vote for seamless content sharing and with a little asterisk here this is not just about us as consultants I think this is as much about our clients and what we have seen over the past few years in the content operation space. We need some kind of way where you can author in a component content management system and then turn around and use that information, for example, in a learning content management system. And there’s, well, exactly, and I was just getting to that. There’s some logistics here. It would be maybe nice to have the same content model underlying all of this, but considering the different authoring audiences, I don’t know if that necessarily has to be the case.

SO: And does that have to be DITA?

AP: I really I’m not even sure if it’s possible. We can discuss that right now. It’s really not possible. I don’t think.

SO: Yeah, as far as I know, nobody can do this right now. You cannot take DITA content and efficiently ingest it into a learning content management system. If I’m wrong, call me.

AP: Yeah. That said, I do know some people, including our clients, who are on the learning training side, and they have chosen to use DITA as their model. But that is not true for every learning organization on this planet, not by a long shot.

SO: And they’re in CCMSs. They’re not in “L” learning CMSs. So they’ve, you know.

AP: Exactly.

AP: The LMS is a target. It is not the place where they are actually building the content.

SO: Yeah. And so, I mean, when I envision this in the ideal universe, it seems that the most, you know, efficient way to solve this from a technical point of view would be to take the DITA standard, extend it out so that it is underlying these various systems, and then build up on top of that. I don’t really care. What I do care about is that I need, and our clients need, the ability to move technical content into learning content in an efficient way. And right now that is harder than it should be.

AP: Oh, entirely. And I would even argue it should go the other way, because there is stuff possibly on the training side that the people in the product content side need. So it’s both sides need that ability.

SO: Right, so give us seamless content sharing, please. Pretty please.

AP: Yes, and I’m going to throw the ball to you this time. What’s number two on our list of demands?

SO: Number two on our list of demands is a unified portal for content delivery. So setting aside the authoring issue for a minute, you know, maybe it’s unified, maybe it isn’t. Give the end user a seamless user experience where they’re going in and they can get all the content they need across all the different, you know, technical content types. Now, there are a couple of specialized portal vendors that do have this and have solutions in this area. But if you’re going to position yourself as we are the solution for all things content, then this needs to be in your portfolio in some way, not just, oh, you know, go talk to this other vendor. So I think a unified content portal, again, I don’t really have a strong opinion on how this needs to be done from a technical point of view, other than words like seamless and good customer experience.

AP: I do have some opinions on how technically it should happen and that is copy and paste from one tool to another better not be part of this picture at all because today it is and it kills me. Especially on the product content side, we got over this hump of automated formatting or manual formatting. We’ve pretty much handled that. I think on the learning side, they’re starting to understand they should not be futzing and manually touching things. And right now, especially on the training content side, to get things to go to different delivery targets, there’s entirely too much copying and pasting between and among tools. It’s like every delivery portal requires you to do that. This is the 21st century people and it should not be happening, no.

SO: So okay, I would like to revise my opinion too. I do have some demands and they are those. I am co-signing Alan’s demands. Okay, what’s next?

AP: Hahaha! Okay, let’s talk about classification, taxonomy, because you gotta be able to label your things to sell different versions. If you’re selling software, you’ve got a light version, you’ve got a professional version and maybe an enterprise level solution. You gotta build in that taxonomy, that intelligence. How are you gonna do that? And how are you gonna do it across multiple content types? That’s tricky, that last bit in particular.

SO: Yeah, and so, you know, the terrible keyword here is enterprise taxonomy, right? You have to build out a classification system for your content, both for the authors and for the end users. Like, the end users need the ability to say, oh, I bought the lite version, only show me that. Not, all these enterprise level features that you don’t have. And how many of us have seen the infamous like car manual that says, oh, if you have the XYZ CXE extended edition, you have this feature in your car. Well, I didn’t buy that version and I don’t have that feature and.

AP: That just happened to me with a printer. I will not name the manufacturer because I’ve been happy with it overall, but the user guide, it actually came with a printed user guide, which was shocking for 2023, which is when I bought it. It was like, and then it will do this, and this. And then it’s like a little parenthesis later. And this model only. Well, that’s not the model I have, man. You’re killing me. So yeah, that’s not where you need to be with that kind. New.

SO: Oh man.

SO: Yeah. And you’re not going to run out and buy the upgraded printer or car. That is not happening. Yeah, it’s too late. So OK, so we need labels so that we can do versioning. But additionally, in this sort of enterprise content ops demand, we need those labels to be consistent across shared content. So for example, in the.

AP: Too late.

SO: And I’ve seen this happen. In the technical content, we have free, pro, and enterprise. And then the learning content, we have light, intermediate, and enterprise. And they’re referring to the same thing, but the labels are different. And hey, guess what? That’s not going to work. So fix it and give us a classification system, a taxonomy that we can use across all these different content dimensions. Now again, there are some tools that’ll do this. I mean, there are enterprise taxonomy tools, barely, some people are using them. Many, many, many people need to be using them and are not, so.

AP: There are.

AP: Right, I was about to say many people are using them and even more should be using them right now. And I will almost give people a pass on this one, almost, almost because it’s like get your ops to a certain point and then this can be let’s improve them even further. But having that built in from the get go, that would not be a bad thing either at all.

SO: Yeah, and related to this terminology, the words that you use for different things. If my learning content talks about a door and my technical content talks about a doorway or an entry point or an I don’t even know, then that’s not going to work. So you need to call the thing what it is and do that consistently across all of your content.

AP: Including your marketing content because if you’re talking about brand and consistency and voice this is a huge part of that and I’m sure your marketing department would be delighted for there to be some controls, some kind of corralling of this to be sure people are consistent and give a consistent brand image but the way we refer to things.

SO: All of it. Yeah. Yeah, and it also ties into some, you know, typically some protection for trademarks and those kind of branding and those kinds of things. And this isn’t, you know, the focus of this, but if you are translating or localizing your content, you have to do this work in all your languages, not just your source language.

AP: 100% and if your source language is crap, the translation is going to be crap too as far as consistency and anything else. Yeah, right, degrade.

SO: It’ll be crappier. It’ll always degrade slightly. So yeah, okay. And then what else have we got in our unified hallucinations slash vision?

AP: There’s one more. Yeah.

Yeah, it’s like we want everything. The last one, that’s yours. I’m gonna give that to you.

SO: Oh, so, you know, we’ve talked about unifying technical content, marketing content, help content, maybe UX content, those kinds of things. But there are two other missing pieces, which you touched on marketing, that’s one, and that’s a big one. And the other one is knowledge base, support content. So you know, where are those in this unified vision? All of these things are…

AP: Yep.

SO: …from an end user’s point of view, they look at all of this content, and yet all of it is being done in point solutions, in dedicated, this is only for the knowledge base, this is only for marketing, this is only for tech comm, this is only for whatever. And so we need to unify all this stuff so that there is in fact a unified customer experience. I don’t see a whole lot going on here with knowledge bases. If you look at marketing content, there are a couple of vendors that have ways to take the technical content and push it over or integrate it into the web CMS. But in general, this is much more challenging than it should be. And depending on your web CMS, you may or may not have a path for this at all, other than put it side by side or something like that. So I would…

AP: And news, yeah, and news flash, guess what? The people reading your content do not give one about how you classify this as sales or marketing or KB or whatever. They just want the information and they want it right then and now. And in a way they can get to it very quickly. They don’t care if you think this is quote marketing content. Just give it to them and make, be sure it’s correct, please. P.S. That’s also very important.

SO: Yeah, and I mean the reality is that people’s websites reflect their org charts and there are all these points solutions and different people own different chunks of the website or subdomains or whatever. But okay fine you know if you’re going to have these acquisitions and tell me how great it’s going to be then show me the results, and this is what this is what we want.

AP: Well, we are asking for the world’s, we might as well get all of our demands out here and that is certainly one of them. All these tools really kind of support these increasingly false kind of classifications based on org charts and whatever else, but the end result, the end content result, shouldn’t necessarily reflect those things, there should be unification there, not these weird distinctions that are based on the way people report to each other within the company, because your customers don’t care.

SO: So while we’re making friends and influencing people, we did also come up, as always, we did also come up with a list of things that we do not care about. So what you got?

AP: As always, as always.

AP: Yeah. I do not care that you have four or five different solutions that do different things under your brand, especially if they don’t talk to each other. If they’re just these multiple tools speaking to different audiences, how is that really any different than, you know, different people owning different things? I don’t, there’s a disconnect there for me, a huge one.

SO: Yeah, and, you know, single, we have, you know, single vendors with lots of tools, which may or may not integrate. We have multiple vendors with individual tools, which again, do or do not integrate like the level of or the degree of difficulty in integrating these various tools does not appear to be particularly tied to whether they live under the same roof or not. You know, fix the integration. I don’t really care about the ownership. I understand that from a business point of view, you do, that’s fine, but fix the integration. And so to my vendor friends who are currently apoplectic, you know, have a drink, whatever, of choice. But your mission, should you choose to accept it, is to address our pain points and our customers’ pain points and actually deliver on the challenge of unified content. And I am so looking forward to seeing progress in this area. Alan, any closing words?

AP: I think I am going to throw back to the Willy Wonka and the Chocolate Factory movie character Veruca Salt and say, “I don’t care how, I want it now.”

SO: Thank you for listening to the Content Strategy Experts Podcast. I have nothing to add to that. Brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

What do you want to add to this wish list? Leave your thoughts in the comments below, or let us know on LinkedIn!The post Our demands for enterprise content operations software (podcast) appeared first on Scriptorium.

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In episode 160 of The Content Strategy Experts Podcast, Alan Pringle and special guest Phylise Banner talk about the limitations of the learning management system, the rise of the learning content ecosystem, and more.

“I think about enterprise-wide applications. Consider the tools that are used to generate help solutions. Let’s just use Jira as an example. You have a knowledge base, enterprise-wide, and everyone at the organization has access to ask a question or search the knowledge base, or something like that. That’s where I want to go, that’s what I want to see. I want my learning experience platform to be like that. I want a knowledge base that I can tap into any place, anytime, anywhere. And then, have my mastery checked in the ways that I want to have it checked. ”

— Phylise Banner

Related links:

Wrangling the Meg of learning content
Content operations for elearning content (podcast)
Developing a strategy for learning content
Flexible learning content with the DITA Learning and Training specialization (white paper)

LinkedIn:

Phylise Banner
Alan Pringle

Transcript:

Alan Pringle: Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize and distribute content in an efficient way. In this episode, we’re talking about how people in the learning space are addressing challenges in their content operations. What do those changes mean for learning management systems? Is this the end of the monolithic LMS?

Hey, everybody, I’m Alan Pringle. Today, we have a special guest, Phylise Banner. Phylise, welcome. Please tell us a little bit about yourself and your background.

Phylise Banner: Sure. Thanks for having me, Alan. My name is Phylise Banner. I’m a learning experience designer. I have, I want to say, over 25 years. I did the math the other day, actually. It’s about 27 years in higher education, and corporate and non-profit government learning design. Before that, I worked in data visualization and information design. I came into this field in a little bit of a different way, although there’s other folks who came in it the same way that I did, considering this from an information perspective rather than from a teaching perspective.

The minute I started working in the field, I was fascinated by educational theory, and pedagogy, and philosophies, and andragogy, and hudagogy. And techno-hudagogy, thanks to my friend Bill Pelz, there. But throughout the years, I have watched technology evolve alongside learning theory, and I’m fascinated by that. I had been in the content strategy space this whole time, both from the information design, data visualization side, also going over into learning design. I’ve had a focus on content strategy all along. I’ve known folks at Scriptorium for probably 25 years.

AP: Well, probably so because we’ve been around since ’97. And we have crossed paths in conferences probably more times than we can tell people. Indeed.

Well, with your background, you’re the perfect person to talk to about this, in the learning management system, LMSs, and what’s going on with them because we’re certainly seeing a shift. And you’ve got your feet even more firmly planted in the learning space than we do. I’m very interested in your perspective. I think a good place to start, especially for people who may not necessarily be in the learning space, maybe even a little more content focused, let’s start with a quick definition of what a learning management system is and what it does for an organization.

PB: Oh, I didn’t know that was going to be on the test, Alan.

AP: Curveball.

PB: Curveball. I’m not going to have the ultimate, perfect definition of what a learning management system is. If we want to talk about a content repository and what different content repositories look like, overlay a content repository, content management system with registration. The ability to create courses, to offer courses and show progress through those courses. Whether it’s simply content, or content interaction and assessment. I would say those are the features that would differentiate a learning management system from a content management system.

Early on, when learning management systems started to become more widely available, the joke was all it is is a content management system with the ability to register thrown on top of it. But there are so many pieces that are built into learning management systems these days, which is why the behemoths got to become behemoths. With student privacy, the data that’s being collected, learner privacy, the interactions between student information systems. Setting up the databases behind the scenes, so that it would be possible, back in the day, for a student information system, akin to Banner, Banner is one of the systems, to be able to talk to the data in the learning management system.

AP: Sure. The people that use these LMSs, and I’m talking more about the trainers, the learning people, what’s the general process for creating content and getting it into one of these LMS systems? What’s their process? Or, does it vary from system to system?

PB: It varies from system to system. It also varies from practice to practice. If we want to talk in any learning space, imagine a training session … We’ll talk about a physical learning experience, where you’re all designated to meet in the same place. You all show up in the same place. Someone walks in the room, drops a bunch of material or folders on the desk, and walks out of the room. That’s how most learning management systems are used. Unfortunately, it’s the way they were designed. It was upload your file-

AP: A dumping ground, essentially.

PB: Exactly. A dumping ground with no context. That’s the same as someone just dropping … I used to do that when I did training. I’d come in, I’d drop it on the table, I’d walk out and say, “That’s what you’re doing to your learners.” If you don’t provide context for your information, that’s exactly what you’re doing to your learners.

The process depends on the tool that’s being used. So we’ll say, am I using one of the big tools. Let’s say it’s Canvas, or Moodle, or Brightspace, or even if it’s Teachable, or Kajabi. It depends on how the LMS itself, or this learning platform, is enabling you to structure a learning experience and upload content, create assessments, enable interactions. The instructional design process or practice needs to happen first.

AP: Right.

PB: We need to design this learning experience. We need to consider how we want the learners to progress through that, how we want them to communicate with each other, with an instructor, with themselves. It’s sort of there’s no right answer to your question.

AP: Sure. That’s true, even on the content side too. It leads into what I want to talk about next. It sounds like dumping ground, or maybe better than dumping ground, there’s still going to be some challenge and obstacles, especially to assign any intelligence to all of this content that you’re putting into these systems. What kinds of things, in general, do you see these people who are creating this learning content, what kind of hoops are they jumping through? What kind of workarounds, what things are they doing to get things to work better in these systems?

PB: I’m going to roll it back a little bit, and talk about when learning content has typically developed, and shared, and reused.

AP: Yeah.

PB: Because that reuse is something that we didn’t think about very much. Not everyone.

AP: You’re not the only industry, either.

PB: Right.

AP: Learning folks, we’re not slamming you at all because, trust us, it is a problem everywhere.

PB: But coming from an information design space, reuse was always in the back of my mind, and classification’s always in the back of my mind.

AP: Sure.

PB: Having always known what a library system could do, what a database could do, how classification could help organize any type of information. Taking a look at learning management systems, and the ability to tag content and content types has been missing.

AP: Yeah.

PB: All along. I remember when I could first build a course in WordPress, and was able to program the heck out of that backend, and classify learning content, classify activities as activities. I also remember Angel, the learning management system, where we could do that within a learning object repository. And then, Blackboard acquired Angel so that went away.

But, I think the struggles we’re up against now to make things talk to one another, our learning content repositories, our learning management systems. If we’re using these old, big solutions, there’s Lectora. I don’t want to go through and just bring out all these names.

AP: Brand name salad, yeah.

PB: Brand name, yeah, salad. But the newer tools are really taking into consideration how we might reuse content. How we might want to, how we might need to.

Some of the things you and I have talked about in the past, and other folks at Scriptorium, are the possibilities of even going as far as using micro-content. Or the DITA learning terms, to really tap into those frameworks to become a little bit more consistent with tagging our content so that we can reuse it.

One of the things that I see, one of the biggest challenges I see right now is you’ve got the training department, and the marketing department, and the documentation department not able to share content, using different systems. You see this all the time, Alan.

AP: We do. We do.

PB: That’s your job. How do we make that go away?

AP: You’re speaking my language. Yes, you are.

PB: Yeah.

AP: We have noticed, we have more clients from the training space now. They are really up against what you just talked about. Reuse and the single source of truth, those are two things that really, a lot of them, their hair is on fire because they are being forced to do copy-and-pasting for different versions. Copying and pasting from one system to another.

PB: Right.

AP: It’s my observation, and you can tell me if this is unfair, that a lot of tools marketed to the learning groups seem very closed and do not play well with others, at all.

PB: Completely. Completely.

AP: Yeah.

PB: We see that changing a little bit.

AP: Good.

PB: Once we started becoming comfortable using APIs and getting things to talk to one another. But the thing that’s still missing is that centralized database of information.

You’ll hear the term learning experience platform being thrown around a lot these days. The way I have seen them used, I have never seen one used to its full potential. If we want to talk about how are we including or taking into consideration informal learning, what I learn in my kitchen about my job just because I happened to learn something that has something to do with something else I’m …

AP: Sure.

PB: Just these tangents and things like that. And, how we capture them.

I am going to call out a product. I want to call out Docebo. The folks at Docebo know I love them. I’ve seen the best approach to learning experience platform, With the standards that exist in the learning space. You’ll need to find someone whose more versed in SCORM than I am, which is the standard for exporting and importing across different platforms. But that’s just taking a package, and downloading it, and putting that package somewhere else. It’s not letting one assessment, or seven questions from one assessment, talk to a different learning experience.

AP: Yeah. I compare a SCORM package almost to an ebook, like an ePUB file, which is basically a container, a ZIP file really, a container file, full of HTML files. A SCORM package is very similar. It is just a container for a lot of files.

I will tell you, one of our clients has been concerned about SCORM packages from an intellectual property, IP point of view, because the second you let that go and it’s just manually uploaded or imported into a system, it can be hard to get controls. But you’ve already mentioned APIs, there are ways to make virtual SCORMs, almost like an API, where you can hold onto it. But the traditional SCORM package, if you just hand it over, I’ve just given you my stuff.

PB: Yeah.

AP: What if there’s an update, what if something’s outdated, whatever-

PB: Exactly.

AP: It’s a big mess. I have also noticed that we will create automated transformation processes to basically create SCORM packages so people can put content into an LMS. The problem is LMS A likes a slightly different version of SCORM than B. Yeah, it is a standard, but there are flavors within that standard, we have observed.

PB: Exactly.

AP: Yeah.

PB: Oh, exactly. Yeah.

AP: That’s another big pain point. But what I’m hearing from you is it sounds like two things are going on. Some of the vendors, the companies are getting wiser with letting people create smarter content, number one. Number two, people are starting to move to those platforms and realize maybe the older ways of having just that LMS sitting in the middle, that pretty much it, maybe is not the way our things need to be. It needs to be connectivity, there needs to be a wider ecosystem of tools that’s not just in your department. It needs to be cross-departments, in a lot of cases, in organizations.

PB: Absolutely. I think about enterprise-wide applications. Consider the tools that are used to generate help solutions. Let’s just use Jira as an example. You have a knowledge base, enterprise-wide, everyone at the organization has access to ask a question or search the knowledge base, or something like that. That’s where I want to go, that’s what I want to see. I want my learning experience platform to be like that. I want a knowledge base that I can tap into any place, anytime, anywhere. And then, have my mastery checked in the ways that I want to have it checked.

AP: Sure.

PB: A lot of times, the learning management systems are talking about being really focused on the learner, and more adaptive. I’ve seen adaptive systems, and especially with generative AI being so widely available.

AP: I wondered if that was going to come up. There we go, the requisite AI mention.

PB: We’ll get there again. The adaptive pieces, what I’m seeing are in content and serving up content.

AP: Yeah.

PB: Adaptive learning means you’re giving me different content because maybe something I’ve searched for. But are you giving me a different assessment? Are you giving me an different option to interact? This is where I see the future of learning experience platforms going.

AP: Sure.

PB: That it’s the experiences that I have will be different, will change. I haven’t seen it well done yet. I want someone to show me.

AP: Well, even on the content side of the world, because we’re focused, Scriptorium, on the product content side of the world. You talk about, “We need to deliver omnichannel content, we need to deliver content, what people want at the time they need it, and the format that they want.” Yes, that sounds great but not everybody is doing it. So again, this is not just about learning folks. This is a problem that’s universal. Yeah, I think there is a lot of room for improvement.

Wherever content is, you have got to have, your source has to have that intelligence built in that lets you do that adaptive content on the fly. A quiz based on your location, and you’re at this particular branch, or at this particular hospital, or this location so you’re going to get this training. If you don’t have that intelligence, metadata, yeah I said, built into that source content, and then it needs to be processed by the various systems, you’re sunk. That goes right back to you’ve got to start during the creation process and get that intelligence built into that content so you can do the adaptive things that you are discussing.

PB: Yeah. You talk about being in that place, or that space, and being served what’s appropriate in that moment of learning need. I’m fascinated by location-based tools. Lidar, iBeacons, like when I walk past this, I might need to learn something different in order to do something past this point. I think all of that is really important.

Let’s go into AI.

AP: Yeah.

PB: We touched on it. We don’t know what might come next.

AP: Yeah.

PB: I’ve embraced it. I love playing in this space. Anything that can help with the … I talk about dreaming drudgery design in development, and anything that can help with the drudgery piece is always welcome in my book.

AP: It’s hilarious you said that because I was about to say we see it as another tool. If it can handle the drudgery of content creation, there’s several things I can think of. It could help you sort. It could help you … Yes, people still index things. Why not let AI take a whack at it? It may not be perfect, but then you can go clean it up. Any kind of pattern matching, that sort of thing, I think it does very well.

Now, we can quibble about should you be going out on open sites and dumping your corporate information in there.

PB: Right.

AP: But if you’re in a closed, large language model that is specific to your company, your organization, why not let it look at your stuff and find relationships that you probably don’t have the time to go dig around and find, and it can. It’s just another tool. Do I think it’s going to replace content creators in any space right now? The only space where I think it might is if you are someone who is cranking out low-quality content, of people who do, shall we say, not entirely truthful reviews on various sites, things like that. Things that can be put together fairly quickly, I think there might be problems for those kind of people, low quality content. But when you’re talking about the spaces you and I are in, I see it more as a tool and not the replacement.

PB: Absolutely. A lot of what I love about this community, we talk about documentation and training on new products, well nothing exists.

AP: Yeah.

PB: We can’t tap into existing content to generate this content. In the learning space, I see so much potential for different types of tutors based on information that we have, existing knowledge.

You talked about intellectual property earlier, and that’s a big deal.

AP: Very.

PB: On the higher ed side, there’s the open education movement, open education resources, and just open education about enabling more access. I’d love to hear your thoughts on what open access looks like in this content space, the struggles we have and maybe what advice do you have for protecting intellectual property, but sharing content? Creative Commons licensing is a beautiful thing, and being able to share learning content would be so helpful but we don’t go there. Companies spend so much money creating from scratch, the same trainings that other companies are creating.

AP: Right.

PB: I just think about all the compliance training I’ve written in my lifetime.

AP: What you’re talking about is a tightrope, and it’s a very difficult tightrope because we are a profit-based society, unfortunately. This is business. It can be very hard to give things away.

I’m going to toot Scriptorium’s horn here for two seconds, in this regard, because what we did is we created a WordPress-based site called learningdita.com, to teach people about an XML specification, the Darwin Information Typing Architecture. Which, by the way, can be a very good fit for learning content. We basically created that where it is out on GitHub, you can download the source files, do whatever, and then you can take the classes for free. This was our thought on that. We are proving our own bonafides in this space, the DITA space, by putting these courses together, but then they benefit people too. And I’ll be blunt, they also benefit our clients because instead of paying someone to pay for an introduction to DITA course, people can take it at their own pace, through this self-paced learning that’s online, and do it that way to get a baseline and it also saves the client some money. It doesn’t even have to be our clients, anybody can go out there and take advantage of this free training and not pay for it.

You really have to think very carefully, bigger picture, how this could pay off. If getting content out there, if providing some open training, open source training to people, it can help you indirectly. It can prove your competence in topics. That’s the angle that I’m coming it. I don’t know if that exactly answers your question, but that’s where my brain has gone.

PB: No, I like that. I wonder, can people reuse and reshape it? If it’s on GitHub, it’s there and someone could take it-

AP: They could take it, and adapt it, and they can take that source.

PB: Yeah.

AP: Basically, the site that we have, a learning management system that sits on top of WordPress, that is ours. That is just one instance, one instance of how you could use this content. If people wanted to take that content and then do something more print or PDF based, or some other format, they can. We’ve even had some other people in our line of work, in different parts of the world, take that GitHub content, translate it, and then create their own instances. In German, in French. That same content is out there and it’s been localized. If you want to, you can go to their learning DITA sites and do it through that language, if you’re more comfortable in say German or French.

PB: There’s nothing to stop someone from taking it and charging for it, either.

AP: If they wanted to, they could.

PB: Yeah.

AP: Again, everything that you said, these are the kind of considerations you have to think about when you put things out there for free.

PB: Yeah.

AP: It’s like you’ve got to let your child go out into the world and do their own thing. I’m comfortable with that, because at the end of the day, a more informed world about DITA, in our case, that is a possible customer for Scriptorium down the road. That is very business-y and maybe even a little repellent to put it so bluntly, but there you have it. There is a case for providing free, open source information, even from a for-profit corporation.

PB: Absolutely. Absolutely. For those of you that are listening that are not familiar with Creative Commons licensing, I highly encourage you to go out and take a look, to see what the different types of licenses are. Because there’s that non-commercial use that I would recommend, in many cases. But, I like to think about learning content and the levels at which we would share it.

AP: Yeah.

PB: I would love to see more collaboration. Not just across departments, but across organizations.

AP: Yeah.

PB: I don’t know how we do that.

AP: And again, there’s goodness to be had, but sometimes in a profit-driven situation, longterm thinking is not the motivator. Short term profits are the motivator, so it gets very sticky in there.

PB: Yeah.

AP: Unfortunately. Because at the end of the day, if you’re a for-profit corporation, you’re not there for the sake of giving things away. You’re just not. With education, I think it’s even a little stickier perhaps, because you are talking about trying to improve people, their knowledge, to give them more information. Where do you draw that line?

PB: I’m going to stop you there and say okay, if we separate this out into knowledge, skills, behavior, attitude-

AP: See, this is the learning person talking right here, and I’m going to sit back and let you do it.

PB: Knowledge, skills, behaviors, attitudes. Let’s think of, what if for skills, because yes there are some skills that are unique, but what if we shared that learning content? I can’t tell you how many times I have reinvented the wheel.

AP: Oh, sure.

PB: Every other learning designer has done the same exact thing.

AP: Yeah.

PB: That’s our job, to continuously reinvent the wheel.

AP: Yeah.

PB: Maybe, we need one giant learning experience platform, where we can have skills. I would say, knowledge, skills … Think about how we’ve learned, and how you want to learn, and how you will learn in the future. I’ve heard people come out and say, “I don’t want to learn from a robot.” You already have been for years and you may not have known that, but you have. The expertise that we’re relying on in any learning experience when we introduce an instructor, we need to factor that in. What does it mean if instructor A has this content that they’re delivering as part of a learning experience, or instructor B has that content and they’re delivering this learning experience? Are they going to be two different experiences? In my mind, yes. They’ll be different, depending on the individual’s expertise that they’re bringing. But is that going to get minimized, will that go away?

I’m rambling on here, Alan. I’m so sorry. But now I’m thinking of influencers, and influencers online, and product influencers. They’re educators, too.

AP: They are.

PB: Where does that content lead us when we’re learning from TikTok, or we’re learning from Instagram?

AP: Sure.

PB: Gosh, I’m all over the place, here.

AP: No, it’s a valid point. I know a lot of people who, they run to YouTube for a video to learn how to do things. This drives me back to the question I would like to wrap, is okay, with all of these changes that you’re talking about, all this sharing that needs to be going on, all this reuse that should be going on, what does that mean for the LMS, from your point of view?

PB: Well, this is a dinosaur I would like to see hit by a meteor tomorrow. I have never been a fan of the learning management system. I think that the information repository with the ability to customize the interactions you want is what an LMS needs to be. Too many times, I have been forced into designing, developing and delivering a learning experience around the limitations of the learning management system.

AP: I have seen clients do exactly what you just said, and they hit a breaking point and they say, “No more.”

PB: Yeah. They’ll sit there and say, “No more,” until someone offers them a solution. What is that solution going to look like? What I see that solution looking like is a lot of pieces that fit together. That it’s app salad, strung together with a central content repository, that can be classified or searched.

There is a learning experience platform out there that you can just create these adaptive learning experiences, and there is no tagging, there is no metadata. I know that they’ve used large language models to generate results, but I still don’t love it.

So for me, the future for me, the meteor may not hit. It may be a slow death. I’d like to be there when they bury Blackboard. Just throw a handful of dirt on that LMS. But I’d love to see someone come up with a solution that helps us stop reinventing the wheel, helps us invent a new form of transportation that we don’t even know about, to push that metaphor a little too far.

AP: No, but I think that’s a very good place to end it. Future thinking, some positivity, but there’s some real work that needs to be done before that.

PB: Absolutely.

AP: Phylise, thank you so much. This conversation went to some really interesting places that I didn’t expect and that is always a plus on a podcast like this. So thank you so much for your expertise, we deeply appreciate it.

PB: Oh, thanks for having me. I love you folks at Scriptorium, I love the work that you do. I love the way that you educate folks. And maybe, someday, we can partner and solve this problem together.

AP: A lot of people would be very happy if we did, indeed.

Thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Rise of the learning content ecosystem with Phylise Banner (podcast) appeared first on Scriptorium.

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In episode 159 of The Content Strategy Experts Podcast, Bill Swallow and special guest Dipo Ajose-Coker share tips for moving from unstructured to structured content.

“I mentioned it before: invest in training. It’s very important that your team knows first of all not just the tool, but also the concepts behind the tool. The concept of structured content creation, leaving ownership behind, and all of those things that we’ve referred to earlier on. You’ve got to invest in that kind of training. It’s not just a one-off, you want to keep it going. Let them attend conferences or webinars, and things like that, because those are all instructive, and those are all things that will give good practice.”

— Dipo Ajose-Coker

Related links:

Challenges of moving from unstructured to structured content with Dipo Ajose-Coker (podcast, part 1)
MadCap IXIA CCMS
Webinar: Everything is Awesome! A DITA Story: A webinar on Dipo’s experience migrating from unstructured FrameMaker to DITA XML
Structured content: the foundation for digital transformation (podcast)

LinkedIn:

Dipo Ajose-Coker
Bill Swallow

Transcript:

Bill Swallow: Welcome to The Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way.

This is part two of a two-part podcast. I’m Bill Swallow. In this episode, Dipo Ajose-Coker and I continue our discussion about the top challenges of moving from unstructured to structured content.

So we talked about a lot of different challenges, and I don’t want this to be some kind of a scary episode for people. Let’s talk about some tips you might have for people, as they do approach this move from unstructured content to structured content.

Dipo Ajose-Coker: Yeah. Now, I would always say the first thing is start small and then scale up. You need to take one example of each type of manual. I used to work with we had user manual, pre-installation manual, service manuals, maintenance manuals, and so on. Some of them are similar in that they’ve got similar type of content, we’re just removing parts of it. But some of them are really radically different. So we took one user manual, and one service manual, and one pre-installation manual, three major types of content. And then you convert that, test it to breaking point. And then, by the back-and-forth that you’re doing in making that the conversion matrix, so fine-tuning that conversion matrix, you’re more confident that, when you then throw the rest of the manuals in there, you’ll have a lot less cleanup. I’m never going to say that you’re going to have zero cleanup, you will always have cleanup. But you will have a lot less to do in cleanup, in manually going to look for those areas where the conversion didn’t work.

I mentioned it before, invest in training. It’s very important that your team knows, first of all not just the tool, but also the concepts behind the tool. The concept of structured content creation, leaving ownership, and all of those things that we’ve referred to earlier on. You’ve got to invest in that kind of training. It’s not just a one-off, you want to keep it going. Let them attend conferences or webinars, and things like that, because those are all instructive, and those are all things that will give good practice. And share that in between. Maybe have a train-the-trainer type of program, where there’s one person who’s your champion within the company, and who does all the conferences, and does all that. And then comes back, and resumes, and trains the rest of the staff.

Your migration must be detailed in the planning. You’re basically, “Step one, we’re going to do this. Step two, we’re going to do this.” I create phases of those because you might have to repeat a whole phase again at a different point in time. The phases, for example, verification of the content. Was what I put in what came out? When I compare my Word document and I compare the XML of it, does it match? And then, you’ll do a few things, and then you’ll publish. But you’ve got to verify again because some of those mechanisms, like I said, pushing content at publication, picking the wrong key, using the wrong DITA val would create different content. So again, you’ve got to do that verification again. You’ve got two verification phases, in that case.

BS: Yeah, I think that’s actually a really good point. Because we also see that, even when you have a smooth migration of one particular content set, once you move on to a different manual, there might be something unique about that one that suddenly, everything goes sideways when you try migrating. And you don’t have a home, or you don’t have a structure planned for a certain piece of content that you probably didn’t realize existed.

DA-C: I’d say also, you’ve got to be flexible. No matter how much planning you put into place, the plan is always 100% correct until you start executing it. And it’s at that point that you’ve got to be flexible and be able to say, “Okay, well things did not turn out right. Let’s adapt to that.” And by the end of that phase, we’ll be able to take a look back and say that, “Okay, well this went wrong at this point. Can we fine-tune it? Or is it something that we should just anticipate that it will always go wrong?” If you know that it’s always going to go wrong, you’d better able to plan for that. You know that you just need to add that step to the phase, to the next phase, in that check that this was as expected.

Look at the long-term benefits. That translation example, in that first boom, bang, “We already paid for the translation six years ago. Why do we have to pay for it again?” The long-term benefit is that, six years ago, you paid 100 grand for your translation, say. And then, every year, you were paying 20 grand because of every update. So that’s six years of 20 grand, 120, plus your 100 initial cost. Then, you switched over to DITA, where they’ve promised you your translations are only going to cost you 10 grand a year from now on. Yeah. Well, that first hit is going to still be maybe not 100 grand, but let’s say 80. People balk at that and say, “Well, you said it’s going to be 10.” No. Because for the next six years, you’re only going to be paying 10. So in the long term, it is eventually costing you less. Apply that to whatever part of it, of the scenario you want. You find long-term, it’s best.

If you look at what’s happening today, and I will only mention this once, ChatGPT and training large language models, and that. Well, training large language models on structured content has proved for efficient than just hoovering up content that does not have a semantic meaning to it, attached through the metadata. You know, attributes that you add onto that saying, “This is author information. Or this is for product X, version Y. But there’s a version X as well available.” All of that, if you look at it in the long term, those companies that have already moved to DITA are going to be better able to start quickly switching their content, repurposing it, feeding it to their large language models. Using it to train their chatbots. Their chatbots are better able to pick up micro-content.

If you look at Google today, you search for something and you get this little panel. You know, that YouTube video that tells you which section of the video answers your question. That’s micro-content. And having structured content, because you’ve got smaller, granular pieces of information, enables you to provide that sort of granularity of answers. Your users are going to be happier in the long term.

You need to, let’s say, plan for compliance. We’ve already mentioned that. Look at how you’re going to manage your terminology because that’s another aspect. How are you going to, first of all, tag it? Making that decision is your information architect. Which element are you going to use? UI control, or are people still going to be using bold italics around that? And how are you going to enforce that people don’t use that non-standard use of the correct elements?

Localization is another area that you need to … First of all, warn all your stakeholders. If there’s people that are going to be people for … Explain. Give this example that I just gave, that in the longterm your translations will end up costing less, the turnaround time will be faster, and so on. And, those issues that we used to have in that world, there was an update while it was out for translation, and then we had to pick up the PDF and highlight all those points that changed in between those two translations. That used to be such a headache for us.

BS: Those were the worst.

DA-C: Totally. And your CCMS is able to do that for you, in that it’ll send only the changed content. It can lock out content, I can lock out things that you don’t want translated.

There’s nothing worse than sending your translations out, and you know that all your UI variables have been pre-translated as string files, and what you’re doing is just importing those and that then puts the correct term inside of those tags. Well, if you send it off and then your translators then decide, “Well, no, I think that’s a better translation for that UI label that is inside,” you’re just causing a whole load of trouble that’s going to come up and catch you later. I’m speaking from experience, again. Things that will get changed during a translation, your system can lock those things out.

Another top tip is to invest in a quality translation service provider. Having a translation service provider that understands structured content is better than one who is just used to doing words translations all the time. They’re better able to understand the concept of, “Well, this topic is reused, so when I’m creating my translation, I must also translate with reuse in mind.” Looking at not breaking tags in content, not moving things around in the content, all of that training needs to be present as well on your translation service side.

And, you’ve got to leverage your technology for efficiency. Major tip there is create workflows, create templates. Templates will help your authors know that, “Well, for this topic type, these are the sorts of information types that I need to put into it. This particular topic needs a short description, and this one doesn’t.” So by picking the right template, they’re guided. They can concentrate, they can focus on creating their content.

Workflows. Oh God, workflows. That’s another big one in that review and approval workflows. What has been reviewed, what has been approved? If you’ve got content that’s already been approved, and then somebody goes and makes a change to that already approved content where it was not due for a change, that will cause problems during your audit. Because remember, you said you could prove to them that this topic was at version X, and we didn’t touch any other topics. Well, if you sent everything off, and then an SME made a change to one of the topics because they saw a mistake in there.

Well, that’s not a good enough reason, when it comes to audit. That, “I saw a mistake, so I made that.” No, you need to follow engineering change management processes, which say that for every single change … I’m talking in regulated industries. For every single change, I must have a reason for change. I saw a type in the text and I just decided to change it is not a good enough reason. If you saw that, then you must create a defect and add that to the change log that you’re submitting to say that, “We changed these. Oh, and by the way, we were trying to fix this error. But as we were going through, we saw that somebody did not put any full stops in all the sentences in this topic, so we decided to raise that as an improvement opportunity, and we added to the docket.” So we have a reason why those other topics, which were initially analyzed as those are the ones we need to change, what are these other topics that got changed? Well, we also created a ticket for that and put it in there.

So leveraging workflows will allow you to force things to go also to the right person. How many times have you forgotten to send it through to legal?

BS: Yeah.

DA-C: Using the final approval workflow, make sure that okay, well the initial engineers are excluded from that because they’ve already done their workflow, but we’re sending it for that final boss-level approval, and legal can finally sign off on it. Those are the things that are parts of what your tool can do.

Your tools can also help you find out what went on where. By being able to roll back, “Well, we made this change. We thought it was an improvement, but eventually it was just a stop-gap, we’ve made a better one. Let’s roll back to before, and then create that new one that documents this.” Well, your toolset, your CCMS is able to do that for you. We used to have to do this, again talking from experience, going into the archive database, looking for one that was roundabout the date of the change that we made, picking that one out, unzipping it. And then, the whole load of trouble.

BS: I remember doing that.

DA-C: Use and leverage technology. Yeah.

BS: I remember doing that quite a bit, especially when we’d have someone from legal running down to the engineering floor and saying, “Hey, we need to find X version from X date, and see if it contains this particular sentence.”

DA-C: Yeah. Yeah.

BS: That was always fun.

DA-C: Oh, yeah. Totally.

BS: And then, needing to roll back and then reissue all the other following versions with the correct change.

