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Inside Applied Data Governance: Expert Perspectives from the ADGP Program Episode 2: Designing Governance That Works with John Ladley

DATAVERSITY Talks · 2026-06-25 · 25 min

0:00--:--

Key moments - from our scoring

Substance score

51 / 100

Five dimensions, 20 points each

Insight Density11 / 20
Originality9 / 20
Guest Caliber13 / 20
Specificity & Evidence10 / 20
Conversational Craft8 / 20

Data governance frameworks serve a practical purpose: they answer leadership's fundamental question of "what does this look like?" in clear, non-abstract terms. John Ladley, a practitioner and educator with three decades of experience who authored the foundational book Data Governance, How to Deploy a Data Governance Program, explains that frameworks are essential building blocks for organizations implementing governance for the first time. He emphasizes that practitioners often lack workflow design experience, making structured frameworks critical to the ADGP certification curriculum. Ladley stresses that 98% of governance success depends on handling the human and cultural elements of change. Organizations should start with existing operating models from industry peers rather than beginning from scratch - using tools like ChatGPT to find relevant examples. However, blindly copying frameworks fails because governance must reflect organizational culture and business model. Ladley criticizes consultants who plagiarize operating models across industries without adaptation, arguing this constitutes negligence. Whether adopting federated or centralized approaches, organizations must view these as labels for explaining their chosen model, not predetermined decisions. The framework must be culturally congruent, practically articulated, and defensible to stakeholders unfamiliar with governance concepts.

Key takeaways

  • →Frameworks must answer leadership's question "what does this look like?" in clear, one-to-two-page, non-abstract explanations of workflows, processes, and policies.
  • →Start with existing operating models from peer organizations in your industry, then adapt them to your culture - never design from scratch or copy frameworks without considering cultural fit.
  • →Federated versus centralized labels describe spectrum positions on a control spectrum, not predetermined architectural decisions made before understanding your organization's actual governance needs and culture.
  • →Culture accounts for 98% of governance success; ignoring it, providing only lip service, or implementing change without addressing the human element guarantees failure.
  • →Operating models must be flexible, evolve over time as capabilities are deployed, include real business metrics (not activity counts), and be articulated clearly enough that people unfamiliar with governance can understand and adopt them.

Guests

John Ladley

Topics in this episode

Operating modelsData governance frameworksworkflow designApplied Data Governance Practitioner (ADGP) CertificationFederated vs. centralized governanceOrganizational culture and change managementData governance body of knowledgeCapabilities mappingBusiness metrics for governanceConsultant practices and ethics

Questions this episode answers

Why do organizations need data governance frameworks?

Frameworks answer leadership's core question of what data governance looks like in clear, non-abstract terms, establish workflows and processes for people to follow once governance is operational, and prevent the harmful scenario of announcing policies as effective on Monday without explaining how people should adhere to them.

Should you copy another company's data governance operating model?

No - while you should reference existing models as starting points, directly copying a framework fails because governance must reflect your specific organizational culture and business model; even models from the same industry won't work as-is if your culture differs.

What's the difference between federated and centralized data governance?

Federated means distributing governance authority across the organization, while centralized concentrates it in the middle; however, these are just labels to describe where you place controls based on what your culture accepts and what's effective for your business, not predetermined architectures.

What percentage of data governance success depends on culture?

According to John Ladley, 98% of governance success depends on how you handle the people and sustainability side of change, making cultural alignment and addressing the human elements more critical than the technical framework itself.

What should organizations include in their data governance framework?

Frameworks should include flexible, initial operating models that evolve over time; capabilities mapped to deployment timelines; cultural alignment; clear communication about what the model means; and real business metrics tied to financial output or data initiative support, not just activity counts.

What our scoring noted

Our reviewer’s read on each dimension, with quotes from the episode.

