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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.”

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Transcript:

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

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.

The post Our demands for enterprise content operations software (podcast) appeared first on Scriptorium.

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

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Transcript:

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

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.

March 2025 update: We have moved LearningDITA to a new platform. The Introduction to DITA course is still free, and you can sign up for courses at store.scriptorium.com.

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.

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:

LinkedIn:

Transcript:

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

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.

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:

LinkedIn:

Transcript:

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

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.

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:

Books:

Contact Dee:

LinkedIn:

Transcript:

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

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 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 [email protected]. 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.

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:

LinkedIn:

Transcript:

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

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 is part two of a two-part podcast.

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.

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:

LinkedIn:

Transcript:

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

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.

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 machine translation that we can apply to AI, and more.

“Regardless of whether you’re talking about machine translation or AI, don’t just run with whatever it provides without giving it a thorough check. The other thing that we’re seeing with AI that wasn’t so much an issue with machine translation is more of a concern around copyright and ownership.”

— Bill Swallow

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Transcript:

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

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 the parallels between AI and machine translation. Hi, I’m Christine Cuellar, and with me on the show today I have Bill Swallow. Bill, thanks for coming.

Bill Swallow: Hey, thanks for having.

CC: Absolutely. So for non-technical people like myself, what are we talking about when we say machine translation, is that like Google Translate? What are we talking about there?

BS: Google translates a form of it.

CC: Okay.

BS: But essentially, yeah, it’s a programmatic way of translating from one language to another.

CC: Okay.

BS: It’s been around for quite a while and we see it commonly in Google Translate and other online uses, but it’s actually been around for quite some time.

CC: Okay. So I know that as AI has become the biggest topic in 2023, we’ve often compared it to machine translation. I know we’re going to talk about that throughout the episode, but can you give just a little intro to why they’re compared so often?

BS: Yeah, I think it boils down to really where machine translation started.

CC: Okay.

BS: So I’m not going to give you years because it’s not at the top of my head, but it basically started out as a rules-based program. So people sat down, wrote these if then else statements essentially, to basically say, if you come across this phrase, then it’s translated in this way for this language.

So they started out with that rules-based approach, and they’ve beefed up the rules and they’ve beefed up the processing. And of course, they improved the examples on the backend of the finished translation and modified that so that the translations kind of became a little bit better over time.

CC: Okay.

BS: Then they switched over in many cases from the rules-based to more of a machine learning model, which then, basically it’s like early AI. So it started to learn patterns and it started to learn about context a bit based on the words and phrases that were being used and could draw additional inference from that.

CC: Interesting.

BS: And essentially that started to develop more and more until we got to an AI use case. So it’s something where you actually get this robust use of machine translation. So it’s actually using a lot more learning models in that translation process. And the machine translation process is a little odd because you can do it out of the box, so something like using Google Translate where it basically uses its own Google index as a resource for translating a lot of that content. But a lot of translation companies and a lot of companies that employ machine translation, whether they are translators or not, some companies do it in-house on their own. They will basically train their machine translation against their own content and their own translated store of content so that it brings back their approved wording, their approved language models.

CC: Gotcha. I can totally see how that is a big parallel to AI right now as we’re talking about having an internal AI versus just throwing content in ChatGPT. That makes sense. You mentioned there was a transition into machine learning. When that happened, how did people react? Was it really similar to how people are reacting with AI? Was it split? What was that acceptance like?

BS: Yeah, I think there were some parallels there. Just as with what we’re seeing with AI now, there’s a lot of concern from people saying, oh, the machine is going to essentially rule, make my job obsolete because it can now write these blog posts, it can write these screenplays, it can develop these characters, it can produce these images. But with machine translation, there was that similar kind of fear where translators were like, oh, it’s going to reduce my margin. It’s going to put me out of a job. But we haven’t really, we saw that to some extent in the very beginning, but what we’ve found over time is that no, the people are still required to go in, proofread that machine-translated content, clean it up, make it more appropriate, and essentially improve what’s on the backend that the machine translation is pulling from so that things are improved over time.

CC: Yeah, process updates and that kind of thing. Improving the bank of-

BS: Right, improving the phrases, getting rid of things that are no longer said in certain areas because language is ever-evolving.

CC: Yeah, that’s true.

BS: You need to be able to keep up with those changes.

CC: That’s true. And how far ahead would you say that machine translation is compared to AI? Is it five years in the future so we can maybe see what might be coming? I know that’s probably really hard to quantify.

BS: Let me get my crystal ball.

CC: Yeah, yeah, there we go. Give us an exact answer.

BS: I’d almost say that they’re on two parallel, but different paths.

CC: Okay.

BS: And that I think we’re going to see a lot more blurring of the lines. Those paths are going to start to come together a little bit more. I mentioned that machine translation is leveraging AI to a good degree these days because it’s the next step in that form of machine learning. It’s no longer a core programmatic learning model, but it’s more of an adaptive one. So it basically will influence its own way of learning about stuff going forward. AI is employing machine translation to many degrees. We saw there was a video floating around LinkedIn of this new utility where, and I think Sarah spoke about it on a previous podcast with Stephan Gentz. But yeah, you basically record yourself saying something and it will turn around, machine translate that content, use your tonal voice and basically re-speak, and then re-sync the video so that it looks like you’re speaking a completely different language.

CC: That’s crazy.

BS: It’s nuts. I watched the video a few times. I don’t know either languages. I think they used French and German. I know enough German to be dangerous, and I know enough French to order a meal.

CC: It’s the priority.

BS: But the German I found was actually pretty spot on from what I could understand of it. And I know Sarah speaks pretty much fluent German, certainly more than I do, and she only found really one mistake, I think.

CC: That’s crazy.

BS: It’s crazy. So there are cases where things are being employed, and I think we’re going to see a lot more of that.

CC: Okay.

BS: On the machine translation side, we’re certainly going to see it adopting more robust AI models so that it can continue to build and improve how machine translation is being done. On the flip side, I do think that AI will be leveraging more of the linguistics modeling that is baked into machine translation so that it can do a better job of representing essentially the human construct of language.

CC: Wow. That video example that you gave and that Sarah shared before, that’s just, I feel like that’s one of those examples that I don’t know, 50 years from now, we’ll look back and the kids will be like, that’s so used to, I don’t know, stuff like that is what they’re totally used to, or I remember back in my day that was a big deal, anyways, it’s just mind-blowing that this kind of stuff is happening. So speaking of those kind of innovations and industry disruptions and that kind of thing, we’ve talked a little bit about how with machine translation and then with AI kind of on parallel paths merging together, what are some of the ways that the disruptions have been really different or have created different things for the content industry?