DA-C: That was always a nightmare. I can remember, there was one particular incident where someone, again, had gone off on holiday. Again, ownership of documents and so on. This change had to be made. There was a stop shipment, which means there was a defect found and the regulatory body said, “You’re not allowed to sell any more until you fix this, and you make sure that it’s all done.” So connect stations, everyone. This person’s on holiday, so we go into the archives, look through, find what we thought was the right one. Only, that person that person had not checked in the real last version. So the corrections were made to the last but one version. And then, when you published it, some of the information that was supposed to be in there was not in there. But we were looking for that specific phrase, we found it. We thought, “Yeah, everything’s good.” Only by the time it goes out and gets off to the regulatory body. Then they say, “Well, what happened to all these other changes then?”

So investigation goes on, and then you’ve got to find out why. Those are all parts of the reason that pushed this organization to say, “Look, we need something that handles this a little bit better.” We had a stop-gap interim period where introduced an SVN system, but that was on a local computer, and we were able to recreate repositories on everyone’s. But that relied a lot on discipline as well. People checking in stuff. And you could always break locks. I spent so much time fiddling with the SVN system on every update. It was just a lot, too much. The CCMS was able to resolve, let’s say, 80% of all those kinds of issues. I’ll never say that a tool is of 100%, but it does help quite a lot.

BS: Yeah. Having had some SVN or GIT collisions in the past that we’ve had to unwind. Branches, upon branches, upon … Yeah. Having a system that can at least manage some level of that automatically is a godsend.

DA-C: Totally.

BS: Well, Dipo, thank you very much. I think this will pretty much wrap the episode. But thank you very much for joining us.

DA-C: Oh, thanks for having me.

BS: Thank you for listening to The Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Tips for moving from unstructured to structured content with Dipo Ajose-Coker appeared first on Scriptorium.

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In episode 158 of The Content Strategy Experts Podcast, Bill Swallow and special guest Dipo Ajose-Coker discuss the challenges of moving from unstructured to structured content.

“I think we could make broad categories of challenges as tools, technology, people, and methodologies, and I think we’ll just dive into these because they’re not necessarily independent—some of them flow one into the other. One of the most complex and challenging parts is implementation. Changing over to a new tool also involves changing processes and training the staff. Basically, some documentation teams struggle with that initial learning curve.”

— Dipo Ajose-Coker

Related links:

MadCap IXIA CCMS
Webinar: Everything is Awesome! A DITA Story: A webinar on Dipo’s experience migrating from unstructured FrameMaker to DITA XML
Structured content: the foundation for digital transformation (podcast)
Misconceptions about structured content (podcast)
Unpacking structured content, DITA, and UX content with Keith Anderson

LinkedIn:

Dipo Ajose-Coker
Bill Swallow

Transcript:

Bill Swallow: Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997 Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about the top challenges of moving from unstructured to structured content. This is part one of a two-part podcast. Hi everyone. I’m Bill Swallow, and today I have a special guest. I have Dipo Ajose-Coker from MadCap IXIA. Dipo, hi.

Dipo Ajose-Coker: Hi there, Bill. Thanks for having me on.

BS: Can you let our listeners know a little bit about yourself?

DA-C: Yeah, I’ve got a background in languages and IT. I did a bachelor’s in that and then, well, almost 20 years ago, I made the move to come over to France, and as teaching doesn’t pay that much, I thought I’d retrain and to do something that still combines languages and informing people, and I found a master’s program for technical writing and that’s how I got into that. I did my master’s and I’ve been working in medical devices, financial technology companies as a technical writer, as a technical editor. Then a couple of years ago I got that itch to change professions again. I wanted a little bit more creativity in my writing, and so I went to content marketing, and so now I’m a product marketing manager for Madcap software representing MadCap Flare, Madcap Central, and Madcap IXIA CCMS.

BS: Excellent. Today we’re going to be talking about how you might be moving from unstructured to structured content and what some of the, I guess, challenges are in that move. I guess we’ll jump right in. I’ll just ask you what is one of the key challenges that people face?

DA-C: Yeah, I think we could make broad categories of challenges as tools, technology, people and methodologies, and I think we’ll just dive into these because they’re not necessarily independent, some of them flow one into the other. One of the most complex parts, the most challenging parts is the complexity of implementation. Changing over to a new tool also involves changing processes, training the staff. Basically, some documentation teams struggle with that initial learning curve. You’ve got to learn a new markup language, you’ve got to learn a new way of writing. Then you also need additional help mostly from IT. You’re getting teams that never used to be involved in helping you put in your Framemaker or whatever it is that you’re using. You didn’t need your IT department in setting up Microsoft Word, for example, where that used to be the writing tool, setting up CCMS involves a little bit more of a lift that documentation teams might not be experienced with or be comfortable with.

BS: The implementation really checks all of the complication boxes, doesn’t it?

DA-C: Totally. You’ve got so many more people involved and you’ve got time scales and everything as well to consider.

BS: I guess let’s dig a little bit into that. You mentioned conversion, learning a new markup system. What goes into that type of an effort?

DA-C: Okay, let’s look at the first thing. Everyone goes to school learns to write English, French, whatever language it is, but then when you want to start moving to structured content, it’s usually an XML-based language, XML markup, we say. It’s not real coding, but it is still learning a new vocabulary if you want a new syntax, a new way of expressing yourself. The fact that it’s structured then means that as you do in your own language, you have a certain way of creating a sentence. You have subject, verb, object, and so on in a particular order, it gives you a particular meaning. That also applies to markup languages. Writers have to learn, in effect, a new language, a new way of expressing themselves that is valid and that the machine at the end of the day… Because we are writing for machinery, when you start writing in XML that the machine can understand, so you’re learning a new syntax, a new vocabulary as well.

BS: I guess coming from that angle in learning to essentially write in a different language, there would be some cultural and probably some workflow changes that would need to happen there.

DA-C: Absolutely. Learning that language for some people might be easy and there’s lots of courseware that’s out there that can get you into that way of writing, but it does involve classes, training entire teams, and not everyone might be open to retraining in a new way of writing. Once you have trained those writers and they’ve got up to a certain level, you can only do so much training. Afterwards, the rest comes as experience. Then another big change that your writing teams will have to make is that ownership, that question of “I own this content, this is my…” Owning the source content is something for the past, it’s cultural change that has to happen within the team in that we’re writing for a team, we’re just contributors now. We contribute to a pool of information and you have to learn a way of writing that makes it that the content that you put into the pot can be used by other people.

My style of writing things might differ from somebody else’s style of writing things. All of those have to start disappearing in the way that the writers actually create that content, and that’s a big change for a lot of people. I’ve worked in teams where during the summer holidays someone says, “Well, okay, look, if there’s any changes, I’ll make them when I come back,” and even if there’s an emergency, they’ve locked down their files, you don’t have the latest versions and so on. You’re having to wait for that person to come back. If your teams, I suppose, one of the ways that you can make the medicine go down better is to let them know that they can own the output.

You own what you put together and in structured in DITA, you have the concept of maps and book maps, so well they own that because they’re the ones that have decided which topic goes before which, and so on so forth. Then when they press that button, the PDF or the HTML output that comes out of it, they can sign their name to that. However, in the creating of the content, you must start thinking “I’m writing for a pool,” as they used to have in newspaper, poolrooms. Everyone would contribute, and then in the end you have a whole newspaper.

BS: I think that would probably go doubly for any content that certainly is going to be written for reuse so that you are absolutely writing for your team and not for just your particular need.

DA-C: Exactly.

BS: All right, so going from old to new, let’s talk a little bit about data migration.

DA-C: Now, this part of it is, I think, one of the most complex and the longest parts of that migration from unstructured to structured. You’ve got to make decisions as to how you’re going to convert that content. Are you going to bring in an outside consultancy or are you going to do it one at a time? You’ve got to make decisions as to whether you’re going to continue updating content that is being migrated, whether to use a production and staging server, whether to wait for that pause. If you are lucky to work in a company that does not do Agile, for example, and you have big breaks in between product releases, you could say, “Okay, well we’re going to take that time to then create all the new content.” Do you also want to convert all of your content? If there’s stuff that you’re not going to be updating, this is your chance to get rid of all that stuff.

Just don’t convert it and know that whatever you find inside of your CCMS is what has a life and is able to continue living. Then you also have to consider that no matter how much help you get, whether you’re writing it yourself or getting a conversion done by a consultancy, there’s going to be some cleanup to be done because if your content was written so well in the first place in Word that you could create a matrix, mapping it directly to DITA, there was no real point moving over to DITA.

Basically, that content was good enough as is, so you are going to have to come back and go over the stuff and change strategies as you go along and think, “Okay, well, we thought we’d be able to reuse this, but actually maybe it’s best to have a branch of this or create a duplicate of that topic.” You’ve also got to think a little bit further forward as to how that content is going to be localized, it’s going to be translated, and some of your reuse decisions must also consider that part of it, as well. In that, is it something that is translatable or should we have separate topics, and so we’re able to translate them differently depending on the context and so on. I think that that shows just some of the aspects of that complexity of that data migration.

BS: Yeah, the localization angle is a big one because even if you had a perfect migration, the way that the content is now essentially tagged is going to be different than how it was tagged before. Even if the text doesn’t change, there’s still going to be some segmentation problems, so you’re not going to get that 100% match that you were looking for the first time out. It’s something that we actually caution a lot of our clients with, as well. It’s like, “Expect to take a hit on the first localization pass. You’ll get a lot of leverage, but it won’t be a hundred percent, and then from then on you’ll see a huge improvement.”

DA-C: Yeah, totally. Real-world experience, this is what we went through when I was working with a medical device manufacturer, and we planned pretty much what we thought for everything, and we had that in mind, all the advantages. Oh yeah, drop in translation costs and so on, and that was what was communicated to the engineering teams who were the ones that eventually paid for the technical publications and so on, you know the way companies work, different departments, different budgets and so on. Then we converted everything and it came to that first release and we sent them what we sent out for translation. We got that translation quote back, and it was just a little under what the initial translation was, whereas what we were doing was just an update of some of the content, and we had some explaining to do in that.

“Oh, yes, well look…” Because of the way, and as you said, segments are different, and if you look at the code for a paragraph in Word, you’d put a bold on there, and then that segment goes off into the translation memory, and it doesn’t matter whether it’s bold or not, the words, that paragraph is there as one segment. However, in XML, your bold is actually elements, B elements, before and after, and when the translation management system starts looking through it basically cuts off at that point where it encounters a new element.

It used to encounter P and then end with P/P, whatever. With this new translated migrated content, it’s going to start off with possibly a P, and then it’s going to come up in bold and then possibly another italics, and end italics and then UI control if you were doing things properly and things like that. Each of those becomes a segment, and so the translator then ends up with, “Well, it matches, but this changes,” those fuzzy matches do cost you a bit more. Think of when we had to go back to engineering and explain all of that in that further translations will cost a lot less, but this first one, you’ve got to be prepared to take that hit.

BS: Absolutely. Actually, speaking of costs, I’m sure there are others that we could mention here.

DA-C: Oh, yeah. Well, apart from training costs, which we’ve already brought in, while there’s free training, it’s never 100% free, because you are paying your staff while they’re doing that training, and so they’re not producing content, so it’s not free. You’re paying someone to do that, but you really should invest in formal training for your staff. There’s the initial setup costs, so there’s the cost of the software, there’s the cost to your IT department in putting in place all of these things. You might need to pay for someone to create the publication outputs that you need to have if you don’t have that expertise in-house.

You might need to also invest in a content delivery system because you were delivering PDFs before, but part of the whole content strategy is to have everything on a portal, on a website, and so well, there’s maybe cost that’s going to be added on to that. There’s the cost of the conversion. It’s either you’re paying a consultancy to do it or somebody in your team is going to be doing that and not working on the project that they’re normally working for, but these are all costs that will be in there. Some of them can be quite high and some of them would be just normal, one-off costs and so on. We’ve already talked about the translation.

BS: I guess let’s talk a little bit about the challenges of maintaining your consistency, because once you move to structured content, yes, structure has a series of rules. You can’t have this element before this element, and a lot of the systems enforce that for you, but what are some of the other things that you need to be careful about when it comes to consistency?

DA-C: Many teams think, many organizations think that once we’ve got this thing in there itself policing, if you want in inverted commas, you don’t need an editor, you don’t need someone to go over that because you’re overly reliant on the tools. However, you need to know that even if you have these rules in the order of elements that are allowed to be used, you might not want a particular element to appear in a particular type of content. For example, you have short descriptions of a particular type of content that you can add to your editor content, but it’s not always appropriate. Well, between user manual for product X, who is being written by Tech Writer One, and the same thing for another product within the same company, but it’s being written by a different person, one or the other might decide to include a short description, and they’re both valid.

They’re both valid topics. However, why does one have a shorter description than the other? You need that editor, you need someone who’s there to be able to take a look at that sort of thing and to help harmonize content across the different content types that you have. You would have maybe an information architect who’s there not just to help set up that order of elements and help your writers learn how to use and put them, but also who’s there to show good practice, who maybe has a session every month to just say, “Okay, well this is the best way to do this,” or “We found these examples. Could we make sure that we’re all following the guide for this type of manual, and this is the way we do it?”

Terminology is another big one in that, and you can either enforce it using a third-party tools that can plug in, or you’d have someone in there making sure that you’ve used this term. When you’re creating terminology lists, it’s not just a list of approved terms. You also should be looking at terms that are not approved.

BS: Absolutely.

DA-C: That must not be used.

BS: Absolutely. I would probably also mention the classic need for style, tone, and voice as well, especially now that you don’t have writers who own their manuals, “This is my manual. I wrote it from cover to cover, it has my voice, or it has my interpretation of the corporate voice in there.” But now you have a situation where you do have that reuse of individual topics in a myriad of different places, and if that style of that tone or whatever changes from one topic to the next, it’s going to be pretty jarring to someone who’s reading the whole piece.

DA-C: Yeah, a simple example is you have a writer who likes to use, “Please do this before you do that,” another writer who just goes, “Do this, do that.” If you are reading from one to the other, that can be really jarring and you might even take offense because you’re so used to the pleases and thank yous from one author, and then you get into this topic, which is actually a troubleshooting one, and you find you get this tone that they’re telling you off, whereas it was just a difference in style that should have been enforced globally.

BS: Yeah, equally jarring going from one topic to the next, active voice, passive voice, active voice, passive voice.

DA-C: Oh, yeah.

BS: Let’s see. We’ve got translation challenges, consistency challenges, some cost implications there, migration, overall cultural issues, and just the overall complexity of doing all of that work. Is there anything else we should mention here?

DA-C: Regulatory compliance.

BS: Ah, yes.

DA-C: I’ve worked in regulatory for pretty much all of my technical writing career, so that’s maybe about 14, 15 years of the 18 that I used to be a tech writer. Adhering to industry specific regulations can get very complex, and while the promise of having a CCMS with version control and being able to prove that this output was created using this version of this topic, I could get that whole list out and prove it to you. If it’s not integrated within the quality management systems of the entire enterprise, then you’ll find that certain departments will not accept that as proof. Also, the mechanisms between your source files and what you can produce with DITA, you’ve got different ways of compiling your final output, and there’s stuff that you use variables for and the stuff that you’re referencing by keys, and so it’s going to use this version as opposed to that version.

You can also push content at the point of publication, so you don’t see it in that source. However, when you do publish it, then you see this new word in there, how do you prove to the regulatory department that all that content is sane it is sound, it meets with the requirements and so on? That was another really complex thing that we had to deal with that. But by integrating the tools between each other, linking topics to requirements, for example, so you always have a requirements database, even if you’re using Jira, that’s your requirements database if you want, but if you can link those two things as a starting point, then wherever a requirement changes, for example, you know which topics are impacted. When you have to do a regression analysis, a topic impact, a change impact analysis, you’re better able to prove that to the relevant departments that, “Well, you changed this requirement. One, we’re sure that all the topics that did refer to that requirement were analyzed and we made the necessary changes, but we’re also sure that we didn’t create any fallback impacts on other topics in the entire manual.”

There’s a lot of complexity in that makes it that you really need to strategize from the start on how you’re going to respond if you’re a regulated industry, but then there’s also the part where it can help you. It’s a very interesting use case that I saw where we’re mapping DITA XML to machinery standards, and so a company that is an OEM manufacturer is able to supply the exact information required by each of the different subcontractors that we have by mapping that to the IIRDS machinery standard. That is a very interesting use case where regulatory and compliance is enhanced by being able to map those two standards and being able to push the right information based on the metadata attributes and things like that, that are tying both together. You’re easing some of the workload, the heavy lift that used to go on there.

BS: Very cool. I think this is a good place to wrap up, but we’ll be continuing this discussion in the next podcast episode. Dipo, thank you.

DA-C: Thank you very much for having me, Bill.

BS: Thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Challenges of moving from unstructured to structured content with Dipo Ajose-Coker appeared first on Scriptorium.

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In episode 157 of The Content Strategy Experts Podcast, Sarah O’Keefe and special guest Dee Lanier discuss design thinking: what it is, what it isn’t, and obstacles and ideas for equity in design.

“Design thinking is not a model first. It is a mindset that incorporates a strong inquisitiveness. What’s happening here? Who are the people that are being affected by whatever problems that are happening here? And what don’t I know that I need to learn before proposing any solutions? That’s design thinking in a larger understanding.”

— Dee Lanier

Related links:

Dee’s top 4 design models:

IDEO, 1978
Stanford d.school, 2005
Liberatory Design, 2016 (updated 2021)
Solve in Time!, 2019 (solveintime.com)

Books:

Demarginalizing Design: Elevating Equity for Real World Problem Solving by Dee Lanier
The Inner Work of Racial Justice by Rhonda V. Magee

Contact Dee:

Website: https://www.lanierlearning.com/
Email: dee@lanierlearning.com
Twitter/X: https://twitter.com/deelanier

LinkedIn:

Dee Lanier
Sarah O’Keefe

Transcript:

In this episode, we’re talking about design thinking with a special guest, Dee Lanier. Hi, everyone. I’m Sarah O’Keefe, and welcome, Dee.

Dee Lanier: Hi. Thank you so much for having me.

SO: It is great to have you. For those in our audience who don’t know, we literally met on a plane. So we were both headed to San Diego for different reasons, and had a really great discussion. And then I decided that that discussion really needed to be recorded, so, here we are. And thank you for being here.

DL: It was a fantastic conversation, and so I’m happy to continue it now.

SO: So, we complained a lot about AI and the state of the universe and a bunch of other things. But Dee, you’re a published author and a consultant, running around doing cool workshops. Tell us a little bit about what you do and how and where.

DL: The where part will probably be the most difficult because it’s literally all across the country, and sometimes internationally. But I am oftentimes brought in to do human-centered design, also known as design thinking work, helping organizations tackle challenges that they are experiencing, and then come up with some form of contract or goals. And then coaching them longer term in executing on their stated goals, and really being one who can infuse some form of instruction and help and supports in some cases. But also just being responsive to the roadblocks that they’re experiencing, some of their communication challenges, things of that nature, and helping them see their goals through. And then celebrating what they have accomplished as well as setting up some of their longer term goals that need to be evaluated over the course of three to five years.

SO: And so, this really sounds a lot like what we do here at Scriptorium, except where you’re talking about design thinking and human-centered kind of approaches, I’m deeply afraid that we are more about the systems and the tools and the software and the, I guess, automation centered approaches. But how do you define, for this audience that sits more on the techie software side of the world, how do you define design thinking for them, for us?

DL: Sure. Well, I feel like I have to always start off with helping people understand what I don’t mean by design thinking. And that is if your brain lights up, and I’m sure some listeners say, “Oh, I know exactly what design thinking is,” and what immediately comes to mind is a model or a process. That is what first comes to mind. And I would venture to say it’s either coming from IDEO’s Model established in 1978, or it’s Stanford D School’s model established 2002 or five, something of that nature. So by and large, what they’re thinking of is a model and they’re thinking of a fairly recent phenomenon. And I like to say first and foremost, design thinking is exactly what it sounds like. It is thinking like a designer.

So if you’ve ever been in contact with any form of designer, someone who does graphic design, industrial design, interior design, you start to notice that these people think differently. And I would say it’s not just different in they just think in a manner that is different than other people. But they literally, they slow down and they ask questions and they seek to understand. And that really is the goal, is the seeking to understand before proposing any solutions.

So with that, I say, “Well, design thinking is not a model first. It is a mindset. And that mindset incorporates a strong inquisitiveness about what’s happening here. Who are the people that are being affected by whatever said problems that are happening here? And what don’t I know that I need to learn before proposing any solutions?” So, that is design thinking in a larger sort of understanding. And then if you’re curious about models, I could share a couple, because you can Google search at least 10. Which again becomes something that sometimes blows some people’s minds when they’ve been introduced to design thinking through a particular model.

SO: Well, we’ll take your top three or four and stick them in the show notes. And I wanted to touch… I mean, it’s interesting, right? Because we go in and we will look at things, and a lot of times we’ll say, “That’s not actually the problem. That’s the symptom.” Right? You see these issues, but you have to figure out what’s the root cause. And so I think really at the end of the day, there’s a lot of overlap there.

And I know that one of your focuses in addition to this design thinking lens and this really understanding the stakeholders and the organization and how they need to change to address the issue that you’re dealing with, is that you have a strong focus on design equity or equity in design. And I wanted to touch on that. I mean, I think most of us are familiar with the really obvious problems like you ask a search engine for images of a CEO and you get a collection of white men with good hair. But your practice goes way beyond this. And so what I wanted to ask you was, how do you look at equity and design? And what are some of the issues that leak into that work in ways that are not as obvious as my really dumb CEO example?

DL: That’s not a dumb example, that’s an excellent example. Or even just doing a Google image search on good hair or professional hairstyles versus unprofessional hairstyles, and then we’ll see what you discover. But that is part of it, even doing that, starting with an investigative practice or a prompt to get the conversation going. But equity and design or elevating, as I like to say, elevating equity in the problem solving process is twofold. The first being making sure that you’re actually gathering the people that are most proximate to whatever pain that is being experienced as part of the process. And so it is not just an expert or consultant who’s coming in, who’s taking inventory of whatever’s happening. And then going off to the side and developing whatever their solutions are. And then coming back to the team and say, “This is what I got. This is what you hired me as a professional or as an expert to do.”

I think that there’s a need for that in certain instances, but when you think about problems or challenges that affect a community, it requires that the community is engaged in identifying what is the root problem, what is the core of the problem. And being a part of the process for describing not just what the problem is, but also gathering the research so that they can see for themselves that they can also share the antidotes of their experience and their exposure to whatever the challenge is. And then them also ideating and being a part of, “Well, we could do this, we could do this, we could do this, we could do this.” And bringing in their thoughts, their brilliance, but really it’s because they’re bringing their pain to the table, and they want to be a part of the solutions.

Because then lastly, whenever their solution is then proposed, and then there are goals set and there’s some action planning and some execution of those things. And if they’re a part of that process all the way through, then that sort of eliminates the blame game of, “Well, this outsider told us we should do this. We never understood or agreed with that. We attempted it didn’t work. And I could have told you from the very beginning, it never would’ve worked.” It kind of separates that us versus them mentality, and instead invites everyone who’s really deeply vested in seeing that problem overcome as a part of the solution. So, that is long-winded answer to part one of, that is what it means to elevate equity and problem solving.

Secondarily, it is literally taking on particular topics that are related to equity in whatever the setting. And so whether that be anti-bias work, which is what I’m oftentimes brought in to do. Or sometimes it is, and giving a distinction between, what are the differences between individual and collective bias versus different forms of discrimination? Anti-racism work. And then also there’s an opportunity, and I see this last category primarily in schools, and that being civic engagement. And so it’s identifying a problem, understanding what the big problem is, and then spending the time with the collective group to problem solve.

But part of the work that I do in the pre-work is really listening well to leadership. And then having them help me identify who are other people I should be talking to learn what is the core issue. So then we just propose, “Okay, this is where we’re going to go with this next.” And it may be starting with bias or it may be going into anti-discrimination. Or it may go into, “Okay, it seems like this is an issue that is particularly related to racism and we need to do some, not just anti-racism training in the sense of me giving you a bunch of terminology. And building up your lexicon and helping you have a better understanding of what these things are. But really being a part of problem solving, identifying the particular challenges that are being experienced typically by people of color within your organization. And then how can we rectify those issues?”

SO: It’s interesting because in many cases, I think the projects that we come into, nine times out of 10, the people on the ground, the line employees that are in the trenches doing the work have a really, really good understanding of what the problem is and how to solve it. They know. I mean, they know what’s wrong and they know how to fix it, and they’ve already figured it out. But because as somebody or others said, infamously, “You get more credibility when you commute on an airplane.” So because we’re outsiders coming in, we get additional credibility, even though we’re potentially saying the same things that your staff, your long-term employees are saying.

And I’ve had, I mean many conversations where I would say to somebody, “Okay, you’re absolutely right about the problem here, and this is exactly the solution. You’re absolutely right about the solution, and this is what we’re going to propose. Now, would you like us to give you credit for it?” And 100%, I’ve never had anybody say anything other than, “No, you have to take credit for this because if I propose it will not get done.”

DL: Very, very interesting.

SO: It is an uncomfortable place to be. Right? But basically what they’re saying is, “Look, Sarah, we are going to leverage your credibility as an outsider to get the thing that we all agree we need.”

DL: Makes sense. Makes sense.

SO: Okay.

DL: Right. Makes sense.

SO: I mean, I can accommodate that, assuming… I mean in the scenario where we all agree that that is the right answer. But it is very upsetting to have person after person after person say, “I know the answer, I just can’t get them to listen to me.”

DL: You’re right. Well, and we may differ in approaches as well as how we differ in particular work that we do, in me more doing design thinking, you doing systems design. But what I like to do is help equip the community with the skills and the actual data that they need to move forward. Which is to say, “If you’re going to argue with this, know that you’re arguing against what the data says. And we are looking at the data.”

So if we can, attempting to be careful with my words, not to be taken in a different sense, but if we can objectify the scenario a bit… Which sidebar, when I do anti-racism work, part of the reason why I work more as a facilitator and guide the process is because it’s also extremely harmful for me to experience microaggressions, even in someone’s question. If I am being looked at as the expert who has the knowledge base, who has to respond to you, when you raise your hand and you have a critical question that also comes across like a confrontation. That can be incredibly challenging.

So instead, if it can be set up where there are small groups and small groups are where in collaboration with one another, they’re also utilizing the same level setting of background knowledge that was not only given, but really facilitated. Because what I do is I try and propose questions and give the tools for people to discover on their own. And then we come to agreements, “Is this what we all saw? Is this what we all heard? Is this what we all understand? Any objections to that?” So I’m objectifying the scenario a little bit to say, “If you are having an argument still, it’s not with me.”

Because that can, for me as a facilitator, as a person of color, trying to lead a workshop that is oftentimes for the sake of helping the people of color within that community to not feel abused, I don’t want to experience the same abuse that they’ve been experiencing. I know why I am there. It’s typically due to a scenario, something that happened. And so, let’s have a conversation about what happened, and then let’s have some conversation about what else is happening. And then, what is your community most interested in tackling primarily? And then let’s discover how to do that. If I can stand more on the side and help lead in that regard, then I also protect myself. And that is honest and real.

SO: Yes. And thank you for doing this work because the whole thing just makes me twitch. Just listening to this, it sounds painful.

DL: Yes. Yes, it can be very painful, ’cause I’ve been saying it. Part of what I do is anti-racism work, part of what I do is anti-racism work. Well, I’ve had to learn a lot even in doing that. Now, my background is totally in this field. My undergrad and graduate work is primarily focused on race relations from a sociological perspective. But knowing about something does not make it easier in a situation where you find yourself being tokenized in the moment, experiencing a microaggression in the moment, noticing someone centering on themselves and their experience. And then confronting you to have to try and counter what they are saying because they see you as the enemy in this setup.

All of that is hard, so I’ve had to learn some things. Had to learn some things such as being mindful in the moment. I will give a shout-out to Rhonda V. Magee and her book, I want to quote it or name the title properly. It’s, The Inner Work of Racial Justice, which is to take a deep breath and pause when experiencing something offensive in the moment. How do we stay professional when we notice that something that is being said or done causes harm, whether it’s to me directly or to others around? And how do we address that situation? So, doing the inner work.

Secondly, making a huge point to level set, to say, “What we’re going to do is attempt to make sure that everyone has the same baseline understanding.” So therefore, if I am brought in to do anti-racism work, I first have a large conversation about the concept of race. Because we’re not going to talk about an ism if we don’t understand the structure in which it’s being built upon.

And I ask three questions and give time and space and also some resources, so that a group can investigate on their own and say, “When was race created? Why was race created and how was race created?” So again, once those things are being investigated and discovered, they’re not doing battle with me, they’re doing battle with research, they’re doing battle with history. They’re doing battle with what is real and not what’s imagined. There are people in that room who could say, “I can tell you this right now,” but there are others in the room that need to discover that for the first time. So, that is part of what I do.

And then the next thing I do is ensure that we don’t move on with doing design thinking through these particular challenges, until we have set some expectations and some commitments from the people that are in that space individually. Because we’re going to work corporately, but we are going to need to individually agree on some things. And so, those things become things that I can always call back on and say, “Remember you said that you would commit to the following.” And so if there’s any need to address any issues, it’s based on their commitments, not the thing that I’ve imposed upon them.

And then of course, I’ve already brought up bringing in definitions of terms so that people aren’t just going off of their understanding of a concept. But at least we’re all utilizing the same definitions, as we talk and discuss them. But then what everyone is able to bring to the table is their experience with those particular concepts.

Those are things I attempt to do to create safety, in a sense, for the participants as well as for myself. But safety cannot be demanded or controlled in a sense of saying to the group, “This is a safe space.” Who says it’s a safe space? Safe for who? And how do we know? But we can do certain things to attempt to create safety. And then we can always stop and pause and call back to, are we actually doing what we committed to do or are we doing something different now?

SO: And so, some of the conversations that we had when we first met were actually revolving around some of these concepts you’re talking about, in terms of safety and bias. But what actually led us off was AI, right? We started in on this question of, “Oh, well, what does it look like to start to bring AI into some of these settings?” Whether it’s to support design work or it’s to support corporate training, K through 12 education, or anything else. The AI is out there, the tools are happening. What do you see? I mean, what’s your sort of capsule view of what’s going to happen, as we go forward with these tools in a variety of settings?

DL: Part of our conversation was acknowledging that AI and the various tools that exist, they’re not going away. We know that that is the case. I wanted it to kind of feel like, “Oh, let’s see if this is a trend that will fizzle away, like Wordle and Bitcoin.”

SO: Wait, one of those has actual value, and it’s not Bitcoin.

DL: I see what you did there. Exactly. But there are billions of dollars being invested in by big corporations. So part of what I do is try and say, “Well, let’s effectively utilize AI or let’s attempt to effectively utilize AI in a research process.” And so that is skill development, much of what it requires to not only participate in design thinking, but then to slow down, stop after what would oftentimes be like a rapid prototype. We quickly, within a very condensed timeframe, came up with what our proposed solutions to whatever said problem is based on this very limited amount of time.

But now that we have more time, extended time, we need to fill in the gaps with what is missing. Some of those may be interviews, and some empathy mapping. But it also requires deeper research. And part of that research requires understanding the tools that exist and how to use them effectively, and being mindful of things such as the bias that exists within them. And so, that becomes a whole workshop in and of itself.

We are going to deep dive into AI because people come to the table. Similarly, as we were talking about race and racism, people come to the table with varying degrees of understanding. And what ends up happening is some people presume that others know exactly what they’re talking about when they say whatever they say. Or there are others that have very, very strong opinions on certain things that it’s clear in certain cases, that they actually haven’t done much research, nor have they actually participated in or evaluated something critically from using. But they’re just like, they heard on NPR, they watched on CNN, they listened on Fox News, and now they have opinions. And I always say opinions matter, but they’re not more important than research.

And so, having people actually deep dive into research, and that includes just starting off with, I got three companies to name to you, Google, Microsoft, and Amazon. What all do they have in common? They are big data corporations. So, let’s start there. And if I say, “One is invested $10 billion here, another has invested $4 billion there, another has invested $2 billion externally here. And who knows how many dollars they’ve invested, invested internally for the development of their tools. And they own the space of data. It’s not going away. What kind of data do they have? How is that data being utilized? How can you be mindful of those things? And then how can you utilize these tools effectively, while also being mindful of the ways in which, if you’re not careful… You are the contributor to the data, and so you can be bringing your bias to the table as well.”

And so yeah, it’s a big, big, big, big discussion that’s still results similar to how all I think design thinking activities should result. And that is concluding with some commitments. And so whether it is revolving around the particular challenge that people are experiencing or with AI and the challenges that it presents, I always bring up a fourfold framework for goal setting. And that is what is it that we are trying to prevent, correct, improve, and excel in? And if we can set our feet on those four foundational pillars, then they become our guide as we continue to move forward. And AI is now just another part of that.

SO: So Dee, thank you. We could probably keep talking for a couple of hours, and I would appreciate that, and I suspect our audience would as well. But if people want to reach out, what’s the best way to find you? And we’ll, of course, also embed information in the show notes.

DL: Sure, sure. Thank you. Well, my website is Lanier Learning, my name, L-A-N-I-E-R, lanierlearning.com. Can also be emailed at dee@lanierlearning.com. I’m still on the Twitter or X or whatever that thing is called @DeeLanier. You can also find me at LinkedIn @DeeLanier. So my name is easy to find, and I would love to hear from some folks.

SO: So, Dee has a book out there in the world called Demarginalizing Design, which I would strongly recommend. And we didn’t have time to get into this, but some really interesting workshop techniques around how to get people engaged doing different kinds of things. Not just talk in a small group, but do some more creative things, which I believe is called, Solve in Time.

DL: That’s correct.

SO: So, that’s out on your website. We will get all of that into the show notes. And I hope that we’ll have an opportunity to have some further conversations about where this mess is going.

DL: We’re all learning, right? Absolutely. Well, hopefully we will have more opportunities such as this. Maybe we’ll even find ourselves on another plane together, having a conversation.

SO: Seems likely. So Dee, thank you so much for being here. And with that, thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Design thinking & equity in design with guest Dee Lanier (podcast) appeared first on Scriptorium.

The Inner Work of Racial Justice: Healing Ourselves and Transforming Our Communities Through Mindfulness

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In episode 156 of The Content Strategy Experts Podcast, Alan Pringle and Christine Cuellar are back discussing more pain points that Scriptorium has resolved. Discover the impact of office politics on content operations, what to do when your non-technical team is moving to structured content, and more.

“Here’s the thing. Skepticism is healthy. If people are trying to poke holes in this new process, sometimes they can actually uncover things that are not being addressed. That is real, that is useful. So don’t confuse that with people who were being a-holes and just being contrary for the sake of being contrary. Those are two different things, and you’ve got to be sure you understand those two things.”

— Alan Pringle

Related links:

Ask Alan Anything: Resolving pain in content operations (podcast, part 1)
Content strategy pitfalls podcast: change management
“Why do I have to work differently?” (podcast, part 1)
Training by Scriptorium

LinkedIn:

Alan Pringle
Christine Cuellar

Transcript:

I’m Christine Cuellar. And in this episode, Alan and I are continuing our discussion about pain points, pain points that Scriptorium has resolved over the years. And we have a lot more to talk about. So Alan, let’s get right into it if you’re ready. Are you ready for round two?

Alan Pringle: Well, I took the first bit okay, I think. So let’s go ahead and knock it out.

CC: All right, let’s do this. Okay, so let’s talk about some more interpersonal pain points. So let’s talk about office politics. How does office politics impact content operations problems that might already exist?

AP: Oh, office politics affects every operation. Not just content, every operation at every level. And you have to be savvy and know how to play the game. If you have had experience with that at the company where you are, or at another company, it can be a very valuable thing to understand that how to read people, how some things are left kind of unsaid, inferring things.

Understanding that when you have a C-level executive who has a priority on, they want content to be like X, that all of a sudden probably becomes a priority for you, even though it may not have been one in your mind. Because the person who has the money sees it as the priority.

So there are lots of things that you have to bridge and address, and it can be a minefield, absolutely. But if you’ve had experience with it before, or again, if you’ve worked with a consultant who has seen these things before and we have seen politics at Scriptorium, lots, it’s inevitable because humans are political beings. It’s just how it is.

CC: Yeah. What are some common office politics or sticking points for content operations? Is there anything unique to content struggles?

AP: This goes back to a little bit about what we talked about in the previous episode, in regard to finding the common communication method, a common language of speaking. Be sure you’re not talking at each other, that you’re talking with each other when you were talking about these things.

And again, this is not just about content. But what is about content is, content does often not quite get the attention that it should. So you may have to spend a little more time explaining its value as we discussed earlier. And that can be a sticking point here.

CC: Yeah. And if you didn’t have a chance to check out the earlier podcast, it is in the show notes, and I do recommend it. Because Alan also shared some specific metrics that you can have on hand to help communicate the value that content brings to your organization. So definitely recommend checking that out.

How about a pain point where people, whether that’s the technical writers or other people involved in this whole process, don’t really want to be helped? They’re kind of happy with what they’re doing. Maybe the reversal is true, they don’t see the need for the change, and maybe managers or executives are the ones pushing that change. How do you navigate that?

AP: Well, you have to find advocates at every level. Even though you’re saying some people may not see the value or are not feeling the pain, I bet there are other people who are sitting back looking at this. Content creators are saying, “This is crap. We need to fix this.”

If they can get other people on board, that’s how you do it. It’s more of a lateral thing. You’ve got coworkers explaining to you, this is why we need to do this. That is much more effective than from top down, you will do this. Although sometimes you may have to play the, you will do this, card. And if those things aren’t done, it may be time for some personnel changes perhaps.

Yeah, that’s not pleasant, but it can get there sometimes.

CC: Yeah, no, that makes sense. Do you feel like once they see the value of what’s trying to be done, or once they see a coworker that’s really motivated by this and sees the benefits, even if this one individual doesn’t, do you mostly see people being won over to the cause, quote-unquote the cause?

AP: Not always, but here’s the thing. Skepticism is healthy. Because if people are trying to poke holes in this new process, sometimes they can actually uncover things that are not being addressed. That is real, that is useful. So don’t confuse that with people who were being a-holes, and who were just being contrary for the sake of being contrary. So those are two different things, and you got to be sure you understand those two things.

But I can tell you I have seen, even on two projects within this past year, where I sense skepticism from certain people and I saw them change over weeks and months. It happens. It absolutely happens. And that’s when you know you’re headed towards success. Because people who were like, “I don’t think so,” are like, “Okay, I see this.”

People who now champion what you’re doing, that’s really rewarding and it will really guide you to success.

CC: And I’m sure that that really helps them, that they were able to question and bring honest questions, and feedback, and concerns about, I don’t know how this is going to work, that kind of stuff. They were able to bring that to the table and have that addressed to the point where they’re now fans. Like you said, they’re champions of … That sounds like a safe environment for them as well. Hopefully that resolves their concerns.

AP: That’s what you want. I mean, that is ideal. And it does happen. Absolutely, it does happen.

CC: Yeah. All right, so how about a pain point where you realize that your team wants to or needs to move to structure, but your team isn’t technical. Do you have any thoughts or examples about how that is navigated? Because that sounds painful.

AP: It is. And it doesn’t happen overnight. Again, we are talking about a situation where you need to win people over, help them understand the bigger picture. And this is where, for example, a proof of concept can speak volumes. Where you take a slice of content and use it, set it up in the new process or quasi-new process, close enough where you can demonstrate the change. Where you can demonstrate the value. That’s one tool that can be very effective in communicating things and bringing people on board.