Insight Density

11 / 20

The episode contains some valuable practitioner perspectives, particularly around culture, frameworks, and avoiding common pitfalls like copying consultants' models. However, much of the content is conceptual and repetitive rather than densely packed with novel ideas. Key insights (culture matters, start with existing frameworks, align to your culture) are valuable but not groundbreaking, and considerable time is spent on anecdotes and general statements rather than concrete operational advice.

98% of your success is how you handle the people and the sustainability side of this, period.
You build the model that works for you... you create an operating model that has controls where culturally they're appropriate and effective for you.

Originality

9 / 20

The core message - that data governance frameworks must be culturally tailored, iterative, and practically grounded - is sound but not novel in the governance literature. The consultant-copying anecdote and the public utility case study add some freshness, but the underlying frameworks and principles recycled here are well-established (culture, governance operating models, federated vs. centralized). The episode reinforces conventional wisdom more than it challenges or reframes thinking.

everything I talk about is something I've done. In fact, I will not talk about something, or I will not relay a concept I've heard unless it's actually been tried in the field.
Don't do it from scratch. Take some material that is already there... Uh go if you're in an insurance company, go find another insurance company.

Guest Caliber

13 / 20

John Ladley is a legitimate practitioner with 30+ years in data governance, published author, and ADGP program contributor with real consulting experience at scale (public utilities, energy companies). However, the episode feels more like a promotional conversation for the ADGP certification than a deep-dive interview with a challenging guest. Ladley is positioned as an expert but is not meaningfully pushed or tested by the host, limiting the value extracted from his caliber.

I have been connected with the data corner of technology since the late 1980s
I am a practitioner. Uh, everything I talk about is something I've done.

Specificity & Evidence

10 / 20

The episode includes some specific examples (the $10 billion public utility with a two-layer centralized model, the consultant metadata mishap with Fred's Manufacturing vs. Amalgamated Insurance), but these are anecdotal illustrations rather than data-backed evidence. No metrics, timelines, financial outcomes, or comparative data are provided. The advice remains mostly at the level of principles and case sketches rather than replicable, evidence-based guidance with concrete numbers or documented results.

I've done operating models for big companies like uh an energy company, $10 billion public utility
And I look at the metadata on the slide, and it says Fred's manufacturing on it... it says Fred's manufacturing on it.

Conversational Craft

8 / 20

Barbara's questions are straightforward and competent but rarely probe deeply or challenge Ladley's assertions. There is minimal follow-up on contradictions, limited pushback on sweeping claims (e.g., '98% success is people'), and no meaningful disagreement. The conversation reads more like a structured interview designed to promote the ADGP program than a dialogue testing ideas. Questions are open-ended but lack sharpness; host accepts anecdotes without verification or deeper inquiry.

Are you ready to share your wisdom with us about data governance?
So the first thing, just tell us about you and um your role in data governance.

Conversation analysis

Computed from the transcript - who did the talking, and the words that came up most.

Most-used words

governance28data26culture18operating17model17important9understand9federated9certification8start8means8program7first6different6applied5real5

Episode notes

Welcome to Inside Applied Data Governance , a DATAVERSITY Talks podcast where we explore the practical realities of data governance with the experts who helped build the Applied Data Governance Practitioner (ADGP) certification. In this episode, we speak with John Ladley about designing data governance frameworks that actually work. Drawing on decades of experience, John discusses why governance structures must align with organizational culture, how to evaluate centralized and federated models, and why copying another organization’s framework rarely succeeds. Discover practical guidance for building governance approaches that are sustainable, scalable, and tailored to your organization’s needs.

Full transcript

25 min

Transcribed and scored by The B2B Podcast Index.

Hello and welcome to Inside Applied Data Governance, a podcast where the practitioners who built the ADGP program share what real-world data governance actually looks like. Whether you're just starting out in data governance or you've been working in the field for years, this podcast is for you. Will you learn real-life lessons and practical advice on the people behind the Applied Data Governance Practitioner Certification? To learn more about the ADGP Certification Program, visit training.

dataversity.net. I'm your host, Barbara Neshaw, and today we're talking to John Ladley, one of the key contributors to the ADGP certification, about designing governance that works. Let's jump right in.