BS: I don’t know if there’s any real difference in how they might be disrupting the industry or how they might be employed. There are differences from a practical matter, when would you deploy a translation management system versus when could you use… Well, AI is kind of a really nebulous term. It could mean anything. It could mean ChatGPT, it could mean image rendering software. It could mean really anything. With machine translation, we’ve seen it become more of a daily utility. So you come across a news article in another language, if you’re using Google Chrome, you might have the option to translate this page. If you’re not using Google Chrome, you can go to, for example, translate.google.com and just provide it the URL or copy and paste a paragraph, and you can basically get an idea of what that website’s talking about. But we’ve seen it become more baked into applications as well. Certainly, there’s a whole industry around providing translation services. So we’ve seen that kind of pick up the pace on round-tripping translation work.

So before you would have someone sit down and actually translate a block of text and they would use translation memory, which is essentially a store of what was translated last time, to kind of pull from and pre-fill the translation, and then that way they can fill in the gaps. That’s a very, very high-level view of translation memory, but essentially it takes that to the next level where it will pre-process the translation for you and provide you with something that’s maybe 95% there. And then you would get someone who is an expert in the language and the subject matter and the target locale, because we know that Spanish is different depending on where you are in the world, for example. And they would proofread it, clean it up, and probably commit that back to whatever the machine translation is using so that it uses that reference next time rather than having to go through that again.

We see it baked into applications as well. So there are some gaming applications that will auto-translate a chat on the fly so that depending on, no matter where you are in the world, you can actually still understand what these players are saying. So if you’re on a team and someone’s saying, go now, and you don’t speak their language, you have no idea what they’re saying.

CC: Yeah.

BS: But the chat translation can kind of help. It’s not perfect, but it’ll help. With AI, I kind of see that moving into a similar role. It’s going to be, now we’re looking at it as, oh, look what this thing can do. It can write me a limerick. It can essentially create me a photorealistic image of whatever I choose to think up. I give it a description and it creates something, and it might be what I’m looking for, and it might not, and there are flaws to those as well. But I kind of see AI being baked more into the backend of a lot of the tools that we use on a daily basis to help with more robust search and query activities, to be used as an editor or a checker for things on the backend, to be a starting point for developing something new.

So whether it’s a piece of code or in our world where we do structured authoring work, it could be something as easy as give me a framework for a new task that I need to produce, and it will lay everything out. That kind of harkens back to more of a template, but you can kind of say, give me a task based on what I’m writing about here in this section, and it can pull some pieces in and fill things out. So I also see it as being more of an aid for finding resources that already exist so you’re not reinventing the wheel and things like that. So things that essentially it’s going to be baked into a lot of different utilities that some of which we use now, some of which we haven’t thought of yet that will make our lives easier.

CC: Okay. So what are some of the pitfalls that we fell into during machine translation that we can avoid with AI? Do you have any red flags or things to watch out for based on how things went the last time, essentially?

BS: Yeah, I think the biggest one is to not take what it provides for granted.

CC: Okay.

BS: So regardless of whether you’re talking about machine translation or you’re talking about AI produced whatever, is to not run with whatever it provides without giving it a thorough check. I think the other thing that we’re seeing though, and it wasn’t so much an issue with machine translation, is more of a concern around copyright and ownership.

CC: Okay.

BS: So who essentially owns the rights to these things?

CC: Yeah.

BS: And it kind of goes back to, well, what was the model used to kind of create them in the first place? Was it using a public domain model or was it something that was trained only on a private store of information?

CC: Yeah. So looking into the future, do you see private AI being maybe the best way to move forward with AI? Not that people will necessarily, or there’s maybe some use cases for public domain AI too, but do you see that though as more of where we’re going to head?

BS: I think it’s inevitable. I think that we’re going to have cases where, we’ve seen cases already where companies have kind of uploaded examples of their own code to see if they could get a public AI model to write more code based on that model. And unwittingly, they basically let their own IP out into the wild, so now everyone can use what these people created that they uploaded in the first place. So that’s an oopsie. So I think that based on cases like that, I think people are going to start employing a private model, basically a walled garden where they can train and develop their own corpus of information, whether it’s images, code, text, what have you, and use that to produce things using AI.

But I still think that, yeah, there’s going to be a public model for, I don’t see that need ever going away. Just as we have public models for everything else that we use on the internet, I think we’re going to see AI have its own footprint there as well. We might need to be careful while using it. There might need to be more guardrails attached, but I don’t see that going away.

CC: Yeah, that makes sense. And you mentioned that with concern for people’s jobs, I know that of course is a concern right now with AI as well. And you mentioned that at the beginning of machine translation, that was, you did see a little bit of job loss, but overall, those experts were still needed to manage the content, make sure that everything that is being created is accurate. So what would you say to people that are really concerned about that right now? Do you think that’s going to be really similar for AI? Are there any differences you can think of?

BS: I think this is actually a good learning point from machine translation because yes, some people lost their jobs initially when machine translation came out. I think in hindsight, that was an error or that was a bad decision to either let people go saying, oh, a machine can just do it. Because it was very clear out of the gate once machine translation really started being used that people are still needed. They’re still needed to clean up what the machine translation is producing. They’re still needed to do new translations into new markets in new contexts with new terms. A machine just can’t invent things and have it be correct for a very specific target audience.

To do any kind of translation correctly, you need to know the subject matter. You need to know the language that’s being spoken in, the flavor of language for the locale in which you are targeting that content, and anything else about that locale that might influence jargon or anything else that might need to be employed. So yeah, I see a similar warning, I guess, for people who are looking at AI and saying, oh, we can reduce our staff by employing AI. It’s like, no, you’re going to augment your staff and they are going to need to learn new skills because they are going to need to learn how to leverage AI to produce basically more and better work. It’s a utility, it’s not a replacement.

CC: Yeah, I liked how you phrased that. I think that that’s a good perspective for employers, for writers, for anyone who is worried about the job climate right now, I think that’s a good way of looking at AI.

BS: And as of right now, we know that AI is being used to generate articles on the web. There are a lot of websites that are using AI to just basically pump out post after post after post, article after article after article. And you can tell immediately once you start reading it that it was not written by a human.

CC: And at the end of the day, it’s still humans connecting with humans. So whatever content we’re putting out there, it needs to be valuable to people that are reading it. It needs to have a purpose, it needs to be doing something. It needs to just be humans communicating with humans. So those big content pumping blog posts, all that kind of stuff, that does bother me because it’s just content for the sake of getting content out there. And there’s humans at the other side that actually need information. So I think this is a really good perspective to have for how to leverage AI in the same way that we’ve leveraged machine translation, how to automate processes, how to have a starting place for people when you’re writing, but not to just make it all about machines and not people. So Bill, is there anything else that you can think of when you’re thinking about machine translation? Any other comparisons between that and the rise of AI? Anything else that you wanted to share before we wrap up today?