Also, you got to remember, you cannot throw a completely different way of doing things on anybody, in any circumstance, at any job, not just content creators and say, “Here’s some new tools. Go do it this way.” No, you’ve got to have some knowledge transfer. You’ve got to have training that’s tailored to all the different levels, all the different users of the system and how they’re going to use it. So all of that is vital.

And again, I’ve repeated this probably ’til I’m blue in the face in past events and podcasts. When you are budgeting for a project, never, ever, ever leave out training, always have budget for training, or you’re going to end up with a system that nobody can use. What’s the point?

CC: Absolutely. And like you mentioned earlier, if the worst-case scenario happens and there is some turnover, I mean, we try to avoid that at all costs and try to win people over. But if that…

AP: That can be healthy. I will argue sometimes turnover can be healthy. If someone realizes that they are not going to be a good fit for this new process, maybe it is a good time to bring someone in who can.

Yes, the loss of that institutional knowledge, the product knowledge, the service knowledge, the process knowledge, I am going to fully acknowledge that is a big loss. It is painful. But big-picture wise, sometimes changes like that are exactly what you need to get things moving.

CC: Yeah, yeah, that makes sense. And if you have training, if you’ve budgeted for training like you mentioned earlier, it sounds like that could be something that not only helps navigate the transition, but it can also help new team members that come maybe six months, a year, or even more so after the changes already happened. It’s an asset that, it’s good to have in place from here on out.

AP: Yeah, I’m glad you mentioned that. Because there are multiple ways to navigate what you just mentioned. You can set up a “train the trainer” scenario, where a consultant or an expert comes in and basically gives people within the organization the knowledge they need to then spread the good news to other people. And people who were maybe hired even six, eight months, a year down the road. So you have got those resources internally.

You can also record training and use that as a resource as well. So there are ways to address that. But it is important. You’re right. It’s not just about the transition, it’s about helping people when they’re introduced to the process as new hires.

CC: Yeah. So shifting to some technical pain point questions, tell us about some scenarios or maybe some ideas you have when technical obstacles come up that weren’t discussed in the discovery stage. So this is probably particularly when a consultant is brought in. But during that initial assessment, there was a lot more hiding under the surface than was realized. How do you navigate that?

AP: I would hope there are not a lot of that going on, because that means discovery probably wasn’t as deep as it should have been. It does happen. But I’m going to hope and cross my fingers that we’re talking about some things around the edges, edge cases, things like that.

When you have edge cases, you have to say, okay, do we need to spend time and money for the system to address it, or is this edge case a one-off, and things need to be reconfigured with this edge case, so it’s not an edge case? That’s one way of looking at it.

But if you find enormous gaps where you have completely glossed over something, there’s part of me that feels like discovery went a little awry. That’s where my brain is right now. And that’s like, did the consultant, did we do our jobs here? What happened here? I would take a hard look at that and there would need to be some soul-searching there for sure.

CC: So that’s a good point. That for the most part, the way that a consultant guides that initial assessment should flesh out the major problems. That’s what I’m hearing.

AP: I really hope, I really hope. Because a lot of times, if you’ve done this as long as we have, that sounds boastful, but it’s just a matter of fact.

CC: 1997, so yeah.

AP: Yeah.

CC: It’s been a long time.

AP: Yeah. Your antenna goes up and you’re like, I hear that, but I know that also means X, Y, and Z. So that’s where a consultant can be helpful. Because they can pick up on things that, on the surface, may not mean anything to someone who is mired in the pain. But it really means something to someone who’s seen this stuff before and can pinpoint, oh, if I’m hearing that, that means these things are also probably true. Let’s go digging around on those things.

CC: Okay. Okay. So how about a situation where you need a specific output, but the current authoring and publishing systems don’t support it? And there’s really no way around that.

AP: This is a signal that is not just about that output. It probably means your ops are not where they should be. Because good content operations, they are going to allow you, enable you to deliver to a yet-to-be-specified delivery format. That is the crux, the joy of good content ops. They are going to be basically future-proof.

If you’ve got things set up in a way where your content source is, let’s call it format neutral, and then you apply different transformation processes to it to create all the end results, delivery formats you need, one more delivery format shouldn’t be a huge burden if things are set up well.

Now, you may have to add another layer of intelligence, some new information into your source content to deliver that. But beyond that, you should be more or less ready for the unknown. That’s where my brain is anyways. I mean, to me, good content ops are not just about the here and now. It’s also about what’s coming down the road in 18 months.

CC: And speaking of that, what happens when your content processes, you just outgrow them? Okay, two questions in there. One, that’s a pain point that was brought up a lot is, what happens when you outgrow your processes? So there’s that. But then also, number two, can you create a solution where you don’t outgrow your processes? Is that even possible?

AP: In theory, I think baseline, you can create something that is somewhat future-proof. I do believe that, and I’ve seen that happen. Especially if your content is structured, and it’s got a lot of intelligence, I’m going to use the M word, metadata, built into it. So you can slice, dice, and present that content in many, many different ways to many different audiences, versions, levels, whatever it is that you need at the end.

And then it also gets into content as a service, where other systems can pull in that content and use that intelligence to create what the end user, the reader, or whoever, what they need. And gives them exactly what they need, and often in real-time.

So yes, theoretically, you can do that. But like I said around the edges, you may have to add a little bit more intelligence here or there to your source to be sure that you can address that new delivery format. So yeah, you can do it. But nothing on this planet is foolproof, as much as I would like it to be.

But having structured, intelligent content that is filled with metadata, if you have that as a core, you can take that a really, really long way. A really long way.

CC: So Alan, are there any other pain points that we haven’t covered in our list that I’ve grilled you on? Is there any other kind of pain point that you’d want us to address right now?

AP: The only thing that I want to say to kind of close this up is that change is a people problem. Don’t consider it a tech problem. That’s kind of my overarching advice, based on all these questions that I’ve heard at this point. And looking at it simply through the lens of tools and technology, I think you’re basically guaranteeing you’re going to have your backside handed to yourself. That’s what I think.

CC: Yeah, that’s a really good way to phrase that. I like how you phrase that. Because that also applies to other aspects of the organization, not just content. But it has a big impact here.

AP: Basically, basic change management applies here. Good project leadership applies here. Yes, a hundred percent.

CC: Absolutely. Well, Alen, thank you so much for letting us grill you on this. Especially because you didn’t have the list in advance. You didn’t know what we were going to bring up today, so thank you for being here.

AP: Sure. It was interesting.

CC: Sure. It brought up a lot of really happy memories of resolving all these things very easily.

AP: And some unhappy memories as well. Yes, it did.

CC: All of the above. Yeah.

AP: Yeah.

CC: Well, yeah. Thank you so much. And thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Ask Alan Anything: Resolving pain in content operations (podcast, part 2) appeared first on Scriptorium.

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In episode 155 of The Content Strategy Experts Podcast, Alan Pringle and Christine Cuellar dig into pain points that Scriptorium has helped organizations resolve since 1997.

“The amount of time content creators spend on formatting and for little payoff, it’s just… the numbers don’t add up. Especially in the 21st century now that we have so many automated ways to publish things to multiple channels, if you are futzing and tinkering with formatting trying to deliver to multiple channels, I can say with a great degree of certainty, you are absolutely doing it wrong.”

— Alan Pringle

Related links:

Personalization in marcom and techcomm
Is Content as a Service right for you?
Content experts will soar when you remove these burdens
“Why do I have to work differently?” (podcast, part 2)

LinkedIn:

Alan Pringle
Christine Cuellar

Transcript:

Christine Cuellar: Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we’re sharing stories about pain, specifically pain points that Scriptorium has resolved over the years. This is part one of a two-part podcast. I’m Christine Cuellar, and with me, I have Alan Pringle. Alan, thanks so much for being here.

Alan Pringle: I think you’re welcome, but I may regret it based on the format of this particular podcast.

Christine Cuellar: Yes, you may. So Alan has no idea about what we’re going to talk about today other than we’re talking about pain points. He has not seen the notes. I’ve instead collected data from our team about lots of pain points that Alan and the team have resolved over the years. So there’s going to be a lot of pain in here, Alan, but hopefully there’s going to be a lot of resolution as well. There’s hope.

Alan Pringle: We can only hope so, and I thought of a little subtitle for this. We can call it AAA, Ask Alan Anything, with very deep apologies to Reddit AMA, and to the American Automobile Association. So yes, this is-

Christine Cuellar: I love it.

Alan Pringle: … the AAA talk, and I’m frightened.

Christine Cuellar: Let’s do it. I’m so excited. I’ve been looking forward to today. Not looking forward to your pain, Alan, just these pain points. Anyway, it’s going to be great. It’s going to be so great. Okay.

Alan Pringle: We’ll see about that. Yeah.

Christine Cuellar: So generally we have some main reasons for why people come. They come because they’ve experienced a lot of mergers or acquisitions, and they’re trying to consolidate different ways of approaching content operations, or they have a lot of localization requirements. There’s a lot of big-picture challenges for why people come to us.

But yeah, we’re going to go ahead and pick Alan’s brain on some specifics. So let’s kick it off with this one, Alan. Can you tell us about a time or about some pain that was involved when you and the team moved a customer or a client from disconnected document systems to a unified system? Tell us how that went.

Alan Pringle: The thing is, this could be many, many people. Here’s the thing. I think you always need to rewind before you talk about the systems because you need to lay the groundwork before that, and that goes back to the pain points you were talking about. Okay. You ask the client, “What pains are you having?” And then, from there, you go, “Why are you having those pains? What can we do to stop those pain points, make things better,” and then you pick your system?

So that’s not a super fun answer, but there’s always this temptation to dive directly into tools, and I’ve said this a zillion times in presentations here, panels, and wherever else, don’t do it. Think about your requirements first. And pain points are a great way to dig out and tease out those requirements. But get those in place first, and then pick the tools that are going to help you address them the best.

Christine Cuellar: Yeah, absolutely. Yeah, start with what you need before trying to make a tool decision. That totally makes sense.

Alan Pringle: Yeah.

Christine Cuellar: How about this pain point? Dealing with manual formatting when authors have to manually format things all the time. Has that ever come up before?

Alan Pringle: All the time. The amount of time content creators spend on formatting and for little payoff, it’s just… the numbers don’t add up. And especially in the 21st century now that we have so many automated ways to publish things to multiple channels if you are futzing and formatting and tinkering with formatting, trying to deliver to multiple channels, I can say with a great degree of certainty, you are absolutely doing it wrong.

Why are you inflicting that upon yourself? Stop it. So yeah, don’t do that. Please don’t do that because it’s not a good use of your time, mostly because your reason for creating this content is to educate, help the people who are reading it. You need to spend the time on that, not on the formatting. It’s just not a good use of your time. It’s just not.

Christine Cuellar: Yeah. Do you have any examples of a company that was held back by the time that their team was spending on manual formatting? So maybe they were trying to translate into new languages or rebrand. Any examples of-

Alan Pringle: Oh, yeah.

Christine Cuellar: … how that went wrong?

Alan Pringle: I mean, again, it’s not so much that it goes wrong. It is that what they are doing is just not sustainable, and it is costing them so much more money. I mean, you think about it, if you have your source content, and because my primary language is English, really my only language is English. I’m going to say your source content is English. So all the time that you’ve spent formatting and getting that ready, you have to apply that to every single language. That effort becomes exponential. It’s multiplied again and again and again.

Please, why are you doing this to yourself? Don’t do that. You need to have a system where your formatting and your source language is as automated as it can be, and then that automation will then apply to the localized content as well. It really is just kind of stupefying to me to see people continue to spend so much time on formatting on source content, much less when they have to localize for, you know, how many different locations.

It is just, again, the money and the time, and then there’s the delay because, say, you ship out to your primary language. Again, I’m going to say English. It’s not always that way, but that’s just because I speak English. And then three or four or six months later, you’re shipping out the other languages. Why? You need to get that window down to almost simultaneous shipment so you won’t have this huge delay because if you have that huge delay, that is an income stream that your company is not getting from those markets that need the translated content. There you go.

Christine Cuellar: Yeah. Yeah. So in a nutshell, for organizations that have had this as their primary pain point, you know, the writing team is spending way too much time, manually, formatting things, and they don’t actually get to do their job, which is write the content. What’s the big-picture fix to that? I know it’s probably different for each person and each organization, but what is… where’s square one?

Alan Pringle: There’s lots of square ones here, so I got to be careful. There’s not a one-

Christine Cuellar: Yes.

Alan Pringle: … size fits all. If you are working in more traditional content development ways, when I mean by that desktop publishing, templatize. Your formatting should be coming from a template, creating a repeatable process, and that template can be applied to your localized content as well.

If you have outgrown desktop publishing, and that does happen, you need to look at structured content, and that means there is no formatting in your source content. It is applied automatically later on. When you do that, it basically takes it out of the author’s hands completely, and automated transformation processes apply it. So those are two go-to’s right there on how to possibly address that problem.

Christine Cuellar: Gotcha. How about this pain point? An organization is being asked to personalize content, or they’re being required to personalize content, but they have to rely on manual work to make that happen.

Alan Pringle: No. Just like I was talking about formatting, it causes me pain to hear about people who are basically copying and pasting content over and over and over again to make slight variations of content for different audiences. It happens all the time. Again, please don’t do that to yourself if you can help it. This can be basically the thing to help push you into improving your content operations.

It’s, again, a question of efficiency, a question of reuse. There may be a core of content that pretty much stays nearly the same or static. It’s just there’s bells and whistles on the edges that need to change based on location, on audience, or whatever else. What you’re going to have to do is build on that intelligence. So you have got some content that’s being reused, and then you have flagged the stuff that is specific to a particular audience or whatever else. When you start getting into building in that kind of intelligence, you’re talking about structured content, usually XML, not always XML, but usually XML.

So you can build in that intelligence that says, “Okay, this is my common core of content. Then here are things that are a little bit different for all of these different things.” And you can have this huge matrix of things that are different, audience location, product version level, whatever else. And then, based on those things, you can put in that intelligence and then turn off… turn certain content on and off when you create whatever delivery points that you have, whether it’s print online or whatever else these days. Lots of choices there too.

Christine Cuellar: Yeah, that’s great. Is that something… Okay, just because this is kind of top of mind because we’ve been talking about this a lot recently. Is that something… If people are interested in pursuing that, should they look more at content as a service? Where would you recommend they dig for more information on creating that kind of a system?

Alan Pringle: Again, I would say go backwards and think about your requirements, what those things are. Personalization as a requirement. Yes, content as a service, and let’s explain what that is. When you have built intelligence into your content about audience, product variant, whatever else, version, you can connect systems together in a way where the system that is going to present the information to the end users, to the content consumers can pull the information that it needs from the repository where you have stored your content with that intelligence built in. Yes, content as a service is great.

It sounds great, but you don’t start there. People don’t just say, “I need content as a service.” They may, but I don’t think it’s something that comes to top of mind immediately. What they’re thinking is, “I need a way to personalize this content for my different users so they get exactly what matches the version of the product that they’re using, for example.” Or, “I need the people who were taking this course and this learning management system to get things zeroed in on the way that they have their software configured and they’re trying to learn about it.”

Christine Cuellar: Yeah.

Alan Pringle: To me, there, there’s a distinction there. Yes, content as a service is a way to solve those problems, but I don’t think people generally go there top of mind. “That is what I need.” They think more about, “I need personalization.” Content as a service is a way to get it. That’s how I would like to frame it anyways.

Christine Cuellar: Yeah. No, that totally makes sense. They need that personalization, but they need to not be relying on some person or a group of people going in and manually making all those changes because that’s just not… that’s not feasible to keep up with.

Alan Pringle: Oh, people do it all the time, and then they end up all having breakdowns because it’s just not sustainable. Yeah.

Christine Cuellar: Oh, yeah. Oh, yeah.

Alan Pringle: It’s awful.

Christine Cuellar: Especially as you grow. And yeah, I can see that’s a major scalability issue in so many different ways.

Alan Pringle: Yeah, yeah.

Christine Cuellar: So do you have any examples of that inaction about companies that need to personalize content that have been set up for success now? Even if it’s an unnamed example or stories you can share there?

Alan Pringle: Yes, and I’ve got to be careful here because I don’t want to get too much into it-

Christine Cuellar: Yeah.

Alan Pringle: … to identify customer. But yes, we have done things where the end user is getting information, whether it be from a web-based portal, for example, that matches exactly their customer profile. So yes, we have done this, and I know you probably want more details than that, but-

Christine Cuellar: No, that’s fine.

Alan Pringle: … I don’t want to go too deep into it, but yes.

Christine Cuellar: Yeah.

Alan Pringle: We have done it. We are doing it as we speak. As we record this, we are working on projects trying to do that very thing. So that’s very much in our wheelhouse, indeed.

Christine Cuellar: Okay. No, yeah, absolutely. That’s great. That’s a great example. Okay, so let’s switch gears to another pain point. What has it been like for… or what do you recommend for people who are struggling with the pain point of inconsistent content? Either inconsistent content or maybe inconsistent ways of creating the content.

Alan Pringle: Well, inconsistency can be many levels here. It can be the tools that you are using. Not everybody’s using the same thing, maybe because of a merger. It can be the way that the content is organized. It’s not the same from one product to another or one service to another. It could also be as getting more down at the content itself. The way that people describe things. You are not consistent in what you call this widget in this document versus how you describe that widget in what it does in this online document over here. So there are multiple layers of inconsistency here, and it can even be as using certain terms and terminology.

You’re not consistent in how you do that. And again, there are technologies that can help with all of those things. For look and feel, templatization can help make things more consistent, or you can move to structured content and have your formatting applied automatically to take care of that consistency. There are ways to basically enforce word choice, control vocabulary tools to be sure that you’re using the terminology in your company consistently or different authors and content creators and content contributors are using a term consistently.

Alan Pringle: So again, there are lots of layers here, but there’s a way to solve all of them that basically you can use tech to take that burden off of you, so you’re not having to always think about those things all the time. Having tech provide you a helping hand. And I dare say there’s a point we’re reaching now where even artificial intelligence, AI tools, can help with some of these things too.

Christine Cuellar: Yeah.

Alan Pringle: So as much as I get so tired of hearing about AI and all the irresponsible talk about it, you can also look at and frame AI as a tool to help you make things more consistent. It can help. For example, maybe look across a vast body of content and find where there are things that are not consistent, so you, as a human, don’t have to go and do all that horrible, crappy work.

Christine Cuellar: Yeah, yeah. And going back to something you said earlier about this. You mentioned, okay, so using a merger as an example, people using all these, trying to consolidate these different systems or trying to just work in these different systems after mergers.

Is it common for people to be, for lack of a better word, putting up with dealing with a bunch of different systems until the pain is just absolutely unbearable and they have to reach out, like putting up with this for years or something like that? Is that pretty common, or do you feel like this is a pain point that is painful enough that people reach out pretty quickly when it crops up?

Alan Pringle: I hate to keep saying it’s not one size fits all, but it’s not. Some people recognize the problem earlier than others. Some people just kind of put their heads down to the grindstone and deal with it and grit their teeth. Other people, especially if you’ve got somebody new coming in who’s maybe done things a little differently before, and they see these things, and they’re like, “Oh my God, what are you people doing to yourself? Stop.”

Christine Cuellar: Yeah.

Alan Pringle: It can be-

Christine Cuellar: Fresh eyes.

Alan Pringle: … a catalyst like that.

Christine Cuellar: Yeah.

Alan Pringle: So…

Christine Cuellar: Okay.

Alan Pringle: Yeah, fresh eyes. That is really a dull answer, but that’s often what happens.

Christine Cuellar: No, that makes sense. Yeah, no, that makes sense. And does it make the problem worse if people put it off, put off consolidating systems, or does that not really matter?

Alan Pringle: Oh, I think it does. I mean, think about it. What happens if you ignore a plumbing problem in your house? Is it just going to go away by itself? No, it most certainly is not.

Christine Cuellar: It’d be nice, but yeah.

Alan Pringle: Yeah. I mean, just think about it. “Oh yeah, I’m going to ignore the fact that I have got a dripping hole in my ceiling or there’s water pouring down my wall. I’m just going to ignore it and hope it goes away.” I don’t think that’s the best way to handle that. And that’s true of content operations as well.

Christine Cuellar: It’s the ostrich approach, right. “If I can’t see, it’s not real. It’s not… We’re fine.” Yeah, that doesn’t ever work out. That kind of leads me into another pain point that actually came up quite a lot. Yeah. Doesn’t work. A lot of people mentioned executives or managers not valuing content, which kind of seems like that would be related to this. That was a pain point that we have often seen. Can you talk a little bit more about that?

Alan Pringle: There is an issue where people who create content and their contributions sometimes are not quite understood, or they’re overlooked by executives. A lot of executives are focused on numbers. That is their language.

Christine Cuellar: Mm-hmm.

Alan Pringle: They don’t care about the tools that you’re using. They don’t care about anything but, for example, that people are getting the content they need and not calling a help center, and costing money. That’s when they care about content. They’re looking at it from a different lens.

Christine Cuellar: Yeah.

Alan Pringle: So if you’re going to communicate to them about content, you’ve got to talk metrics, you’ve got to talk numbers, you’ve got to talk money, and that’s where sometimes content creators fail. They don’t look at things that way. So that’s sometimes where a consultant can come in handy and start to help you speak “C-level-ese”—

Christine Cuellar: Yeah, yeah.

Alan Pringle: … basically to kind of bridge that gap between, “This is what’s broken versus this is how we can fix things, and it will increase productivity and better metrics.” Less money spent, better results, that sort of thing.

Christine Cuellar: Yeah, that makes sense. And it sounds like bridging that gap of communication both ways, you’re both helping executives understand the value and helping content people communicate their value. Is that accurate to say?

Alan Pringle: That is fair, and again, not one size fits all. There are some executives, especially that have come up through the ranks of content. They get it.

Christine Cuellar: Yeah.

Alan Pringle: They totally get it. So there are some people, and those people are great to work with. Sometimes, people need a little education, and I’ll just leave it at that.

Christine Cuellar: Yeah, yeah. No, that makes sense. And so you mentioned metrics. What are some metrics that content individuals can have just on hand to start communicating their value to their team, to their company?

Alan Pringle: One thing you can do is kind of get what’s the dollar value you can place per hour on what it costs for a content creator to develop and distribute content. Find a way to find out what that amount is, what that dollar value is. Then, take a look at, for example, what if you automate publishing and cut out 80, 90% of that work by automating publishing? What’s that worth? What’s the dollar value on that? What’s the dollar value on getting closer to simultaneous shipment on localized content?

When you get your product, your service, whatever out there to other markets in this very, very global world environment now, everything’s so interconnected if you get things out to all the different markets, almost at the same time, how much more money are you going to pull in than if you had to wait three, four months for the localized version to get out there to those customers? So think about things like that.

Christine Cuellar: Yeah, those are great. Those are really helpful examples. And do you have any specific recommendations on how those should be communicated? Is that something that should be in a big kind of company team meeting? I know that’s probably a case-by-case basis, but-

Alan Pringle: Well, again, I mean, what is the executive team’s preferred way of communicating? There’s your answer right there.

Christine Cuellar: Yeah. Yeah.

Alan Pringle: If they don’t like email, why are you going to send that … email? Don’t do that.

Christine Cuellar: Don’t send an email that doesn’t communicate your value.

Alan Pringle: No. If they like spreadsheets, put that mess in the spreadsheet. It depends on the audience. You need to find a common ground with the people that you’re creating these stats for and share it in a way that they can absorb and appreciate whatever that is. And me telling you what to do here is not as helpful. You need to do some digging or have your consultant work with you to figure out the best way to communicate that and do it that way.

Christine Cuellar: Yeah, absolutely. That makes sense because ultimately, I think if you can communicate… Because content really does have real business impact and real business value, and so it’s just about communicating that.

Alan Pringle: Yeah. And this is… And it’s not even just in regulatory situations. Yeah, content in regulatory situations matters a whole lot because if it’s non-existent or wrong, somebody’s going to die or get injured.

Christine Cuellar: Mm-hmm.

Alan Pringle: Even beyond that, even if you’re not in a regulated environment, there are contributions content can make to keep customers happier, to keep down support costs, and many other things. Not everything is tangible. A happy customer, that can be hard to quantify. But a happy customer not calling your support line, you can quantify that. So that’s-

Christine Cuellar: Yes.

Alan Pringle: … one way to look at it.

Christine Cuellar: Absolutely. I know just personally, for me, I’m much more likely to continue or stick with a company where I can do… I can be pretty self-sufficient. If I have problems, I can look it up and deal with the problem myself. And if I do have to contact support, it’s a quick call that gets resolved easily.

That’s just… I think that is how people make their purchases nowadays. And I know that’s kind of more of a consumer kind of mindset rather than business-to-business. But that’s a big part of the consumer experience is can I get what I need just with the content that you already have out there in the world?

Alan Pringle: Yeah. And I think it’s worth mentioning here that when people go to your site and look at the content that’s available out there that’s associated with whatever product or service they’re considering, it could be support content, it could be a help portal, it could maybe even be training content. They are not just looking at your marketing to make a decision here.

Christine Cuellar: Yep.

Alan Pringle: There are other content types that come out to play. And anything that’s out there that the public can get to and see, believe it or not, that’s marketing content, and you need to treat it as such and understand its value as that as well.

Christine Cuellar: Yeah, absolutely. Well, Alan, I think that’s a really good place to wrap up. Clearly, we could talk about pain all day because we have a lot more to…

Alan Pringle: It’s my job, what can I tell you?

Christine Cuellar: Yeah. Yeah. So we are going to continue this discussion in the next podcast episode. Alan, thanks so much for being here with us today.

Alan Pringle: I haven’t run away, so let’s-

Christine Cuellar: Yeah.

Alan Pringle: … get to the next episode.

Christine Cuellar: Thank you for listening to the Content Strategy Experts Podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Ask Alan Anything: Resolving pain in content operations (podcast, part 1) appeared first on Scriptorium.

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In episode 154 of The Content Strategy Experts Podcast, Bill Swallow and Christine Cuellar discuss the similarities between the industry-disrupting innovations of machine translation and AI, lessons we learned from... Read more »

The post How machine translation compares to AI appeared first on Scriptorium.

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In episode 153 of The Content Strategy Experts Podcast, Sarah O’Keefe and special guest Dr. Carlos Evia of Virginia Tech discuss the upcoming book ContentOps Edited Collection: Content operations from... Read more »

The post ContentOps edited collection: Content operations from start to scale (podcast) appeared first on Scriptorium.

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In episode 152 of The Content Strategy Experts Podcast, Sarah O’Keefe and special guest Stefan Gentz of Adobe discuss what knowledge content is, what impacts AI may have, and best... Read more »

The post Applications of AI for knowledge content with guest Stefan Gentz (podcast) appeared first on Scriptorium.

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In episode 151 of The Content Strategy Experts Podcast, Bill Swallow and podcast guest, Jack Molisani discuss how content careers have changed through the pandemic, layoffs, quiet quitting, and AI,... Read more »

The post Adapt to evolving content careers with guest Jack Molisani (podcast) appeared first on Scriptorium.

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In episode 150 of The Content Strategy Experts Podcast, Alan Pringle and special guest, Patrick Bosek of Heretto talk about choosing a content model, factors to consider, and when you... Read more »

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In episode 149 of The Content Strategy Experts Podcast, Sarah O’Keefe and Christine Cuellar discuss the unique challenges, opportunities, and considerations of content operations with elearning content. “As an instructional... Read more »

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In episode 148 of The Content Strategy Experts Podcast, Anthony Olivier, founder and CEO of MadCap Software, and Sarah O’Keefe discuss the MadCap acquisition of IXIASOFT, what’s on the horizon... Read more »

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In episode 147 of The Content Strategy Experts Podcast, Alan Pringle and Christine Cuellar continue talking about how teams adjust when content processes change, and tools you can use to... Read more »

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In episode 146 of The Content Strategy Experts Podcast, Alan Pringle and Christine Cuellar talk about how teams adjust when content processes change, and how you can address the question, “Why... Read more »

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In episode 145 of The Content Strategy Experts Podcast, Bill Swallow and Christine Cuellar discuss the impact content operations has on your learning and training content, and how to make... Read more »

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In episode 144 of The Content Strategy Experts Podcast, Alan Pringle (Scriptorium) and special guest Rich Dominelli (Data Conversion Laboratory) tackle the big topic of 2023: artificial intelligence (AI).

“I feel like people anthropomorphize AI a lot. They’re having a conversation with their program and they assume that the program has needs and wants and desires that it’s trying to fulfill, or even worse, that it has your best interest at heart when really, what’s going on behind the scenes is that it’s just a statistical model that’s large enough that people don’t really understand what’s going on. It’s a model of weights and it’s emitting what it thinks you want to the best of its ability. It has no desires or needs or agency of its own.”

— Rich Dominelli

Related links:

Data Conversion Laboratory
AI songwriting is not a sin, says Neil Tennant of Pet Shop Boys
Samsung Bans Staff’s AI Use After Spotting ChatGPT Data Leak
Structured content: the foundation for digital transformation (podcast)

LinkedIn:

Rich Dominelli
Alan Pringle

Transcript:

Alan Pringle: Welcome to The Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. Hi everyone, I’m Alan Pringle. In this episode, we are going to tackle the big topic of today, artificial intelligence, AI. And I am having a conversation with Rich Dominelli from DCL. How are you doing, Rich?

Rich Dominelli: Hi Alan. Nice to meet you.

AP: Yes. We have talked back and forth about this and I expressed I have a little bit of concern about touching this topic. There is so much bad coverage on AI out there right now. Click bait-y, garbage-y headlines, breathless reporting, and I’m hoping we can kind of temper some of that and have a discussion that’s a little more down to earth and a little more balanced. And let’s start talking about what you do at DCL and then we can kind of get into how AI connects to what you’re doing at DCL.

RD: Sure. As you know, Data Conversion Labs has been around since 1981, and we are primarily a data and document conversion company. So my role at DCL is a architect for the various systems at DCL that covers a wide variety of topics, including implementing workflows, doing EAI style integrations to obtain new documents, and also looking for ways of improving our document conversion pipeline and making sure that conversions are working as smoothly and automatically as possible.

AP: And I’m hearing a lot about automation and programming and I can see AI kind of fitting into that. So what are you seeing? How are you starting to use it? And you may already be using it at DCL.

RD: So AI is a very broad term and I feel like it’s something that’s been kind of shadowing my career since the dawn of time. Back in the Reagan era in the 80s when I was graduating from high school and looking to start my college career, I was told at the time not to enter computer science as a field because computer programming had maybe two or three years left and then computers going to be programming themselves with case tools and there won’t be any careers for computer programmers anymore except a couple of people here and there to push the button to tell the computer to go. That obviously hasn’t panned out.

AP: No.

RD: Although I feel like every few years this is a topic that starts cropping up again. But at DCL we have used what we would call machine learning more than AI. And I guess the differentiation there is machine learning is using statistical analysis to process things in an automated fashion. For example, OCR and text to speech were both pioneered by Ray Kurzweil.

AP: And OCR is, just for the folks who may not know.

RD: Sure. Optical Character Recognition. Taking text or printed words or even handwriting and analyzing it and generating computer readable text out of it, taking that image of a file and converting it to text. So as I said, Ray Kurzwell did some early pioneering work on that in the late 80s, early 90s, and eventually worked on models of the human mind and comprehension. And I think that’s what people are envisioning now when they say the word AI. But even the panorama mode in your camera is a version of machine learning and AI. It takes the ability to stitch images together smoothly and processes that automatically.

Other places at DCL where we do use AI on an ongoing basis is we do natural language processing, looking at unstructured texts and trying to extract things like references, locations, entity recognition where we have a block of texts and buried in that block of texts is a reference to a particular law, or a particular document, or a particular location or person. So that type of work we’ve done. We use it for math formula recognition. So if we have an academic journal that has a large amount of mathematical formulas, for example, we do some work for the patent office and patent applications frequently have mathematical or chemical formulas in them.

AP: Sure.

RD: Putting that information out and recognizing that it is there to be extracted out would be an application of AI that we use all the time.

AP: With the large language models that we’re seeing now, a lot of them are kind of reaching out and people can start experimenting with them. What are you seeing in regard to those kinds of situations? I don’t know if public facing is the right word, but the stuff that’s more external to the world right now.

RD: It is certainly the most hyped aspect of AI right now.

AP: Exactly.

RD: … where you can have a natural language conversation with your computer and it will come back with information about the topic you’re looking for. And I think that it has some great applications for things like extracting or summarizing text. It’s a little risky though. For example, I have a financial document, a 10K form from IBM. Buried in that document is a list of executive officers and a statement of revenue. And I ask ChatGPT, “Given this PDF file, give me a list of executive officers.” And interestingly enough, it does come back with a list of executive officers, but it’s not the same list that appears in a file. It’s a list that it found somewhere else in its training data. When I say please summarize the table on page 31, it does come back with a table, but the information that appears on it is not what is on that page of the PDF app. And in the artificial intelligence world, this is called a hallucination. Basically the AI is coming back with a false statement. It thinks it’s correct or it’s trying to convince you it’s correct, but it’s not.

AP: Yep.

RD: So that is very concerning to me, because obviously we want as accurate as possible when you’re doing document conversions. And if that doesn’t occur all the time, I mean if it came back with an accurate example, but let’s say two or 5% of the files that I throw at it, it comes back with fiction. That’s not an acceptable thing because it’ll be very hard to detect. It looked really good until I went back and said, oh wait a minute, wait, where did it get that from?

AP: We have done some experiments and I’m sure a lot of people listening have too. Like I asked for a bio on myself and it told me that I worked at places where I have never worked. So yeah, it’s not reliable. And I think there’s another element here too that scares me beyond the reliability. A lot of these models are training on content that doesn’t really belong to the person who put together the engine that’s doing this. It’s compiling copyrighted content that doesn’t belong to them. I think there are a lot of legal concerns in this regard. I was talking with someone on social media about how you can maybe use AI to break writer’s block. The group, The Pet Shop Boys, the songwriter, and the vocalist of that group, Neil Tennant recently said, I have a song that I tried to write 20 years ago and I put it away in a drawer because I couldn’t finish the lyrics.

I wonder if AI could look at the song and the kind of work I’ve done and help me figure out how to finish some of these verses. Now I may turn around and rewrite them and change them, but it might be a way to break writer’s block. And I see that being a useful thing even for corporations. Put basically all of your information in your own private large language model (AI) that doesn’t leak out to the internet. It’s internal. So then you can do some of the scut work, like writing short summaries of things, seeing connections maybe that you haven’t seen. But the minute you get other people’s content, their belongings, other people’s art involved, it becomes very squishy. And I’m sure there are liability lawyers just going crazy right now thinking about all this kind of stuff.

RD: Well, you certainly see a lot of that in the stable diffusion space, the art space.

AP: Yes.

RD: Where AI is being trained on outside artists’ work and are very easily able to mimic those artists often without their permission. I do think you touch on a very important point there, actually two. One, the fact that anything you type into OpenAI by default is being shared with,

AP: Right.

RD: … OpenAI. And as a matter of fact, Samsung, the company just banned OpenAI for all of its employees for that very reason because they had taken to using it for summarizing meeting notes and things like that, and they discovered very quickly that trade secrets were leaking because of that.

AP: Intellectual property. Not a problem, let’s just share it with the world! Yeah.

RD: Yeah. So actually what Samsung is doing is exactly what you said. They’re making an in-house large language model for their employees to continue to be able to do that type of work using that. The other aspect of what you touched on, which is where I think the real sweet spot is right now, using these tools as a way of augmenting your ability.

AP: Yes.

RD: Especially as a developer, just because that’s my space.

AP: Sure.

RD: As a developer, most developers have a stack overflow of Google when they’re trying to research on how to attack a problem properly. “What’s the best way of solving the problem?” Now you have your paired programming buddy ChatGPT, and you can say, “Hey, I need to update the active directory with this and how do I do that?” And ChatGPT will spit out working code, or even better, I can throw code that is obfuscated, whether intentionally or not.

AP: Right.

RD: … at ChatGPT, and it will produce a reasonable summary of what that code is attempting to accomplish. And that is fantastic. And you see tools like Microsoft Copilot, which they’re doing in conjunction with GitHub. Google also is having a suite of Bard tools for helping you do that and that type of thing is starting to leak into other spaces. So Microsoft Copilot, for example, is now being integrated into Office 365. So it will help you while you’re writing your memo, while you’re working on your Excel spreadsheet, while you’re working on your PowerPoint, rephrase things, come up with a better approach. In Excel, it’s great because it’ll tell you, well, this is the best way of approaching this macro, for example, or this formula and that type of thing is, I think, fantastic.

AP: Sure. And I’m more on the content side of things and we’re seeing some of the similar things that you’re talking about. For example, the Oxygen XML Editor has created an add-on that will hook into ChatGTP, PT. Look at me getting that wrong. I do it all the time. FTP, GPT, sorry.

RD: Too many acronyms.

AP: Too many acronyms floating around here. So basically it will, like for example, look at the content you have in a file and write a short summary for you so you don’t have to do it yourself. That could be a very valuable thing, but again, do you want people in the world seeing or getting input from your content? Probably not. So if you could create your own private large language model (AI) and then turn everything into that, I see there’s a lot of value because it will help for example, a lot of people who are writing an XML, it can help clean up their code like you were talking about. Or you could take some unstructured content and it could do probably quite a passable job of cleaning it up, adding structure to what was unstructured content. So I do see some very realistic uses there that could be very helpful. And do I see these things taking away someone’s job? Not right this second in this regard, but I see it basically taking something that’s not so much fun off their plate so they can focus on more important things.

RD: Absolutely. The most recent phrasing I saw for that is it replaces that junior programmer that most groups have that you’re looking to do scut work. This is the person who’s going to do the eight days of data entry to convert everybody over to a new system or that type of thing. That type of work nobody wants to do, but that’s what junior developers get stuck with.

AP: And that is very true, and there is a writer strike going on right now, and part of the concern with that strike is content that may be created by AI. Now, is AI going to write a really good script right now? Probably not. Could it write something that is the starting point, the kernel that someone can then take and do something bigger with, clean it up? Yes. And that may eliminate junior writer positions. So there is some concern, very similar to what you’re talking about. There is this situation where we have to think about how are people going to get into an industry when AI has taken away the entry level jobs. That’s going to be something very difficult to tackle, I think.

RD: I suspect you’re right. But on the other hand, you end up in this collaborative space where if you do have that writer’s block, like you said earlier.

AP: Sure.

RD: This gives you somebody to bounce ideas off of and have a conversation with about the subject, about the program, about the article, or about whatever, the song you’re trying to write, which is fantastic. Now at DCL we have had some success. We are doing some work where we’re using a large language model to associate authors and institutions, for example, out of documents. And we have great success in that. Usually we can programmatically determine it, but on those fuzzy edge cases, and I think that’s where ChatGPT and large language models fit in is when it’s a really fuzzy edge case that it’s difficult to accommodate for all things. We’re actually using it and having good success at matching authors and affiliations on a consistent basis and double checking the work that we’re attaining programmatically.

AP: That’s great.

RD: For having your own ChatGPT clone, there is a lot of work out there. There’s GPT4All, there’s Mosaic, there’s a bunch of things where you can download a large language model to your local machine and run it and the performance is not as great as this massive monolith that OpenAI has going. But it’s not bad depending on what you’re trying to do with it. It’s not quite as advanced as GPT-4. But the nice thing about the open source community and their approach to this is you’re starting to see people iterating constantly. So Facebook was working on their own large language model and intentionally or not, there’s some debate about that. It was leaked out to the internet and it became this iterative community in the machine learning space where people were constantly iterating on this model, expanding the model, growing it.