Hi, John, and welcome to the show. Hello, Barbara. How are you? Good to see you again and talk about data governance.

Are you ready to share your wisdom with us about data governance? Well, I'm ready to answer questions. We'll see if that's if there's any wisdom or not. We'll try that one.

So the first thing, just tell us about you and um your role in data governance. Yeah, the role in data governance, I have been connected with the data corner of technology since the late 1980s, actually. And uh just kind of evolved along the way. Uh along the way, I got to a point in the mid-twos that the literature out there was abysmal.

Uh it was not useful. Uh, some of the literature we had was harmful. So I started to roll up my sleeves and wade deeper into it, less of a practitioner, more of a um educator, I guess, and researcher. And I ended up writing uh two editions of uh a book.

The long title is Data Governance, How to Deploy Blah, blah, blah, blah, blah, a data governance program. Um uh third edition is on hold right now due to AI and figuring out how to stuff all that AI stuff into the same number of pages we're allowed to have. So, but um, that's how I got into it. I, you know, I've been more than anything, I will tell people I am a practitioner.

Uh, everything I talk about is something I've done. In fact, I will not talk about something, or I will not relay a concept I've heard unless it's actually been tried in the field. And that's how I got here. Thank you so much for that introduction, John.

Are you ready to share your wisdom with us about data governance? Well, I'm ready to answer questions. We'll see if that's if there's any wisdom or not. We'll try that.

Oh, you have lots of wisdom. So let's start off um with such an exciting topic: data governance frameworks. But they are important. So, from what your perspective, why are data governance frameworks important for organizations?

One of the most common questions I get asked uh over the years is from leadership. And they go, This all sounds good, it all sounds like something we need, makes sense. What does it look like? And you need to answer that question in a very clear, non-abstract manner, uh, one or two pages, uh um 50 words or less type thing.

All right. You can't answer that unless you've designed some sort of operating framework, operating model, whatever you want to call it. All right. Um, so that's the first thing.

The second reason they're important is if your organization's never done this before, which would be the case if we're talking about doing the governance of data, then you sure as heck need to lay out what it looks like and show people what they need to do once you say we're we're we're in operation now, right? So um you're basically building workflows, um, maybe designing processes and and policies. Um you have to lay that all out. I still see it.

It's scary, but I'll still see someone say, Well, we wrote a bunch of policies, and on Monday, those policies are effective. By government, be careful, we're going to enforce them without any idea what that means. And and no explanation on how people can adhere to the policy or what it means anyway. So um that's why they're important.

Uh uh, it's a fundamental building block. Yeah, we spent a lot of time in the ADG body of knowledge on frameworks and building out your data governance uh program. Why was this so important to spend that much time on? Well it turns out that the typical practitioner um isn't real good at workflows, never had to do them before.

We've been very oriented in data, we've been very oriented in in non-processed related depictions. Um uh we've never thought about this gets handed off to that, that gets handed off to that, right? And so as a result, um we're kind of rusty at it. Okay.

So we had to put that in the in in the certification program. Right? We absolutely had to do that. It's not fair to say you're certified to do something and you haven't covered this stuff because you ain't certified if we ever covered this stuff.

Very important. You know, and in our last podcast, you talked a lot about culture. So the next question kind of relates back to that. Um, what do organizations or practitioners often misunderstand or underestimate about the role of culture in governance and building the structures?

Um well, there's two two things that happen. We will still see organizations that deny the culture discussion is relevant. I I was on the phone with someone earlier today uh who is still struggling with uh her leadership team and uh her peers and the level above her, and then the executive level. So we're talking third level down.

So we're talking high up in a very large organization. Um, and um getting anyone to listen because they don't think it's important. Um that's the big problem is culture gets lip service. Well, again, it's two things.