BS: I’d say approach it both optimistically and cautiously.

CC: Yeah, that’s really good, especially with the concerns that you mentioned about copyright. We do have an article that Sarah O’Keefe wrote and recently updated as well about AI and the content lifecycle. So we’ll post that in the show notes. Also, some other interviews and information that we’ve provided about AI. So all of that will be linked in our show notes. And Bill, thank you so much for joining the show and talking about this today. I wasn’t in this space while machine translation was happening. It’s really interesting to hear about the parallels because they really are very similar in a lot of ways, and it’s cool that we have some takeaways from both.

BS: Thank you.

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 How machine translation compares to AI appeared first on Scriptorium.

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 start to scale. This is a free collection of insights from leading industry experts that will be available in October of 2023.

“This is going to be a free book. We are not going to become rich and famous with this book because we decided that we wanted to make the content in the book accessible for everybody who is interested in learning about content operations. It’s going to be published as an open-access book by Virginia Tech Publishing.”

— Dr. Carlos Evia

Related links:

LinkedIn:

Transcript:

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

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 ContentOps Edited Collection: Content operations from Start to Scale. 

Hi, everyone. I’m Sarah O’Keefe. I’m delighted to welcome Dr. Carlos Evia to our podcast today. Based at Virginia Tech, Dr. Evia is a Professor of Communication, Associate Dean for Transdisciplinary Initiatives, and Chief Technology Officer in the College of Liberal Arts and Human Sciences. He’s also Director of the Academy of Transdisciplinary Studies and affiliated with the Virginia Tech Centers for Human Computer Interaction and Communicating Science, and also a member of the Stakeholder Committee for the Virginia Tech Center for Humanities. In his copious free time, aside from these things, he has been involved with work on DITA standards and especially the Lightweight DITA initiative. So Carlos, welcome aboard. I’m glad you found 20 minutes or so to join us here.

Dr. Carlos Evia: Hello, Sarah O’Keefe. It’s been a while, so good to catch up with you.

SO: It is good to catch up with you. So tell us about this new content ops book. You spearheaded it and I guess I should mention that I about a million years ago, contributed to it. I don’t actually remember what I wrote, so this could be a problem. So tell us about the book.

Dr. CE: Well, it’s new. It’s new to the world because it’s coming out next month and by next month, I mean October of 2023. But it’s a book that has been about 10 years in the making. And some sections of the book really read like creative nonfiction because there are characters that are people in real life and surprise, you are one of those characters. Because the idea for the book started some 10 years ago when we will meet at conferences. And I don’t even remember what happened first, if I invited you to come visit my class here at Virginia Tech or if I saw you at the STC summit, and I was like, “Oh, wow. She’s very smart. I have to invite her to come to my class.” But I don’t know, I guess we were already chatting and talking to each other. I cannot claim that we were friends. I would dare to say that now we’re friends. We’ve had many meals together, family involved, so I guess that counts as friends.

SO: I certainly hope so.

Dr. CE: So you and Alan Pringle in Scriptorium published a very handy book that I used for many, many years in my classes, Technical Writing 101. And you had three editions?

SO: Yeah.

Dr. CE: Yeah. So after the third edition, I started chatting with you on Twitter, when it was called Twitter and not X or whatever it’s called now. And I said, “Oh, wouldn’t it be nice if we write a new version of that book because I have been using it in my college level classes for many years and I have ideas on how to expand it, how to improve it.” And we have been talking about it for many years. And then finally before the pandemic in 2019, we were together at a conference in your neighborhood. It was in Durham. And we sat down and we said, “Okay, let’s finally start thinking about it.” And we made an outline and then we both realized that we could not call ourselves technical writers and that we could not write another edition of a book called Technical Writing 101, because what we were doing was way more than just technical writing.

Yes, of course, what paid the bills was doing technical writing, but you were doing more sophisticated things. I was teaching more sophisticated things that were not just writing about technical subjects. So we brainstorm about many ideas on what do we call it? And we ended up with how about content operations? That’s a thing, and people are talking about content ops. And then the pandemic hit. And when the pandemic hit, everything stopped. And I remember that we had nothing better to do. We will get into endless Zoom conversations, and we started inviting people and we invited Patrick Bosek to chat with us about it. And he said, “Wait a minute, if you’re talking about content operations, we have to bring Rahel Bailie.” And we brought Rahel.

And I guess at the time the idea was that we were going to have a book with four authors and you were going to write some chapters and I was going to write some chapters and Rahel was going to write the introduction and Patrick was going to write something. And then we were like, “What if we invite more people?” And we started making a list of topics that we wanted to cover and we ended up inviting more people. And this is where we are. The book became an edited collection with several chapters written by experts in industry who had something to say about how content operations is impacting the work that they do, not just in our home neighborhood of technical communication, but also in marketing and other forms of more persuasive content.

And finally, the book after those delays, and there were a couple other delays that we can talk about later and we will talk about those later, finally, it’s coming out next month. And I was able to see a draft of the cover. I think I shared with you the draft of the cover and yeah, it’s coming out. Oh yeah, important thing to mention. This is going to be a free book. We are not going to become rich and famous with this book because we decided that we wanted to make the content in the book accessible for everybody who is interested in learning about content operations. So it’s going to be published as an open access book by Virginia Tech Publishing.

SO: So I think this means that if you want an electronic copy of it, it will be freely available. And if you insist on print, then presumably people will have to pay to get the actual physical print edition.

Dr. CE: That is correct. And I don’t think the print version will be an on-demand print service, and it’s not going to be very expensive. But there will be, I think, EPUB and PDF versions that would be downloadable from the Virginia Tech Publishing website.

SO: And I appreciate that Virginia Tech Publishing did this because of course, academic publishing is notorious for these $500 science textbooks and they’re apparently doing it all wrong, and I appreciate that. So this is great.

Dr. CE: We didn’t want to go in that direction on purpose because we know based on the kind of books that you have published with Scriptorium, the kind of work that I have published about DITA and Lightweight DITA, that we have readers in parts of the world that they just cannot buy a book, but they’re very interested in these topics and that’s why we, and I appreciate that you and all the other people who made contributions to the book accepted and signed the agreements to have this be released as open access with awareness that there won’t be any sweet money coming to you in royalties for the chapters that you contributed to this book.

SO: Well, I’ve done a number of commercial books that had royalty agreements associated with them, and I can assure you that the delta between that and what we’re doing with this book is far smaller than you might hope. I mean, it’s never been a big moneymaker. So in addition to Rahel and Patrick, I don’t want to leave anybody out, but I did want to mention that we brought in Kevin Nichols to talk about customer experience in content ops. Jeffrey MacIntyre is dealing with personalization. We’ve got Loy Searle on localization and content ops. Kate Kenyon did a really good chapter on governance, and then we’ve got some really interesting forwards and epilogues and afterwards from some other luminaries in the industry. So it was a really fun project to work through.