You can access it now through Mosaic, you can access it through Alpaca and you can access it through GPT4All, and you can actually have those conversations running completely local with ever leaving your PC. So for those types of things, I think it’s great. Now, is it perfect? No. For example, a very easy test. There’s actually a YouTuber named Matthew Berman who tracks a lot of this, and he has a spreadsheet of about 20 tests he gives any new large language model, and a very simple example is most large language models still fail the transitive test. So in other words, if A is greater than B and B is greater than C is a greater than C? Okay. Or if John is faster than Fred and Fred is faster than Sarah, is John faster than Sarah? A lot of them fail that test. They just come back with an erroneous answer. The other issue you see is a lot of the AI models are not being updated constantly. So they’ll still see it as 2021, for example.

AP: Right. And what you just said kind of reminds me of something. All this somewhat overblown talk AI’s going to take over the world. Well, AI’s not going to take over the world if the content that it’s basically scraping, and I know that’s really simplifying things a whole lot. If that content is not good, it’s not updated, humans aren’t putting intelligence in it, it’s not going to be that useful. We still have to provide the underpinnings for a lot of the intelligence in these systems. So are our brains going to be replaced today? Probably not.

RD: No. But the bar, or I guess the bar is getting lower and lower as time moves on.

AP: Fair. That is fair.

RD: It’s definitely getting better. For example, GPT OpenAI has updated ChatGPT where we’ll now actually go out to the net and get more up-to-date information. It may not have internalized that information, but it will actually perform a web search, extract information that way now and come back with it. And that was released recently. You have now work going into how quickly you can train a model, which is a huge thing. GPT-4 has been trained on 100 trillion parameters, which took weeks and weeks of time to train and to do a new one using that methodology would continue that curve. It would take months to train a new one, but there’s now work being done of, okay, if I have a pre-trained model, how do I quickly iterate on that model so that it doesn’t take me weeks? It may just be a question of ingesting new information on a daily basis, a little bit of news feeds or that type of thing.

AP: Sure. Let’s talk about risk to wrap up here. I brought up the copyright angle. What do you see as a big concern here, your biggest concerns?

RD: So, there’s a couple of things that are big concerns of mine. One, I feel like people anthropomorphize AI a lot.

AP: Yes.

RD: They’re having a conversation with their program and they assume that the program has needs and wants and desires that it’s trying to fulfill, or even worse, that it has your best interest at heart when really what’s going on behind the scenes is this is just a statistical model that is as large enough that people don’t really understand what’s going on, but it’s a model of weights and it’s emitting what it thinks you want to the best of its ability. And it has no desires or needs or agency of its own.

AP: Yeah, I want to make t-shirts, Large language models are not people, so yeah.

RD: The other thing is we’re starting to, and there’s some press about this where we’re talking about — bias.

AP: Yes.

RD: A good example of that or not so good example of that is when you have an AI model that hasn’t been trained for anything but western culture. It’s inherently biased towards American values, American positions on the world. What the AI will spit out may not be culturally acceptable in other places and vice versa. I mean, an AI trained in China is probably not going to give you the same response for things that you care about in America.

AP: Yeah.

RD: You can also, a lot of these companies have inherent rules and there’s actually a game going on. Microsoft’s AI started as a program code named Sydney, and there’s an ongoing game that people who are doing prompt hacking or prompt engineering to try to discover all the rules inside Sydney. It’s things like, well, Sydney will never call itself by Sydney and things like that. And it almost starts devolving to the point where you’re dealing with Isaac Asimov’s three laws of robotics or Robocop’s prime directives, where you have a list of instructions that are overriding the basic approaches that the AI can do. This is probably getting too philosophical for a content program, for a content transformation podcast, but I mean these types of things will color responses. So if you are asking in AI when it’s ingesting a program to emit certain key characteristics, those key characteristics may be shaded by these rules, may be shaded by this training.

AP: And that training came from a person who inherently is going to have biases, right?

RD: Exactly.

AP: Yeah. Yeah.

RD: So that type of thing is a problem.

AP: Yeah. I mean, AI in a lot of ways is a reflection of us.

RD: Yeah.

AP: Because it’s, a lot of times, parsing us and our content, our images, and whatever else. This has been a great conversation. It went some places I didn’t even expect, and that is not a criticism, trust me. So thank you very much, Rich. I very much enjoyed this, and it’s good to have a more balanced kind of realistic conversation about what’s going on here. I appreciate it a whole lot.

RD: Okay. It was very nice talking to you.

AP: Thank you for listening to The Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post AI: Rewards and risks with Rich Dominelli (podcast) appeared first on Scriptorium.

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In episode 143 of The Content Strategy Experts Podcast, Gretyl Kinsey and Christine Cuellar are back discussing the common tripping points companies stumble over while implementing their content management system (CMS) and their component content management system (CCMS). This is part two of a two-part podcast.

“If you’ve got people working in a web CMS and you’ve got people working in a CCMS, and they’ve always worked separately, and then suddenly you ask them to come together and collaborate and maybe have one group or the other choose a new tool so that they can share content, but they’ve never had that process of working together, there’s going to have to be not just a tool solution to get them working together, but a people solution and a whole different mindset in the way that they work together.”

— Gretyl Kinsey

Related links:

Balancing CMS and CCMS implementation (podcast, part 1)
Glue strategy: connecting web CMS to CCMS
Connecting the XML and web CMS mindsets
What is a CCMS, and is it worth the investment?

LinkedIn:

Gretyl Kinsey
Christine Cuellar

Transcript:

Christine Cuellar: Welcome to the Content Strategy Experts podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. Hi, I’m Christine Cuellar. In this episode, Gretyl Kinsey and I are back continuing our discussion about implementing your CMS and your CCMS. And today, we’re specifically talking about the tripping points that your company should watch out for and other tools to consider as you’re going about this implementation. This is part two of a two-part podcast. Thanks, Gretyl, for coming back on the show.

Gretyl Kinsey:

Absolutely.

CC:

So what are some more tripping points that can trip organizations up when they’re implementing their web CMS and their CCMS?

QK:

Yeah, one big one is kind of what we were talking about with those competing priorities, right? So we talked about having the competing priorities between the creative side and more of the marketing customer facing side versus people who need more structure in their content because of legal and regulatory requirements. And what this often looks like at an organization is that you’ve got your web CMS people, and then your DITA CCMS people and those competing priorities. And one thing that we see a lot of times as a tripping point or something that gets them tripped up when they have to look at maybe aligning on tool selection or getting new systems working together is figuring out how to strike that balance we talked about so that they’re not competing priorities, but they’re instead aligning their priorities. So we do see a lot of common areas where they struggle to come into alignment.

And a few things, a few examples of things where I’ve seen this go wrong are where each group is choosing their own tools without communicating about it. That happens a lot of times, especially if there isn’t really proper involvement from management. People have just been told this group, this department, pick a tool that is going to improve what you’re doing. And then of course you have a whole other department somewhere else that’s being told the same thing. They’re not talking to each other about it at all. And then eventually down the road, they’ve picked their tools, they’re all established, and then something comes up where they realize that they needed those tools to be compatible for sharing content or connecting to each other, and then they can’t. Because when they were choosing the tools, they didn’t think about that. They didn’t talk to each other. So then they’re stuck in a really expensive and painful mess to fix if they need to get past that problem.

So that’s something that we have been called in as consultants to help fix several times, and that we’ve seen organizations take that path without really stopping and thinking, before we evaluate and choose a tool, we’ve got to get all the different groups who might have a use for that tool or need to integrate tools talking to each other. So that’s one big thing that can go wrong. Another one is related to how the upper management at an organization does or does not prioritize content. So one issue we see a lot is where, let’s say one type of content gets prioritized over another, and we’ve seen some examples where they have a very heavy emphasis on training content. Let’s say this organization has an educational focus. It’s all about learning. It’s about the training materials. So maybe they focus on something like a learning management system, but they don’t realize that they also have to deliver some legal documentation.

They also are going to be marketing their services, and they don’t think about aligning all the different tools that these groups are going to be working on. And once again, it’s too late, right? And so what happens when the management is really prioritizing one type of content over all the others, is that when these different groups have those competing priorities, management’s decision makes one group the winner and everybody else the losers when it comes to their priorities.

CC:

Oh, yeah.

QK:

And so that can make things really tricky if the groups need to work together, but there’s clearly one group being favored, and being given all the budget and all the resources while the others’ needs are being ignored. And then of course, the even worse situation is when upper management does not care about content at all. They don’t really think about content as a priority for the business. And so that’s bad for any or all groups who produce content. So if you’ve got the situation of, let’s say people in a web CMS and people in a CCMS, for example, and those groups both need to be aligning and improving the work that they’re doing, but management doesn’t care about content at all, then that just leaves it as the groups having to fend for themselves, and it kind of can turn into a free for all of the competing priorities because they don’t have any guidance for management.

So I think that’s a really important thing when you’re looking at content from more of the bird’s eye view where we come in as consultants, is we look at not just the content creators, but we look at the different levels of management and particularly the highest level and how much do they prioritize content, and how does that affect their decisions, because that obviously has an effect on the groups producing the content and really can make or break the work they’re doing.

CC:

Yeah. And it also affects the business because content is a really big asset in your business, to really bring value to your customers to make your operations flow very smoothly. So I would say that the business is also losing out when you don’t prioritize content. So a lot of times, that resource does go, I guess, untapped.

QK:

Absolutely. And then we also see groups struggling to align on their priorities and their tool selection because they’ve always been siloed. So that gets back to sort of what we talked about earlier where you want to avoid those silos just because this is something that can happen. If you’ve got people working in a web CMS and you’ve got people working in a CCMS, and they’ve always worked separately, and then suddenly you ask them to come together and collaborate and maybe have one group or the other choose a new tool so that they can share content, but they’ve never had that process of working together, then there’s going to have to be not just a tool solution to get them working together, but a people solution and a whole different mindset in the way that they work together.

So that can really be challenging for tool selection as well. Because if these people have never even talked to each other, and then you’re asking them to come together and evaluate some new software for one or both groups, then it’s going to make that process, I think, a lot trickier than if they had been working together all along.

CC:

Okay. So we’ve seen how upper management not prioritizing content causes a lot of issues. How would you recommend upper management start to be active so that the content departments, all of them, can really feel supported, and they can get the most out of their content?

QK:

Yeah. So I think it comes down to a lot of what you said, actually realizing that content is an asset for your business and making it a priority. And then within that, upper management should be taking an active role in helping these groups to choose the tools that are going to work for everyone and benefit the entire organization, and not just leave it up to an individual department to say, “Hey, make a decision.” If you are going to invest in a new system for your organization, then I think it really behooves you as a manager, or especially even at the C level, to make sure that you have a hand in that evaluation and that the tools that you’re selecting are going to benefit the entire company. And then another thing is realizing all the different things that content can do for the business and continuing to invest resources in it.

And that’s not just tools, but also people, making sure that your content creators are going to be maximizing the value and the potential of your content. And the more that you put into that content, the more you’re going to get out of it. So making it that priority. And then of course, taking a leadership role in fostering communication between groups that might have those competing priorities or those competing needs. So this is an area, where I think in particular, we’ve seen it be helpful to bring in an outside voice like a consultant, just because even if you are in upper management and you’ve got sort of that bird’s eye view of your organization, you still are not going to necessarily have the objectivity of an outsider. And so…

CC:

Yeah.

QK:

… it might help a lot if you’re struggling to get groups who have been, let’s say working in silos, or who are going to have to choose maybe a CMS over here and a CCMS over here. Getting them into alignment, it might just help to get a consultant in to really hone in on what some of the communication issues are, and then help move past it so that you can actually make that selection.

CC:

Yeah, absolutely. Getting an outside perspective, I just feel like that always helps because they can see things that you’re not seeing or thinking of and be that third party unbiased voice that really guides you in the right direction. So what are some other tools that might need to be connected to a CCMS as well? I know we’ve talked about… I mean, the big one we’ve been talking about is a CMS and a CCMS. Are there other tools that need to be connected to a CCMS or even to the CMS?

QK:

Absolutely. So one example, which I mentioned a little bit earlier, is an LMS or a learning management system. And again, if you are an organization that has a lot of training content, a lot of educational content, a lot of learning material, and that is both for in person or e-learning, or any other kind of non-classroom training, then a learning management system might be really beneficial for the process of storing and creating and managing that particular type of content. And then also another example would be TMS, or translation management system, and then lots of other related translation tools. So this is something we see really commonly if you have to deliver translated or localized content, and it becomes more and more important, so kind of focus that you put on those particular tools, the more languages that you have to translate into because this is really an area where both cost can be an issue, but then also where you have to get it right, because there are a lot of times those legal and regulatory requirements around delivering content in certain locations, in certain languages.

And so that’s something that you really want to make sure that you’re doing correctly so that nobody’s going to get into any trouble. And then another example of a tool you might need to be connected is a DAM, or a digital asset management system. And this is for storing and managing things like images, videos, other digital assets that are used in or delivered with your content. And a lot of times when you look at something like a CMS or a CCMS, those usually have the capability of storing digital assets, but where we see organizations leaning toward using a DAM is if your content is very heavy on digital assets and not just text, or if there’s a lot of sharing of digital assets that has to happen across groups. I know in particular, and we’ve seen this, where for example, if you’ve got heavy machinery and you have a lot of diagrams of not just the machinery, but all the little pieces and parts that go into it that you might be in charge of selling or doing maintenance on, that’s the kind of organization that might have a dam.

Or if material has to have a lot of screenshots and illustrations and things like that, where if you look through any documentation, you would see just as many images, if not more so than words, then that would be an example of an organization where having a dam might work. And with all of these kinds of tools, it’s sort of what we talked about with the connectivity, that you can have either the level one connectivity where they’re actually integrated, or sort of more of the level two where they’re disconnected but can still share content. And this is where it becomes really important to think about a content tool chain or content ecosystem rather than just a disconnected set of tools, right? Thinking about how you’re going to make all of these different tools that you need for different parts of your content processes actually work together as a single working ecosystem.

So if you do need a CMS and a CCMS, and then maybe an LMS, a TMS, a DAM, or any of these other things, then it’s important to think about how you can get them all working together efficiently so that you can get the best value possible out of your overall content production.

CC:

Absolutely. And as you’re listening, if you’re in a similar situation trying to make these decisions or figure out what to do with all of these tools that we’ve been talking about, if you ever get stuck, there’s someone who can help, and it’s us. So if you ever have questions, feel free to contact our team. We’d love to help support and get you the information that you need.

QK:

Absolutely.

CC:

Gretyl, is there anything else you can think of that you want our listeners to be thinking about or understand about balancing their CMS and CCMS implementation that we haven’t already covered?

QK:

I think the one last piece of advice I will leave everyone with is to take the time to plan, take the time to really think about and evaluate your priorities, and don’t rush into any purchasing decisions when it comes to these kinds of tools. Like I mentioned, these implementations are major undertakings. They are major investments. They shouldn’t be taken lightly. And if you really want to get the most out of having these different kinds of connected tools or connected systems, then it is imperative to take that time upfront and really do a proper evaluation so that you don’t get stuck with a really expensive purchasing decision that was not the best one for you.

CC:

Awesome. Thanks. That’s great feedback. Well, thank you so much, Gretyl, for taking the time today to talk about this — twice!

QK:

Absolutely. Thank you.

CC:

And thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Balancing CMS and CCMS implementation (podcast, part 2) appeared first on Scriptorium.

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In episode 142 of The Content Strategy Experts Podcast, Gretyl Kinsey and Christine Cuellar discuss balancing the implementation of a content management system (CMS), and component content management system (CCMS). This is part one of a two-part podcast.

“When you have two types of content produced by your organization and different groups in charge of that, and maybe they’re in two different systems, that it’s really important to get those groups working together so that they can understand that those priorities don’t need to be competing, they just need to be balanced.”

— Gretyl Kinsey

Related links:

Glue strategy: connecting web CMS to CCMS
Connecting the XML and web CMS mindsets
What is a CCMS, and is it worth the investment?

LinkedIn:

Gretyl Kinsey
Christine Cuellar

Transcript:

Christine Cuellar: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. Hi, I’m Christine Cuellar, and in this episode we’re going to talk about how to balance the implementation of both your CMS, which is your content management system, and your CCMS, which is the component content management system. This is part one of a two-part podcast. I’m here with Gretyl Kinsey. Hi, Gretyl!

Gretyl Kinsey: Hi, Christine. How are you?

CC: I’m doing great. Thanks for being on the show. So, Gretyl, before we get started, I just want to kick off with a real basic question, and I know that we have a lot of content on this that we’ll link in the show notes. What’s the difference between a CMS and a CCMS?

GK: Sure. So a CMS or a content management system is generally a broader term, and that’s for a tool or a system that allows your organization to store and manage content. And this could be talking about a lot of different types of content storage in management and operations around that. A lot of the common ones that we see are things like storing print-based documents such as PDF files or updating and publishing your web pages. So this is really more of an umbrella term that you see for content management.

And then in a narrower scale, a CCMS or a component content management system is a specific type of CMS, and that’s used for creating, storing and distributing structured topic-based content. So, for example, we see this a lot with XML and more specifically DITA content. And the component portion of that name is talking about the fact that you have content in individual topics or chunks, and those are called components, and those are assembled into the deliverables that you send out to your customers.

CC: Gotcha. Okay. So why do a CMS and CCMS need to connect? What kind of integration are we talking about here that we need to be balancing?

GK: Sure. And I want to talk a little bit here about what exactly we mean by connect first, because there are two different angles to this that we see a lot. So one level of connection is when you have actual integration or connectivity between the systems where they hook in and talk to each other. And some systems are built actually with this in mind. So they’re designed to connect out of the box. So you might have a tool that has a web CMS and a CCMS under the same brand, and they’re designed to hook together and communicate. And then other times you could have CMSs and CCMSs that have the ability to connect with each other, but it’s not built that way out of the box. So it would be some kind of a custom connector that’s built like an API that allows them to have that integration.

And then the second level of connection that we talk about is where you have the ability to send content back and forth between two disconnected systems. So rather than that direct connection or integration, this requires a compatible content format and a process for getting that updated content from one system to the other. And this could be a one-way or a two-way connection, but it’s sort of more of a bridge rather than a direct integration where the systems are not actually connected, but they can still share content.

CC: Gotcha.

GK: And so when we’re talking about either of these levels of connectivity, either these types of connectivity, the ultimate goal is to prevent the CMS and the CCMS from becoming disconnected silos, because that is something we do see in a lot of organizations and it can have some real consequences for your content development. So one big one is inconsistent information coming out of each of those two systems. So if you’ve got all of your content in a CMS and then you’ve got a separate CCMS silo and they can’t connect or share content at all, you might have completely different processes for checking that content, making sure the messaging is the same, and if it’s inconsistent, then that looks bad to your customers at best, and then could get your organization into legal trouble at worst. So that’s one really important reason why we want to avoid those kinds of silos.

Another reason is that there can be difficulties with brand consistency and messaging. So this is not just the consistency of your content itself, but how it looks and feels to your customers. And, of course, this can be a really big headache if you ever need to go through a rebranding.

CC: Yeah, the marketer in me is just cringing right now, as you mention it.

GK: Oh, yes. And this is actually a reason that we’ve had some of the organizations who have come to Scriptorium for help is because they needed to go through a company rebranding and they had their content at a bunch of different silos and couldn’t figure out a quick or efficient way to make that rebranding happen. And then of course, that problem can and does get magnified if the rebranding is due to a merger or an acquisition because if you’ve got two or more companies coming together and they’ve all been working in silos, then suddenly how do you get everything rebranded under one name as quickly as possible and as painlessly as possible. If you didn’t have those silos to start with, that could happen a lot more effectively and with a lot less hassle and headache for everyone.

And then of course, another reason to avoid silos is that you waste a lot of time and resources creating and publishing the same content potentially in two different places. If you don’t have a way to share the content, then there may be times when a marketing group that’s working in a CMS needs the same information. So things like technical specifications, if you’re selling a product that people need to know that information about, but then also that same information would obviously be in your tech docs and if you have two disconnected silos like a CMS and a CCMS that can’t integrate or share content, then people would be writing that information twice. And that just wastes a lot of time.

CC: So when it comes to a timeline of the, I guess what we typically see when we’re implementing a CMS and a CCMS, do they get implemented at the same time? Does one of the systems typically come first? What does that standard timeline, I guess for lack of a better word, look like?

GK: Yeah, and I don’t know that there really is a standard per se. I can say that unfortunately they are almost never implemented at the same time.

CC: Oh, gotcha.

GK: If you do have that opportunity to do a complete overhaul and get a CMS and a CCMS at the same time, I would say definitely take advantage because that is pretty rare. What we see more often is having one system that’s already been chosen and established, and then you have to choose another one that will be compatible with it. So whichever one your organization has put in place first, that sort of gives you your parameters and your requirements for the other. From our perspective, we do see more organizations that already have an existing web CMS, because that is a little bit broader. It might manage some more of the parts of the content lifecycle than something like a more structured environment like a CCMS would. And so then what will happen is they’ll realize they have a need for structure and then realize they need a CCMS to manage that content and then need to choose a CCMS that will align and be compatible with the existing web CMS.

CC: Okay. So what are the pros and cons of each of those: implementing together versus separately, that kind of thing?

GK: Yeah, sure. And one thing I also want to point out about that is that there’s a big “it depends” kind of factor, which I know is the thing you hear from every consultant that it depends. But I know that one thing we always look at before we even get into the pros and cons are things like limitations that come into play. And so, one of the big ones we see at almost every organization is the budget. So how much budget do you have? Who controls that money? Are there timeframes in which you have to use it? All of that can really make a lot of your decisions for you about implementing, whether it is one system or more than one system at the same time.

And then of course, you have deadlines and timeframes that are set by your organization around their production schedule and other goals. And so that can also be a really big limitation for implementing a new system. And then of course, it’s important to think about what business needs are actually driving the decision to implement a new system or maybe more than one new system in the first place. So all of those are the big considerations that we think about first.

And then when we think about the pros and cons, like I said, if you are implementing a CMS and a CCMS at the same time, the big advantage is that’s rare. You want to take advantage of that opportunity, because you can evaluate both systems at the same time instead of already being locked into one tool and then having to make another tool fit with that. So that’s obviously the major advantage that you have is that you have more of that freedom to look at your options and maybe pick something that’s going to be a really good fit for you without sort of limitations or parameters.

But of course, that being said, sometimes those parameters can be good. So if you already have, let’s say the typical scenario, you already have a CMS in place, maybe if you didn’t have that in place, you would be looking at five or six CMSs and then five or six CCMSs as well. And you have a lot more tools to evaluate in the first place. You have a lot more areas of compatibility to assess. And so that timeframe is going to take longer to make that decision. And you can get bogged down by indecision-

CC: That’s true.

GK: By saying, maybe we have two or three options that would all be good fits for different reasons. But if you already have, let’s say your CMS in place and then you’re just looking for a CCMS that can play nicely with it, maybe you’re only narrowed down to two or three options. And it takes a lot less time to really find out what the right decision is. So there are pros and cons in that way.

CC: That’s true.

GK: Another thing to think about also is just risk. Because implementing any system is a huge undertaking. It takes a long time. You have to go all the way from the evaluation to making the selection, to getting everything stood up and ready to go. And then there’s always a little bit of experimentation and churn as you actually start getting content into that system and getting your publishing lifecycle going. And so if you’re doing that for more than one system at the same time, there is a lot more risk of

something possibly going wrong, not going according to plan. And then of course, the investment that you have to make into an implementation is quite large as well.

So there’s definitely, I think, less risk in only implementing one system as opposed to trying to do two at the same time, even if you do have the advantage of, we got to choose these together so we know they’re going to work well together. So yeah, there definitely are pros and cons for whichever way you end up doing it. A lot of times it won’t be your choice. It’s going to be limited by all the various circumstances I talked about at your organization, but things to think about just in case you’re ever in that situation.

CC: And so something that comes to mind is, I know that when you’re implementing systems, whether it’s the systems we’re talking about here, or just systems in general, a lot of times organizations can get stuck when both systems have competing priorities and that can cause a lot of problems in how things are implemented and in the timeline of how things are implemented, all this kind of stuff. So are there competing priorities for a CMS and a CCMS?

GK: Sure. And one big one that we see a lot is that when you’re talking about the people who are actually developing your content, your authors, your subject matter experts, contributors, a lot of them tend to see creative freedom in how they create the content versus consistency as competing priorities. The less structure you have for your content, the more creative freedom it gives you, but then it also introduces a lot more room for inconsistency and human error. And so there’s always that balance to strike. And if you have groups at your organization where, let’s say, one group needs that creative freedom, so maybe your marketing team, they need the ability to have full freedom of their design and what information they’re putting where, but then you’ve got another group that they need the rigidity that comes with topic-based authoring and with having information delivered in a specific way for legal and regulatory requirements, then obviously something like structured authoring is going to benefit them.

I think it’s important that when you have both of those types of content produced by your organization and you have two groups that are sort of in charge of that, and maybe they’re in two different systems, that it’s really important to get those groups working together so that they can understand that those priorities don’t need to be competing, they just need to be balanced. That’s always the challenge when it comes to those priorities is, yes, they seem like they are competing, but really it’s more about striking that balance and making sure that each group understands the importance of the other group’s needs and how they can still work together and share information that needs to be shared, but also still have the ability to work in the way that they need to work to get the content out the door.

There are tools that can help you strike that balance. So, for example, a web CMS can give your marketing team the creative freedom that they need, but also so can some types of CCMSs. So there are ones that use topic-based authoring and those smaller components we talked about, but not an XML structure like DITA. So that might be an option to look into. And then of course, an XML or a DITA-based CCMS can give other groups, like your technical team or your training team, that structure and the components that they need to create that more heavily regulated technical or legal content. So it’s really worth having these different groups explore the options that are out there and help turn what seems like competing priorities into those more balanced or coordinating priorities.

CC: Gotcha.

GK: I think it’s also worth noting that just because your content is structured, so topic-based XML, DITA XML, that doesn’t mean that it cannot be made to look beautiful when it’s published. There are a lot of things that we can do with PDF output, HTML output, all other kinds of output formats to make things look really nice. So you don’t always have to have that unstructured nature to give you the creative freedom for a really nice look and feel. And then also, it can be delivered in creative ways. So because it is componentized, because it’s in little topic-based chunks, that actually lends itself really well to having flexible delivery, to delivering personalized content to different segments of your customer base and to having a lot of different formats that they can receive it.

So yeah, I think we see a lot these days where people can log into a portal and get stuff served up to them according to parameters they’ve put in about what they’ve bought. We can see a structured componentized content used to serve chatbots, all kinds of other things. So there is a certain degree of creative freedom in structured content as well that I think a lot of people don’t always realize from the outset just because there is that structure.

CC: And I’m going to jump in on that because I think when it comes to marketing content, I feel like your freedom to be more creative when a lot of the mundane technical tasks are taken off of your workload, and that is something that structured content allows you to do. So that’s something, me standing on my little soapbox, I get excited about when we’re looking at structuring content and streamlining content operations is that, yes, you may feel like your creative freedom is a little bit restricted, or maybe it’s a little bit more complicated for you to learn how to get the kind of creativity and design that you want from your published content, but the benefits of having your workload reduced because you’re not focusing on things that you don’t need to be focusing on anymore is really massive. And in the long run, I think that frees you up a lot. I get excited about stuff like that.

GK: Oh, yeah. And I absolutely agree. I do think from the side of people working in structured content, they realize how much more freedom they have when they’re not doing a lot of manual design tasks anymore, when they are free to just write the content they want to write and realize that-

CC: Exactly.

GK: … it can be delivered and mixed and matched and put out to their customers in a lot of different ways. And so it really does, I think, take a little bit more practice in doing things to realize how much more freedom that you can get when you work in structure.

CC: Exactly. Yeah. All right. So I think that’s a good place to wrap up our conversation, but we will be continuing this discussion in the next podcast episode. So thank you so much, Gretyl. I really appreciate you talking about this today.

GK: Absolutely. Thank you.

CC: And thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Balancing CMS and CCMS implementation (podcast, part 1) appeared first on Scriptorium.

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In episode 141 of The Content Strategy Experts Podcast, Alan Pringle and Christine Cuellar discuss the story behind LearningDITA, the free DITA training created by the Scriptorium team.

What we are trying to do with this site is give people a free resource where they can go and, at their own pace, learn about what DITA is and how it can apply to their content and their content processes. It’s a way to take some of the technical mystique out of it, to bring it down and help you learn what it is and how it works.

– Alan Pringle

Related links:

LearningDITA – Free DITA training by Scriptorium
Structured authoring and XML
Managing DITA projects: Five keys to success
Getting writers excited about DITA

LinkedIn:

Alan Pringle
Christine Cuellar

Transcript:

Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we’re talking about LearningDITA, the free DITA training created by the Scriptorium team.

Hi, I’m Christine Cuellar.

Alan Pringle: And, I’m Alan Pringle.

CC: Alan, welcome to the show. Thank you so much for talking with me today. We’ve just received a lot of great feedback about learning DITA on LinkedIn. A lot of people are thanking us for the course, talking about how it was a great experience for them, so we thought this would be a great resource to dive into.

AP: Sure.

CC: My first question for you is, what is Learning DITA, for those listeners that have no idea what we’re talking about?

AP: Learning DITA is a free online resource where people can go and take several courses to learn about DITA. DITA is an open source standard that gives you a way to describe your content in a modular fashion. It’s really good for helping you basically build in intelligence into your content, so then you can then filter it, sort it, and do that stuff with it.

CC: Got you. Okay. Learning DITA is the free training that the Scriptorium team created many years ago. When was Learning DITA created?

AP: We may have started somewhere in 2014 into 2015. That’s when we started. I think the first course came out, probably came out right around 2015.

CC: Okay. It’s been around for a while. Was there anything like it at the time? Why did you feel the need to create this resource?

AP: Well, I mean, you just heard me describe DITA and you hear things like –

CC: (Laughs) Yes, it’s a lot of words.

AP: You hear Darwin information typing architecture and, you may hear from someone at work, someone you work with, “We may need to use this,” and you’re like, “What is this? This sounds like some scary sh*t. I’m not doing this.” What we are trying to do with this site is give people a free resource where they can go and, at their leisure, at their own pace, learn about what DITA is and how it can apply to their content and their content processes. It’s a way to take some of the, I guess, technical mystique out of it, to bring it down and help you learn what it is and how it works.

CC: That’s amazing. Yeah, that’s a great resource. Who are the experts that are behind the Learning DITA course? Who created it? I know you mentioned the Scriptorium team, so who was involved in that?

AP: Well, a lot of the people that you have heard on this podcast have contributed Gretyl Kinsey, myself and several other team members have. We have written a lot of that content. It’s not completely Scriptorium, I will be very clear on that. We’ve had some other people who have contributed some content and we appreciate it. We have set this up so that the actual source content for learningdita.com, which is DITA XML files, they are freely available in GitHub. You can download them and look at the source. You can treat it or view it as a proof of concept.

This is how DITA works. The source files are DITA, and I don’t want to go too deep into the weeds, but we basically transformed that, DITA XML, into a WordPress friendly format, markup language, and sucked it into WordPress where we use a learning management system that sits on top of WordPress. You’re going to see courses where you go through exercises. There are assessments in addition to reading about things. They’re linked to reference information. There’s all kinds of ways to absorb and understand DITA through learning DITA. Again, it’s free and we tried to make it, shall we say, less threatening, very accessible.

CC: Yeah. Yeah. I’m actually taking it right now. I’m going through the courses and my whole career has been in marketing. I know nothing about technical writing. DITA was a whole new word to me when I started this position. If I can do it, anyone can do it, basically. It really has made the concept very down-to-earth for me.

AP: Don’t sell yourself short. That’s one point, I’m glad you brought this up. People really may assume that DITA is strictly for product and technical content, and that is no longer the case. I think it’s fair to say early on, it was created specifically by IBM for technical content, product content, but it has expanded its reach. The fact that you are using, when you’re taking the class, you were using an LMS to basically consume DITA content that is training content, that shows you right there, this is not just about user manuals anymore, not by a long shot. There’s proof in the pudding. There it is, you’re using learningdita.com, and believe it or not, you’re consuming DITA content, but you may not know it, but it’s there under the covers.

CC: Yeah. It’s been really helpful. I’ve always been really passionate about processes, optimizing processes to make everybody’s jobs easier, to make your workflow easier so you can do more, better and easier. Just work smarter, not harder, I guess is a better way to say that. The whole approach to structured content and DITA, it was scary at first to be looking into, but that’s the core concept is, let’s structure things in a way so that we’re flexible, we’re scalable, we’re not making our team repeat things over and over, we’re doing things better in a way that’s more accurate, and I really love it. I still have a while to go, I haven’t completed the course yet, but I love that heartbeat behind what DITA is and what Learning DITA is.

AP: Right, and it’s really, it’s trying to bring something that may seem very scary and technical down to Earth. A lot of people hear, XML, that is “extensible markup language,’ they think they’re going to have to type computer code.

CC: Yeah, that’s what I thought.

AP: Right, that is not necessarily the case. Sure, if you are comfortable typing code, you can type code, but there are a lot of authoring tools and experiences that can sit on top of DITA to hide all that, so you feel more like you’re just using a word processor. But the bonus is, under the covers of that authoring experience, the DITA structure is basically managing your content. Like enforcing a template, it is forcing you to write to a particular structure and to include intelligence about what you’re writing like, who’s the audience? What product is this for? Is this for a teacher or is this for a student? All of those kinds of things, and when you build that kind of intelligence into your content, it makes it much easier to mix and match and assemble and filter and create all kinds of versions and alternatives based on the audience who is consuming your content.

CC: That’s great. Like you said, not just product and technical content. Every aspect of content needs to be thinking about that. I know in marketing content, that’s a big thing. Who are we writing to? What’s the purpose of this? Having a structure that forces you to keep that in mind is a no-brainer. It feels like it’s great.

AP: Right, exactly. If you feel that you are in a situation where you find yourself doing a lot of manual work, you’re doing a lot of copying, pasting, that may be the biggest clue. If you find yourself in a content development process where you were making multiple versions of the same file and then making a change here, change there, but then forgot about the fact you’ve got versions 14 and 15 over here that also need that change. That’s the kind of thing that DITA can help with.

If you have any kind of inkling that you might need a better way to make versions of content to reuse content, take a little visit to learningdita.com and learn a little bit about DITA and see if it might be a way that it can solve some of your problems. I am not going to sit here and tell you that DITA is a fit for every organization, it is not, but it does address a lot of the common pain points that anybody who creates content in a professional way, the kinds of things they have to deal with and that make their work life a lot of times just downright unpleasant.

CC: We’ll include a link to Learning DITA in the show notes. Something also to mention, not only is Learning DITA free, but it’s a flexible course, so you can take it at your own pace. You can do a lot of it and then stop, whatever you need to do. It’s not scheduled or anything, it’s as flexible, free, low risk as possible.

AP: Yeah, there are multiple courses and it starts with the basics and then builds upward. Are you going to take all of the courses? No, you may not need to, and I’m going to have to do a refresher, I’m going to cheat and look and see how many courses we actually have, because I don’t remember, let’s see. I think we have 9 or 10 courses right now, so there’s a lot there. Like you said, you take it at your own pace. You can start with the introduction, get your feet a little wet, and then start diving in a little more deeply into the structures that make up the DITA standard.

CC: We talked about this a little bit. Who is Learning DITA for? I know you mentioned that the most common scenario is someone saying, “Okay, here we’re going to introduce DITA, this is what we’re going to start working with,” tells it to an employee who may be like, “I have no idea what you’re talking about,” and is panicking. For one, is that the only scenario for learning DITA? For two, who is Learning DITA for?

AP: Learning DITA is for anybody who wants to know more about the DITA standard and how it could apply to their professional world, or even not even professional world. If you have any interest in improving content processes, content operations, and you may be more of a manager who doesn’t actually create the content but still want to understand what’s going on with DITA and how it can maybe help your organization, it’s for anybody who wants to understand better content processes and how DITA could possibly provide fixes for any problems that you have with your content operations.

CC: How many people have registered for Learning DITA or taken or completed the courses?

AP: Well, we did start in 2015, so there’s quite a few. I think we’re somewhere hitting near, as of this moment, 15,000 people have signed up to use the courses, so yeah, it’s a lot. It makes me feel good to see something that we put together being embraced by the content community and getting their hands a little dirty and figuring out how this DITA thing works and doing it at their own speed and sometimes on their own time. My hat’s off to them for digging in and learning these things.

CC: Yeah, I love that it’s such a community-oriented resource. It feels like it’s been so helpful for people. It sounds like people also contribute or give feedback or have asked for other courses.

AP: They have. We have a lot of resources listed on the site and within the courses, and a lot of those point to things that other people in the DITA community and content community they have created. Again, it’s not just about us at Scriptorium, this is about the content world and how you can really improve your content operations by breaking your stuff into more modular structured content that DITA supports.

CC: When someone finishes the Learning DITA courses, but then they need more training, they realize, “I’m going to be getting more into this,” where would you point them? What should they do next?

AP: Once you’ve gone through those courses, I would say there’s a good chance that you may be in an organization that is looking at implementing DITA, and if you need help doing that, we as Scriptorium and there are other consultants that do this too, talk to somebody who can help you, for example, set up your workflow, your database workflow, help you figure out how to map your content to the DITA model. Then, not only do that legwork upfront the assessment stuff, you also may need help actually standing up and configuring your DITA system and then training people how to use that system. We do all that at Scriptorium. If you need help beyond what we offer for free, we will be more than happy to oblige you and provide you with some consulting and training services to get you set up and running in DITA.

CC: Absolutely. Well, Alan, is there anything else that you want to be sure we communicate about Learning DITA or anything else that’s coming to mind that you really want people to know or understand about the resource?

AP: We appreciate people contacting us. If you see something that’s not quite right or you don’t understand, we appreciate that being pointed out and we will do our best to correct it at some point. It’s also a community resource. I can’t stress enough, we’re trying to demystify DITA, make it less scary, and that’s the point. If you, in your head, have an idea of how you can contribute and do something along those lines, please do it, I will note. Other people have taken our Learning DITA source content and then created versions of Learning DITA and German and French, and I believe even Chinese.

CC: That’s amazing.

AP: There are other people who have taken that stuff and then translated it and then used our process to create the same thing in other languages to make it even more accessible and reachable to other people.

CC: Yeah, that’s great. That’s really great. Well, I’m just really impressed with the whole Scriptorium team for coming up with this resource. Since I’ve started, I’ve just seen nothing but really positive feedback about it. I love how, as we’ve already talked about, it’s community-oriented, it’s just a free resource that helps people really understand. I love the phrase that you use de-mystify, because I think that that can happen a lot of times in our jobs, we just get overwhelmed by what we don’t know, especially when there’s the expectation that we’re going to do this now or you need to know this now. It’s great that the team saw that need and then fulfilled it with this resource. It’s really great.

AP: Yeah. and it’s always a problem when you’re dealing with technology. There’s always this fear of the unknown involved. If you can cut that fear out, you’re going to have a much better time when it comes time for you to possibly implement a DITA workflow.

CC: Yeah, absolutely. Well, thanks so much for talking about this, Alan, and thanks for being here today.

AP: You’re welcome.

CC: Thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post What is LearningDITA? (Podcast) appeared first on Scriptorium.

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In episode 140 of The Content Strategy Experts Podcast, Sarah O’Keefe and Éric Bergeron, president and CEO of IXIASOFT, share the story behind the MadCap acquisition of IXIASOFT.