It it it it's you just ignore it, it's inconvenient. And I see that a lot, and that's what I was describing with this other person. Or you get lip service. Oh, yeah, yeah, yeah.

We understand that yeah, you go do that stuff, but that and that works until you say, now I need you to provide air cover while I go down a hall and tell someone to don't do it that way anymore. Okay. The you know the fact is it if you're going to govern data, it means you haven't governed it till now. I'm gonna apply Vulcan logic here, okay?

We have not governed, we are going to govern, therefore, something is different. Difference equals change. Don't tell me to do this without changing anything. Don't tell me to do this without addressing the human element of those changes.

It's not fair to people to do that. Right? So you have to understand that 98% of your success is how you handle the people and the sustainability side of this, period. Sure.

So important because people have to understand it and they have to fit it into their work. So, with that, think about that. What does it actually look like? You know, what does good look like?

And how do we move from the early stages all the way through to being mature? Well, if you're talking in terms of an operating framework or an operating model, a couple of characteristics. First of all, your initial operating models or frameworks are not your permanent ones. Again, you have to be light on your feet, you have to be flexible.

So you're going to start small and expand. You're going to leverage what you've learned within your culture and then tune it and move forward. All right. Um, you're going to deal with issues on a smaller scale with whatever protocol you've designed, and then correct that and alter that so you can deal with issues on on bigger scales as as they do that.

So um so from day one, you want to say things like, This is our operating model now. Here's our operating model in a year or two, or something like that. So so so first thing is you've got to understand that it's not just one picture. Okay.

Um, the second thing is that behind the details of the scratched out on a whiteboard organization chart thingy that we tend to do uh is has to be some thinking. You have to uh understand the capabilities you're deploying and at what time you're deploying them, and then match up your operating model to those capabilities. If you don't do that, if you just do this, oh, we need an executive middle and execution three-layer little triangle, zip sop, write some words on it. That's our slide, we're good to go.

No, go home. I I'm I I'm I like I said on the first uh uh podcast here, I um uh I don't have any time for that. I'm the old crabby guy. I I I told someone recently that if you worked for me, I was a consulting in an organization, I said, if you worked for me, I would have fired you today.

Do you understand that? She said, Well, I'm glad I don't work for you. I said, Well, yeah, it is a good thing you don't work for me because I explicitly told you don't do things a certain way. And you explicitly went and did them that way anyway, because you thought you you knew better.

You have done something anti-cultural. The culture does not want to hear those words from you. Those words are are hostile to your culture, but you just felt that you had to show off how smart you were, right? And I had a little trouble because that was outside of my statement of work, because my job's not to manage people usually, right?

Because as you can tell, I'm pretty bad at it. But or you're not. Yeah, any, yeah, uh anyway. Um, so uh flexible, aligned with capabilities, um, and measured, even one or two simple measurements, and not counts, not count how many people are in a meeting, not counting what's in the catalog, but you want to measure uh financial output uh associated with whatever program you're supporting or whatever data initiative you're supporting or something like that.

Um, a real honest to God business metric, okay? And that means that means you're on that road to maturity. The maturity after that is just expanding that. All right.

You just keep cycling through it. Right. Yeah, finding measurements that are meaningful interact. Mark, we get so many questions in our webinars from people trying to wrangle data governance.

I mean, some days it feels like everyone's wrestling the same dragon. Absolutely. And the first thing I tell them is don't do it alone. That's why Dataversity Training Center exists.

Real practical governance courses that take you from what do I do to I've got this. And you always drop the line about certification. Because it matters. The applied data governance certification shows you can actually turn governance into results.

It's like your governance badge of honor. And then we get to meet everyone at DGAQ plus EDW 2026 where governance nerds like us come to swap stories and solutions. If governance is your mission, start at dataversity.net.