Dr. CE: Yeah, I’m very grateful that it started during the pandemic, and I will just email people that some of them we knew from conferences, some of them we didn’t know, and somebody will make a recommendation and I will knock on their virtual doors and be like, “Hi, I have this project that is going to be free and you won’t be making any money out of it, but people will know about content operations. Do you want to write something?” And they said yes. So that was very generous.

SO: So the intent here is to put a stake in the ground and sort of say, “Okay, this is what we think.” This is where we think content operations is and what it is and how it connects to all these other aspects of content, of I want to say communication, but what it looks like to have a content lifecycle that has all these tentacles into all these other pieces and parts. Customer experience is a great example because once you know what your customer journey needs to look like, you can connect that to, and thus I need this kind of content and therefore I need this kind of a content lifecycle. Who’s the target audience for this? Who do you think should be reading this book?

Dr. CE: Well, the way that we started conceiving the idea and what eventually became the book, and it goes back to when I first met you and I invited you to come and visit my class. And again, you were very generous to drive all the way from Durham to Blacksburg to talk to a class of 20 students who were learning about DITA. And I didn’t pay you, I just bought you dinner, and I really thank you for that. That was like, gosh, how many years ago, 13 years ago or something like that.

When I was learning and putting in practice the things that I learned when I was in graduate school and also my experience being a technical writer in industry, I always applied the things that I knew to my classes and I was reading and doing the traditional approach of exposing myself to new ideas, going to conferences. But I realized early on in my career as a professor, which I’ve been doing this gig for like 23 years now, don’t tell anybody, that one of the best ways to bring fresh ideas into the classroom was to invite guest lecturers.

And in particular, in the case of technical communication and the type of technical content enabling content that we do, I realized that bringing guest lecturers from industry and particularly consultants was the best way, in my opinion, to expose my students to practices and knowledge that were not in written textbooks, that were not even in academic journal articles because that was not the work of people who were in academia. So I think the book is structured like that, is the equivalent of a guest lecture. Somebody who comes to your classroom, in the case of people in academia, and is going to be presenting their ideas and give you some pointers on how to implement this into your content work.

And on the other side of the spectrum, we have people in industry, and this will also be the equivalent of having somebody who is a guest and comes to give a presentation about a new topic that people might be interested in. And from the work that Rahel and I were doing for a couple of years when we were working on our chapters for the book, we realized that there’s a lot of interest from many corners of the content universe on the topic of content ops or content operations, be it because people think that is related to dev ops or design ops or many other ops that are out there, or because people want to get an operational model on how to tackle enterprise level content.

So if you’re in academia, what I hope is that this book helps you expose your students and yourself to perspectives from experts in industry when it comes to technical content and marketing content and many other aspects of persuasive and enabling content. And if you’re in industry, I hope that this also helps you continue your learning or start expanding your learning on topics related to the content lifecycle that go beyond just planning how to do things in a content strategy, but really developing a good governance model for content operations that really keeps everything, we hope, under control, but we know that things are never going to be under control, and that’s when we are probably going to have to write a new book in a few years.

SO: Well, yeah, I mean, it’s funny that you talk about the intersection of academia and industry or practice. I mean, first of all, I live in Durham, North Carolina, so Virginia Tech is actually not that far, and it’s this really pretty drive through the mountains. So no particular trouble there. But I think the really important thing about this is that the work that you’re doing at Virginia Tech paying attention to this question of how do we apply, how do we look at what people are doing out there in the world and then intersect that with the rigor of the academic inquiry and practice and all the rest of it, I think is really important and unusual.

There’s not actually very many professors. There’s a few, but there’s not very many academics out there that are looking at this kind of information through a practical lens in addition to the study of rhetoric and all these other underpinnings that I think are important to the practice of whether it’s technical communication or any kind of communication. So I’m always happy to come and talk to students. They have a habit of asking questions that I can’t answer because they are much better grounded, really, than I am in the theory. I know an awful lot about how to make things happen, but anything I’ve learned about the theory that’s underlying it is kind of incidental to what I’ve done.

So it’s always interesting to hear those voices and hear people talk about the research that they’re doing, especially the grad students, but everybody, and the questions that they’re asking as they’re getting all this foundational learning. And you talk about being a professor for a while, it is very, very unusual for somebody in our age cohort to, we’ve had a longstanding argument about who’s older, but we won’t get into that just now. But we fall into the same generation certainly, and I think our birthdays are like a year apart or something dumb. And I think we decided I’m older, although for a while I thought you were older and that was awesome. Anyway.

Dr. CE: That might be correct.

SO: But the thing is that for us, a generation ago when we were in school, in college, there wasn’t a whole lot of any of this. There wasn’t really the study of TechCom or, I mean, there was certainly rhetoric but not rhetoric as applied to TechCom and enabling communications. And so people like me tend to be very poorly grounded in the academics and the preceding research that has gone into this. So I appreciate being able to do that. So how do you define, what’s your best definition of content operations and how that fits into the world?

Dr. CE: Well, the book actually borrows Rahel’s definition, that I think I have a coffee mug here with her definition that she mailed me. And she talks about you have your content strategy, and I guess at this point, people kind of know what a content strategy is. I think the listeners of this podcast need to know about content strategy or maybe they’re interested in content strategy. And that’s the plan of how do you develop, maintain, publish, sunset or revitalize content. So Rahel’s definition says that content operations is the implementation of that strategy.

So it’s like a good example that she has been using for years is that think about if you’re an architect and you make the blueprints for a house, that’s the strategy, that’s the plan. But ain’t nobody telling you in those plans how to live in the house, that you have to change the air filters of the air conditioning, that you have to clean the toilets. Nobody’s telling you that. So that’s the operational part of it, and that’s the content operations component. Other people, sometimes I’m in that camp, see content operations as bigger than that and including the process of developing, implementing and revising the content strategy.

So I think it’s a combination of knowing who is available, what is available in resources and what is missing or what’s needed to really keep a healthy lifecycle of content. That includes the planning, that includes the actual writing, creating, I was going to say filming, but nobody uses film anymore. The actual recording of videos and audio and the publishing and the evaluation assessment and then making new versions or just putting to sleep content that nobody cares about. So it’s really about how to live in that house that you created with all the daily and monthly and yearly transactions that need to happen that when they sold you the house, when they sold you the idea of the house, those were not considered. But based on the work from experts like you and the people who wrote chapters for the book, we are offering these lessons that say, “Hi, we have lived in houses and we know how to take a look at those operational components that you might not even consider now that you’re starting your strategy.”