“The question that everybody is asking, and we really want the answer to, is this seems like a very sensible combination, but MadCap as an organization has done a really excellent job with their marketing, and much of their marketing has been based on the concept that DITA is not something that you need. Flare is happy and easy and safe and wonderful, and DITA is none of those things. So, when you say this is a bit of an odd combination, I think everybody’s looking at, ‘Well, wait a minute, there’s been a lot of DITA bashing over the past 10 years or so.’ What do you do with that?”

—Sarah O’Keefe

Related links:

MadCap Software Acquires IXIASOFT – What Does That Mean?
MadCap Software Acquires IXIASOFT to Add Enterprise-Class DITA CCMS to Product Offerings, Expand Support for Customers’ Content Strategies
IXIASOFT acquired by MadCap Software – What’s Next?
LearningDITA – Free DITA training by Scriptorium

LinkedIn:

Éric Bergeron
Sarah O’Keefe

Transcript:

Hi everyone, I’m Sarah O’Keefe. In this episode we’re talking about MadCap and IXIASOFT with Éric Bergeron, president and CEO of IXIASOFT.

Éric, welcome to our podcast.

Éric Bergeron: Thank you very much. I’m very happy to be here today.

SO: Well, and we’re excited to talk to you, since I think the entire industry has been talking about nothing but this merger for the past couple of weeks since the news broke. And so I wanted to ask you a couple of questions about what’s happening here and where is it going and what does it mean for those of us that live in the DITA XML world. And I’ll guess I’ll lead with the obvious question, which is why sell IXIASOFT to MadCap?

ÉB: Yeah, very good question. Unfortunately, I will have to give you some background before answering that question, and I will try to do that very quickly. Six years ago, IXIASOFT was a very traditional software publisher. We were selling perpetual licenses with a yearly maintenance plan. We were installing the system on-prem, customer side. And the product was a desktop application connecting with the backend server. So very traditional.

And six years ago, we decided to change the business model and provide to our customers a SaaS solution. So we had to change the business model to provide subscriptions. We had to change the product to move from a desktop application to a web-based application. We also had to put in place a new team to manage the hosting and the management of the solution. And we knew that it would take approximately five years to do all that work. And we were near the end of that five year period.

So the timing was good for us to look, “Okay, what’s next for IXIA? What will be the next growing phase? What should we do to grow, continue to grow?” And at that time, MadCap arrived with Battery and they contacted me. And they had a plan. And we listened to their plan, and we discuss it with them. And finally, we realized that the timing was perfect. I think the story and the plan, the project is great, and that’s why we decided to sell. And also because I will turn 60 very soon and I was starting to think about my retirement. It’s true. But really, the driver was really the plan, the project, I think they had something interesting to propose and that’s why.

SO: So what can you tell us about that plan or that vision? What is the vision for the combined company that you can share?

ÉB: And again, I was a teacher in the past, so I need to explain things. But for me, there’s a spectrum of solutions on the market. And some solutions provide the ability to manage documents, other systems provide the ability to manage more components, and some systems manage components with structure. And I think with the combination of MadCap and IXIA, the last two, we will be able to provide that to the market. We will be able to provide a component system to create unstructured components with MadCap Flare and Central. And with this IXIASOFT CCMS, we will be able to provide the tool that will let our customer manage components and very structured components.

So that’s the goal, I think it’s to have a broader offer and propose to the market a solution that will let them move from unstructured on-component systems like Word and FrameMaker, move them to Flare and Central. And eventually, if they need more structure, they will be able to move to the CCMS. And I think that’s a great project.

And the other reason why I was interested to proceed with that transaction is also because MadCap, they had some big customers that outgrow their solution. And they were looking for a more structured system. And IXIA will be the place they will go. So that will make the IXIA customer base grow. And that was a guarantee for us that we will have more customers, they will keep the product, they will continue to improve the product, and that will also increase the customer base. So that’s also an answer to your first question. But that was also the other reason why I was interested in that transaction. And I think for the market it’s great to have those two products together in the same organization.

SO: So I know that you and Madcap, both IXIA and Madcap have said in the short run, “Nothing is changing. Do not panic. Remain calm.” But looking at this a little bit more long-term, what kinds of changes should IXIA, or for that matter, Flare customers expect in the midterm? Six months, a year, five years, what does that look like?

ÉB: Yeah. For the next six months nothing will change, really. It’ll continue to be the same. However, IXIA for example, we will have a user conference at the end of May in Munich. This year the user conference will be in Europe. And we will have MadCap customers that will come to the IXIASOFT user conference. Because some of the MadCap customers are interested to learn more about DITA and maybe use that eventually. And we will provide to them a path from Flare Central to IXIA CCMS. So those are small changes, but we will start to see MadCap customers maybe more in the IXIASOFT CCMS community. But internally nothing will really change.

Over in the next year, two years, what we want to do is really propose to the market some tool to make the content move more fluently from Flare, Central to the CCMS. So we’ll have an importer, for example, to import Flare content to the CCMS. That will arrive probably after the first six months, but it will be there. And that will clarify the path for customers moving from Word to Flare, and eventually from Flare to the CCMS, to DITA. So that we will see in the future.

And more midterm, long term, I can say that Battery, you mentioned Battery previously, we talked about that, they decided to invest in MadCap and IXIA, but they want to continue to make that combination grow. Maybe eventually there will be other acquisitions to continue to complete the offering and to propose to the market a broader offer for people that want to create and publish content. So that will probably happen eventually.

SO: So what do you think this looks like in sort of in that five years down the road? My track record on five years is not very good, I don’t know about you. But what do you see as the big picture vision in that longer term timeframe?

ÉB: Agree with you, five years in technology is very long. And I’m not the best for visionary things. One thing I really believe is technical documentation, but documentation in general will change a lot. We are moving definitely from books to components. In the past we were providing documentation with books and manuals. Now, for me, documentation is more and more knowledge base. And there will be more and more modern tools to publish that information. ChatBot, for example. ChatBot will ask questions to users. With the answer, they will find the relevant content, then they will push that to the end user. We will have tools like Fluid Topics, Zoom and Congility that will be used more and more. So we need to create content that is compliant or compatible with those tools. And I think component systems are very good systems to create content that can be leveraged by those modern tools.

The other thing is, for sure, in the past there were a lot of text and picture diagrams. I’m pretty sure we’ll have more and more video, audio, augmented reality, virtual reality objects too. So that’s the future of the documentation. And our tools will have to provide the functionality to create those contents, but also to publish those contents. So that’s the future of our world, I think. I don’t know exactly how we will navigate in that evolution, but it’s definitely for me I’m sure it’s going in that direction.

SO: So I guess the question that everybody is asking and we really want the answer to is this seems like a very sensible combination, but MadCap as an organization has done a really, really excellent job with their marketing. And much of their marketing has been based on the concept that DITA is not something that you need. That Flare is happy and easy and safe and wonderful, and DITA is none of those things, right? And you don’t need it and it’s just generally not great. So when you say this is a bit of an odd combination, I mean, I think that’s what everybody’s looking at is that, well, wait a minute, there’s been a lot of DITA bashing over the past 10 years or so. So what do you do with that?

ÉB: Yeah, it’s funny that you mentioned that, because after my first call with Battery and MadCap, I went to the MadCap website. And I look at that saying, “Oh, how can we work together? We’re so different.” But when you are selling a product, you are doing the best marketing pitch to sell it. And not having a DITA tool, they had to do that. And so I fully understand. But we talk about it and you probably realize that all that information was removed from their website after the transaction, because they had to do that to promote their product, but they don’t need that anymore. And it’s the opposite now. They need to embrace DITA and put DITA at the right place. And it’s true. And I still believe that not everybody needs DITA. Some organizations, they don’t need that highly structured content. And so it’s okay to produce content that is not very structured. If it answers your needs, it’s fine.

Maybe eventually they will need more structure, and the good news now they have a solution for that. We can propose to the market the path to move to higher structured content. And what we want to do is provide tools that will let you move from unstructured components to structured components. So yeah, it was funny to see that on their website, it’s funny to see that disappear now. And now we will put on our website content that will explain the new reality. But I fully understand it was… And you’re right, we were a little bit like an odd couple, but we’re learning to live together now and I really believe that it’ll work very well.

SO: I have some questions about who’s the neat one and who’s the not so neat one, but I think we’ll set that aside. Is there anything else that people should know? Things that I haven’t asked you about, but information that you want to make sure is out there about this merger transition?

ÉB: Maybe one thing I would like to share with you is the fact that, for me, it was my first experience selling my company really, and I was really happy to do it with MadCap. And especially because Anthony, the CEO of MadCap and I, we share a lot of values, same values. And when you look at the history of Antony, he founded MadCap 17 years ago with friends. He was working before at eHelp. And they worked together for a long time. They grew organically all those years. And it’s the same for IXIA. If you look at the IXIA team, we are working all together for a long time, very, very long time. And 20 years, 25 years, some of them. And we have the same experience a little bit.

So I think this transaction, this merger was interesting and went very well. Because when Anthony and I, we were talking, we were at the same place. We were able to understand each other. And I believe that that merge will work because of that and because people working on both organizations share the same values. And for me it was really, really important. And that’s another reason why I accepted to enter in that transaction because I wanted to make sure that my team, my customers, and I say my, but IXIA is not a one-man show. It was really the IXIA team, the IXIA customer base. I’m sure they will be respected in that process and they will be happy in the future. So that’s just another thing I wanted to say.

SO: Well, and that’s an interesting point because we always talk about how… I mean, the work that we do and everything else, it’s about people, right? It looks like a technology problem, but it’s always about the people. And I guess here again, we’ve fallen or I’ve at least fallen into that trap of saying, tell us about the technology, tell us about the integration. And you’re saying, well actually, as always, it is about the people. So yeah, that’s a great point. I think I’ll leave it there. So Éric, thank you for being here and sharing this background and this information.

ÉB: I was really happy and thank you for the invitation.

SO: And congratulations to you and the whole team and to the MadCap team and Anthony and all the rest of them.

ÉB: Thank you.

SO: And with that, thank you for listening to the Content Strategy Experts podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Éric Bergeron explains the MadCap acquisition of IXIASOFT (podcast) appeared first on Scriptorium.

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In episode 139 of The Content Strategy Experts Podcast, Sarah O’Keefe and special guest Keith Anderson dive into their experiences with structured content, DITA, and user content.

“My definition of context is anything that affects the cognitive processing of information. […] So, whether you’re consuming information by reading or listening, there are so many factors that affect how you process the context of the content.”

Related links:

Resilient Context – Keith Anderson’s website
Structured content: the foundation for digital transformation (podcast)
LearningDITA – Free DITA training
Content strategy in UX teams (podcast)

LinkedIn:

Keith Anderson
Sarah O’Keefe

References:

Floridi, Luciano. The Fourth Revolution: How the Infosphere Is Reshaping Human Reality. 1 edition. New York ; Oxford: Oxford University Press, 2014.
Duranti, Alessandro, and Charles Goodwin. Rethinking Context: Language as an Interactive Phenomenon. Cambridge [England]; New York: Cambridge University Press, 1992.
Stein, Howard F. Euphemism, Spin, and the Crisis in Organizational Life. Westport, Conn: Quorum Books, 1998.
Stein, Howard F. Nothing Personal, Just Business: A Guided Journey into Organizational Darkness. Westport, Conn.: Quorum Books, 2001.

Transcript:

Sarah O’Keefe: Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about structured content, DITA, and user context. Hi, I’m Sarah O’Keefe, and I’m here with a special guest, Keith Anderson. Keith is a longtime friend and one of the very few people I think in the world who understands both DITA’s structured content and the world of UX content. So Keith, welcome aboard.

Keith Anderson: Hi. It’s good to be here.

SO: Thanks for coming.

KA: Of course.

SO: So first, give us a bit of a background on structured content and DITA and what your sort of experience is in that space.

KA: Oh, okay. So I go back to SGML days when I was working at a telecom company and we were doing structured content back then, and it was mainly in DocBook, but structured content lent itself really well to being repurposed or single sourced, like we used to call it. There was a point where we were actually single sourcing out the instruction sets for online help, for printed documentation, for instructional design, and we also used them for test scripting. So that’s kind of how I understood the power of structured content.

SO: I just want to note that we are still wrestling with single sourcing and learning content and technical content. So having somebody tell us we did this back in the day, pre-DITA is pretty encouraging.

KA: Yeah.

SO: So then digital transformation comes along, and I think you’ve said that there you can’t really apply DITA directly, but you came up with a way of making that work. What does that look like?

KA: Okay, so out of what I would call the mainstream content management systems, out of all of them, only Adobe Experience Manager actually natively supports DITA. And Adobe has DITAWORLD every year, but when you look at content management systems like SharePoint and Sitecore, they don’t support it. So I was brought on board to do a project a few years ago. It was an online help system, and when I did the content audit, it was like two and a half billion words, and they had been maintaining it in some old tool and then they were just porting it over to the online help system. But it was taking a lot of time. They were trying to move everything into Sitecore. And a few things that I noticed, one was they weren’t using some of the best Sitecore features, which are inheritance and repurposing content. That’s just built in.

The other thing that they weren’t doing was planning out content to be repurposed. So I got the bright idea that I would use DITA because when we did our design thinking sessions, we kept coming back to that, the fact that this was an online help system and DITA lends itself really well to that. So I came in and I ended up with my own little server and … Let me back up just a second. Sitecore, all it is a fancy interface for a bunch of XML schema. And so I thought, well, theoretically it’s possible to enforce DITA on Sitecore and DITA broke everything else. And I started doing research and I talked to a guy in The Netherlands who told me that the surest way to hell was to try to put DITA in Sitecore.

So what I did to circumvent this was I did content modeling and I came up with the idea of using DITA as a platform independent model, meaning that we use it for terminology and we use it for reference, but we can’t technically implement it. So the platform is not dependent on any of the schemas in DITA. And we did that, and that actually helped quite a bit because it did provide us with structure. And then we were able to set up search hierarchies and things like that on the solar server. Solar is the search engine that ships with Sitecore most times, and it worked out pretty well that way.

SO: So you’re saying that essentially you used the concept of a DITA reuse or something like that, but you implemented it without using the standard DITA [inaudible 00:04:39]?

KA: Right. But it was a really good place to refer to. So we used the DITA vocabulary, we used the idea of how DITA content is separated out into topics, and then I introduced topic-based writing to these authors who had been doing very verbose writing on things that didn’t need to be verbose. So we were able to cut out two thirds of the content just by going through and doing that.

SO: So that’s really interesting because it’s one of the big issues that our clients struggle with is this question of, okay, we have web content and we have DITA content, and how do we put the two together? Or how do we integrate them in some way? So in your work, in addition to looking at these sort of structured concepts and putting them in, even if you’re not strictly speaking using DITA or I guess even if you’re not using DITA period, you focused very much on context and the relationship of content and context. So I guess we have to start with the basics, which is what is context or what is your definition of context?

KA: My definition of context is anything that affects the cognitive processing of information. It’s an idea that context is three-dimensional and that, well, the author Luciano Floridi, he created a term called infosphere, and he essentially says that in today’s world, we are living in an infosphere. And it makes a lot of sense because if you imagine context is all around you. So whether you’re consuming information by reading it or you’re listening to it or whatever, there’s so many factors that affect how you process the context of the content. So for example, when I lived in the Chicago area and I took the train downtown every day, I was constantly reading, but was interrupted a lot just by train stops or noise or whatever until I learned to put on headphones just so I could read and focus on that instead of what was happening around me.

So context is very situational. Some things affect you, some things don’t. There’s many, many examples of when you have more context, it completely alters the way that you see something. One example that I could think of is controversial, but it’s Bill Cosby. With all the controversy that’s happened with him, does that for you as an individual, does that affect how you see his life’s work, which was comedy? And so there are factors where context utterly changes things over time. And some things you can control, some things you can’t. I think companies like Comcast who are notoriously hated by most consumers have trust issues regardless of the intent of content writers in the company. And that’s a context those writers cannot control.

SO: So they have no goodwill and that’s their context.

KA: Yeah. And the flip side of it is the context of creation. And back in the day when we were doing online help, you remember how we would talk about can you write good online help for bad software? I mean listen, we had late night drunken discussions about this at STC conferences, but I think the modern dilemma for content strategy is can you write good content for a bad corporation or for a bad organization? I think it’s a philosophical issue. How do you build trust? How do you be authentic without engineering authenticity? All of those things are contextual and people pick up on it. It’s like magic. You can tell if somebody has written something under pressure versus they’ve taken their time and they’ve crafted prose. Readers know this and they know it intuitively just because of the way our brains are wired.

SO: So I guess this is really interesting because the canonical example of context is always location. If you’re at this location, you get different kinds of information, or if you look up weather, if you look up weather that corresponds to your current location and there’s a tornado warning or something like that, it will give you a very different experience than if your phone knows where you are but you’re looking up a tornado warning hundreds of miles away. And it’s just like, hey, by the way, there’s a tornado warning, maybe traffic, but if it’s right on top of you, it’s going to give you a different kind of experience because the context matters. Obviously I’m concerned about the tornado no matter what, but if it’s on top of me, I’ve got an immediate, “I need to stay alive” problem as opposed to a sort of more, I guess, academic distant interest. So what does it look like to have DITA or generally what you were describing, DITA like structured content and context? How does that work?

KA: Well, there’s a couple of things that I’ve noticed with it. So context can end up being synonymous with metadata, and that works out really well because then you can have contextual cues built into the metadata for people who want to dig deeper. But when you’re writing agnostic content, so when you’re chunking and you’re putting things in structure and you’re writing agnostic content, that content usually gets assembled almost like a stack of Jenga pieces and it’s put together. And so if you repurpose my instructions, and you repurpose a concept topic like in DITA, and you put concept of procedures together, they could be written by two different authors, the style of the pros and all of that needs to be under really strict editorial control for consistency purposes. But with some of the projects that I’ve seen lately, what Microsoft is doing with Microsoft Viva, another good example is Notion. I don’t know if you’re familiar with Notion, but you notice these building blocks and you build things on top of each other and you can have different contributors all building onto the same thing.

All of that stuff taken as a whole is how readers actually take in the information. So inconsistencies in those building blocks will be evident. So one way to handle that is definitely having strict editorial guidelines and following a way to do it. But the other thing too is to have metadata and have enough content to orient the users to the whole piece of what they’re about to read. Every page is page one idea of producing content.

The other thing that I’ve noticed is that when you take agnostic content and you don’t really give it a lot of thought, sentence construction starts to fail because good writing is like you write one sentence after the other, but each one is building in anticipation of what the reader is looking for. And so you’re trying to build the anticipation and then you’re trying to reward the reader by continuing to read. Very hard to do whenever you have chunks and different people are working on chunks.

SO: Yeah, it’s interesting because I don’t think I’ve ever thought about the … We think about the emotional state of our readers, but I don’t know if we’ve connected that to the idea of context. But certainly in technical communication, the generalized assumption is that somebody who is looking something up in the docs or for that matter in the knowledge base is annoyed or frustrated or angry because they’re blocked. The only reason they’re looking in the docs is because they’re trying to do a thing and they can’t do the thing and they need help. So they are somewhere on the continuum from annoyed to having a tantrum. And it makes for a very difficult writing challenge because as you said, they’re not going to give you the benefit of the doubt. So here we are. So what does that look like? I mean, what does it look like to integrate the ideas around context into your overall content strategy?

KA: Well, what I’ve been working on, on the side is developing a universal context model that should be conjoined with standards like DocBook and standards like DITA. And the context model would help drive or maybe not drive, but guide authors as they’re writing as to what should happen next. I’ll think of a completely non-technical example, but something that everybody probably understands is with all of the police shootings and things that have happened in recent years, I don’t know if you’ve ever seen where the police reports get changed, and then they get released again, and then they’ll update them again. And a lot of this has to do with officer trauma, it has to do with different witnesses, everybody’s on an adrenaline rush when they’re trying to get the paperwork started, then people remember things later. The problem with that is that a lot of police reports are free form narratives. They’re not scripted.

So in some ways, the old school green screens, like call centers used to use with scripting, worked a lot better because it guided somebody down to where they needed to be to get something done. So having a context model that kind of underlies the content and it helps drive form fields and things like that, I think that’s critical for the content of the future because as artificial intelligence is growing and language learning models are expanding, they still need guidance and they need human interaction. And I almost think that it’s better that the machine learning happens within a more closed system as opposed to learning like what’s happening with ChatGPT, where it’s just all of the internet ever is what the chatbots are learning. And I don’t think that’s doing anybody any good. I’ve seen all kinds of horror stories about it already, and I think Microsoft just released their demos for Bing just a few weeks ago. And the horror stories are, I see one in the news just about every day.

SO: So what kind of challenges do you see lying ahead? What are you trying to achieve with connecting context into content strategy? And what does that look like? What kind of interesting challenges do you foresee coming?

KA: I think it’s a way of building trust. So let’s take journalism. So if you look at really good reporting that you see, you realize that there is institutional knowledge that larger publications, New York Times, The Washington Post, they all have that institutional knowledge, and we make assumptions based on their reputation that they have an editorial process. But because of the way politics have kind of become so divisive, a lot of the articles and things get picked apart.

A context model on the other hand, might have reporter notes, might have direct quotes from anonymous sources, and then you might have editors who sign off on it and it’s all part of the metadata that maybe you want to know more about the story that you just read, you could actually access. And I don’t think there’s anything wrong with even tying a context model to blockchain for trust purposes. This editor who works for this organization, has this many years in, and it’s almost like having a reputation server to help provide trust. So that way you’re able, as a reader, to weigh how much you trust the news source based on the metadata rather than just taking the article at face value.

SO: Well, you’ve given us a lot to think about because, and I suspect we could go on for another 20 minutes or much, much, much longer, but I think we’ll leave it there for now. Keith, thank you. This was really, really interesting.

KA: I’m glad to be here.

SO: Yeah, a whole bunch of new ideas and we’ll leave some additional resources in the show notes, including I believe Keith’s website and some other bits and bobs that should be useful to people listening to this podcast. And with that, thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Unpacking structured content, DITA, and UX content with Keith Anderson appeared first on Scriptorium.

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In episode 138 of The Content Strategy Experts Podcast, Gretyl Kinsey and Christine Cuellar talk about a common content strategy trap: what happens when information architecture (IA) is missing, and why you need IA.

“Without IA, you can’t get the most value out of your content. When we think about things like the time it takes to create your content, or getting benefits out of it like reuse, saving money on your translation costs, saving time to market on your translation, all of these things really make your content work for your organization. If you don’t have solid IA in place, it’s going to be really hard to do those things and truly get that value out of your content.”

Related links:

Content strategy pitfalls: planning (podcast, part 1)
Content strategy pitfalls: best practices (podcast, part 2)
Understanding information architecture (podcast)
Information architecture in DITA XML (podcast)

LinkedIn:

Gretyl Kinsey
Christine Cuellar

Transcript:

In this episode, we talk about a common content strategy trap, what happens when IA is missing and how you can avoid it. Hi, I’m Christine Cuellar, and today I’m joined by Gretyl Kinsey. Hey, Gretyl!

Gretyl Kinsey: Hello everyone. How are you?

CC: Good, how are you doing?

GK: Doing well.

CC: Thanks so much for joining the podcast. So in a previous podcast, you and Bill were talking about some common content strategy pitfalls, and you briefly touched on this topic, but we wanted to unpack it a little bit more today because it seems to be something that’s commonly resurfacing. But before we dive in, I’m going to pull the newbie card. Gretyl, can you tell me a little bit more about who you are, your role here at Scriptorium and some of the experiences that you’ve had?

GK: Sure. So I have been a technical consultant at Scriptorium for actually more than a decade now. I started as an intern in 2011 and I’m still here still learning all kinds of new things with all the different projects that we do. I mostly am on the content strategy and information architecture side, so that’s why I think it’s perfect that we are talking about IA today, that’s a lot of the work I do. I’ve seen all kinds of things from really, really ideal IA projects all the way to ones that needed a lot more help and a lot more guidance, and so have a lot of wealth of experience to draw on at this point.

CC: That’s great. So can you tell us what is IA for maybe our listeners that don’t know what that is?

GK: Sure. So if you’re unfamiliar, IA stands for information architecture and it is sort of a subcategory under the overall umbrella of content strategy. And IA specifically focuses on things like your content model, metadata, reuse, linking, basically how you plan to organize and structure your content and what decisions need to go into the process of doing so.

CC: Got you. Okay. So why does IA commonly get skipped or overlooked?

GK: There are actually several reasons that we see this happening. One of the big ones is just a lack of resources. So depending on the size of your company, how much budget you have, how much time you have to dedicate to content, how much content expertise that you have on board, you may or may not have the resources that you need to actually plan and create a good IA. So that’s a big reason why it might get skipped. Another one is just not prioritizing content until it’s too late. So maybe putting the resources that you do have into other areas and really thinking about content as more of a last minute or a last resort kind of thing.

And another one is a culture of disconnect around content. So in some organizations we will see a lot of collaboration around content and that can tend to lead to maybe a better thought out IA, but then in other organizations there may be content silos where you have different departments or different groups working on different kinds of content or different pieces of content, and we can see in organizations like that a general lack of collaboration.

And sometimes even if you’re not in silos and you are more interconnected with your technology, there may still be on the people-side, a lack of collaboration. So if there is that culture of disconnect around your content, then you’re probably less likely to have a good IA or to skip it or overlook it. And then another one is mergers and acquisitions. And this is just because when one company acquires another or when multiple companies come together, that’s going to give you a mix of the IA and content processes that each group may or may not have had before and maybe no clear winner. And depending on what other things are happening in that merger, then IA might fall by the wayside if, again, it’s kind of not a big priority.

CC: That totally makes sense. Okay. And why is it a problem not to have IA?

GK: Well, without an IA, you can’t get the most value out of your content. So when we think about things like the time it takes to create your content, getting some benefits out of it, like reuse and saving money on your translation costs, saving time to market on your translation, all of these things that really make your content work for your organization, if you don’t have a solid IA in place, it’s going to be really hard to do those things and truly get that value out of your content. Another reason why it’s a problem not to have an IA is because it makes it hard to deliver content as effectively as you could otherwise. And especially if you have a really heavy customer demand for things like content delivered in digital formats rather than print only, or if you’ve got a lot of demand for highly personalized content, those are the kinds of things that really require a solid information architecture.

It’s also really difficult to convert content from one format to another. If you have a need to do that, we see this a lot with, for example, going from unstructured content to structured content such as something like Microsoft Word or unstructured FrameMaker into data XML. If you don’t have a good information architecture for what you’re converting your content into, that conversion is not going to go very successfully because there’s not going to be the kind of consistency and structure and organization in your content that you need to make that work well.

And then of course, one of the biggest issues is that without a good IA, it’s very hard to scale up your content development processes. A lot of times content production can work really well on a small scale if you haven’t done a lot of planning and a lot of organization and thought about how your content is put together. But then as soon as your business starts to grow, you realize that you have to get a lot more content out the door a lot more quickly and maybe have it personalized for different segments of your customer base. Maybe you’re starting to translate for the first time and you’re just have this need to scale up. If you don’t have a solid IA in place, that scalability is also going to be really painful, if not, impossible to achieve.

CC: Yeah, that makes sense. I feel like growth is always such a good indicator of gaps and processes and it’s such a good time to take a look at things and see where you can change. So scalability is always something I feel like we come back to on our podcast and our blog post. So what are some of the examples from your work where these issues have come up?

GK: There are actually all kinds of challenges that we have faced here at Scriptorium with IA. So one of them kind of touches on what I mentioned in the last question, which is we were talking about taking your content from unstructured to structured. We see a lot of clients who are looking to do digital transformation, and so that’s going from more of a print-oriented life cycle to a digital-oriented life cycle for more flexible delivery. And a lot of times that does involve a move from unstructured content into structured content. And so, of course that does mean a major change is required in your IA. So that is not an easy one-to-one match if you are working in something like Microsoft Word, something desktop-oriented to start, and then you are going from print only to print and digital, some kind of a hybrid and maybe involving some personalized delivery in there. You’re not going to have a one-to-one match of what you had before in your Microsoft Word, your unstructured frame, your InDesign to what you have now that is going to put that digital delivery on the table.

So that’s a really big IA challenge to think about what is our implied structure in the content that we have right now that is more desktop publishing oriented, and then what does the structure need to be for something that’s going to allow us to have a more digital-oriented life cycle. So that’s always really difficult. It’s a long and oftentimes painful process, but it’s a necessary one. And it’s where I think for us, as consultants, we can really come in and help if an organization is struggling with that. Another challenge that we faced is helping content creators deal with the learning curve that comes with a new IA. And just like I mentioned on that last point about digital transformation projects, that’s where we tend to see a lot of us happen the most is that you’ve got a lot of people who are very experienced writers and experienced at that aspect of content creation, but they don’t have the experience of working with a more digital focused content life cycle and the IA required to support that.

So for example, if they’re going into something like data XML that would support a new digital life cycle, then they’re going to require a lot of knowledge transfer, a lot of training, and a lot of support all throughout that process because that learning curve is pretty steep. Another challenge that we see a lot is conflicting ideas around how the IA should be designed and built. And this is true whether you have one IA that you’re already working with and you’re looking to improve it or whether you’ve never thought about it before and you are just now realizing that you need to solidify an IA for your content. So there can be differences of opinion with different groups who are working on content. Like I mentioned earlier, if you’ve got those content silos and people who don’t work collaboratively, then they might have really, really different ideas of how the IA should be done going forward.

You can also have an issue where if an organization isn’t really getting adequate feedback from their customer base, then they don’t have that in mind how that should feed into decisions around how the IA should be built. And all of this is really where it can help a lot to get some outside perspective from a consultant. So when we come in and we see these conflicting ideas happening, we’re able to give them that perspective and say, “Here’s what we’ve seen at a lot of other organizations that might help you to learn from that experience. Here’s what we typically see as industry best practice.” And that can help resolve those conflicts and guide them through to getting an IA that’s actually going to serve their organization best.

CC: That’s great. It’s just like a tiebreaker, a third party to come in and be able to be that unbiased voice to give support for what’s going to be best.

GK: Sure, absolutely. And then another challenge that we faced is trying to work around aggressive or sometimes even unrealistic implementation schedules. And this happens a lot because the schedules are often set by non-content creators. It might be people and upper management people at the sea level who aren’t really in the weeds and don’t fully understand all the ins and outs of what’s required to create content, convert it from one format or structure to another, develop an IA that’s going to work for you going forward. And so, if there’s that tension with the schedule saying, “We have to meet this deadline because that’s going to affect our scalability, our other goals,” that can sometimes result in a project being pushed forward without adequate time to plan for your IA.

And then what that eventually causes is some messy situations where because you did not put an IA in place properly or didn’t think about all of the different things your IA might need, then you try to produce content and it’s not going to serve you in the way that you thought it would. So even though a schedule might be really aggressive, even though you might have deadlines, it’s still important to prioritize the IA and not let that be something that falls by the wayside in favor of meeting a deadline.

CC: Got you. So I’m curious to know a little bit more about pilot projects or proof of concepts. I know it was mentioned in a previous podcast and we’ve talked about it a little bit in some other places. Can you unpack what those are and how they may be able to help your developing a new IA?

GK: Absolutely. So pilot projects and proofs of concept are a really good way to mitigate risk when you are developing a new IA or changing an existing one or really doing any kind of change to your content processes. So specifically when we’re talking about IA, you could use a pilot project to try out a new IA that you are planning and thinking about on a small subset of your content and that can let you see what works and what doesn’t in real-time, give you that practical example, and that way you can make adjustments to the plan for your IA before you roll it out across your entire body of content. And then if you’re still trying to convince management that a new IA is a good idea, you’re trying to get the budget required to roll that out across the organization, then having a successful pilot project can actually help you do that. It can really convince people, “Here’s the return on investment that we’re going to get if we put this IA in place and here’s the proof that it’s going to work.”

CC: That’s great. Yeah, that’s really helpful.

GK: I also wanted to note that IA development does require a lot of flexibility. You are almost guaranteed to have to go through multiple iterations, you’re never going to get it perfect on the first try. And that’s why we do recommend a pilot project or a proof of concept because it lets you start small and it allows you to build in the room for that flexibility all throughout your project rather than being under that deadline pressure that I talked about. If you have that pressure to get it right and you know that that’s not going to work, then you’re setting yourself up to fail. So putting a pilot project in place, doing a proof of concept really just helps get rid of a lot of that risk.

CC: Yeah, absolutely. I’m sure it puts everyone’s minds at ease. So I’m curious if someone wanted to start a proof of concept or organization wanted to invest in these first, how do they do that?

GK: That’s always really interesting. It kind of varies from one organization to another, but where we see it often originate is there will be maybe a writer or a manager of a group of writers, one person who really sees an opportunity and isn’t at the level where they have the pull at the organization, where they have the budget, have the resources, but they do have the knowledge for, “Here’s an idea that might work.” And so, a lot of times these proofs of concept just originate from the ground up from people who are actually working on the content, and that’s what allows them to grow their IA and their overall content strategy for the larger organization.

CC: Got you. Yeah. So they’re the ones that are really recognizing the need, probably the ones also hitting the pain points, unfortunately, to say something needs to change. So that’s interesting. Circling back to your response earlier on that actually, when you mentioned that sometimes content isn’t a priority until it’s too late. Could you kind of unpack what could be included in too late? Either signs that it has been too late and we need to focus on content or some pain points that might be coming up to help you avoid getting stuck in too late.

GK: Sure. So one of the red flags that we see a lot that says, “Either it’s too late, you should have started planning an IA earlier or now is the time to start,” is that if you have a lot of inconsistencies in your content getting in the way of being able to take advantage of all it can do for you, that’s definitely a sign that you need a lot better IA planning. So if you are trying to do reuse for example, and you’re unable to do so because of how your content is structured, if you realize that you need to start translating into other languages, or maybe you already are, but you need to translate into a lot more languages and that’s costing you a lot of money because you can’t do reuse, if you are running into issues with publishing, so if you’ve got people requesting custom content or personalized content and you just are not set up to deliver that, all of those things because your content is written inconsistently, it’s structured inconsistently, that’s definitely a sign that you need an IA.

Another one is the inability to search your content or filter your content due to a lack of sufficient metadata. So metadata is a really important piece of your overall IA puzzle. And a lot of organizations don’t really think about how it’s going to be used both internally by content creators and externally by your audience, by your customer base. And so, if you haven’t thought about all the ways that people might need to search the content and find information they need, that they might need to filter the content down to delivering specific pieces to specific people or even filtering your search results, all these different ways that you can find the right information within your set of content, a lot of that is driven by having the right metadata in place.

So if you find that people are unable to do that, then that’s another one of those signs or pain points that says, “Okay, we need to rethink our IA and make sure that metadata is a big part of that and that we have considered that.” And then just like we’ve talked about several times throughout this discussion, challenges the scaling. So if you have issues with meeting your goals for growth and scaling your content up to meet that demand, then that tells you, “Hey, let’s go back to the ground up and think about our IA that we should have had in place all along. And then that will allow us to do what we need to do to scale up our content development processes.

CC: Yeah. So if any of those pain points sound uncomfortably familiar, that is definitely something that we can help with here at Scriptorium. So we’ll have a link in our show notes where you can contact us to get a conversation started. Gretyl, is there anything else you can think of that you want to share with our listeners about IA or anything else we’ve talked about today?

GK: I think the biggest thing is just don’t overlook it and don’t leave it out.

CC: Yeah, absolutely. Well, thank you so much. I really appreciate you being part of the podcast.

GK: Absolutely. Thank you.

CC: Yeah. Thank you for listening to the Content Strategy Experts podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Why information architecture matters (podcast) appeared first on Scriptorium.

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In episode 137 of The Content Strategy Experts Podcast, Sarah O’Keefe and guest Larry Swanson talk about the fragmentation of content over the past 30 years, from the delivery of books to UX writing.

“What are the changes that this fragmentation has introduced from a business or an economic point of view? One is the notion that we’re all publishers now. This is where the whole field of content marketing comes from — this notion that it’s a better way to promote yourself if you demonstrate expertise around what you’re doing.”

Related links:

Content Strategy Insights podcast – Hosted by Larry Swanson
Content strategy in UX teams (podcast)
Why having an enterprise content strategy is important to your UX

LinkedIn:

Larry Swanson
Sarah O’Keefe

Transcript:

In this episode, we talk about the fragmentation of content over the past 30 years, from delivery of books to UX writing, where you publish content inside software. Our guest today is Larry Swanson, an independent content designer and content architect who also has his own podcast called Content Strategy Insights. Hi, everyone. I’m Sarah O’Keefe, and, Larry, hello!

Larry Swanson: It’s great to be here, Sarah. I love your podcast and I’m delighted to finally be on it.

SK: Well, likewise. So we’re going to have, I think, dueling podcasts and it’ll be fun. Tell us a little bit about what you do. Tell us a little bit about who you are and where you’re coming from and what your life looks like in business.

LS: Yeah, it’s inevitable that I ended up where I am. I’m a word nerd from birth. My mom was an editor. I’m also… My dad was an engineer, so I’ve had this weird combination of technical and grammatical stuff throughout my life. And yeah, so I went to journalism school, which seemed like a good idea at the time. I immediately abandoned journalism for book publishing when I got out of college. I went to a course called the Radcliffe Publishing Procedures Course. Because of that, I think just that journey, the way I got into journalism school was interesting, the fact that I went right into book publishing out of there. I’ve always been more interested in the process of how this happens than about the writing itself. I’ve done some writing and can communicate well, but I’ve never been a writer. I’ve always been the publisher, the editor, the marketing guy, the meta-practitioner.

SK: Yeah, which is interesting because I think that that’s quite similar to how we describe ourselves here, that if you’re looking for domain knowledge, that’s something that you should have inside the organization. We’re the people that come in from the outside looking at your publishing systems and what that looks like.

So you and I were talking a couple of weeks ago, which is actually where this podcast topic came from, because we were looking at this question or this idea that many of us actually came from traditional book publishing, and now we’re doing things like publishing software strings inside software, doing UX writing or UX design, but we came from this traditional book world. And that got us started on the concept of fragmentation and what that means and what the implications are. I wanted to start with content challenges. What kinds of content challenges do you see in this long term, I guess, but 30 years is really the blink of an eye, but in this transition from a book-based publishing world to UX design, UX writing content embedded in software?

LS: Yeah. Well, it’s funny. The first thing I reflected on when we talked about this is what’s the same. And I’m surrounded by awesome word nerds and good collaborators, so that’s been the same throughout. But it manifests entirely differently now. Whereas we used to have these long, convoluted, literally years-long processes to develop a manuscript, put it into that sausage factory of everything from developmental editing to the composition, and then all the distribution and the physical manufacturing of the books and all that, a quick turnaround would be nine months. Sometimes if you got a really hot topic, you could turn it around that quickly. Now we’re dealing in milliseconds for some of this stuff. I think of that Oreo commercial during the Super Bowl. Remember when the lights went out? And they created a whole advertising campaign in 10 minutes about “you can dunk in the dark.”

So we’ve kind of gone from years to seconds and the whole cycle. Around the time, the start of this transformation, for me, a guy named Nader Darehshori. He was at the time the CEO of the publisher Houghton Mifflin. He said that publishing is just the business of the discovery, development, and dissemination of ideas. There’s a lot going on in there, and it used to take a long time for it to happen, but that ad that Oreos did during the Super Bowl, that whole thing happened in literally 10 minutes or something like that. So that compression of time has led to, I think, the need to be super hyper-attentive to the procedures, how you do stuff, and the stuff you have in place to facilitate that sharing of ideas more quickly.