What is one piece of advice you would give to someone responsible for developing their organizational framework? Don't do it from scratch. Take some material that is already there. I know I've got some operating model stuff in my books.

Uh, lots of other authors have operational things and their things. I would say start with something that's there, add the new capabilities you need to something, and then float it. See how it sticks, throw it up against the wall and walk it through with some people. All right.

Um don't ever draw it on a whiteboard, make it into a PowerPoint slide, and then say this is how it's gonna work. Because you're kind of dead on arrival. You know, you're messing with people's view of how work is done. That's the cultural part, right?

Because you can't do that, all right. So the piece of advice would be um uh uh don't start from scratch. Learn from other people's mistakes now. I mean, we've been at this now since the 90s, so 30-ish years.

Don't don't don't just start with a white sheet of paper. Uh uh go if you're in an insurance company, go find another insurance company. Sit down at ChatGPT or Claude and ask them, hey, do you have an example of an operating model for an insurance company for data governance? And you'll be amazed the juicy stuff you'll get now, right?

Yeah, I yeah, that's my advice. AI has definitely made our life easier. I remember when I used to spend hours and hours of research and still have to double check it all and everything, but I would spend hours of research, hours reading articles, and does a lot of that for me. It is it in that aspect, it's a wonderful thing.

Sure is. You know, we want to find examples and we want to not start from scratch. It's like you said, we've been doing this for a while. Yeah.

But people always want the easy way out. You know, why would it fail if you just copied somebody else's and brought it over and said, hey, I'm doing this as is. Because you haven't floated your culture by it. You know, I can have a bank here and across the street I have another bank.

Okay, I can have cogswell cogs and spacely sprockets, okay, and are floating in the clouds each other. And, you know, it's just it's from the Jetsons, right? Um, and they're both making stuff. They're making sprockets and cogs, all right.

Um, but they're both two different cultures. I mean, it it's it's it's not cartoon, it's not fiction that, you know, uh Mr. Spacely and Mr. Cogswell are both two entirely different people, all right.

And their companies exhibit two entirely different behaviors, even on a stupid cartoon. All right. Uh uh, so the bank on this side of the street is gonna have a bank on that side of the street, and they're gonna be you can't use the same one. You you've got to reflect cultural capacities and tendencies in in the operating models.

You you just cannot copy one. You know, I I have to do a quick sidebar here. The the the worst offender of copying stuff for frameworks are consultants. So you bring in, I guess I probably shouldn't name a firm, but I I I could name four offhand where they have been caught blatantly copying an operating model from another business, not even in the same industry.

Wow. And they didn't change the metadata on the PowerPoint slide. I mean, look, if you're gonna copy, if you're gonna be unethical, at least, you know, there's there's pride among thieves. All right.

I mean, at least clean up after yourself, wipe the prints off the gun, okay? But no, that they don't do that. And you know, so they are doing uh for amalgamated insurance, and there's a slide, and I look at the metadata on the slide, and it says Fred's manufacturing on it. And I go, and and I mean, come on, that you that means you're ignoring the culture, they they don't know what they're doing.

And I am really sad to say that uh they fail because you forgot the culture. Um and uh um and the worst offender of that, um I I just have to say it, I'm sorry, it's just due diligence on my part, are consultants. They they they're abysmal. I've told three clients in the last two years that they actually had grounds for a lawsuit.

I talked to a lawyer friend of mine for malfeasance for stuff. And these are firms, I don't dare tell you their names because these are big firms with big bills that they give you for stuff. And the material I've seen has been disgusting. All right.

So, in general, if you're gonna copy it, it's not gonna work for you. You're you're behind the the the the the curve. Specifically, if you have a consultant working for you and they copy it, get your money back. Definitely.

Yeah. Yeah. That's that is not a good business practice. No, and it's it's it's an epidemic.

Goodness. Things you just don't think about, but then find out later. No. Oh yeah.