So I think that’s a complicated way to tell you what I see as part of operations, but it’s heavily influenced by the work of Rahel Bailie, who was very generous to write the introduction to the book. And then last year when the book was almost ready, this close to being ready last year, Rahel and I sat down and said, “This is missing something. It’s missing a chapter that talks directly to content developers, not their managers, not people who are at the high level of strategy or the high level of governance, but people who are actually going to create the content. How does content operations can help you or create challenges for you?”

So Rahel and I went into a months’ long adventure of writing this long chapter that at one point we decided this might be a separate book altogether, but we created this new chapter that is included now in the final version of the book that is speaking directly to people who are going to be creating content. And how thinking about the work that you’re doing as part of a system and not just, “I’m here in my lonely cubicle or working from home because hashtag remote work forever and I don’t talk to anybody else.” So I think that’s the whole process of thinking about operations in a systems approach.

SO: Yeah, that’s interesting. And I think that looking back at some of this stuff, back in the olden days, there was really this concept that as a content creator, technical writer, whatever, I had ownership of a particular book or document or set of documents, but it was like, I’m the writer of the admin guide and you are the writer of the user guide, and I’m going to go learn admin things and write them down, and you’re going to go learn user things and write them down, and then we’re going to have this big complicated print production process. And I know an awful lot of things about press checks and blue lines that I haven’t used in 25 years. I used to know things about blue lines and press checks. But I think one of the reasons that we really need content ops is because the concept of authorship has fragmented, right?

I’m not writing a 500-page admin guide. In fact, it’s pretty unlikely that the organization is writing a 500-page admin guide. We might be writing 500 topics worth of admin stuff, but I’m writing a hundred of them and you’re writing a hundred of them and a couple of other people are contributing bits and pieces. And then we put it all together as the sort of, here’s the help for the admin person, and we put it online.

So the print production process is gone, the press check process is gone, the physical production is gone. And we are fragmented in the sense that nobody has the overarching view of what is this set of content. And because that doesn’t exist, because there’s not me as the owner of this book, which, by the way, from a psychological point of view, introduces a whole set of other complications. But because that owner doesn’t really exist anymore, our systems have to be better so that the five of us, or the 27 of us that are all writing three topics can contribute in a consistent and useful manner. Your systems don’t have to be as good when you’re relying on individuals, single individuals.

Dr. CE: And it might be that the system has people who are in charge of ensuring that the user experience of those who need the content is going to be good and satisfy the information needs. And that’s not the job of the developers. I mean, as the writer, as the creator of videos or audio, it might not be your job to ensure that whatever website, app, product that comes out of that machine that generates the content is going to satisfy the needs of a human being. And it might be that it’s not your job as the creator to be in charge of managing that whole process.

So that’s why the systems approach of thinking and being aware, it doesn’t have to be that happens at the big enterprise level, as you know, because that’s the job that you do every day at Scriptorium. Even small organizations, I don’t want to say corporations, have adopted these models of creating reusable chunks of content that you create. And based on the metadata and the connections that they have behind the scenes are going to be reassembled in different deliverables for the needs of different audiences and in different contexts and in different models.

So it’s not just the work of a lonely writer. It’s a combination of approaches. And I think that content operations really takes a look at that lifecycle. And like you have said before, not every implementation of content operations is going to be super high-tech and mega efficient. You might have your content operations approach that is based on the budget that you have and the scale that you have. And it might not be the prettiest, but at least you have an idea and you want to have, not that you can always achieve that, but you want to have some sort of control over your content publishing structure instead of letting whatever, I’ll just write a piece of paper and see how far it goes if I send it like a paper airplane. So yeah.

SO: So you mentioned the machine and the systems, and I don’t think we’re allowed to have podcasts this year without talking about AI. So do you think that the, I’m trying to avoid using the word fad. Do you think that the rise of AI, and especially this sort of 2023, all of a sudden AI is everywhere and everything is AI-enabled and everybody’s talking about AI, do you think that’s going to change content ops? How is it going to change content ops? What do you think?

Dr. CE: I think it has already changed it. Remember I told you that there was a couple of moments in which we had stopped the publication of the book and revised it. Well, the first one was, I told you, Rahel and I decided that we wanted to write a chapter that talked directly to content developers. And the second one was that Patrick Bosek and I and you were in one of those meetings, we sat down and we said, “We cannot publish a book on content operations without talking about AI and particularly ChatGPT,” because it was the boom of everybody’s talking about ChatGPT and all the conference presentations were about ChatGPT. So the book was already going to print when we said, “Wait a minute. We need to open it and revise Patrick’s chapter, which is about the technology that supports content operations and include a statement about ChatGPT.”

So I honestly think that artificial intelligence has already impacted and changed the work of content operations. It might not have affected, like you said, all the content operations implementations of the world because some might be with limited budget and limited scale. But I think that there are many use cases that are happening right now.

The main consideration is this. It’s not about learning to use the tools. It’s not about seeing how much money you can invest into having AI create your content. It’s about, as the person who supervises and is in charge of the whole operations or the persons, if it’s a large team, consider the ethical implications of using artificial intelligence and decide, “I’m going to use AI for this, to summarize this, to create this. What are the possibilities that by doing this, I put some of my users at a disadvantage? What are the implications of by doing this, I’m going to completely run my bulldozer over the diversity of my readers, of my users, and I’m going to have damaged their perception of their interactions with whatever information products I’m creating.”

So I think the big conversation has to be not is AI going to impact content operations or content because it’s already impacting it, but how do we supervise and bring this into the cycle of content operations in an approach that doesn’t leave people at a disadvantage? And it might be that doesn’t leave content creators or content managers at a disadvantage, and it’s concentrated on the ethical perspectives, on the use, implementation and feeding of artificial intelligence tools. So I think that’s where the conversation is really going to go in the near future.

SO: That’s interesting. And I think additionally to that, the question of trust and reputation. If you develop a reputation for generating junk because I asked ChatGPT to write my bio and it made up a bunch of stuff, and then I just used it because why not? But it seems to me that this is going to, and we’re already seeing search degrading because of all the AI generated stuff. So I think in addition to the ethical issues, there’s some really, really interesting questions around whether the efficiency that you get out of generated content, is the plus of gaining that efficiency greater than the minus of the trust and reputation problems that you’re going to have if you’re not very, very careful? I mean, you could generate it and then you can review it and clean it up and fix it, but you just gave back your efficiency gains. So then is it really a net positive?

I do think that gisting and summarizing can be very useful, but I have some real concerns about when you go in and you tell it to tell me how to operate this medical device, first of all, people don’t use Chat to ask it how to operate a medical device. But if and when you do, be careful because it might make some stuff up. And I can’t remember where this was, but yesterday I heard somebody say that, on a podcast I was listening to, and when I figure out who it was, I’ll dig it out and I’ll put it in the show notes, but essentially that when we create enabling content for new products, we are in the business of creating new content and ChatGPT does not do a very good job of creating new content. It only reissues what it has. And so if you’re creating something brand new, somebody has to do that work. And I don’t think the person or thing doing that work is going to be an AI-enabled large language model.