I think one of the very first books we read is, when I went to a publishing course right after college and read this book called One Book/Five Ways, where they took the same manuscript and gave it to five different university presses and got five different treatments of that. So I’ve always been really conscious of… and there were sort of best practices exemplified in that, but everybody did it their own way, and that’s another thing that’s only magnified. There used to be something much more like best practices. Now it’s like everything is bespoke. And yet, you have to have a way to do it so that you can be bespoke. And that’s where we’ve gone from these long tunnels of production and distribution stuff to these more fragmented, increasingly decoupled modular architectures that permit taking content, mostly words in text form, but also recordings of various kinds and even 3D stuff in the metaverse, and being able to do stuff with them more quickly.

That’s been the biggest change, is it’s still people sharing ideas with other people in a media format. I think a person from Mars who could magically look in at us and just look at… They would think, oh, it’s just the same thing. And it’s like, yeah, it kind of is, but there’s a lot more going on now to make it all happen.

SK: So I understand the concept that a lot of the increase in velocity is that we got rid of physical distribution. We don’t have this process of printing books and binding books and shipping them to bookstores, which does take a significant amount of time. But backing up from there, you mentioned developmental editing, and where are the developmental editors in our fragmented content chain? Is that concept just gone?

LS: No, I think it’s still here, but it manifests differently. I think think that happens in the craft. Content strategy is a discipline. You might call it fragmenting, but I call it… I think I’d equally call it specializing. I’m still a generalist and I’m kind of weird that way, but for the most part, the content practitioners now, they’re either a content creator or a strategist or a designer or an engineer or a content operations person, people managing it, and there’s many other specializations that are happening. I think that’s part of how it’s happening, is that it’s the craft that permits the acceleration, that things are developed differently, and we’ve figured out… We are still figuring out, I should say, because the articulation of the field of content design is really only… I mean, people have been doing it a long time, but people have only been calling it that for 3, 4, 5 years, something like that. But look at how quickly it’s taken off. And Kristina Halvorson is shutting down Confab to focus on content design at Button.

So it’s a very fast-evolving thing, but it’s the collection of crafts that develop the ideas now rather than this kind of sausage factory, linear progression of things. Does that make sense?

SK: I think so. So looking at… You’ve mentioned the sausage factory a couple of times, which is, I think, an apt metaphor, unfortunately. What does this look like from a tech point of view? What are the changes in the processes, systems, and I guess especially software that we use to produce content?

LS: Yeah. I think what’s funny is what… I remember being exposed to SGML, the predecessor to HTML 30 years ago. I knew that there were ways that you could deal with words separately from their presentation. But I think that’s been the main thing, is the disarticulation of the content, the meaning, the words, the pictures, the images, all that stuff that make up the content, their disarticulation from the physical… We used to have these physical artifacts where we shared the information, and now it’s all digital. And within that sharing, the tech that makes it happen, it’s instrumental to the whole thing. Where it used to be tech was the facilitator that created the object, now the tech is the object. It’s like an interface at the end of a thing rather than a physical artifact.

And it’s more of a people challenge, I think. It’s not hard to get into all that technical stuff and figure out, oh, I can make these words appear here with this technology. Piece of cake. Getting people to abandon WYSIWYG mentalities around graphical user interfaces and author content in new ways for more abstracted out and then reassembled experiences, I think it’s… The technology has kind of made it, to my mind, a logical evolution, and it’s like, oh, cool, we can do all this. We can make our little Lego kits however we want and put them together however we want. But I think there’s still this legacy thinking that a lot of us have that I still struggle with every day of that linear process that creates physical artifacts that we still have.

People still talk about creating web pages. It’s like, really? Is that what you’re doing? I don’t think so. I mean, maybe it manifests as a page in that one moment, but the elements on that page are increasingly customized or maybe even personalized for a unique experience. They’re responsive to the device that they’re on and the screen resolution and the accessibility needs of the end user. There’s all these different things that go into that are technically easy enough to implement, but helping everybody along the way understand this different way of doing stuff. On my podcast, it almost always comes back to, you know, this is mostly about people, and I think the technology stuff, yeah, it’s mostly about people.

SK: Yeah. Well, and it’s interesting. I mean, as you’re talking about WYSIWYG and people acting as though WYSIWYG is their birthright, which has been around forever, it hasn’t. I mean, you don’t have to go very far back in book publishing to find that people would on a typewriter type a manuscript, which bore no actually resemblance to the final book. It was a typed manuscript with no formatting, I mean, paragraphs and maybe some chapter headings, but it had to be actually composed into a book, and woe be unto you if you had figures and tables. Those were nearly always included in an appendix at the end of your manuscript, right? Here’s Figure 1 inserted on typed page 75. So this concept of WYSIWYG and putting it all together and getting a visual preview for the author is relatively, I mean, relatively new. We’re talking about, what, 1987 or thereabouts.

LS: Yeah. When was it? PageMaker and then Quark, and I think that’s where that came from.

SK: PageMaker was… Yeah, roughly. I think the first time I saw it was about 1988, so somewhere in the ’80s. Yeah.

LS: Yeah, that’s right. You know, it’s funny the way you said that, like it’s our birthright to be able to see what we’re doing. It’s like, nah, it’s just a little blip in publishing history.

SK: Right, and, well, of course if we go far enough back, then we will discover that people used to actually compose their pages as they went, and they were totally WYSIWYG because…

LS: Right. No, and as we were talking about before we went on the air, like Gutenberg, the implications of that were more about replicability, and the scribes before him knew what they… You saw exactly what you were publishing.

SK: What you see is what you get.

LS: Exactly.

SK: No podcast of ours is complete without a mention of Gutenberg, so we’ll check that one off the list.

So the tech, it swings back and forth, and sometimes you’re WYSIWYG and sometimes you’re a cog in the machine. And people seem to prefer largely not being a cog, right? They like to exert that at least perceived control over what they’re doing. So then turning our attention to the business of publishing and the business of content, what do you see there? I mean, what are the changes that this fragmentation has introduced from a business or an economic point of view?

LS: At least two big things. One is that notion that we’re all publishers now, that this is where the whole field of content marketing comes from, that this notion that it’s a better way to promote yourself if you demonstrate expertise around what you’re doing. We both do that with our podcasts. This is why people know we’re so awesome at our content practices. It’s because we have podcasts. And there’s a million other ways that you can do publishing-y kinds of things. But the business intent of those, rather than selling podcast episodes for money, we’re using it as marketing.

There’s that, that notion that everyone is now a publisher, but there’s also the notion that the business of publishing itself has changed. There’s both the fact that we’re all now publishers, just made that whole world a lot bigger, but there’s still publishing happening within there. You think about media like Netflix and the New York Times and game publishers, everything from consoles to the new 3D stuff. So publishing is still happening, but there are a lot of other business things that happen with the same technology, which I don’t think that was true. I mean, it was kind of true with old-style publishing. You would use the printing press to create an internal newsletter or something like that.

But it was not as ubiquitous as it is now, because everybody has access to this stuff. No matter what line of business you’re in, you’re using those technologies to do slightly different stuff, which I think is where the whole field… That’s one way to contextualize the rise of user experience design, because you’re serving like, okay, I just need to sell some stuff. I’m a merchant, and so I have this e-commerce world of stuff that I can do with these ostensibly publishing technologies, because they’re about just sharing information. But you’re sharing information in service to getting somebody to place an order. Or if you’re a marketer, you’re sharing information in service of getting a lead. Or if you’re a publisher, you’re sharing information to get paid for that thing you just published, whether it’s an advertisement or a subscription. And if you’re…

So that kind of publishers, merchants, marketers have always been, to my mind, the three main buckets in the business world of digital business. And their websites all kind of look similar now, but there’s different business prerogatives that underlie them that lead the whole… I’m working at a big travel company right now, and this business logic that underlies that whole thing, it just looks like any other website, just lists stuff about the travel products. That’s way different than a big affiliate site that was just selling links back to Expedia. A big travel company like Expedia is doing all that business stuff. The travel agents and airlines and hotel chains used to do it. So I think it’s broken down a lot of barriers that make new kinds of businesses possible.

So I think that’s the biggest level of it, and they’re all using the same technology. They all have to abide by those same practices around, if you want to be found, you better have a responsive website so you better abide by responsive web design principles and be using CDMs and all… whatever the latest technology thing is to improve the end… and it’s always about user experience. The reason that’s important is because users don’t have the patience to wait for a slow-loading webpage. I can’t articulate it as well as we hoped I might when we talked about this interview, but there’s something going on there where it’s much more about the end user and meeting their needs. So I think you can trace back almost all these developments to the need to improve that, the places that are doing it well, anyway, to help people find the right information at the right time.

Google does that pretty well, help people get the movie that they really want to chill to that night. Netflix does that really well. And it’s all about satisfying user needs. And that, to me, is this technology that we first saw as a way to accelerate and increase the velocity of publishing activities, it’s like, oh, I can sell stuff with that too. Oh, I can deliver media that’s customized to a person’s interest. Yeah, that would’ve been nice to have Blockbuster could have sent somebody to your house and interviewed you about what video you want to watch, but that’s not very scalable. So anyhow, so that notion that it is all technological that permits the scalability, that’s the foundation of most of these business models, is that ability to take a good practice and just, boom, do it for millions of people at once.

SK: Yeah, I think scalability is a really, really good point. And velocity, velocity of publishing is sort of related to that. They’re not exactly the same thing, but can you scale up and produce more and more and more content and can you do it fast or instantaneously by… because our old distribution, put it on a truck and send it to a bookstore, has been replaced by push this button.

LS: That’s right.

SK: And sometimes not even that.

LS: There’s something in there about… I think one of the other really important things that we just don’t think about consciously enough but we’re all doing all the time is automation, that we’re automating tasks that used to take… I think that’s really coming to the fore now with the generated AI stuff, ChatGPT and those kinds of things, that, like, oh, I don’t have to outline this. I’ll just have ChatGPT do this for me. That kind of task automation underlies a lot of this. I can’t articulate exactly how that’s going on, but I think that’s an important part of it as well.

SK: Well, and I guess with a call-out to AI is up next and we’re not really sure what that’s going to do for us, that seems like an excellent place to close this. So Larry, thank you so much for coming in and sharing your thoughts and giving people something to think about and be scared of.

LS: I hope I didn’t scare anyone. And thanks so much, Sarah. I really enjoyed the opportunity to chat with you, and I hope that rambling stuff made some sense.

SK: Well, I think so. We’ll see what our audience thinks. So thank you, Larry, and thanks to you for listening to the Content Strategy Experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

The post Content fragmentation with special guest Larry Swanson (podcast) appeared first on Scriptorium.

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In episode 136 of The Content Strategy Experts Podcast, Alan Pringle unveils horror stories of content ops gone horribly wrong.

Related links:

How Scriptorium optimizes content to transform your business
Who is Scriptorium?
Content creature feature
Beware the monster of change management

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Alan Pringle
Christine Cuellar

Transcript:

Christine Cuellar: Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we share some content operations horror stories. Today I have our COO, Alan Pringle, with me. Hey, Alan. How’s it going?

Alan Pringle: Hey there, I’m doing well.

CC: Are you ready to talk about some horror stories?

AP: The question is, are you and is our audience ready for this? Because I’m not sure that they are.

CC: Well, I hope we all like horror because we’re diving deep into some stories. So, Alan, why don’t you kick us off?

AP: Well, I do appreciate the horror genre, I have for a very long time, and I’ve noticed that my favorites tend to have very short titles. Like last year there was Barbarian, which I really liked. Then there was the 1978 movie Halloween, the original. I’m not talking about the newer ones. I don’t like those as much. And then the Evil Dead and the Conjuring, they’ve got these short, snappy titles. So I thought we could kind of play with that whole idea and label some of the things that I have seen along with the other Scriptorium folks over the years.

CC: Absolutely, love that idea.

AP: So let’s talk about the first horror story. So everybody, let’s gather around our digital campfire and we can exchange scary tales.

CC: Grab our marshmallows.

AP: Yes, that. Yes. Let’s call the first one, The Update.

CC: Dun, dun, duh.

AP: Exactly.

CC: Always chaos and carnage with an update.

AP: In this case, it was ugly and gory indeed. We had a client who was changing their name, changing their branding. They had hundreds of desktop publishing files, and unfortunately, these files were not templatized, which means to do an update to change the company tagline, to change the company logo. They were going to have to go through and touch every single one of these files. Yeah.

CC: Talk about horror.

AP: Absolutely awful. The good thing is there is a happy ending here that is not all blood and guts. Because there was so much of this content involved, it made more business sense to convert all of these desktop publishing files to structured content. And by doing that, we set up an automated publishing workflow. So instead of going through and touching all of these files, we did the conversion and then we set up transformations of that structured content into, for example, PDF files, and the automated publishing process automatically put in the new logo, put in the new tagline.

So people didn’t manually have to do it. We ran that structured content through this transformation process, and voilà, we had the PDF files that had everything in it, and people didn’t have to physically touch them. So instead of making a huge one-off investment in all this manual work, the company did something really smart and invested in better content ops. So since then, if they have had to update their logo or their tagline, all they would have to do is go in and touch their transformation process, fix that there, and just rerun everything and then the process will handle it for them.

CC: So much better.

AP: Yeah, it’s magical.

CC: Yeah, so much better. I love that it’s not only easier for the team, but it’s also better quality. It’s easier to produce better systems rather than leaving things open to mistakes. I just love that about content ops.

AP: No. No, you’re exactly right. This created a repeatable automated process, and those are two huge wins. So that has a happy ending.

CC: Unlike most horror movies, there is a happy ending here.

AP: Well, you got to have the sequels.

CC: Yes, that’s true. That’s true. The 500 sequels.

AP: Exactly.

CC: All of which pale in comparison to the original, but yes, correct.

AP: Usually. Correct. You’re a hundred percent correct. Let’s go with the next story, which I call Cut and Paste, and this is not limited to just one client, and I am sure our listeners have been through this very thing before where you have one piece of content that pops up in multiple places in your documents. Unfortunately, that content has been cut and pasted manually a zillion times, so you have a bunch of different versions of that and a bunch of different files. And this is where your sequel comes in. Somebody will go in there and slightly change one of those, which is supposed to be the same wording, change a word or two in there, and now you have the sequel, Cut and Paste: The Mutation. That is never, never good, and it just compounds headache after headache. And then for part three, which probably should be in 3D, a three-dimensional movie.

CC: Yeah.

AP: It would be… yeah, Cut and Paste Three, Localization. Yeah, that’ll have ‘em running out of the theaters, because every time that you translate something like this and you’ve got all this copy and paste in your source content, and then you translate it, what are you doing? You are basically replicating the same horror that you had in how many different languages? It’s incredibly inefficient, it’s incredibly expensive, and it’s a headache for everybody involved.

CC: Yeah.

AP: This is why you need better content operations, and you basically need to figure out reuse scenarios. You don’t necessarily have to do XML or structured or authoring or use X tool or Y tool to do this. A lot of tools have the ability to set up mechanisms for reuse. Even Microsoft Word at a low level has some of these features. So what you need to do, you need to templatize this content. You need to set it up so you are referencing things that are going to be repeated often. So when you do have to make an update to that, you change it one time and it just automatically fixes itself across your body of content. That is the ideal thing you need to do, especially before you start localizing your content into other languages.

CC: Absolutely. Yeah. And that’s something we do touch on more in our blog posts that we published about how Scriptorium optimizes your content. We’ll go ahead and link that in the show notes as well, so you can check that out.

AP: Yeah, no, and that’s a very good point. Localization is often one of the drivers that has people talking to us and realizing our content operations, they’re broken. So yes, localization is one of these things that can really make or break you when it comes to your content.

CC: And from my understanding, a lot of times companies are reaching out because they’re missing out on a localization opportunity, is that correct? That’s the pain point that they’re experiencing is they’re missing out on something they either are being told they need to do or something they want to do, but there’s no way that they can go ahead and meet those requirements or step into that new opportunity with their current operations process.

AP: No, it’s true. In some cases, there are regulations that say you will provide this content in the languages where you’re shipping this content, to locale specific content. So are you going to end up having your products sitting on a dock somewhere while you scramble to get these documents in place? Which sounds absolutely bonkers. It has happened. Same thing for services too. I mean, in this global international environment, if people don’t have that content in their language, they’re not going to use your product. And that goes for the interface. Is it in their language? Is the content that explains how to use it in their language? So yeah, you can lose out on an income stream because you are not ready to localize and to do it efficiently.

CC: Absolutely. All right, now onto our next horror movie. It’s The Spreadsheet From Heck. And I’m very curious about this one because this one really messes with me.

AP: Yeah. The more R-rated version is spreadsheet from (beep). I know I will be bleeped for that, but that’s more accurate. So yeah, Christine’s going to have to get out her buzzer and bleep me on that.

CC: I will, yeah.

AP: Spreadsheet From Heck. First of all, if I saw a trailer for a movie that had the word spreadsheet come up when I was in the theater, I’d just get up and leave. Yeah., Because I get enough of that during the workday. I do not need to see it when I’m trying to have fun, thank you very much.

CC: Trying to escape reality here by going to the movie

AP: Exactly. I don’t need it reinforced in my face for an hour and a half. But someone has made the observation, it was not me, and I want to be very clear it was not me, someone has made the observation that the most common content management system is probably an Excel file.

CC: That’s horrible.

AP: It is horrible, but there is a degree of truth to this. There’s a kernel of truth there. A lot of people will plan out their workflows. “Here are all our files. This is the schedule. Here’s when it needs to be reviewed. Here is when it needs to be approved,” all that stuff. There is some degree of automation, yes, that you can do in a spreadsheet, but that only goes so far. And there’s some really critical things that you need to keep track of when you’re trying to manage just gobs and gobs of content.

I cannot imagine trying to do all of that in a spreadsheet, yet some people valiantly try, and they may be successful for a while, but I am nearly certain there has got to be a tipping point where you cannot do this anymore. And that’s true of almost everything we’re talking about in this episode. These things can work one off, or if you’ve got a very small body of content, the minute your requirements change and require you to do more, the stuff doesn’t scale. And this is a perfect example of where scale is going to inflict a great deal of harm on you. Maintaining that sort of stuff in a spreadsheet, that is a no-go from my point of view.

CC: No, I can’t even imagine from a content marketing perspective because I know I just specialize in content marketing and I’m not producing content on the scale that a lot of our clients and even our staff are producing content. I can’t imagine organizing all of that in a spreadsheet and having tasks remind me of when to follow up, when to do what, when to update what, all that kind of stuff. I truly can’t imagine managing that. I think it would just…. It would be a horror movie.

AP: Exactly. Like I said, it’s not ideal, but it happens more than it probably should.

CC: Speaking of something that happens more than it probably should, let’s move on to the next movie, The Email Chain.

AP: And people are going to think this may be some throwback to some lower tech era, and the sad truth is yes, today in the 21st century, there are still people, still companies who do content reviews by sending either PDF files or bits and pieces of information in an email. And they go back and forth making changes and getting approval. That to me, I mean, please just set me on fire. It’s deeply, deeply inefficient, yet it still happens today. And I’m sure there’s some people out there saying, “Surely not.” Surely yes, it does still happen, believe it or not. Very painful.

CC: Yeah, less efficient and more overwhelming, like you said. So things are going to get lost. Little updates, revisions, that kind of thing, that’s definitely going to get lost. So it’s more work to produce a lower quality piece of content versus moving it over to a streamlined content operations system.

AP: Yeah. And we think the spreadsheet is bad, I think the email chain may be more horrific than spreadsheet from whatever word you want to say there.

CC: Yeah.

AP: Those both point to using technology that’s really not the right fit, but it’s ubiquitous, you’ve got it handy, so you’re going to rely on it. Not the best business decision. I can understand why you would do it, but in the bigger picture, it’s not where you should be going.

CC: And speaking of the bigger picture, one thing that stood out to me when we were… on our previous podcast with Sarah is companies often reach out to us when they’re hitting some pretty significant pain points and when they’ve definitely recognized that it’s time, something’s got to change, we’ve got to become more scalable. But you don’t have to wait until then to optimize your content operations. I mean, I would recommend doing it now before you hit those pain points. Don’t wait until you’re missing an opportunity. Don’t wait until things are… you’re stuck in a never ending horror movie and you can’t get out. Now’s the time.

AP: Yeah. Yeah. Basically nip it in the bud. And what’s popped into my head is the movie, and there have been multiple versions of this, Invasion of the Body Snatchers. In our case, I think we might want to call it Invasion of the Time Snatchers, because if you let this stuff compound, compound and compound, all that’s going to do is just basically completely drain your organization of any resources to even try and make incremental improvements in how you create your content.

As you improve how you create your content, it is going to make it easier for you to create better content. The content itself will improve, but if you’re stuck in this mire where all of these inefficient processes are eating up all of your time and they are not something that you can repeat, they are not scalable, it’s like the Groundhog Day of horror. It just repeats and it loops back on itself over and over again. And that is a sad reality for a lot of people. But as you suggested, the minute you start having an inkling that’s happening, that’s when it’s time to realize it’s time to take action. Let’s fix this.

CC: Yeah. And anybody that produces content has content operations. So there’s always the opportunity to optimize. There’s always the opportunity to see where you can automate and make things better.

AP: And it can be baby steps. Absolutely. And I think that’s a very good point to make. All these things that we have mentioned that are not super efficient or sound even remotely fun, they are all content ops. They’re just really bad content operations. So it’s not a matter of, “I don’t have ops, I need them.” It’s a matter of improving, and these things can be taken in baby steps. You can be incremental. For example, even trying to templatize things to give you some degree of consistency, that is a small step you can take if you’re working in word processing or desktop publishing. Templatize things so you have a very standard way that you create content, the formatting is standardized. Because if the content creators don’t have to spend time fiddling with that stuff, that is time they can invest in writing better content to help the people who are reading it.

CC: I like that mindset shift that you brought up: When you have bad content ops or things aren’t working well, those problems compound on each other. But in the same way, when you have good content ops, the benefits of that compound on each other. So you have more time to be able to make content better, and to even revisit your processes and revisit them over and over to see, “Now that we’ve optimized, how can we get to the next level? How can we get to the next level?”

AP: Absolutely. There is always room for improvement, and it’s a good idea not to rest on your laurels and do a check every once in a while, because you never know what creature might be hiding in your closet.

CC: Yeah. Might be Jason.

AP: Michael Myers, Freddy Krueger, the Babadook, you name it. Yeah.

CC: Not that this is about content and ops, but the sequels in Halloween cracked me up, how they continuously repeated, “Evil dies tonight.” And evil never did die tonight, so.

AP: No, it didn’t, and I wish that it had. This could be a whole other podcast. Those later reboots did not please me, but we’ll talk about that some other time amongst ourselves.

CC: Yeah. Good idea. Well thank you all for listening to the Content Strategy Experts podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check out the show notes for the links we talked about today. And thanks, Alan.

AP: Thank you.

The post Nightmare on Content Ops St. (podcast) appeared first on Scriptorium.

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In episode 135 of The Content Strategy Experts Podcast, Sarah O’Keefe and new team member, Christine Cuellar, talk about who Scriptorium is and how we use content to optimize your business.

Related links:

25th Anniversary of Scriptorium
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LinkedIn:

Sarah O’Keefe
Christine Cuellar

Transcript:

Sarah O’Keefe: Welcome to the Content Strategy Experts podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we’re talking about who we are and how we use content to optimize your business. And I’m joined by our newest team member, Christine Cuellar. Hi everyone. I’m Sarah O’Keefe. Our host today is Christine, who has just started as our new Marketing Coordinator. So of course we put her to work right away. Welcome to the team Christine, and guess what? You’re in charge of this podcast.

Christine Cuellar: Sounds good. Hello everyone. I’m excited to be here. Since I’m new, I’m going to be asking all the newbie questions. So I thought this would also be an interesting podcast for our new podcast listeners. Sarah, I’ll go ahead and kick it off with a basic intro question. What started Scriptorium?

SO: Well, canonical answer is I was annoyed by a layoff. So a million years ago, I worked for a software company that did the canonical hockey stick growth from zero to 60, from 80 people when I started to 500 people 18 months later. And then that company with about four others got acquired by a larger company. And in the process of sorting out all those companies that the mothership parent company had acquired, in the process of that assimilation, many of us got laid off and we were all a little cranky about it. And I decided that if executives were going to make dumb decisions, I could be the executive making dumb decisions. And so basically I was angry, and here we are 26 years later.

CC: That sounds great. And you have an article that goes more in depth on that story as well. We’ll go ahead and link that article in the show notes. So what does Scriptorium do?

SO: That is…

CC: A big question.

SO: I know you think I’d have it figured out by now. But we are interested in content and technology and publishing, and specifically we’re interested in product and technical content. How do we take that information that is so often overlooked and under-invested in and manage it, produce it, do things with it in such a way that we can maximize its value for our customers? So we are interested in taking interesting technology and applying it to content so that we can perhaps automate content development or automate content delivery or improve the publishing process or do multi-channel kinds of things. All those buzzwords that you hear these days we’re interested in how do we make the most out of the investment that you have to make in technical content.

CC: And what’s the scope of our work?

SO: We start typically with an assessment or an analysis or a where are you now? What’s working? What isn’t working? Where are the pain points? And then work our way from that to what are your business needs? What are you trying to achieve? Do you have problems with people calling tech support with basic questions that are or should be in the documentation, but instead they’re making an expensive phone call? Do you have problems with translation, localization with people who would prefer your content in their local language, but you haven’t made that investment because it’s so expensive to translate or localize. So part A is what are your business needs, what are the problems you’ve identified? And part B is how do we develop a solution that leverages your content to fix that? And then I guess part C is we actually build the solution.

CC: Wow.

SO: So some really, really common things here are people saying all our stuff is in Word and it’s not working. We can’t scale it, we have a problem. Some huge percentage of our work is actually structured content. So that’s definitely a point of emphasis right now. That’s not where we started because 25, 6, 7 years ago, structured content had less market share than it does today. But that’s a common thing that we hear is that people have identified that structured content will address some of their requirements, and they need us to help them get there from whatever system they’re in right now. And then I think a key point is that we do not have software. We are a pure services company. And in addition to not having software in the sense of having a product that we sell, we also don’t resell software and we don’t accept referral fees from the software vendors in the space.

CC: Great. Thank you. And thanks for those examples too. Those are really helpful. So what kind of implementation work? You mentioned that briefly. Can you expand on that a little bit?

SO: A typical project for us is somebody who has decided that they need to improve the maturity of their content development processes, move it out of a word process or unstructured, sort of flailing at it, and just throwing bodies at the problem in order to make more and more and more content. And instead design and then build out a system that is more efficient, that leverages reuse, that leverages formatting, automation and all the other cool stuff that we can do. So when we say implementation work, what we’re talking about is that we’ve been through or you’ve been through as the customer and have said, this is the problem. Here’s the proposed solution.

And now we need to do things like pick a content management system, convert all the content from whatever format it’s in now into future state content format, get it moved in, stand up the system, configure the system, get all the people, the authors, the content contributors, the reviewers, the approvers moved into the system, move the content itself, and then go to production. So when we say implementation work, we’re talking about the process of actually building out or configuring the system that’s going to support all these things for you.

CC: Great. Thanks. And you mentioned earlier on that one of the first parts of the process is to just identify some pain points, figure out what’s going on in the organization that needs to be addressed. What are the most common pain points?

SO: I think the number one issue that we see is scalability, as in we can’t scale. We are being asked to do more and more formats. We are being asked to do more and more languages. We are being asked to do more and more content variance because our products are complex or we do customer specific information. So a given customer gets a custom version of the product, that type of thing. Scalability, especially scalability in localization, I think is the number one issue that we run into. So that looks like somebody saying, we know our process isn’t great, but it works okay because we only have five languages, but now we’ve been told we’re expanding into the European Union and we’re going to need 30. We simply cannot take the current five language inefficiencies and multiply by six to get to 30 languages.

There is no way. We have to automate, we have to refactor, we have to reuse because if we don’t do those things, our costs are just going to skyrocket. And maybe more importantly, our time to market. We can’t get to market on time in all these languages in our current process. It just piles, delay upon delay upon delay. So scalability is a big one. Now, related to that, we see things like multiple incompatible content creation systems that don’t talk to each other, but yet need to share information in some way. This is really, really common after a merger. Because company A had system A and company B had System B, you put them together, they can’t talk to each other, but they need to because the customers now are joint customers. From my point of view as a customer, I don’t care that you were company’s A and B, you’re now company merged. Company C.

And I demand that when I go to your website, it looks like a single company, and you can’t get there because these two content creation systems are just not talking to each other. Now, having said that, when I say A and B and two content creation systems, what’s actually far more common is that it’s more like five to eight. It was two companies, maybe it was three companies.

CC: Wow.

SO: But five to eight systems that simply do not talk to each other in any way, shape, or form. Happens all the time because old company A, they had a different merger five years ago and they never did the work. And so they’ve never pruned and it just piles up.

CC: So it just piles up.

SO: And you get this just, it’s technical debt to a certain extent. It’s content rot. You can call it whatever you want, but it’s a mess. Inside of that, it doesn’t require multiple systems, but duplication and redundancy of content. Content is expensive to develop, expensive to manage, and expensive to translate well. And so it’s not good to have multiple copies of the same thing. And it’s especially not good to have multiple copies of the same thing that say two slightly different things for no reason. Happens all the time. So scalability, systems incompatibility, which then blocks you on the things you need to do with your content flowing back and forth, and duplication, redundancy. Those are three things where it’s actually pretty easy to get a hard return on investment.

Some really solid numbers that show if we clean this up, things will be better. In addition to that, we’re seeing a lot of demands now for content integration. The E-Learning or training group is sourcing content from tech docs. They can’t do it well because their learning management system and the tech docs content management system refused to talk to each other, but they really do need to integrate that, and then they need to flow it over and link it to marketing content. And it can’t be done because all these systems hate each other. That’s becoming a big issue. And there’s some really interesting solutions coming on that, but that’s where we are with this. So if you’re looking at those first three issues, if you’re looking at formatting automation, scalability, content creation, duplication, we actually have a calculator for that on our website that lets you get at least a first cut at what this is going to look like.

CC: Great. And we’ll go ahead and have that in the show notes as well. So why content strategy?

SO: It is of course an overloaded term. I look at it as thinking about how you manage information across the lifecycle within an organization. How do you create, how do you edit, review, approve governance, which I know is a dirty word, but when you create content, typically you have to delete it at some point. For the most part, it doesn’t live forever. Some content does live forever and explicitly needs to live forever. But how do you do that? How do you first make sure you have the right information in a given piece of content, and then how do you get it where it needs to go and manage it and update it and translate it and foster it throughout the entire life cycle? So content strategy to me is the overarching plan. And it’s the people, the processes and the technology that you use within that plan to do the things you need to do. So you’ve got your business needs, business requirements, and then the content strategy that provides the solution or the plan that gets you to meeting those requirements.

CC: So when and why should someone, any of our listeners, when do they know it’s time to contact us?

SO: Well, everybody should totally call us immediately. Everyone. No. I would say it this way. If you are in a situation where it is pretty obvious to you sitting inside your organization that the current approach is not sustainable, you can’t hire the people, you can’t scale up because you just have to keep adding people because you have all these terrible processes that take up too much time. You have too many manual workarounds, too much copy it over here and then paste it over here and then spend hours and hours reformatting it to get it into wherever, that kind of thing. If you’re frantically running in place just to keep up or even not able to keep up, it might be time to take a look at whether better systems, better, more mature content life cycle, better, more mature content strategy can get you to where you need to go.

And I would say that in the big picture, people call us when they reach the point where they look at this idea of doing some sort of a transformation on their content and… Because it’s going to be painful. I’m not going to tell you, it’s going to be painful. The fear of doing that is less than the pain of staying where you are. And we’ve done a lot of these projects and we’ve done all sorts of fun, successful things, but ultimately people stay with what they have almost always too long because it’s comfortable. We all do this. I’m not pointing fingers at anybody other than maybe myself, but we all do this. We’re like, no, this is good enough. And then at some point you realize that you passed okay and good enough two years ago, and it is time. And that is the point at which you should probably reach out to us.

CC: That’s great. Well, thank you so much Sarah, and thank you all for listening to the Content Strategy Expert Podcast brought to you by Scriptorium. If you want more information, visit scriptorium.com or check out the show notes for relevant links. And we’ll see you next time.

SO: Thank you, Christine. Welcome aboard.

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In episode 134 of The Content Strategy Experts Podcast, Sarah O’Keefe and guest Jodi Shimp talk about the role of content strategy in UX teams.

Related links:

Jodi Shimp, Global Content Strategy

LinkedIn:

Sarah O’Keefe
Jodi Shimp

Transcript:

Sarah O’Keefe: Welcome to the Content Strategy Experts Podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize and distribute content in an efficient way.

In this episode, we talk about content strategy as a part of UX teams with special guest Jodi Shimp.

Hi everyone, I’m Sarah O’Keefe. Welcome to the Content Strategy Experts Podcast, Jodi.

Jodi Shimp: Hi. Thanks for having me.

SO: I am so glad to see you and/or hear from you. So for those of you who don’t know, Jodi and I worked together for many, many years on a lengthy project, and at one point, she introduced me into a big meeting as her content therapist, and I guess this is my revenge. So today we’re here to talk about content strategy and what the role of content strategy is in UX teams. And Jodi, what brought you into this? What’s your interest in this topic?

JS: Yeah, so I spent those many years working on that project with you, but a lot of years developing and leading content strategy from the ground up for a large manufacturing business, and even as part of product interfaces, and then I switched over to join Wayfair as part of their customer-facing content-strategy team. And by that, that team was responsible for the UX content for all five Wayfair brands in all locales.

So although we worked with branding and merchandising teams and content ops and a lot of different groups, we were really primarily part of the experience design team, along with product designers and user researchers. It was a real change from content strategy work when we’re talking about all the levels of structure and meta, and all of the different things that you think of with content strategy, and it was a big departure from working on physical products. So there was a really fast learning curve necessary for that.

SO: So what was the biggest difference? You came out of producing physical products, which by the way is pretty hard to say, and moved over to a digital product company. And from a content strategy point of view, from that lens into the organization, what happened? How was it different?

JS: Yeah, so coming from the physical product side where I had also built content strategy as a function from the ground up, and working with a product that requires a longer lead-time and a longer development time, and moving over to digital where things move very, very quickly, working with a lot of very intelligent people who have created things in a very fast-moving environment that changes super quickly, it was a lot harder to put the wheels on that vehicle as it’s moving forward at a really quick pace than it was in the physical product world that I had been used to before. Even though that had also been accelerating because of more and more content on the product itself in the form of digital displays, it was nowhere near the same speed as the technology companies move.

SO: So you come into a digital product moving at the speed of, I guess, electrons, and into an experience-design team. So I guess foundationally, I keep asking this question, how is UX different from content strategy? And also, please tell me the difference between content strategy and content design.

JS: Yeah, so I think that’s a blurry thing that maybe nobody knows the answer to quite yet, but I can frame it up in how I’ve been seeing things develop specifically at Wayfair, and talking with different content strategists that are at companies like Amazon and Spotify and Shopify and all of those.

So content strategy as a terminology is really starting to become something that people think of marketing as in the technology world. So they’re thinking of those marketing teams, because of marketing content strategy and whatnot. And then there’s the UX content strategy. We’re often starting to hear more content design in that, and I think that’s because those content strategists in UX design teams are often part of experience-design teams. So they sit with the product designers and the user researchers and work side by side with them in these user-experience-design teams.

So that’s starting to be called more commonly content design. But I’ve also seen it still called content strategy, as it was Wayfair. And some places it’s content strategy, some places it’s content design, and sometimes I think they’re really being seen interchangeably still. But I’m starting to see a little more definition between the two.

And then I still think of content strategy as an overall, more talking about that structure and adding the meta and making that smart content that it’s really able to be reused in different places, and it identifies itself of what it is and how it should be used and all of those things. So I hate to say that the lines are still really blurry, but I think they are.

And I think the other common thread that I’m still hearing, whether it’s at conferences like LavaCon or just talking to peers in other companies or on LinkedIn posts, is content strategists, content designers, UX writers, all feel like they spend a lot of their time explaining what they do to other people and trying to help people understand why they’re there and why it matters. Just because you can write in a particular language doesn’t mean that you really understand how to get a user from point A to point B in the most concise way, and most delightful way in a lot of situations, so they enjoy doing so and can do so effectively to accomplish the task that they’re trying to achieve.

SO: And it’s like you said. I mean, in a scenario where you have to say, “Oh, I’m a content strategist, but no, not that content strategist, I’m the other kind. No, not that kind, the other, other kind.” I mean, it’s just-

JS: Right.

SO: And we’re not even going to deal today, because we don’t have enough time, with the question of content engineering and content operations. We’re just going to put that aside and move on. I mean, we’re supposed to be content people, and we are super terrible at self-description, and we argue these terms for years.

JS: Yes. Yes. One of my most enjoyable things in joining that technology team was to the entire 180-person design team, I gave a presentation about what is content strategy and why does it matter to product design, and went through all of the pieces. Here’s why it matters. Here’s what we do. Here’s how we approach content. And we’re not just wordsmiths that come in at the end and make the words pretty, just like you product designers aren’t there just to make the interface pretty. It serves a function and a purpose to help a user achieve their end means. And I got, surprisingly, to me, a lot of feedback on that particular presentation from product designers and user researchers about how they now understood it.

And we also followed that for people who were interested in doing content workshops, content studios, where we took different product managers, user researchers and whatnot through the process of how we would think about content and how we would structure the content and why that matters and what it means in the long run for the content. So that was another effective way with those teams to help them understand the purpose of content strategy in design teams, and we had a lot of success with that over a longer period of time.

SO: So you’ve mentioned content designers, content strategists, user researchers and product designers, I think. And so what did that look like? So you’d have, I guess, an experience-design team that had those four contributors, and then what?

JS: Experience-design team works in a lot of technology companies as part of atomic teams, or sometimes called four-in-a-box model. And that four-in-a-box model really means user-experience design, which includes the groups or the individuals that you talked about. It also includes product owners or product managers, and back-end engineers and front-end software developers.

So the goal is that they’re working in an agile environment on specific features or digital products to, from start to finish, create new or revise existing product features or products together. And the goal is that they’re there from start to finish so that everybody’s working in lockstep and having different review points throughout that development so that what is designed by the user-experience-design team is actually what’s created at the end and tested and then published, released, for the end user, whomever that end user is.

And sometimes, that is super effective. Most of the time, it’s super effective. But there are a few drawbacks that I noticed, being in those technology teams. One of those is, because you have each of these individual atomic teams working on features, it can be really difficult for those teams to connect with other atomic teams.

And so as content strategists, we’re often really concerned with, “Okay, how does somebody get to this feature? Where are they going after they leave this feature?” Because a user might experience multiple features over the course of accomplishing one task: deciding what they want to buy, being inspired, looking through choices, all the way through that end checkout, and then maybe coming back. “Where’s my box? Where is the thing that I ordered?” three weeks later when it still hasn’t shown up, or things like that.

So as content strategists, we want to connect all those different groups together, but the atomic team wants to move fast and quickly, and sometimes that makes them separate from the other groups so that each can move independently and quickly. So there’s positive things to that model, and then there’s some drawbacks too for content strategists, and I’m sure the other teams as well, but especially for content strategists.

SO: You talked about the speed, the velocity at which you’re working in an organization like this. We haven’t talked about whether that’s a positive or a negative, but we’ll just say it was faster. But was there anything that you really missed coming from physical product that was different that wasn’t there, that you’re sitting there thinking, “Ugh, we used to have this and I don’t have it any more”? Was there anything like that? I’m curious about the difference.

JS: So I’ll start with the reverse of that, actually. The thing that I did really like about digital products is you have a lot different opportunity to iterate on ideas and introduce gradual improvements, where with a physical product, once you’ve released the physical product, apart from the actual user interface, it can be really difficult to make incremental improvements, and expensive to make incremental improvements.