Our next question How should organizations think about federated versus centralized models? Those are good labels to explain what you put on the board. But other than that, you build the model that works for you. So federated means you distributing some authorities out there, and centralized means the authorities in the middle.

And you know, you can use the metaphor of a Republican form of government like the United States is supposed to have, um uh, and uh a different form of government in another another country. Okay. And it's just where's the control and things like that. But you create an operating model that has controls where culturally they're appropriate and effective for you.

And the federated or decentralized is really a label. Say, well, our model, it looks like we're gonna be more federated than centralized here. So just and use that. Don't do this.

John, could you have a phone call with me? I do a class with someone and they say, Could you follow up? I go, yeah, I follow up. We get on the phone and says, Look, um, I work at you know, amalgamated consolidated industries, and and we're gonna do data governance, and we need to know now whether we're gonna be federated or or or central.

And I go, well, what else have you done? She goes, Oh no, we just started last Tuesday. And I went, you're throwing darts. No, no.

So how should you think about them? Labels to help explain what you're showing them. Period. Uh should based be based on your business model as well, and what's going to work for your company.

Yes. You do not start saying on day one, I think we're going to be federated, so let's design a federated model. No, you have no idea the extent of federation. This is spectrum.

You have no idea. I have look, I have I've done operating models for big companies like uh an energy company, $10 billion public utility generates electricity for millions of households in the United States of America. And their operating model has two layers. It is highly centralized.

And when I went in there, they said, Oh, we're going to have to have a federated model because we have a funky culture. And I go, what kind of culture do you have? They go, well, you know, it's typical for a public utility. Now, I happen to have worked with a lot of utilities.

I know that they are basically um uh medieval in their corporate structures. And I mean, they're serfs and vassals and warlords, all right. Um, uh uh in there. And, you know, and uh if you work at a public utility, you're smiling right now, and you're lying if you're not, you're lying to me if you're not smiling.

Okay. Um, it's a very rigid, rigid chain of command, all right. And their operating model was everyone's in charge and everyone else is doing crap. That was it.

That was our that was our data government. It was it would it was not federated at all, it was most tightly centrally controlled dictatorship of ever design, and it worked like a champ. Wow, because that's what that culture accepted. Okay.

Yeah. Again, culture is extremely important. Oh, yeah. Which might lead us to the next question, and our last one is what is one thing organizations tend to miss when selecting a framework?

Two things. One, we've already beat it to death in culture. You've got to come up with a way, and it might mean hiring somebody that actually has done organization development work and helping you uh um qual qualitatively depict your your culture. Okay.

Uh the other things uh that you uh uh tend to miss with um uh the framework is is it practical? Okay, you could have the most coolest, biggest, you know, your gigantic mega corp with five or six layers of things and communicating and all this stuff, and you said this is what's gonna work like a dream, but then you don't articulate that well enough, all right, or you don't justify it well enough, or it comes off um as um you didn't think it through. All right. So you you have to also understand the um the marketability of your operating model.

Um, so you know, you look at the culture, you come up with something that's culturally congruent, but it still might be incomprehensive to the people looking at it, because you know, a lot of people don't think about culture in their their jobs. They just know that's how things get done. And they might not understand it at all. They might have a different vision in in their head.

So so not explaining it well is is isn't is the other the other part of that problem there. So much of it goes back to communication and being able to communicate things the way someone's gonna understand it. Yes. Absolutely.

This has been very informative, John. Thank you so much for joining us today. I'm delighted to be here again. And uh if if you like what we were talking about, folks, uh sign up for that certification.

Uh it's not that if you put some new letters on your resume, you're gonna get a huge raise. But I will promise you you'll be a lot smarter than you were when before you started. That's some great advice. And for our listeners, if you'd like to learn more about the ADGP certification program and the applied data governance body of knowledge, visit training.

dataversity.net. Until next time, I'm Barbara Neshaw, and this has been Inside Applied Data Governance.

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