Dr. CE: There are many tests and forms of evaluating the content created by human beings or created, I mean, it’s not really created, it’s assembled by artificial intelligence. But I am old school when it comes to some of my metrics. And I know that some people have challenged this, and I know that some people have come up with better approaches for evaluating the content, the quality of technical content. But I go back to IBM’s Developing Quality Technical Information, and I want to be sure that the content either created or written or produced by human beings or by artificial intelligence is easy to use, easy to understand, and easy to find. And I send people back to reading the second edition of IBM’s DQTI.

And that is pretty valid today because you can have a machine generate paragraphs and paragraphs of content, and you can have very nicely machine-generated DITA tags that give it some structure. And you can have ChatGPT help you do the XLT to do a beautiful HTML5 transformation. And your content might look like it’s good, but it has to be measured by is this really helping human beings? Because otherwise it’s just garbage regardless of how pretty the code behind the scenes is, which is not necessarily that pretty because ChatGPT doesn’t know much about DITA and it doesn’t know how to establish the difference between a task and a general topic. But that’s a conversation for another day.

SO: And I mean, that’s probably a good place to leave it. I think we’ve raised more questions than we’ve answered.

Dr. CE: That’s what I do.

SO: But the book is going to be out shortly, we hope. So October 2023. And we’ll include a link in the show notes that will point you over to wherever it is that you’ll be able to order or pre-order it from. So we’ll set all of that up. I remembered who it was that talked about new content. It was Jack Molisani in our podcast from a couple of weeks ago, so I’ll add that link. And Carlos, thank you. This has been really interesting as always. Glad to see you. And sounds like we need to talk some more about what’s going on here.

Dr. CE: Yes, indeed. Thank you very much, Sarah.

SO: Thank 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.

The post ContentOps edited collection: Content operations from start to scale (podcast) appeared first on Scriptorium.

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 practices for integrating AI in your content operations.

“As a company and as a content producer who’s publishing content, you are responsible for that content and you cannot rely on an agent to produce completely accurate information or information that is always correct.”

— Stefan Gentz

Related links:

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Transcript:

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

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 welcome Stefan Gentz from Adobe. Stefan is the principal worldwide evangelist for technical communication. He’s also a longtime expert in the space with knowledge of not just technical communication, but also localization and globalization issues. He’s here today to talk about the opportunities and applications of AI in the context of knowledge content.

Hi, everyone. I’m Sarah O’Keefe. And Stefan, welcome.

Stefan Gentz: Hello, Sarah. Nice to be here and thanks for inviting me.

SO: Always great to hear from you and look forward to talking with you about this issue. So I guess we have to lead with the question of knowledge content. What do you mean when you say knowledge content?

SG: It depends a little bit on the industry, but generally, there’s enterprise content and there are multiple areas in enterprise content and we all know marketing content and that beautiful content on marketing websites and advertising and so on, but there’s also a huge amount of other content in an enterprise and what kind of content that is is a little bit depending on the industry and which sector we’re looking at. But they also share a lot of content, which is produced across multiple industry verticals.

If you look at software, hardware, high-tech like semiconductors and robotics and so on, we have content like getting started guides, user guides, administrator guides, tutorials, online helps, FAQs and so on. But we also have things like knowledge bases, support portals, maybe API documentation, and you will find similar content in the automobile and industrial heavy machinery industry where you also have user manuals, maintenance guides, things like that, but also standard operating procedures, troubleshooting guides, safety instructions, parts catalogs and so on.

And when we look into industries like BFSI, banking, financial services and insurances, we have content like regulatory compliance guidelines. Of course, also policies and procedures, but also things like accounting standards documentation or terms and conditions, and again, knowledge bases and support portals, training portals for employees, et cetera, or partners.

And in healthcare, medical pharma, we have a lot of similar content, but we also have things like citation management, clinical guidelines, the core data sheets, CDS, dosage information, product brochures, regulatory compliance guidelines again, SOPs, maintenance guides and so on. And we have in other industries, things like installation guides, user guides, flight safety manuals in aerospace and defense, technical specifications of products, kinds of products and so on.

So there’s a huge amount of enterprise content that is produced in companies and marketing content is probably just a fraction of the content that is produced in other departments, like classic technical documentation, training departments, and generally, also as I just said, knowledge content producers or I think you originally mentioned product content which also fits, but I like to call it knowledge content because it’s a very broad term that covers not only knowledge basis as many people think, but all the content that carries and transports knowledge from the company to the user of that content.

SO: Yeah, I’ve also heard this called, I think we’re all searching for a term that encompasses the world of… It’s almost like not-marketing, not persuasive, the other stuff, other.

SG: Non-marketing content.

SO: I’ve heard it called enabling content in that it enables people to do their jobs, but of course, enabling has some pretty not so great connotations.

Okay, so we take your knowledge content and we wanted to talk about what it looks like to apply some of these recent AI innovations into the context of knowledge content. So what are some of the opportunities that you see there?

SG: There’s a huge amount of opportunities for companies using AI. Maybe we can break it a little bit down into two areas and let’s not talk about creative gen AI, like Adobe Firefly or Midjourney or so that are engines that are used to produce visuals, images, and graphics, but let’s talk about the written content here.

So I see two areas there and one is the area of authoring where content is created, and then there’s the area where content is used and consumed, whatever the consumer might be, maybe chatbot or chatbot interacting with an end user, or maybe even other services that use the content. And we can, of course, when we think from the content consumer perspective, a chatbot is definitely an area where AI can help to find content better and give better answers and maybe also rephrase content in a way that is appropriate to the content consumer. If I’m talking to, let’s say, 10-year-old children, or if I’m talking to a grownup with a university degree, they might have different expectations in how they want to get the content presented to them in terms of language, in terms of voicing, voice and sound.

SO: Right. The 10-year-old understands the technology and you don’t have to explain it to them.

SG: That might be, of course, true. Yeah, maybe they don’t even need the chatbot. So that’s the content consumer perspective, which AI can help to find better results, more fitting results, and produce nicer answers.

But there’s the other field where content is created with authoring content, and I see a lot of opportunities there. And at Adobe, especially in Adobe Experience Manager Guides, our DITA CCMS for AEM, there, we are implementing a lot of AI functionalities. I’m not sure how much I am allowed to talk about that, but we showed a couple of things at the last DITAWORLD, Adobe DITAWORLD in June where we presented some of the features that we’re implementing into AEM guides, into the authoring environment.