So I think that is a thing that I actually enjoyed, was that opportunity to go from a true MVP product that can be released and then incrementally improved, where when you put an MVP physical product out there, there’s more risk in that, I think, and you can’t go back and, “Hey, I’m going to install this new feature on your car because we think it’s cool, so we’re going to add a new button,” after someone’s already purchased it, where with the digital products you can.

But the negative was not having that hands-on piece through the development where you’ve seen a 3D-printed model or the mock-ups and you’ve compared hand in hand, one beside the other. You’ve got A/B testing in digital and other user-testing opportunities where you can mock the different ones up in a digital environment. But it felt very different from the physical progression, to me, than the digital progression.

SO: That’s interesting. What about localization? I know that you had a heavy emphasis on localization in your former life, and what did that look like in this digital product world?

JS: Yeah, so localization’s my pet favorite thing to have around. I don’t know why, but it really is. So I look at every product, whether it’s physical or digital, through that lens of localization, and I’m constantly asking myself, whether it’s something that I have anything to do with production or not, “But how would that work if you put it in a different environment?”

And there’s some things that work great if you put them in a different environment. My blow dryer is one that doesn’t work great if you put it in a different environment. I’ve probably burned up a more than one hair dryer trying to use them in the wrong environment. But those are the sorts of things where that’s my lens always.

So in the technology teams, in the UX design teams, working for a company that did not do a ton of localization beforehand, that was probably… And originally the reason that I joined Wayfair was to work on localization and really help guide that map and create playbooks: how do we do this better?

So there was a lot of education, and one of the biggest things that I took away as a positive from Wayfair was a really cool look at what software engineers could do with localization, and having software-localization engineers on those teams, how cool that was, because I had always relied on outside vendors to do any of that before. But now you have software engineers who are creating APIs right into the work-stream of how to translate content right there.

So they’re building and testing and playing with machine translation engines. They’re building a platform, an interface, that takes whatever we feed it from whichever software within Wayfair, and then that can feed that out to the localization providers or a CAT tool or whatever that needs to be, an interface there. So that was really cool working with those localization teams.

But I did find the same similarities that I’ve seen in other industries, where a lot of the localization problems, they get blamed on the translators; they get blamed on that localization team. And they’re really problems of the source content, whether it’s problems because it wasn’t written succinctly and clearly, or if it’s problems because they didn’t think about the fact the expansion was necessary and the same words won’t fit in the same space when you translate from English to German. So lots of education back to those source-content teams and the source software-engineering teams to learn how to handle localization libraries for metric units and things like that. So translation problems often start at the source, and I found that to be the same whether it was digital or physical, the source.

SO: I just remember that incident, which I think you know about as well, where we were looking at a particular translation and the feedback came back, “Ugh. The Spanish translation is terrible.” They used five different terms for brake-pedal or some word or phrase that should be a single word. And they were like, “This is a terrible vendor. They used five different terms for this word, and we need a new vendor and localization is bad,” and et cetera. And then we went back and we looked at the original English source, and what we discovered was that in the English source, they used eight different terms for brake-pedal.

JS: Yes.

SO: And the localization team, or the linguist, had actually gotten it down to five, which was a big improvement.

JS: So much.

SO: And they were still getting yelled at for being bad and not getting it down to one. It is true that it should be one; it’s just that it wasn’t one in the source, which is where the problem originated, and they were getting blamed for not magically inferring that these eight different terms were actually a single thing, which seemed a bit unfair.

JS: Yes. It is unfair, and that’s why one of my… Well, actually at both the big companies that I’ve led, this type of thing, terminology-management program, is one of the most critical elements. And as machine translation becomes a greater part of localization, really it’s going to be for everyone, I think 50% of translations for customer-facing products are coming from machine translation at this point. And that’s pure machine translation. That doesn’t even include machine translation with post-editing. For companies to manage terminology well, whether they’re physical products or digital products, it doesn’t matter, that terminology is critical to having well-translated products, as with all the other content.

SO: And presumably it’s only going to rise.

JS: Exactly, because I hear a lot more already company leaders saying, “We can translate, so we should,” where in the past, when it was much more expensive and much slower, and machine translation wasn’t an option, you’re very, very specific about which content gets translated. And now the expectation is becoming that everything should be translated, so how are we going to do that effectively?

And a lot of the localization aligns with accessibility. If you make it so the source content is written well and well structured, and that metadata is there, then accessibility requirements serve everyone better, whether you need the specific accessibility adjustments or not. And the localization requirements drive the same thing. It’s talking in simple language. It’s talking in consistent terminology, consistent structure, that makes localization smoother too.

SO: Well, that seems like a perfect place to close this out: with a call to make your source content better and more accessible so that people can use it better, or we can translate it better, and/or it can be more effective out there in the world. So Jodi, thank you for coming in and sharing some of your hard-earned wisdom with us.

JS: Well, thank you for having me. It’s been a pleasure, as always.

SO: Yeah, it’s great to see you. And thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

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In episode 133 of The Content Strategy Experts Podcast, Sarah O’Keefe and guest Carrie Hane of Sanity talk about headless CMSs.

If your organization isn’t already going down this route, it will probably go there soon. Whenever it’s time to get a new CMS or change hosts. It’s usually triggered on the IT side to switch to it. But like I said, the developers love the flexibility and ease of this decoupled tool. Yeah, it’s really technology driven, but it’s a real opportunity for everyone in an organization to rethink how they’re creating and using content.

—Carrie Hane

Related links:

Sanity

LinkedIn:

Sarah O’Keefe
Carrie Hane

Transcript:

Sarah O’Keefe: Welcome to the Content Strategy Experts Podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about Headless CMSs with Carrie Hane. Hi everyone, I’m Sarah O’Keefe. I’m here with Carrie Hane from Sanity. Carrie, welcome.

Carrie Hane: Hey, Sarah, good to see you.

SO: You too. Tell us a little bit about your background and what you’re doing these days at Sanity.

CH: Yeah, well, my background. For longer than I would like to admit, I’ve been working in-

SO: I know what you’re talking about.

CH: … web and content strategy and helping organizations use technology to better serve the people they’re serving. Obviously the web exploded in the late nineties, and that’s where I started. And so I’ve been able to learn from really smart people, lots of mistakes, and finally get to a point where I guess I’m considered an expert. Five years ago, I co-authored the book, Design and Connected Content, that really laid out a framework for developing future friendly digital products, which includes websites but isn’t exclusive to websites. And then last year I started at Sanity, headless content platform as Principal Evangelist. Now my work involves helping people understand structured content, the value, how to use it, what value it has, and how they can make their lives easier by using technology to support their work, no matter who they are.

SO: Tell us a little bit about headless CMSs. What is a headless CMS specifically?

CH: Technically, it’s a content management system that separates where the content is stored, which is the body and where it’s presented, which is the head. You can store your content in a headless CMS and then send it to any display anywhere. Yes, it’s a website. It could also be an app, it could also be voice assistance. It’s Google, everybody sends their information to Google whether they know it or not. It’s all of those things. It’s a future friendly way to think about plan and store and create your content for whatever comes next.

SO: When you differentiate between a headless CMS and I guess a head on CMS, but I suppose generically, we’re talking about web CMS versus headless is kind of how this breaks down. Although I guess technically headless CMSs are a subset of web CMSs or something like that. But what makes the headless CMS special? What’s the main point of differentiation between, we’ll call it traditional web CMS and headless?

CH: Well, a few things. For content creators, it allows us to really embrace the create once, publish everywhere, the cope framework of working. Whereas in a traditional, monolith web CMS, we could only ever create content for one website and that website only. We would have to create another instance if we wanted that same content to go to an app or to go somewhere else, so those different heads. It lowers the amount of content that we need to create and maintain, kind of future proofs our content because it’s not tied to any specific presentation. Then even if we are only using it for one website, we can reorganize the content because it’s not tied to a certain site map. Or we can redesign the website without having to redo all the content. That is, if your content is good in the first place, which is a wholly separate thing, which we will have to have another podcast about.

In that sense, it kind of lives up to a promise I think a lot of us have been expecting for a long time. On the technical side, it helps technologists create more componentized ecosystems, so that no matter what the latest trend is in front end frameworks or processing or hosts or whatever, I don’t even know all the terms for all of the things that IT needs to be thinking about now, but that tech stack is no longer all tied into one product or one suite. It can now use the best in breed of whatever is needed, so it’s future friendly in that way as well.

SO: Who’s the target audience for this? Who’s adopting headless CMSs, and what are some of the justifications for that? You’ve touched on a few things already, I think.

CH: Yeah. Well, honestly, organizations of all types and sizes are adopting headless CMS. I just saw this week we were talking about it among my colleagues, that the size of the market of headless CMSs is expected to more than double by 2030, which is only seven years away, by the way.

SO: That’s not helpful.

CH: If your organization isn’t already going down this route, it will probably go there soon. Whenever it’s time to get a new CMS or change hosts or, I don’t know what else. There’s a lot of things, it’s usually triggered on the IT side to switch to it. But like I said, the developers love the flexibility and ease of this decoupled tool. Yeah, it’s really technology driven, but it’s a real opportunity for everyone in an organization to rethink how they’re creating and using content.

SO: What does it look like to implement, to make that transition over to headless CMs, assuming that you’ve started in, I hesitate to say traditional web CMS, because that’s ridiculous, but here we are.

CH: It looks different for every organization. I think one of the things that can happen when you make this switch is a complete digital transformation. Organizations who are committed to going through digital transformation, are really completely changing how they’re approaching their digital experience. Other groups are like, “We need a new CMS, a new something yesterday,” so they literally just recreate what they have in whatever tool that they buy, just reconfigure the connections, but all the content goes over in whatever way it was.

The design looks the same, they might even have the same underlying CSS in frameworks, so it really varies from that. Going from exactly what you have now to a new tech stack or completely changing everything. And then obviously lots of things in between. But yeah, it’s an interesting time to be watching all of this because it is accelerating. I remember first hearing about headless, maybe 10 years ago, and now I don’t know how you can work in the content management world and not hear about it and not be thinking about it.

SO: I know a lot of the people listening to this podcast, and certainly my side of the world is sitting largely in XML, DITA and technical and product content world. What you’re describing to a certain extent when you talk about multichannel publishing and separating content and formatting, kind of sounds like XML based publishing and kind of sounds like DITA specific… Well DITAs obviously an implementation of that. I guess then the question I have to ask is, is a DITA component content management system actually a headless CMS?

CH: I suppose technically because it’s a body that’s separate from the head, I don’t really have any experience with DITA CCMSs, so I don’t know more. What I associate that with is technical communications, which is only in my mind, one use case for any of these systems. I don’t know, have you seen other use cases? What are your thoughts and what are you seeing?

SO: Well, there are other use cases, and we have some customers that are using XML structured content and specifically DITA outside the core tech pubs, tech com world. But ultimately, when I look at these two, I would say the DITA world, the DITA XML world is optimized for a certain kind of content type. And what you’re describing with headless is a lot of the same principles, but it’s not specifically optimized or built around a framework that is designed for technical content specifically. It’s almost like the DITA CCMS world is the specialized… Sorry, people that was not really intended to be a terrible pun. But is sort the solution that’s intended for a specific industry or a specific use case, we’ll say. Whereas the headless approach, or when we talk about headless CMSs, we’re talking about something that is intended for more of a general purpose solution. I guess it’s a subset. Is that fair?

CH: Yeah, I think-

SO: Sorry, headless is the super set and DITA PCMs would be the subset. And I guess the other important note is that although it’s not required, DITA and XML are based on a sort of a tree view of a document, similar to HTML. And the headless CMSs as a general rule, are built on knowledge graphs, which are less of a tree and more of a multidimensional thing that’s hard to conceptualize.

CH: Yeah, a graph.

SO: Yeah. The knowledge graph. And the really sad thing about knowledge graphs is that I saw those for the first time about 20 or 25 years ago when we had things like information models and entity relationship diagrams in some of the software that I was supporting. What do you see as some of the biggest challenges, as we talk about this concept of moving websites or web content or content outside of tech com might be the fairest way of saying it, into this headless approach. What are the biggest challenges that you see there?

CH: I think the biggest challenge is the content creation world. The content strategy world is not ready for that. And not because people don’t get it, it’s because they don’t even know what they don’t know. Most organizations are not mature enough in their content operations to really take advantage of a headless CMS. And so the danger becomes the tech. IT moves them there because they need it for their tech ecosystem. And then they’re given the keys. I’ve heard some people say they’re given the keys to a Lamborghini and they don’t even have their driver’s license yet.

I hear a lot of people say, “I don’t like headless. I don’t like that,” because they’re disoriented. It’s not what they’re used to. It’s set up completely different. And so then they blame this technology for a problem that’s not the technology’s fault. And then what will happen? Will we go backwards? Probably not. But it’s going to take a lot for the whole… I think it’s even bigger than a market, the whole world really. We’re all moving or moved to digital first publishing, and what isn’t digital these days. And we’re still in this old mindset of print analogies, print whatever, and haven’t thought of new ways of approaching how we can create and publish information. And I think headless is a big opportunity and it’s potentially a jumping off for a new era in publishing, but we’re not going there fast.

SO: What you’re describing sounds exactly like the pain we went through in trying to move people from a word processor, style based mindset, to a structured content, separation of content and formatting mindset. And I’m not saying we’re done and it’s been super painful and the change management issues have been extensive. If it’s going to be pain and there’s going to be all this change and change resistance and all the rest of it, what are some of the opportunities? What makes it a worthwhile change?

CH: It opens the door to doing more fun stuff because it can reduce the amount of content you’re creating and maintaining. People who create content can get out of the business of constantly reacting and putting out fires and move to being more proactive and creative and thinking about these new ways to reach their audience, connect with their audience, and instead of constantly trying to keep up. As people who work within organizations or with organizations are so far behind actual people, the consumers out there who want new things and new ways of interacting with things. And I think we’re on the cusp of that. I’m not saying headless is the end goal, but I think it’s a good jumping off point for trying out new things and getting our houses in order enough, so that we can then move forward instead of being on a treadmill and trying to keep reaching for a different goal that just keeps staying the same distance away.

SO: That seems like a good place to leave it. We are going to attempt to get off the treadmill and onto the, I don’t know, the ski slope, maybe a little bunny slope.

CH: The trail.

SO: The trail. That metaphor did not work at all, but we will hop off the treadmill onto an undisclosed other means of transportation that is actually going to advance us forward. And Carrie, thank you for coming in and talking about this, because I think this is, at this point, a topic that’s not well understood and we need more people out there to explain it and explain where this is going.

CH: Yeah. Well thanks for having me. It’s always fun to chat.

SO: Yeah. And we’ll do some more of that in 2023. That’s a truly terrifying thought. And with that, thank you for listening to the Content Strategy Experts Podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

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In episode 108 of The Content Strategy Experts podcast, Alan Pringle and Gretyl Kinsey kick off an occasional series about stakeholders and content operations projects. In this episode, they talk about IT groups as an important stakeholder in your content operations.

“The IT department can be such a great ally on a content ops project. IT folks are generally very good at spotting redundancies and inefficiencies. They’re going to be the ones to help whittle that redundancy down.”

– Alan Pringle

Related posts:

Scriptorium’s Content Ops Manifesto
Content operations (content ops)

Twitter handles:

@alanpringle
@gretylkinsey

Transcript:

Alan Pringle: Welcome to The Content Strategy Experts podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about IT groups as an important stakeholder in your content operations. Hi, I’m Alan Pringle.

Gretyl Kinsey: And I’m Gretyl Kinsey.

AP: In this episode, we’re going to kick off an occasional series about stakeholders and content operations projects. And yes, even though content is the primary umbrella, primary objective on a content operations project, there’s still many stakeholders from all across an organization that are going to be involved, so it’s not just about the content creators and the people authoring content. What are some of the other ways that stakeholders come into play, Gretyl, on a project?

GK: Well, a lot of times there will be the most important stakeholder, which is your executive champion, who is in charge of the money and the resources to actually get your project approved and get it started, so that’s always someone that we make very definite sure to talk to when we get involved in content operations. You might also have developers or engineers who are working on the product itself. And of course, as we’re going to be talking about today, you might have IT, information technology, a department that’s in charge of managing your tools and your processes. So all of these other groups, even if they don’t directly create content themselves, they definitely have an important stake in it, and they need to be part of the decision making processes.

AP: I agree. It essentially takes a village to get one of these projects done, so it’s really good to have an understanding of other people’s responsibilities in the organization and to get their viewpoints and feedback to be sure that your content ops project is going to be successful.

GK: Absolutely. So as Alan said, we want to start this series by focusing on information technology or IT departments. And that’s because they are significant stakeholders in content projects. We’ve had a lot of times in the past with projects that Scriptorium has been involved in where it was actually the IT department who came to us first and who initiated the entire content strategy overhaul.

AP: Absolutely. And that’s an important thing to note. A lot of people may assume, just because it’s a content project, that we’re going to be contacted by the people authoring that content. And in multiple cases, that has not been the case at all. We have had people contact us who were much more into the tools and tool management and information technology side of a company who didn’t create content at all, yet it was still part of their responsibility because they’re the ones overseeing the tool chains and some of the processes for those groups, content creating groups.

AP: And speaking of those content creating groups, I think it is fair to say in our years of doing this, Gretyl, that we have seen a lot of content folks who had some gripes about IT groups. And then the IT people had their own stories about the content creating people. So there’s a lot of that going on, and we could spend how many podcasts on that topic, but I don’t think it’s that interesting. What we want to focus on instead is really how the IT department can be such a great ally on a content ops project. And they really have some skills and viewpoints and access that are absolutely necessary to get things running and to work well.

AP: And one of the first things that I can think of in regard to that general skillset is that IT folks are generally very good at spotting redundancies and inefficiencies. And that kind of makes sense because if they are managing the infrastructure of tools, they’re going to be very sensitive about, for example, if you have multiple tools doing the same exact thing within an organization, especially after say a merger, where you’ve got two different companies coming together, and you’re going to have all these layers of tools doing the same thing. They’re going to be the ones to help whittle that repetition, that redundancy down.

GK: Yeah, of course. I know one of the earliest projects that I was involved in that had IT coming to us as the primary stakeholder who was interested had actually spotted not only kind of these redundancies or inefficiencies in what tools they had, but also in how people were using them. So they kind of had a little bit more insight into how content creators were kind of doing a lot of manual processes with these tools that they had in place that could’ve been something more automated, how they were spending a lot of time on these things that really they knew of much more efficient ways to handle them just by nature of being in IT and seeing other departments kind of handle those processes more efficiently. So that’s definitely a good thing that they kind of have this broader view of what tools should be in place, what the kind of overlaps are, if there are any, and how they can get those out so that you could have a much more efficient way of using the tools that you have in place.

GK: And I think that kind of leads into another strength of IT departments, which is that they tend to have a sort of more broad, or company wide, or enterprise level view of the organization. And that’s just because of the way that they manage tools across departments. They can really kind of have that bigger picture of how they’re being used.

AP: Absolutely. And that perspective is sort of like when you bring in a consultant like us. We bring in a third party view because we’re not so close to it. We can give objective advice on how things are set up, how they’re running. And the IT group can do something very similar. They’re not in there day to day using the tools, authoring, or whatever. They’re a step back, so they’ve got more of a bird’s eye view, and that can be very, very helpful, like you mentioned, in spotting these redundancies.

AP: I think another thing worth pointing out is these folks usually have programming chops. And they have the skillsets to customize things, and they’re not scared to do so. A lot of times, to get maximum use out of your content strategy plan to be sure it’s working the best, it may require some very particular configuration, connections between tools, et cetera. And when you’ve got an IT group that’s savvy at those things, that is a huge, huge benefit to you and your content project.

GK: Absolutely. I really can’t think of a case that I’ve ever seen where one single tool did everything that an organization needed out of the box. And I think that’s true the more tools that you get in your tool chain, you are going to need some sort of custom configuration most of the time. And so when you’ve got an IT department who is really involved in the overall content strategy, they can help you see what exactly are the customizations that you’re going to need. They can be a really valuable asset to your content department in making sure that those customizations are done. And so again, that’s why it’s just really important to involve them from the outset before you really even get into the process of choosing what those tools are going to be. They can help you make the decisions about what customization might be involved based on what you choose.

AP: And I think it’s worth acknowledging that making those customizations does cost money. And when you’re doing your content strategy planing for how you want your content ops to go, looking at return on investment is going to be a big part of that assessment, so getting that feedback and input for what it’s going to cost to stand up these customizations, these configurations, is very important because you need that information to figure out essentially how long it’s going to take you with improved efficiency or whatever, to basically recoup those costs. So yes, customization is a great thing, but you need to have the clear understanding fairly early on about the kind of cost projections to get that work done and how you’re going to get that money back and then make more gains beyond that to make it worth everyone’s while to do that customization.

GK: Absolutely.

AP: We’ve kind of already touched on this, but let’s take a little time to talk about the kind of functions that an IT group is going to handle, contribute to, in content operations projects, or even the content strategy planning that precedes it. What are some of the things that come to your mind, Gretyl?

GK: So one of the first ones that comes to mind right off the bat based on what we just talked about is enterprise architecture. And that’s because like we said before, IT has that kind of big picture, bird’s eye view of all of the tool chains across the organization. So when it comes to developing your information architecture for content, particularly at the enterprise level, thinking about not just one type of content and one department, but all of your content across an organization, IT can really be helpful in figuring out what your strategy is going to be for that enterprise level information architecture.

AP: And speaking of enterprise, the more organizations move into the content as a service model, where basically it’s less about delivering a PDF, or a help set, or a marketing slick, or whatever, it’s more about giving the end user whatever kind of content they want in the specific format they want it, when they want it. That really requires a lot of connectivity. It requires a lot of understanding of the entire tool chain and how everything is connected within the enterprise. And the more we move to that content as a service CaaS model, the more critical I think IT is going to become in these sorts of projects.

GK: I agree. I think we’re seeing a lot more demand for Content as a Service for custom, personalized delivery for on-demand content. So I agree absolutely that IT is going to be playing I think an even bigger role as more of these kinds of projects are undertaken.

AP: Something else that I think that really falls into their wheelhouse is to help with evaluating new tools that you’re going to need to develop, manage, and distribute your content. If you’re doing, for example, a new content management system, you’re probably going to set up some proofs of concept with a vendor or two and get that set up and running. And it would behoove you to get some input from IT about how those tools are set up and how efficient and how well they work, also to do security checks. I think a lot of tools now are more in the cloud. Less and less, we’re seeing companies deploy tools on premise on their own servers. Instead, they use cloud based tools. Even so, security is still a concern. And that is something that they need to be part of. How you stand those tools up, how good the security is, all those kinds of things that you want to look at in a proof of concept, that definitely needs the input from your IT people.

GK: Yes, absolutely. And as consultants, we’ve been involved in that process of the demonstrations and the kind of questioning of the vendors with regard to choosing what tools you want. And there have been some of those times where IT was heavily involved. They helped come up with a lot of the information, a lot of the feedback, a lot of the things that were asked of those vendors during that demonstration and kind of testing process. And then we have had other projects where sometimes tools were chosen, and then later the company came back and said, “We should’ve had IT involved and we didn’t, and that was a mistake because we’re seeing that we might’ve made a wrong choice here. We didn’t evaluate this one particular aspect that was really important.” So definitely when you are looking at tool options, especially if you’re choosing more than one tool, so if you’re looking at maybe a CCMS and an LMS, that you would really want to have IT involved to help make those decisions and make sure that everything is going to work together as you intended to.

AP: Right. And once again, I go back to the whole enterprise level viewpoint, the connectivity among these systems. You cannot have blinders on and pick a tool that suits just your purpose. It has to fit in the bigger ecosystem you have for tools. Otherwise, everybody’s going to have their own little tool communities, and that’s just a mess that you don’t want, and frankly, an IT department probably is not going to tolerate very well.

GK: Yeah, exactly. And that’s a really great point because it leads us to the next kind of thing on our list of how IT can help with a content project, which is that they are really good at making those connections among disparate departmental content and data sources. So if you have a situation where you’ve got, let’s say, technical content, training content, marketing content, and all that needs to be connected and you don’t really have the infrastructure for that, IT is going to be your number one resource to make sure that can happen.

AP: Right. And I think one other thing that kind of puts a bow around all this is content governance. And I know you’ve talked a lot about that, so I’m going to kind of let you take that on because that’s been a topic I know that you’ve written about and talked about on the podcast previously.

GK: Yeah, sure. So content governance is what happens when you need to have someone in charge of overseeing all of your content processes and the changes to those processes over time, the evolution of those processes. And again, this is a place where it’s very important to have IT involved. A lot of times when we have had companies that we’ve worked with putting a governance strategy in place, it’s either been driven by IT or they’ve made sure to have someone from IT be part of whatever team of resources is in charge of content governance. And it all cuts back to what we’ve been saying, it’s because they have that viewpoint from the enterprise level. They’re the ones who are going to really know and understand how all of the parts of your content tool chain work with the content lifecycle. So when it comes to maintaining and governing and improving your processes, it’s imperative to have IT involved.

AP: Absolutely. And I think one of the last topics that I want to touch on before we wrap up are some final thoughts in regard to content ops projects, considerations that really feed into IT and having their participation. And the first one that I think really comes up is authoring tools. One thing that I have really learned over the past few years is when it comes to authoring content, it is very much not a one size fits all situation for the tools used to create content. There are absolutely legitimate reasons to have different types of tools for authoring content, even if they feed into the same repository or management system for the content.

AP: And a good example of that is sometimes you have part-time contributors on content projects, such as product engineers. Once in a while, they’ll go in and add some feedback, put in just a little bit of information. They do not want to deal with the overhead of a super duper professional strength authoring tool. They want to get in and get out very quickly with minimal overhead, minimal time spent on learning a tool. Whereas the people who are day-to-day creating content and that’s their full-time job, they’re going to want a lot more control, a lot more features, a lot more bells and whistles to get the content done and do the things they need to do that are a little more complex, for example, in regard to reuse, and get that done correctly, whereas the people who are part-time contributors probably don’t care as much about that because it’s being handled by the full-time content creators. So there is absolutely a valid reason to have different authoring tools. And it’s probably better not to force people’s hand to use just one tool because of some kind of perceived redundancy there.

GK: Yeah. And one thing I’ve seen IT help do with this in particular also is even if you do have the same authoring tool, there may be features that you can turn on or off for certain kinds of users. And so you could have different levels or different user roles, and IT is kind of in charge of managing which people are your power users, your ones who need all of the bells and whistles and all of the controls, which ones are maybe only in a review capacity, but not a content creation capacity, so they might need some different controls, which ones are just those kind of part-time occasional subject matter expert contributors. And that’s where it can again really be helpful to have IT involved to make sure that, whether they are using different tools altogether, or kind of different variations or access levels of the same tool, that everybody can do what they need and kind of not be forced into a bunch of features and things that they don’t need.

AP: Absolutely. And surprise, surprise, I think the last point we’re going to make is that a lot of times, very niche, very particular content tools may be required to get the best return on an investment for your project, like we talked about a little bit earlier. But you still have to balance the cost of those niche tools and configuring them and making any customizations against the overall cost of even just implementing and then maintaining those very specific tools down the road. So there’s got to be some ROI calculations done, and this is where IT I think will be very, very helpful in figuring out that return on investment.

GK: Yeah. Before you ever decide what your tools are going to be, IT can help you say, “Yes, this is going to get you everything you want, but it’s going to involve X many dollars or X much time for maintaining these customizations that are going to be involved for training people on how to use them,” really helping you think of all the different aspects that are going to be involved in using that tool. And they might be able to recommend something that gets you, let’s say only 90% of the way there instead of 100%, but you’re going to save so much cost for things like customizations and maintenance that maybe it balances that out. So it’s really helpful to have that perspective before you make your tool decisions.

AP: And that’s great advice and observation there, Gretyl. And I think we’re going to wrap up, so thank you very much.

GK: Thank you.

AP: Thank you for listening to The Content Strategy Experts podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

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In episode 107 of The Content Strategy Experts podcast, Bill Swallow and Gretyl Kinsey are back for another episode in our Content strategy pitfalls series. They talk about what can have happen when you lack a unified content strategy.

“One way to get funding in place is to start the conversation among different groups. Get these groups together and start talking about what their ultimate goals are with their content strategy and their content operations. That way you can have multiple voices coming together and asking for a larger pool of money that can be shared.”

– Bill Swallow

Related posts:

Content strategy pitfalls podcast: risk management
Content strategy pitfalls podcast: change management

Twitter handles:

@billswallow
@gretylkinsey

Transcript:

Bill Swallow: Welcome to The Content Strategy Experts podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we look at another content strategy pitfall, what can have happen when you lack a unified content strategy? Hi, everybody. I’m Bill Swallow.

Gretyl Kinsey: And I’m Gretyl Kinsey.

BS: So, before we jump into talking about what can happen when you lack a unified content strategy, we should probably start with explaining exactly what a unified content strategy is.

GK: Yeah. So, if you’ve listened to any of our podcasts before, looked at any information on Scriptorium’s blog, you might have also seen us refer to this as enterprise content strategy. So, what we mean by enterprise or unified content strategy is a plan for managing all of your content processes across the organization. And a lot of times that involves bringing all of your different content producing groups into alignment with each other.

BS: And as you can imagine, if everyone is working against a different strategy and doing different things, a lot of bad things can happen. One thing that we see right out of the gate when an organization does not have a unified content strategy, is that there are a lot of inconsistencies throughout the entire content chain, from authoring the content all the way through to the customer experience on the final destination of that content.

GK: Yeah, absolutely. A lot of times this happens, because not everybody in the organization places the same amount of value on content. I know one example that I’ve seen of this might be something like, an executive sees a lot of value from something like the marketing content, because that’s directly making sales. But they don’t realize maybe the importance or the value that other kinds of content like your technical documentation, your training modules, maybe your legal materials might have. So, those groups maybe don’t get as much funding, as many resources, as much invested into them. And then you end up with this inconsistency, with this lack of cohesion among the different content producing groups, just because there wasn’t really value placed on content as a whole.

BS: And we also can see this within even what we consider a traditional content group. So, for technical documentation, a lot of times you will have user focused guides and user focused content, and you will also have deep technical content, perhaps API references and so forth. And oftentimes, we even see several different strategies being used for these various sub-components of what we would refer to as the umbrella of technical documentation. And even in those cases, you can start seeing a lot of dissonance between how the content is being authored, how it’s being produced, and how it’s being received.

GK: Yeah, no matter whether you have these subgroups that you’re talking about or your larger content producing departments. Another issue that we see is that these different groups may come up with different content strategies separately. When you’ve got all of these different ideas and these different ways of work trying to come together for the first time, you can have a lot of issues like change resistance. You can have egos coming in and you can have a lot of debate over what approach is the best approach. And so, that’s why, whenever we talk about a unified content strategy, it’s oftentimes easier to work on it from that perspective from the start, rather than trying to bring together a whole bunch of separate content strategies from different groups.

BS: And a lot of these inconsistencies and a lot of these mismatches that you might see as you try to combine two different strategies into one, could range from how people work when they author, it could be what tools they’re using and whether they’re even compatible together with other groups. It could be the tone and voice of the content that’s coming through and that there’s a stark difference between the two, and there’s no way to easily glue them together without it sounding completely bizarre to someone who’s reading it.

GK: Yeah, absolutely. And I think that’s an important point, because when you start having those inconsistencies, you reflect outward in the content to where they’re going to be affecting the way that somebody might use that content. If whether you are a customer who is trying to decide whether to buy a product or you’ve already bought your product, you’re trying to figure out how to use it. If the content is not consistent, if some of these issues from the way it’s been created are spilling over into the user experience, then that’s going to have a negative impact on your company. And so, that’s why I think what we said up front about the value of content is so important and you have to really think about that from all different angles.

BS: Right. And a lot of times any of these changes are going to come really with a significant cost. And a lot of times we look at the dollar signs or the price tag on the tools involved in being able to swap tools and migrate content over into a new system. But sometimes that’s not even the largest cost we’re talking about. If there are workflow changes that need to happen within a company, that usually means not only changing what that process looks like, but training everybody up on using it correctly. It probably involves a completely different way of authoring into some fashion. So, whether they are using different tools to author, there are different ways of going about producing that content.

BS: If the tone and voice needs to come to alignment, a lot of stuff needs to be rewritten. If there’s localization involved, then anything that has been translated previously is no longer a leveragable asset, in which case you’re starting from scratch with retranslating everything. So, it’s really important when you are defining your content strategies, that you take a look around and make sure that you’re not operating in a silo and potentially magnifying the cost of unification later.

GK: Yeah, absolutely. And one thing that you mentioned that got me thinking about another pitfall when it comes to that cost was you mentioned tools and process changes. And I think one pitfall that I’ve seen a lot of companies fall into is they make decisions about their tools or their process changes and purchase new tools without consulting everyone who might be affected by that decision. So, for example, let’s say that you have got an LMS at your company and you need to upgrade, and you only consult people in training and e-learning who use the LMS. And you don’t talk to other content groups who may share content, who may need to use some of the training materials as part of technical documentation, as part of marketing content, for example. And then when you purchase your new LMS, it affects those other groups and there’s that spillover.

GK: And we see this happen all the time. We see it happen with component content management systems. We see it happen with localization, where these kinds of tool decisions are made without really taking into account the unified content strategy and the effects. And I think when we’ve got those kinds of content silos, that’s where it’s more likely to happen because you don’t really think outside of your particular group.

BS: To that point, if one of the key factors in moving toward a unified content strategy is to be able to intelligently reuse content rather than copying and pasting, or what have you, the tools are really going to make or break that particular aspect of your content strategy. Because if one group is authoring in one particular tool that has a very specific file format or some kind of binary format, it is going to be near impossible to be able to get that content out and reusable as a single chunk of content. A lot of times it will either need to be copy and pasted or re-keyed or something to get it into another system to be able to use it. And that completely defeats the purpose of reuse.

GK: Yeah, absolutely. And I think this really speaks to why whenever, at Scriptorium, we come in and help companies with their content strategy is we often say tools should be the last thing you do. You need to come up with all of your goals, all of your specifications, all of the reasons why you’re buying that tool in the first place before you start looking at options. Because what happens when you make those decisions in the early part of that process is you don’t think of all the different factors. And then you end up either in a situation where you’re locked into using a tool that doesn’t really work for you or to get out of it. It’s going to be like Bill said, really expensive. There’s a lot of costs involved with these kinds of tools. So, rather than making an expensive mistake, it’s always better to take more time upfront, to work on the strategy itself and really understand what it is you’re looking to get out of those tools before you buy them.

BS: And with every strategy comes one particular item that is often overlooked when putting a content strategy together, and that’s content governance.

GK: Absolutely.

BS: And if everyone is doing different things with different tools and different ways and using different processes and different quality control checks, it is going to be very difficult to get any kind of overarching governance in place to be able to make sure that everyone is working as they should be throughout this process. The governance is going to be rather wide in scope. And the more differences you have between different teams working together, the more difficult it’s going to be, to be able to govern all the aspects of content creation across the enterprise.

GK: Yeah. I thought it was really interesting that you mentioned how governance is something that people don’t consider enough. I also have seen it be treated as an afterthought, when really it should be one of the most important parts of your content strategy. And I think when we have a situation where there’s a unified content strategy and that’s the goal, then people tend to consider governance as a greater part of it. But you’re right, Bill, that when we’ve got a situation where there are all of these different silos, all of these different tools and they don’t fit together into one streamlined content set of processes, then governance is just going to be herding cats. It’s going to be wrangling all of this mess that you’ve got, instead of truly moving your strategy in a better direction for the whole enterprise.

BS: Right. I mean, the governance angle really is speaking to a lot of the other pitfalls that we talked about. If there are multiple different tools in place, it’s very difficult to govern how those tools should work and at what point in the process that tool should have a handoff and what that quality check should look like. If you have many, many, many different strategies in place, regardless of whether you’re using the same tool or not, it’s very difficult to get those quality checks and get those points defined as to where you do certain reviews, where you do certain checks and balances. It will just exacerbate the problem of not being able to produce content that looks like it came from one organization with one voice, with one intent to its audience.

GK: Definitely. So, I want to close out by talking about one issue that’s at the root of all of these pitfalls, which is that oftentimes when we see this lack of unified content strategy, it tends to come down to a lack of funding or resources, or maybe unequal funding across different departments. And a lot of times that’s outside of their control. So, I want to talk about what companies can do to account for that limitation and how you can avoid some of those pitfalls, even if you’re dealing with a lack of funding or resources.

BS: So, one way to get this funding in place is to start that conversation among different groups, to talk to different groups that may have a different content strategy that is underway or that they’re using, or that they’re thinking about. Getting these groups to come together and start talking about what their ultimate goals are with their content strategy, with their content operations. And start pulling together those ideas, and being able to look at the tools that they’re using, for example, or that they plan to use in their new content operations and start pulling that together and making sure they’re compatible, if not identical. And that way you can have multiple voices coming together and asking for a larger pool of money that can be shared, rather than individual groups getting their own little pocket of cash to work with.

GK: Yeah, I think that’s absolutely critical, to make sure that you have that communication across departments. Another idea that I’ll suggest that might help, if you know that you’re going to be limited on funding, you know that you’re going to be limited on budget. At least one thing that you can do for now is once you’ve done what Bill has suggested, you’ve maybe gone to some other departments, you’ve talked about your content needs, start seeking out an executive champion. So, even if you can’t get the money immediately, even if you know it’s going to take time, the sooner that you can start planting that idea in someone’s head about why content is valuable, why it’s going to help to eventually get that funding in place, what it’s going to do for the organization, then the better your chances are of actually securing that.

GK: And one really, really solid way to do that is by gathering some metrics. So, what information can you actually provide to the executives about how much money that you are losing right now with inefficient or inconsistent content processes and how much you’ll save by fixing those? One thing that you might even consider doing is taking what limited funding you do have and conducting some sort of a pilot project or a study to just show here is what we’re thinking with regard to content strategy. We’ve talked it over with other groups, they want to buy into this too. And here is just a little bit of proof that we think it’s going to work. And if you can show some of that evidence, then I think that really helps to prove that value of content and maybe start to have the folks at the top who have the cash take it more seriously.

BS: Yeah. Showing that return on investment is critical, especially to gain an executive sponsor. Another thing to look at is not necessarily the cost savings that you have by working together and doing these things in unison, but it’s also looking at opening marketing or opening market opportunities for your organization. So, if you have been hindered by the way you work from entering into new business markets, or being able to broaden an offering to an existing business market, and your thoughts of having a unified content strategy can get you there, that return on investment will be much greater than the savings you’ll get from streamlining existing processes.

GK: Absolutely. And don’t forget to account for time as part of your savings as well, whether that is things like time to market, whether it’s time saved in your actual content workflow. Just remember to take into account all the other factors that can go toward the idea of return on investment aside from just strictly the cost savings.

BS: And I think that’s a good place to close it.

GK: Yeah. So, thank you so much.

BS: Yes, thank you all. And thank you for listening to The Content Strategy Experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

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In episode 106 of The Content Strategy Experts podcast, Gretyl Kinsey and Bob Johnson of Intuitive talk about accessibility and the Darwin Information Typing Architecture

“If you’re doing it right, accessibility doesn’t look any different than what you’re doing day to day. You’re just adding accessibility considerations when you author your content.”

– Bob Johnson

Related posts:

Accessibility podcast with Char James-Tanny
Intuitive’s website

Twitter handles:

@gretylkinsey

Transcript:

Gretyl Kinsey: Welcome to The Content Strategy Experts podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about accessibility and the Darwin Information Typing Architecture with special guest Bob Johnson of Intuitive. Hello and welcome everyone. I’m Gretyl Kinsey.