And one is, for example, the engine checks the content that an author is creating and compares it with the repository of content that is already there. And then makes suggestions like, “Oh, I understand that you’re trying to write that safety note, but there’s also a small snippet of content with a standard safety note in your company that maybe you want to turn that what you’re currently writing into a content reference, con reference, or maybe that single term that you’re writing there, you could turn that into a key ref because there’s already a key definition in your DITA map,” things like that.

So to assist the author to leverage the possibilities that their technology writes in a more intuitive way, instead of thinking for maybe minutes, “I remember I had written a note for that already, or I had already written that safety note,” the system will assist you with that and give you the suggestion, “Hey, this is already there. You can reuse that content.” That is authoring assistance.

We also showed, I think, some sort of auto-complete. So you’re starting to write the sentence and then a small popup comes up giving you a couple of suggestions how you could continue the sentence. And we all know this predictive typing thing for quite a few years, but usually, they are more created on classic statistical engines that try to predict what you want to write. But our solution there will take the repository of content that is already there in the database as a base for making suggestions that will fit much better than just a statistically calculated probability, how you probably want to continue the sentence.

So this kind of authoring assistance with auto-complete and predictive typing, that gets much better when you have an AI engine that understands your existing content and can build these suggestions on top of that. That is definitely one area.

SO: We’ll make sure to include a link to that presentation, which I actually remember seeing, in the show notes. So for those of you that are listening, it was at DITAWORLD 2024 and-

SG: 2023. You’re quite ahead to the future.

SO: I’m sure there will be an AI presentation at DITAWORLD 2024, however-

SG: Oh, I’m very sure. Yeah.

SO: Yeah. So this year, the 2023 presentations had this demo of some of the AI enablement that’s under development, and we’ll get that in there for you.

SG: Yeah. So these two areas are definitely areas where AI will help authors in the future, but there are many more things. For example, when you think in terms of DITA, you have that short description element at the top and an AI engine is pretty good in summarizing the content off of that topic into one or two sentences. And if you try to do that as a human being and you have your topic in front of you with maybe 10 paragraphs, a couple of bulleted lists and a table, and then trying to find two sentences that are basically the essence of the topic and making two nice sentences, “This topic is about dah, dah, dah, dah, dah,” that is quite hard for a human being, and an AI engine can do that in two seconds.

This is another area where AI will help people to get that job faster. And of course, they can then take that suggestion or not or rephrase it and rewrite it if they want, but they can take it as a starting point, at least. Short description summarizing the content.

It’s also rewriting content, maybe for multiple audiences. Originally, a couple of months back, I bought a tumble dryer from a German company for household appliances, and they have that classic technical documentation that comes with a tumble dryer explaining in long written sentences how to use it. And there are better concepts sometimes to do that. For example, a step list. And I copied and pasted three, four paragraphs there and said, “This is classic documentation. Can we write that a more simple way, maybe as a step list in DITA?” And then I got a step list with the paragraphs broken down, the steps that are ascribed in these paragraphs broken down into step list, step one, step two, step three, and so on. And that made the content much more consumable and accessible.

And so one could use AI here and say, “Okay, here’s my section in my DITA topic, for example, with the legally approved official technical documentation content,” and then I just duplicate that and let it rewrite as a step list maybe for the website. And then I could even duplicate it again and say, “Now let’s rephrase that for multiple audiences,” and say, “Okay, I have that TikTok generation person in front of me and they want to be addressed in a more personal, more loose language, more fun language, and please rewrite that content for this audience.” And then the engine will rewrite that content and say, “Yeah, hey, yo, man, you can put your dirty cloths into the dishwasher or into the tumble dryer, not the dishwasher. And you will have a lot of fun watching how it’s rotating when you hit the start button.”

And then you can change. That’s, of course, an extreme example, but you can create multiple variants of your content for different audiences very easily then. And I see that, and a lot of people are talking about doing that on the front end, on the website for example. I see that more from a responsibility perspective, on the authoring side when an author is doing that and approving it, so to say, maybe checking it if the information is really correct, the steps are really in the right order, whatever, and then it goes checked for different audiences into the publishing process in the end because that responsibility is, I see that not on the AI engine, I see that on the author who needs to make sure that the content is still accurate and correct.

SO: And I think that’s a really important point because at the end of the day, the organization that is putting out the product and/or the content that goes with the product, they can’t say, “Oh, I’m sorry. The AI made the content wrong. Too bad. So sad.” I mean, they are still responsible and accountable for it, which actually brings us very elegantly into the next topic that I wanted to touch on, which is what are some of the riSOs, some of the potential challenges and red flags that you see as we start exploring the possibilities of using AI in our content ops?

SG: That’s a very important topic I think to talk about because even very advanced engines like ChatGPT come with certain challenges and problems. There is, of course, we just talked a lot about, is the information correct or is it inaccurate or is it maybe even just invented by the engine? Usually, people call that hallucinating by just generating content and it would continue to generate content as long as you want and it will invent things.

And I was throwing some content to ChatGPT and said, “I want to write a nice blog post or a LinkedIn article. Can you give me some quotes that fit to the content that I have provided you?” And it provided me five, 10 quotes that sounded like some CEO would have said that, and it was even giving some names. And then I was aSOing, “Is that person, John something, really existing? And is that a real quote?” “No, I invented that, but it might fit. It could have been said by someone.”

SO: It could be real.

SG: Yeah, it could be real. That was basically the answer that ChatGPT was giving. That comes with a huge problem because as a company and as a content producer who’s publishing content, you are in responsibility for that content and you cannot rely on an agent to produce completely accurate information or information that is always correct because it will always generate content and will not let you know that it generated that content.

It’s extremely difficult for a human being to even check that content and say, “This is probably correct, and this might be just made up, and this might be an invention from ChatGPT because it just generated on a statistical probability that this content will probably fit.” And that is a big problem. You don’t have that when you let ChatGPT write code like JavaScript or maybe even DITA XML. There, it’s pretty accurate because it’s based on a certain framework, like a DTD or a JavaScript standard document that explicitly declares or defines how something needs to be structured and which element can follow on which other element and so on. But for more loose content, it’s extremely difficult and good for an author to distinguish that.

And this is why I also say there’s no danger that human writers or content producers will get jobless because of such an engine. No, the role will change. Maybe we use these engines more to generate content, but we as authors become more the reviewer and the editor of that content. It’s a little bit like machine translation where you had a machine translation engine translate your content, but then you need to do post-editing to make sure that this content and the translation is really correct and that the correct terms are used and so on. And we will see a similar development with gen AI for text-based content for sure in the future when it comes to all kinds of content production, maybe technical documentation, maybe knowledge bases, et cetera.

SO: So then can you talk a little bit about the issues around bias and the ethics of using AI and where that leads you?