Bob Johnson: And I’m Bob Johnson.

GK: And I am so happy that you are a guest on our podcast today. So, would you just start off by telling us a little bit about yourself and your experience with DITA and accessibility?

BJ: Sure. I actually have routes in component content management that go back before DITA. I worked for a web CMS vendor that published a web CMS that was component based. And we implemented Author-it, which is a component based CMS and authoring tool primarily for technical content. We eventually moved to a DITA publish, which solved some problems for us. And since then, I’ve worked with a number of companies, both on the authoring side and the publishing side. I’ve managed CCMS acquisitions, I’ve managed DITA transitions for companies in the medical device sphere, in software, and in medical reference conThe web CMS vendor is also where I got my experience with accessibility. We wanted to sell to government customers and so we needed to be able to make section 508 compliance statements. And so, I had to study up. Later on, I worked for a company that had been acquired by Oracle. Oracle takes a rather different approach to accessibility than a lot of companies. Where other companies centralize their accessibility practice, Oracle makes each business unit responsible. And so, I took the responsibility for helping this acquisition implement accessibility in its content. When I went looking for documentation about accessibility and DITA , I didn’t find anything.

BJ: So, I sat down with the web content accessibility guidelines and developed a matrix to indicate which guidelines applied to techcomm, which one applied to authoring, which one supplied to publishing. And they built a mitigation strategy based on that. I later shared my experience at DITA North America and have been working since then to share that experience with technical communicators across various markets. You mentioned at one point in our emails, what is accessibility? And that’s a really good question. I’ve never found a legal definition, but what I usually use as a definition is accessibility is the characteristics of a product and its content that allow users with disabilities to access the content or use that product.

GK: That’s great. And from your perspective, based on all of that experience you just described, what does accessibility look like when you are authoring DITA content?

BJ: In all honesty, if you’re doing it right, accessibility doesn’t look any different than what you’re doing day to day. You’re just adding accessibility considerations when you author your content. So, for example, when you add a graphic, you make sure that you add an alt text so that users, for example, on a screen reader can get a description of that graphic. You make sure that your table designs are simple and easily navigated. Designs that look easy to the human eye can be very tricky to navigate on a keyboard, which is what most users on a screen reader will be doing. It also looks like authoring content that’s well structured and very focused so users, for example, with cognitive disabilities, don’t encounter problems or distractions that might make it harder for them to follow the thread of the content and understand it so they can fulfill their tasks.

GK: Yeah. And I know it’s really interesting what you said about images and tables in particular, because I think for a lot of our clients at Scriptorium, that’s one of the areas that when they’re authoring content in DITA, and they become concerned about accessibility or maybe they start to have new regulatory requirements for accessibility, with their content, that tends to be one of the biggest areas they have to start with. And a lot of times when they have legacy content, one of the areas where they haven’t really been addressing accessibility in the past. So, I think that’s a really good starting point that you mentioned.

GK: I want to talk about one other concern that we tend to see a lot, which is when we have something like DITA or structured authoring in general, where your content and your formatting exists separately, then that means there’re going to have to be two maybe different groups thinking about the way accessibility works. So, how can we be proactive in designing accessible content when you’ve got that separation between your content and your formatting?

BJ: The place to start is remembering that there’s more than just visual disabilities when it comes to accessibility. One of the responses I frequently hear when I talk to people about accessibility is, why do we need to do this for a small portion of our audience? And if all you think about is users that are blind, that is a relatively small portion of the audience. But visual disabilities itself is actually larger than just blindness. Visual disabilities also encompasses color blindness. About 8% of North European males and about 5% of North American males are red-green color blind. That’s a substantial portion of any audience. And you have to consider that, particularly when you’re implementing your interface, to make sure that color is not the only signal that something is changing or something has meaning.

BJ: You need to be sure that the form of whatever it is also changes so it indicates that there’s something you need to pay attention to. Similarly, when you’re designing an interface, you need to be concerned with neurological disabilities, and certain rates of flashing are known to induce seizures and you don’t want to flash at those rates. When you’re thinking about authoring, again, you want to think about not just visual disabilities, but physical and cognitive disabilities. People with physical disabilities may be navigating by keyboard similar to users on a screen reader. If they have, for example, carpal tunnel or epicondylitis, which is an inflammation of the epicondyle tendon in the elbow and makes it difficult to navigate by mouse, you may need to use the keyboard in that situation.

BJ: And you want to make sure as the author that you make a table, for example, that’s well defined to navigate. You want to make sure that your text content minimizes distractions for users with cognitive disabilities, like ADD or dyslexia. You want to make sure that it’s well organized, that there are a lot of bullets, that you keep your paragraphs short and tight, you keep your topics short and tight. And you really want to avoid using inline links, because those are distracting for both users on screen readers and users with cognitive disabilities.

GK: That’s a really interesting point about the inline links, because we’ve also seen that pose issues for reuse in DITA as well. But I don’t know that we’ve ever really seen it come up as an accessibility issue, but that is a really great point. And I know we’ve been encouraging a lot of companies that do heavy reuse to get their inline links into something more like a related links list at the end of a topic, rather than sprinkled all throughout. But that’s a really good point too, that it can also really have benefits on the accessibility side to do that.

BJ: Definitely. I have some personal experience with this. I have two children that both have cognitive disabilities, ADD and similar related disabilities. And watching them during the COVID pandemic and having to do their school work remotely and seeing text content that they’ve had to use that has links embedded in the text. They’ve found it easy to get distracted and lose the thread of what they’re working on. And that’s equally important for someone that is using content for a business application, or if they’re a consumer trying to, for example, place an order for a product or a service. You don’t want them to lose that thread and go off and do something else.

GK: Absolutely. I thought it was also really interesting what you said about making sure that your topics are short and focused because that’s another area where a lot of companies have come to us and said “we have legacy content that was written more in kind of a book like format, and we want to get it more modular.” And a lot of times, accessibility is a driving force behind that, especially as they’re going into more online forms of delivery, like Webhelp or HTML or a dynamic portal. So, that is a really interesting point too, of how they can author their topics in a different way that’s better for accessibility. So, that’s all covering the authoring side, but what about on the output transform development side, what can be done with the design and the way that you deliver that content to make it more accessible?

BJ: You need as the publishing designer to make sure that you implement whatever accessibility affordances that your authors design into their content. You also want to make sure you consider some of the color issues that I mentioned earlier, to make sure that those users have the correct signals for content changes, not just around color, but around form as well. You also, if you’ve got any kind of streaming content, streaming audio, streaming video, similar to this podcast, that you also make either a transcript or closed captions available so that users with auditory disabilities can follow along or even access the content. Because obviously, a user with an auditory disability is going to find it very difficult, if not impossible, to listen to this podcast and the transcript is going to make that available to them.

GK: Absolutely. One other question following on from that I wanted to ask is that one thing that we’ve seen sometimes with clients who are trying to take things from their legacy formats into something a little bit more modular is that they tend to have lots and lots of hierarchical nesting. And I wanted to get your perspective on any issues that might cause for accessibility. Because one thing we’ve seen is when you have many, many levels of headings, it can only go so deep in a visual representation before it gets really convoluted and confusing. And I think from an accessibility point of view, a lot of times our advice tends to be to try not to have your nesting and your hierarchy, whether it’s for headings or even list items to go too many levels deep. And I wanted to get your perspective on that as well.

BJ: Now, that’s a good point and both for users with visual disabilities and users with cognitive disabilities. Excessively, deep nesting is really problematic. So, for example, a user on a screen reader, deeply nested content can be very challenging to navigate, especially when you’re navigating by keyboard. So, making a shallow structure is going to be much easier for that user on the screen reader to navigate. A user with ADD or executive function disorder is going to have similar problems navigating an excessively complex structure. It’s difficult for them to keep focus or to focus on their navigation of a very complicated structure.

BJ: So, to make it easier for the users with those disabilities, you really want to focus on making your structure relatively shallow. Three levels deep is about the deepest recommendation for any form of navigation that I have seen by accessibility experts. And by the way, I consider myself an advocate, not an expert. I advocate for implementing accessibility and technical communication content, but I’m not necessarily an expert on accessibility.

GK: Any other final advice or words of wisdom that you have to help people who may be starting to introduce accessible content or address accessibility for the first time?

BJ: One thing is to realize that you don’t necessarily have to do everything at once. Very often, when people look at accessibility, they feel overwhelmed. I usually recommend a three pronged approach to implementing accessibility if you haven’t done it before. Anything that new, anything you doing new starting now, make sure you implement accessibility and follow your accessibility practices. Anything that you touch going forward, whether it’s to implement a new feature or to mitigate a defect, plan for implementing accessibility mitigations as well, as part of that work.

BJ: And then for each period of work, whether it’s a sprint or some other form of work, plan implementation of accessibility mitigations in a section of your content to make that whole section accessible or to implement accessibility in that whole section. Also, work with your leadership to determine what aspects of accessibility you need to implement. It turns out that some accessibility mitigations you implement for certain disabilities might not be good for users with other disabilities. And it’s up to your leadership, your accessibility experts, and your legal team to determine which accessibility mitigations are most important for your organization.

GK: Thank you so much for all of that fantastic information and for joining us on the podcast today.

BJ: Thank you for having me. Glad to join you.

GK: And thank you for listening to The Content Strategy Experts podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

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In episode 105 of The Content Strategy Experts podcast, Alan Pringle and Sarah O’Keefe talk about an exit strategy as part of your content operations planning.

“You need to be thinking about the what-ifs 5 or 10 years down the road while you’re picking the tool. Are we going to have flexibility with this tool? Is it going to be able to help us support things we may not even be thinking about or may not even exist right now?”

– Alan Pringle

Related posts:

Scriptorium’s Content Ops Manifesto
Content operations (content ops)

Twitter handles:

@alanpringle
@sarahokeefe

Transcript:

Alan Pringle: Welcome to The Content Strategy Experts podcast, brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about an exit strategy as part of your content operations planning. Hi, everyone. I’m Alan Pringle.

Sarah O’Keefe: And I’m Sarah O’Keefe.

AP: And today, Sarah and I are going to talk about something that probably doesn’t get enough attention, and that is an exit strategy for your content operations.

SO: Yeah, and it seems vaguely impolite to talk about the process of leaving a vendor when you’re planning and thinking about which tools to buy and which systems to build and how to build up your content operations. But I think it beats the alternative, which is not to think about leaving a vendor and then 5 or 10 years down the road, you have to exit and you are truly, truly in trouble.

AP: Yeah, and I can understand, I will admit, I have caught glimpses of side eye from client stakeholders more than once when exit strategies came up during content strategy assessments. We’re talking about getting out of a tool before it’s even selected, and I can kind of understand the thought process. Why are we talking about that now? Well, as you pointed out, you really need to talk about it during the planning phase. Otherwise, you’re going to be left with a lot of muck when something happens and you’re forced to leave a tool for some reason.

SO: Yeah. The side eye from the vendors is even better when we start asking awkward questions. But the alternative, we’ve got projects right now where we are looking at, how do we exit a particular component content management system, move a customer to a new system because it’s time, and they need to move for good and valid reasons. And what we’re running into is that because the inbound 5 or 10 or 15 years ago didn’t really take into account the inevitable exit, we have huge migration costs. We’ve got relicensing costs. We’ve got rebuilding, recustomization, reintegration. It’s almost as bad as the original project of going from unstructured to structured content. It is super expensive if you don’t have a good path to exit.

AP: Sure, and let’s kind of take two steps back. The bottom line here is that planning to get away while you’re choosing your tools is a risk mitigation strategy. It’s a way to keep things from completely blowing up 3, 5, 10 years down the road. So it’s a way to lower your risk. As part of that mitigation of risk, let’s talk about some of the odds and ends that you really need to be thinking about as a way to develop your exit strategy.

SO: You know, we talk a lot about standards and I think everybody listening to this knows that we do a lot of work with XML and a lot of work with DITA-based content. But with that said, you kind of want to start with this question of, am I going use a standards-based tool… now we’re talking about something like a DITA CCMS or an XML CCMS… or should I use a commercial tool, which maybe isn’t standard space per se, but has a really good setup that meets my needs? If you can find something that meets your needs out of the box, doesn’t really require customization, that should work for you. But I would argue that the more customization you’re planning, the more complex your setup is going to be, the more important it is to fundamentally have a standard underlying what you’re doing, because otherwise you’re going to be again in big trouble when you try and get out.

AP: So basically, the more you tinker, the bigger your problem may be when you do need to leave this tool set or tool ecosystem.

SO: Right, exactly, because whatever configuration customization thing you do will not transfer over to the next system, whatever that may be. So you sort of look at it and say, well, it’s a one off. I’m going to do this, and as long as we’re in Tool X, this will work, but as soon as we exit Tool X, all that work that I just did has basically zero value.

AP: Yeah, and it also sort of… It may force your hand where you are locked in with a system until you can do something about all those customizations, and in some cases you may not be able to do anything about those customizations.

SO: Yeah. I mean, we worry a lot about lock-in, getting to a point where you have built a system, a process, a technology stack, a tool set that is so specific and unique to that particular underlying layer that you have that it becomes impossible to get out. The more customization you do inside a tool, the more custom connectivity, the more integrations you build to other tools, the more locked in you’ll be, because, again, if you switch tools, you’re probably going to have to rebuild all of that, and it was daunting to do it once and it’s going to be more daunting to do it again.

SO: So the more you integrate and customize, the higher your exit cost is going to be. You have to balance that against the fact that obviously you’re doing the integration because you get productivity, you get value from it. How high is that value, and can you recoup that over, again, three to five years before you are potentially faced with having to switch tools for some external reason that you have no control over?

AP: Yeah, and this is where you really have to look at your business case, your investment. Are you going to recoup that money? And if you do, that’s great, but if you don’t and you keep basically investing in these customizations layer upon layer upon layer, it’s going to be very hard to unwind all that stuff, and more importantly, it is going to be hideously expensive, both from a money point of view and a person-hours point of view, to get that stuff recreated.

SO: Right. So to take a very concrete example here, if you have a DITA-based CCMS and you build style sheets, DITA Open Toolkit style sheets, to do all of your output, then those style sheets should transfer from one DITA-based system to another, with let’s say minimal-

AP: Yeah.

SO: … rework. Certainly some CCMSs do have some proprietary stuff going on that you have to either put in or strip out, but overall, something like 90% or 95% of your style sheet should just work if you move it out of one DITA-based system into another one. If, however, you build out your output using, let’s say, a proprietary publishing layer in a particular tool and then you switch tools, you have to start over. So that’s a concrete example of where vendor lock-in would cost money down the road.

AP: And I think it’s important to point out here that it’s this exit strategy or these problems with not having an exit strategy are not just related to tools. There are some things that have to do with finances, contracts, so on, that also have a big part in these kinds of problems. So let’s step back from the tools a little bit and talk about the bigger-picture implications of finances and contracts and that sort of thing.

SO: Right. So if I’m… This is a case where the interests of the vendors selling commercial tools, software, and the interests of the customer, the organization buying commercial tools or software, do tend to diverge, right? Because if I’m the vendor, I want the longest-term contract possible. I want you to stay with me. I want you to pay me every year, as we all do, because that allows me then to reinvest in my tool and make it better and keep you as a long-term customer. It also reduces my risk as a software vendor, right? A five-year contract is better than a three-year contract is better than a one-year contract, and especially in a Software as a Service, in a SaaS world.

SO: So, okay. Well, that’s fine. But if I’m the customer, then you’re looking at an ROI of maybe two years or three years, and I don’t want to be locked into five years. Concrete examples of things that can happen. The software that I rely on gets bought by somebody else and they discontinue it. They take it over and they discontinue it. I have to exit. The organization that I work for gets merged with another organization, and then another organization, and suddenly we have not two systems, but, like, five different authoring workflows.

AP: And we’ve seen that. We have seen that.

SO: Yeah, I’m not actually making that one up.

AP: No, you’re not.

SO: So we have to consolidate because we’re supposed to actually deliver a unified customer experience, which is pretty hard to do with two or three or five CCMSs.

AP: Right, and also, most IT organizations are not going to stand for having three versions of a tool that essentially do the same thing when you do merge together. So from a financial point of view, it does make sense, and from a support point of view, to jettison two and stick with one.

SO: So two years ago, I picked a system. It’s a good system, but we got merged. Now we have a much bigger group. My sort of facts on the ground have changed. Or, we picked a system, it was fine, but now we’re doing more languages, or, oh, we need to integrate with this new chatbot thing that we’re doing over here in the corner and I don’t have any way of doing that out of the system that I’m currently in. And I didn’t account for that on day one, because it was 10 years ago and chatbots weren’t a thing, right?

SO: So those are the kinds of issues that you run into, where change or having to change, having to exit, is basically inevitable. At some point, a new requirement comes along, or your company changes, or you grow, or you shrink, or you change markets, you add localization, you add more localization and more languages. Something happens, and the thing that was a good fit for you is no longer a good fit for you. So what does it look like at that point to exit your business relationship with your existing vendors and your existing set of vendors? If you’re locked in for a really long time, you’re in trouble because you can’t do what you need to do.

AP: That lock-in can make things very difficult for you if you need more flexibility and you need to pivot and be nimble and really kind of change course a little bit if you are so locked down in something that doesn’t give you the ability to address those things. So basically you need to be thinking about the what-ifs 5 or 10 years down the road while you’re picking the tool. Are we going to have that flexibility with this tool? Is it going to be able to make some changes and help us support things we may not even be thinking about or may not even exist right now? Some delivery format that we don’t know about. Is this flexible enough to help address a concern we don’t even know about? I mean, that’s the kind of thing you have to be asking yourself.

SO: You know, to take a concrete today analogy, this is exactly like the office space problem, right? Suddenly everybody’s working remote. There’s all this office space. Are we going to use it again? Are we going to come back to our office? The facts on the ground have changed, and maybe the thing that was selected is not the right thing anymore, but here we are with a 5-year or 10-year or 15-year lease, right? It’s exactly the same problem, that you get locked in and then things change. Maybe everybody’s working remotely and your particular system isn’t really set up for a distributed workforce.

SO: And now back to the CCMS, right?

AP: Right.

SO: Most of them now, most of the clients we see, are in fact SaaS and not on premises, but you think about those kinds of issues. Well, what if you need everybody in the same building to use the system, and being in the same building is not in fact an option?

AP: Yeah. You have zero flexibility in a case like that, so it is definitely a problem.

SO: Yeah. It’s not that you made a bad choice. It’s just that there’s new information.

AP: Yeah. So let’s talk about dealing with, like you just said, that new information when you didn’t do that upfront planning. What are the ramifications of not thinking about the exit strategy when you’re essentially entering a tool?

SO: It just means that, at the inevitable point when you do have to leave the tool for whatever reason, you are then going to have to figure out, what are my options? How can I get out? How bad is the migration going to be? How do I dismantle or rebuild or recreate these integrations that I have? How do I think about the features that I have?

SO: One thing I would say is that I would caution people against trying to move from Tool A to Tool B and completely recreating or reproducing the old authoring experience. If you switch tools, and particularly if you switch authoring tools, authoring tools have different strengths and weaknesses, and what you want to do is take a tool and take advantage of its strengths. You don’t want to ignore its strengths because you never did it that way before, and you don’t want to rely heavily on its weaknesses, again, because that’s how we’ve always done it, right? So there’s some change that has to happen there. The authors will probably need some training and some help to shift over, but you really want to think about, well, what’s in here and what’s the state of the art and what are the new things that I can do?

SO: But largely, if you have to migrate or if you have to change tools, what you have is, at that point, a tactical problem, right? You just have to do it, and you have to look at the facts as they are, the features that you have available to you, the options that you have, and figure out what to do. But I think I would argue that exit strategy and risk mitigation is something that you should be thinking about or should have been thinking about before the tools and the technology stack and the processes were originally set up. And of course, if that’s not the case or it was your predecessor, then that’s just how it is.

AP: Bottom line, an exit strategy should be part of your content strategy. So while you’re doing the assessment, you need to be thinking about this and not dealing with the ramifications of not considering it 5 or 10 years later.

SO: It’s a lot cheaper to do it before you build. Yeah.

AP: Exactly. And on that note, I think we will wrap up. Thank you, Sarah, very much.

SO: Thank you.

AP: Thank you for listening to the Content Strategy Experts podcast, brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

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In episode 104 of The Content Strategy Experts podcast, Elizabeth Patterson and Sarah O’Keefe discuss Scriptorium’s Content Ops Manifesto.

“The bigger your system is and the more content you have, the more expensive friction is, and the more you can and should invest in getting rid of it.”

– Sarah O’Keefe

Related links:

Scriptorium’s Content Ops Manifesto
Content operations (content ops)

Twitter handles:

@sarahokeefe
@PattersonScript

Transcript:

Elizabeth Patterson: Welcome to The Content Strategy Experts podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we talk about content ops and Scriptorium’s Content Ops Manifesto. Hi, I’m Elizabeth Patterson.

Sarah O’Keefe: And I’m Sarah O’Keefe.

EP: And so we’re just going to go ahead and dive right in. Sarah, let’s start off with a definition. What is content ops?

SO: There are lots of great definitions out there written by people smarter than me, but the one that I really like is pretty informal. Content ops is the engine that drives your content life cycle or your information life cycle. So that means the people, the processes and the technologies that make up your content world. How do you create, author, edit, review, approve, deliver, govern, archive, delete your content? That’s content ops.

EP: So Scriptorium recently published a Content Ops Manifesto. And in this manifesto, you describe the four basic principles of content ops. So what I want to do is just go through those one by one, and I will of course link the manifesto in the show notes. So the first one you have in the manifesto is, semantic content is the foundation. What exactly does that mean?

SO: I wanted in this manifesto to take a small step back from hands-on implementation advice, and the things that we tell people to do, you need to go through and build out your systems, and here’s how you make them efficient and focus instead on the principles of what that looks like without getting too much into the details. And so with that in mind, each of these principles is intended as a guidepost that would apply for any content operation that you’re trying to build out. Semantic content is information that is essentially knowledgeable and about itself, or self-describing. Now this could be as simple as a word processor file, where you have some paragraph tags that say, “Hello, I’m a heading one,” and “Hello, I’m a heading two,” and “Hello. I am a body tag,” that kind of thing. So you need to have tags, labels of some sort that describe for each, whether it’s a block or a little chunk or a string of text.

SO: What that text is. Is it a heading? Is it body text? Is it a list or part of a list? That kind of thing. So that’s tags. Now, there are lots and lots of ways to do tags across every tool that you could imagine, but you need some sort of semantic labeling. Second, we need metadata. So we need information about the information itself. Usually this is classification tags. So things like, “I am a beginner level task,” or even, “I am a task. I was last updated on this date. I belong to this product or this product family.” So metadata provides you some additional context about the information and describes it further, but it doesn’t really describe the information itself, but rather where the information belongs or who should be using it. Metadata is broadly… If you’re struggling with metadata, take a step back and think about, if I were searching for this information, what kind of labels or tags would I want to use to find what I’m looking for?

SO: And then we have hierarchy and sequencing. So hierarchy means that you’re looking at the structure of the content from the point of view of which things are subordinate to which. So let’s say that you have an installation procedure and there are six things you have to do in a specific order and each one of them is a task or a process of some sort. Well, you need to be able to say these six things are in a group. There’s the installation process, which consists of these six things, that’s hierarchy. And then sequencing is… And they have to be done in this order, right? You have to do one, then two, then three, then four. You can’t start with four and then do one or your installation won’t work. So there’s this process or this idea that you’re collecting up information. And when you do these bigger collections above and beyond a tiny little string, you need hierarchy and you need sequencing.

EP: So the second principle that you touch on in the manifesto is that friction is expensive. And when we’re talking about friction, in this sense, we’re referring to the process that you’re slowing down productivity. So what are some common points of friction and what are some things you can do to eliminate them?

SO: Yeah, so friction is any time you have really human intervention, right? Because computers are very, very fast at what they do and humans, well, we have other skills, but-

EP: We make mistakes.

SO: We do make mistakes, but we’re good at certain kinds of creative things. We’re good at saying these things go in this logical sequence, but what we’re not good at is applying the same formatting consistently over and over and over again. Right? So friction is any place in your process where there’s human intervention. So I’m going in and I’m hand formatting things, or I’m downloading a collection of files, zipping them up, sending them to somebody else who’s then uploading them into a different system and expanding them and reinstalling them there. Anytime you see a process that is driven manually and/or driven by paper, you probably have friction in your process.

SO: And we think these things have gone away, but there are a non-zero percentage of people out there who are doing reviews by the process of, “Let me print this thing out and go give it to you and have you write on the paper and then give me the paper back.” That introduces friction. The problem with friction is if it’s just you and me and we’re working on two or three pages of stuff, and we’re in the same location, not that big a deal. But as you scale, as you have more people and more documents and more languages and more variants, that manual process that used to be okay when we had 10 or 15 or 50 pages of content, becomes unworkable, right? Because it slows you down. So when we talk about friction in a content ops context, what we’re usually talking about is where are these points of manual inefficient intervention and how do we get rid of them?

SO: And when you start talking about eliminating friction, we fall back on things that you’ve heard previously in a non-content ops context, automated formatting, automated rendering across all the different formats that you’re looking for, reuse content instead of copying and pasting, connect systems together so that you can share content efficiently, review workflows that are not human dependent and not paper dependent, but rather roles. I need somebody with the role of approver to look at this thing. I don’t need it to be you personally, Elizabeth, and as it happens, you’re on vacation this week, right? So I don’t want to send it to you. And I certainly don’t want to send it to your email specifically. What I want is for the system to say, “Hey, this thing is due for a review and here are the three people that are authorized to do it.”

EP: So friction, I mean, it’s going to take time and effort to eliminate that friction, but it’s definitely worth it in the long run.

SO: The bigger your system is and the more content you have, the more expensive friction is, and the more you can and should invest in getting rid of it. Yeah.

EP: Definitely. So the third principle outlined in the Content Ops Manifesto is to emphasize availability. What exactly does that look like?

SO: So is content available? What that means is if I am your content consumer, and I need a particular piece of content, can I even access it or have you locked it behind a log-in that I don’t know about or that I don’t have credentials for. So literally, not available to me. The information exists, but I can’t get to it. So that’s question one is, have you made it available and in many cases, availability in that aspect of it is actually synonymous with, “If I Google, will I find it,” right? Because I don’t necessarily know where you’ve stashed it, but if I can find it, then it’s available to me. Now, there are outlier cases where you do need to put things behind log-ins for good and valid reasons and that’s fine provided that your end audience knows, “Oh right. I have these credentials. I’ve signed up for the subscription. That’s where I’m going to go look for the information.”

SO: That’s fine. So where do you put it? What are the rights to get to it, right? Do the right people have the right access and do they know about it to get to it? Now, the second factor with availability is actually accessibility. And here, I mean, in the technical sense of, can I consume this content successfully? So there are a bunch of aspects of accessibility which usually have to do with physical limitations. So we’re talking about things like, I’m colorblind. Did you design the content in a way that I can still use it, even if I have some vision limitations? Is the content consumable by screen readers so that if I have a vision impairment, I can use it? If we’re doing a podcast, is there a transcript so that somebody with a hearing impairment or somebody who’s deaf can read the transcript instead of needing to use hearing?

SO: So you get into this question of, have you provided ways for people to access the information that allows for the possibility that they have some a physical limitation? There’re some others around keyboard navigation, right? Can I tab through the buttons instead of having to click on them? Have you allowed for people that have tremor or issues with fine motor control so that asking them to specifically click on a tiny little button on a screen somewhere is maybe not an option. Is there a mobile option as opposed to a desktop? Maybe I’m accessing all your content from a mobile device and if you haven’t thought about that, then I’m going to have problems trying to read the teeny, teeny tiny print on my not so big phone screen, right.

EP: And we’ve probably all experienced that and it is frustrating.

SO: It’s so annoying. So when we talk about availability, we’re talking about literal availability, like where did you publish it? And do I have access? Talking about accessibility and all the various facets of accessibility, there are lots of useful guidelines on that out there that are more detailed. And then we also need to think about languages and localization. If I’m a non-native English speaker and my comprehension of your text is going to be much, much better in French, which by the way, I can assure you, is not the case for me, you have an obligation to provide that content in French, if you want to market to your primary French speaking audience, right?

EP: Absolutely.

SO: So you need to think about languages. Localization also ties into the question of, well, if I’m writing content for a particular locale, a particular location, you need to think a little bit about what that looks like.

SO: So to take a really basic example, if you’re marketing to somebody in Florida, you probably don’t need to sell them snow pants in October, right?

EP: Probably not.

SO: They are not buying snow pants in October. So that’s like a really basic localization principle that… You want to think about your market and how your market differs by geography or by locale. That gets tied in with language. But they’re not really the same thing, right? You’ve got geographic stuff, you’ve got regional things and you’ve got different regulatory schemes. So for example, to take the infamous example, any legal advice that you’re giving somebody always ends with “comma except in Louisiana.” So, oh, also don’t give anybody legal advice because we’re not qualified, right. But you have to think about those kinds of locales and the different regulatory schemes to make sure that you’re covered and you’re not giving people bad advice based on making the assumption that we all live in the same spot.

EP: Right. So the last principle in the Content Ops Manifesto is to plan for change, which is something that we touch on in a lot of the posts that we publish and the podcasts that we publish. So how do you plan for change?

SO: We really are annoying about change managment.

EP: It’s so important.

SO: It’s our favorite word, our favorite phrase, or actually it’s our second favorite phrase because our first favorite phrase is, “it depends.” But let’s say it this way. When you start thinking about content ops and building up these processes and these technologies and these systems that you’re going to use to drive your content engine, the number one thing that I would advise you to do when you do this is to think about your exit strategy. So in other words, I am buying product X and I’m going to put all my content into it, or I am implementing system Y and I’m going to put all my stuff into it and that’s going to drive what we’re doing. I want you on day one, when you’re going into this really cool system that you’ve decided is going to be the be all end all for at least the next couple of years, to be thinking about what if I’m wrong or what if things change?

SO: What if that company gets bought by a competitor and they discontinue the product? What if the system that you put in place doesn’t work or a new requirement comes along and your system can’t accommodate it. You need to be thinking on day one about, “Okay, well, I’m going to go in, but if I have to get out, do I have a way of getting out? What’s my exit strategy? What is the cost of exiting this particular system or process? What is the cost of changing tools and technologies?” Because I’m not saying you should have a foot out the door. It’s more that we know that change is going to happen.

SO: Change is totally inevitable and somebody is going to come along with a new requirement that we’ve never thought about before, and we’re going to have to meet the moment. And so we need to know A, what things am I picking and are they extensible? Can I add on, can I accommodate these new requirements inside the system I’ve built or selected? And if not, how expensive is it going to be to get out? Now, if the answer is, it’s going to be super expensive to get out, but this thing meets 100% of our requirements right now, it’s extensible in these 15 ways and I don’t see a reason that we would need to get out, that’s okay. That’s a decision that you’re making, but you need to do a strategic assessment of, what is my exit strategy and what are the implications of needing to exit from whatever it is that I’m about to pick?

EP: Right. And I think exit strategy is a good place to wrap things up. So thank you, Sarah.

SO: Thank you.

EP: And if you would like to read the Content Ops Manifesto that will be linked in our show notes. So thank you for listening to The Content Strategy Experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

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In episode 103 of The Content Strategy Experts podcast, Alan Pringle and Bill Swallow share some considerations for transitioning into a new component content management system or CCMS.

“You need to look at the requirements you have now. Are they being supported or not supported? Do you see this system helping you move forward with your content goals in three to five years?”

– Alan Pringle

Related links:

Buyer’s guide to CCMS evaluation
Life with a content management system (podcast)

Twitter handles:

@alanpringle
@billswallow

Transcript:

Bill Swallow: Welcome to The Content Strategy Experts podcast brought to you by Scriptorium. Since 1997, Scriptorium has helped companies manage, structure, organize, and distribute content in an efficient way. In this episode, we share some considerations for transitioning into a new component content management system or CCMS. Hi everyone. I’m Bill Swallow, and today I’m here with Alan Pringle.

Alan Pringle: Hello everyone.

BS: And we’re going to jump into a discussion about when we should be switching our component content management systems. So I think Alan, I’ll probably start off with a question to you. How do you know it’s time to move on with your existing CCMS?

AP: Well, everybody’s situation is going to be a little different, but in general, there’s some things that you can look out for as warning signs you may need to reconsider your CCMS. One of them being, sure things worked great when you stood the system up, but now a few years later, you’re finding that it is not scaling to meet your needs. You’ve got a whole lot more content in it. You have some feature sets that may not be there, that would be very helpful to you. So it’s a matter of, is that system keeping up with your growth and your changes? Is it keeping pace?

AP: In regard to the feature sets that I just talked about, if you discover that you’re spending a lot of time doing customizations to make things work for you, that may be a warning sign that you need to take a look at what some other systems offer as out of the box features because you do not want to be in this loop where you are spending a lot of time and money and investing in a system by basically doing patchwork add-ons to it. That’s not sustainable in the long run. If there is a system that has the feature that you’re looking for automatically, it may be worth considering that system, instead of doing this patchwork add-on to your existing setup.

AP: We’ve also seen cases where we had a client that was involved in a merger. And because of that, there were multiple component content management systems in the mix from the different, mostly technical publications departments that merged together from the different companies. So when you find yourself in a situation where you have acquired another company or you’re being acquired, you may have a situation where you’ve got overlap in your tool ecosystem, and in general, a company is not going to want to support two tools that do the same thing.

AP: So you have to take a look kind of from a bigger business point of view, at what the overarching goals and efficiencies that the company wants to make. And some of those efficiencies may be, we’re not going to have two CCMS’s here, we need to migrate everything to one. And I think it’s worth mentioning in that case, just because you’ve got two systems in house, you may want to look at a third option, so that way, you are really not picking winners and losers because everyone has to move. I am not saying that is the perfect solution for everybody, but it’s absolutely something you should consider, if you do participate in a merger and have some overlapping systems.

BS: So everyone shares the pain pretty much. Okay, so let’s say we made the decision that we have outgrown our existing CCMS. How do we start to evaluate new options?

AP: Well, you need to gather information and you can do it internally, kind of be your own consultant, or you can hire someone to come in to help you do this. Basically, you need to take a look at the requirements that you have now, how well they’re being supported or not supported, as the case may be. And kind of break out your crystal ball. Where do you see things three to five years? Do you think this system is going to support you and some new things you may need down the road? So, that’s the kind of thinking you have to do. How well are you being supported in the present, and do you see this system helping you move forward in three to five years with your content goals?

BS: And I think once you start putting all this information together, at that point, you may want to consider doing a request for proposals from multiple different vendors. And in that case, definitely include your existing vendor because there may be something that you may not currently have in your existing configuration that they may be able to offer as well. Plus you’ll be able to use them as a baseline against your other options.

AP: Yeah, it’s not necessarily that you have to immediately assume that your current vendor is no longer going to be part of the picture. There may be a chance that they have new offerings, new features like you mentioned, and you can use the RFP process to kind of uncover some of that too. And from a business procurement point of view, I am sure your procurement department is not going to be disappointed to get a chance to renegotiate a contract. That’s just gross. And I know it sounds very matter of fact, but it’s the truth. It’s a matter of renegotiating and looking at a tool and seeing if it’s supporting things and what kind of funding is going to be required with any update that you have with that tool, if you choose to stick with it.

BS: Okay. So we’ve identified issues with our existing CCMS. We’ve gone through and identified a new option, whether it’s to stay with the existing one with some changes or to move to a new system. What are some of the common issues or roadblocks that you might encounter as you start to switch systems?

AP: This is true of anytime you switch technology, even if you, for example, were on an Android phone and you changed to iOS on an iPhone. There are going to be some features in one operating system that are not going to be exactly equivalent on the other side, you’re going to lose some features and you may gain some features. So you may have something set up that is very specific and tailored to the particular tool, the particular CCMS you’re using now. Is there anything in that, that is not going to translate well or come over to the new system? And there’s several components here in regard to this. Are there features you were using that are specific to that particular CCMS, that are not supported because it’s a proprietary feature, in whatever you’re moving to? That’s one consideration. And then another side of that is, do you have any connectivity, any connections to other kinds of systems?

AP: And this can include a learning management system, a digital asset management system, a translation management system. Are those connections that you have, can you get the equivalent setup in the new CCMS? Are there automatic API connectors from your new system to these things? Are you going to have to rebuild or completely recreate your existing connectors when you move to a new system? So you’ve got to look at anything that is very particular to the CCMS that you’re currently in and how well that will transition over. And then you have to think about your bigger tool ecosystem and how those things are connected and how you’re going to basically reconnect everything together when you switch to a new CCMS.

BS: So I’d also expect in this case, if in your existing CCMS, you’ve been making a lot of customizations on your own and hacks and whatever else to get things to work properly, you’re probably going to have to find either a resolution for those or unwind them, even in your content, perhaps, as you start migrating to a new system.

AP: Exactly. And this goes back to what we were talking about earlier, where if you have done a ton of customization to your CCMS, at what point do you say, “Is enough, is enough. I can’t keep adding and adding these custom hacks to this tool because it’s becoming inefficient.” That very much ties into what you’re talking about here.

BS: Okay. So we’ve talked about problems in the existing, evaluating new options and problems when you’re probably migrating. So what can you do to make this transition a success?

AP: Well, this is a tiresome piece of advice, but its solid advice, and that is, you need to make a transition plan. This is not something you can just jump into. You need to take a look at your “real work schedules,” because you do not want to be making this transition, when you have deadlines, deliverables, anything going on at your company where you’ve got a new product release coming out. That is not the time to do this. So you need to step back, look at what’s coming schedule wise, in the next few months, figure out when would be a good time to do this, and then start giving some thought about, “Okay, what might be the first thing that we can try and move over?” You may want to try to do a pilot to move over just some of your content to be sure that everything has stood up correctly, instead of going whole hog and doing everything at once. Those are two things that immediately pop into my mind.

BS: And probably keep both stood up and keep using the old one as your production system until everything is verified as complete on the new one.

AP: Absolutely. I think you also need to basically take a very deep breath and realize things are going to go wrong and be flexible and be ready to deal with things that are going to go sideways because they will. And there are going to be some things you may have an inkling, this may be a little challenge, but there may be other aspects you haven’t even considered that cause you problems. So you can’t go in with this super rigid idea, we must hit this exactly right, because in general, technology is going to wag its finger in your face and say, “I do not think so. I’m going to cause you a problem here.” But some planning can minimize those things, but I don’t know about you, I’ve yet to see any transition from one tool to another, CCMS or otherwise, that was perfectly smooth, and there were no hiccups. I have yet to see that ever happen, period.

BS: No, there’s no golden system. Going back to your phone analogy between Android and iPhone, there are excellent things about each one of them, but they also both have their problems.

AP: Exactly. And then finally, too, because you are moving to a new tool, you’ve got to realize skills people had in the old tool set, are not going to be quite as useful. So you’re going to have to provide training and support to be sure people can basically remap the skills they had from the old tool to the new tool. And that may be a little rough, especially if people have really invested a lot of time and thinking into workarounds to get things to work in the old system. And those things are no longer available. That’s a lot of muscle memory you’re going to have to undo with some training and best practice information, so people don’t keep doing those workarounds because they’re no longer needed.

BS: All sound advice. And I think we could probably wrap up here. Thank you, Alan.

AP: Sure.

BS: And thank you for listening to The Content Strategy Experts podcast brought to you by Scriptorium. For more information, visit scriptorium.com or check the show notes for relevant links.

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