SG: An AI engine like ChatGPT, for example, is of course trying to create unbiased content, but we were talking about that. I don’t have an example for that, for written content now, but we were talking about that example from the lady who was giving a photo of herself and then aSOed then the generative AI engine, “Please make me a professional headshot photo for an interview letter.” And it created a nice photo with nicely made-up hair and some nice dress and so on with a nice background and looked very professional, like a professional headshot from a professional photographer. The only problem was that this photo was showing a person with blue eyes and blonde hair while the person who provided the original photo to be beautified was an Asian person with a different look.

And that brings that discussion of the bias of an engine. Maybe it was feeded and trained with 5 million photos of professional business people photos from a Caucasian background and maybe just 1 million photos from an Asian background and maybe even less from an Indian background or whatever. And then this engine is making statistical calculations and says, “You want to turn that into professional business photo? Based on my training set, my training data set, I will make you a Caucasian-looking person.” And that is a huge problem.

And this is where this governance of AI generated content will maybe even become a full job one day where we say we need to make sure that the content that an AI engine is generating is really appropriate and culturally sensitive and is not biased and taking all kinds of other factors into consideration, and maybe an AI engine is not yet able to do that.

SO: Yeah. So the question of what goes into the training set is really interesting because of course, it is a little unfair to blame the AI, right? The AI is, in its training sets, reflecting the bias that exists out in the world because that’s what got fed into it.

And I don’t want to go down the rabbit hole that is deep fake videos and synthetic audio, but I will point out that just earlier this week, I saw a really, really interesting example of an engine where somebody took a video of themselves speaking in English and talking about something. Actually, they were sort of saying, “Hey, I’m testing this out. Let’s see what happens.” And then the AI processed what they said, translated it and regenerated the video with them speaking first French and then German.

And so it was, I don’t want to say live video, it was synthetic video of a person who spoke in one language and who was then transformed into that same person speaking fluently in their voice in a different language that they do not in fact speak because the content was machine-translated, and then they used the synthetic audio and video on top of that to generate it.

I mean, my French isn’t very good. It sounded plausible. The German sounded fine. I heard one mistake, but he sounded like a fluent German speaker, and there wasn’t any obvious weird rearrangement. They somehow matched it onto there. It was quite impressive and it was fun to watch. And then you think about it for a split second, and you realize that this could be used in many different ways, some of which are good and some of which are not.

SG: Yeah. I mean, we had some really ugly examples here in Germany where some political party was using gen AI photos to transport a certain political message, and then it came out that these photos were not from actual events that they were claiming it would be, but were AI-generated.

So there’s a lot of danger in there, and we will also need to adapt as societies and human beings to get a better find feeling what is generated content and what’s not? That will become increasingly difficult, but at least developing the awareness that what we get presented as content, especially when it comes to images, that we’ll need to develop stronger than ever before. Photoshop is there for a long time. We all know that photos can be Photoshopped, but with this new approach of generative AI that this awareness becomes even more important.

But when we talk about ethics, I know we are running a little bit over time probably, but there’s another aspect in ethics that I see as something we need to discuss in more detail in the future. We feed the engines with content, existing content, and maybe it’s content that is even intellectual property of someone. And then this engine produces new content that is leveraging the knowledge of that, that is in that content, to produce new content. And then something, especially in the context of university content, research content and so on, who’s the owner of that content that is newly created? And whose intellectual property is it? And what is, if content is generated that is very clearly rephrased of existing content from some content that is maybe protected by licenses or so?

So there’s also this ethical discussion that we need to have and that will for sure maybe even need some regulation on the government level in the future.

SO: Right. And the answer right now, at least in the US is that if the content was generated by a machine, you cannot copyright it. That implies that if I feed a bunch of copyrighted content into the machine and produce something new out of the machine, that I have essentially just stripped the copyright off of the new thing, even if it’s a summary of the old thing or a down-sampling or a gisting of the old thing, the new thing is not subject to copyright unless there is significant human intervention.

So yeah, I think that’s a really good point because there’s a big riSO there. And there’s also the issue of credit. I mean, if I just take your content and say it’s mine, that’s plagiarism, but if I run it through an AI engine and plagiarize from millions of people, then it’s suddenly okay. That seems not quite right. Okay, so yes, tell us-

SG: A plagiarism engine that checks the content is probably very useful in the future, yeah.

SO: Yep. So lots of things to look out for. And I think it sounds as though, from what you’re saying, you see a lot of potential benefits in terms of using AI as a tool for efficiency and recombination of content.

So if you join me in, I’ve already moved on apparently to DITAWORLD 2024, so if you look ahead a year or so, what do you see as the opportunity here? How are companies going to benefit from doing this, and what kinds of things do you think will be adopted the fastest?

SG: I think coming back to the beginning basically, these two areas of authoring and authoring content, content creation and content consumption, and these are the two fields where companies can benefit and will benefit from the near future as soon as enough of these new features will have found their way into the tools themselves.

Faster content production is definitely one part, but that also means that authors need to learn how to create content with AI engines, the art of prompting as a keyword here, and to detect the voice and tone of generated content. It’s relatively easy after a while to identify, oh, this content was written by ChatGPT, for example, because the standard way ChatGPT is generating content is sort of always the same, and you can easily identify it after a while. This will give some job changes and means that companies will need to adapt to that before they can really benefit from it.

People, authors, and content creators need to learn how to get the right content out of an engine, out of prompting, prompt engineering, how to write proper prompts, and that will take some time and trainings and so on, but then it’ll really speed up the content production process a lot. And the second benefit is then with the content consumption, providing just better customer experiences by having more intelligent chatbots that provide better answers, right-fitting answers, maybe assisting users of a long blog post on a website with giving a small summary of that and things like that.

So there will be many benefits for companies using AI, just only when it comes to this specific area of content, knowledge content, but there will be other areas of course as well, financials, detecting patterns in financial data, and so on, for research and so on. There will be a lot of benefits, but when we talk about content, the content we are talking about here today, there will be mostly the biggest benefits will be probably content production, which also includes, for example, translation.

SO: Yeah, I think I agree with that, and that sounds like a relatively optimistic note to wrap things up on. Stefan, thank you so much for all of your perspectives on this. You’ve obviously thought about this carefully and you’re sitting inside an organization at Adobe that is actually building out some tools that are related to this, and I’ll be interested to see what comes out.

Tying back to that, the DITAWORLD 2023 recordings are available, and we’ll put those in the show notes. There were a couple of presentations in there, this was back in May, June, that addressed the state of AI and some of these similar kinds of considerations along with that. I’m not sure if it was exactly a demo, but there was a discussion of what the AEM Guides team is thinking about in terms of product support. So we’ll make sure to get that into the show notes.

Scriptorium has a white paper on AI and we’ll drop that in there, and then I think there will be more discussion about this going forward. So thank you again for being here, and we’ll look forward to hearing more from you.

SG: 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.

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