The Business Already Gets Governance — Data Leaders Just Aren’t Listening with Donna Burbank

Good morning. Good afternoon. Good evening. Good whatever time it is, wherever you are on planet Earth. I am so thankful that you’ve decided to join us today. We’re gonna have a great conversation.

We’re gonna be talking about governance and governance more specifically in the boardroom and how governance has become the topic in corporate boardrooms. How do I know?

Well, that’s gonna be the expertise of our guest today. I’m I’m thrilled that Donna Burbank is joining us. Donna has been active in the data and analytics space for a while. I’m not gonna say a long time because that would make that would make me old too.

But Dawn is extremely active in in our space. She’s the founder and managing director of global data strategy, which is a obviously focused services firm focused on data strategy. But not just data strategy, actual implementation, getting stuff done too. We’ll probably talk about that a little bit, but Donna and I have been orbiting the data and analytics sun together for for a while. This is the first time we’ve ever done this on a podcast, so thank you, Donna, for joining us today.

Thank you. I’m looking forward to it. Yeah. We seem to meet each other at random places around the world, but we’ve never done this.

So Yeah. I I know. I was I was thinking about that before before I jumped on. I was thinking about our last random encounter, which was on the Elizabeth line in London.

Like, randomly, I don’t even think we were at the same event, or maybe we were.

I don’t even get surprised anymore. I’m at some random airport. Oh, there’s Malcolm.

Yeah. Yeah. Well, that’s so for me, I don’t know if you know Sanjeev Mohan, but but that’s for me, that’s Sanjeev. Like, I could I could right now, I could probably just drop my headset and run to my local airport, and I’d see Sanjeev.

It just it just it just just it just is for whatever reason. But, no, it’s it’s it’s wonder wonderful we could finally do this. We’ve had a lot of conversations over the years about things, and and glad we could kind of formalize it. So, anyway, the genesis of this conversation and and the topic of today’s podcast is how governance is now front of mind for senior leaders.

And I’m not just talking about any senior leaders. I’m talking about the boardroom. I’m talking about the c suite. I’m talking about the people who are investing billions of dollars into venture capital and private equity to actually kind of drive software markets.

And again, how do I know this? Well, Donna had a chance to attend something called the World Economic Forum. So and where she was hearing about governance from these leaders. Donna, why don’t you what is the World Economic Forum for those who may may or may not know, and how did you find yourself at it?

Yeah. No. Great question. So, World Economic Forum, if folks, you know, don’t see it in the news pretty regularly, it’s in Davos every year, which is a lovely little ski town in Switzerland. And it it is the place where it basically, the name says what it is. It is the the forum where all world leaders tend to get together and sets the stage. They always have it in January.

And it really is kind of setting the pulse for what what the what what the world is seeing in terms of the focus is economics, but it’s also, you know, world hunger and, you know, you know, really trying to drive global change. And the topic is different every year. It could be global health. It could be manufacturing growth. Right? And these are presidents and prime ministers, generally CEOs of the major companies.

Major nonprofits are there, you know, Red Cross and things like that. And so I got the opportunity through a partner company of mine called The Digital Economist to go speak on data governance. And and sort of my my goal for myself this year, and and, Malcolm, I know you and I have talked about this a lot, we tend to sit in our own little silo and say, how come the business isn’t hearing us? Right?

Because we’re in we’re talking to ourselves about others. So I sort of say, well, what other forums am I not going to? When I got the opportunity to go to the forum that, you know, is really driving things, I I I took the chance to you know? And I thought I was asked to go speak that I was gonna go because we tend to do this.

I’m a data person. I can pick on us because I’m in the club. Yep. Sort of the hubris or whatever of saying, I’m gonna go teach people about governance, and and this is what we can talk about.

Oh, was I surprised. It was already top of mind. And what was disappointing is that our our people, our data management, our data governance, our master data management weren’t in the room. It was the platform vendors, the database vendors, and the AI vendors, but there was no one in the in the middle from the from the tech side representing.

I I was there. There were a few other speakers speaking about governance. But what was interesting, it was the business speaking about governance. So it would be a topic on ag tech, how we use AI for agricultural growth.

There’s something that you know? And the first item is how are we gonna govern the data. I would be having a coffee. One of the wonderful things, if you get the opportunity to go take it, it’s a lovely, very collaborative environment.

You meet people on the train, and you gotta be careful. It could be the prime minister or something. Right? So the guy next to me on the not talking to me, talking to his colleague was saying, I’m starting a data governance program.

I’m wondering how to set up my stewardship structure. I’m stepping back like, wait. They’re talking about our stuff. And that’s really a flip.

And I I wrote a a a blog because we always talk about that you might wanna catch after that. We can put it in the in the link. But, we always talk about data literacy, and I think it’s it’s the flip. We need to think of business literacy.

We’re not going to these forums and talking to people about, we’re listening because they’re already asking for it. And so I think that was a big moment that you and I were talking about at the last conference of we’re not in the right conversations. So it’s.

Well, that’s okay. So that’s really striking. There’s a lot of things to unpack there.

One of the things that we could unpack is if if what you say is true, and I have no doubt why would I disbelieve you, because you wanna tell your story, and I would wanna tell the story. So if that’s true, then then why is the pervasive mindset? And I can say that it is because you and I are going to the data events. Right?

We’re we’re talking to the people who put the shovels in the ground. Okay? And and and we’re at these events. We’re at the presentations.

The predominant mindset of people at these events is nobody cares.

Right? So and and and and that’s obviously not it’s it’s it’s not everybody thinking that way. But but the predominant mindset I wrote an entire book on this. The prod which I still need to ship you, by the way.

The predominant mindset around this is the business doesn’t get it. The business doesn’t see the value of governance. Nobody’s committing the resources for stewardship. Nobody’s supporting my MDM effort.

And what you’re saying is that, oh, no. There’s interest. They they want to figure this out, and they they feel like they need to figure that this out. Is it is that is that kinda, like, one one of your bigger takeaways?

I think so. I mean, there’s several reasons for it. Maybe there’s two big the one just that we can immediately we as the data community immediately start to take action on. And as you mentioned, they run a consultancy, and it’s the one thing I tell my team all the time is just listen first, speak in the business language, and not talk at at each other.

And we can all inherently understand that. Right? Wouldn’t you want these great group of friends who you have a doctor friend that someone can tell you what this medical speak means in really clear terms and not talk down to you or a lawyer friend that can explain things or someone about your car that can tell you what’s wrong with it without feeling like you’re stupid. Right?

And I’ve had I’m honored enough to be in the boardrooms across a lot of the large companies helping folks with these types of things. And I’ve had people be very blunt with me. I don’t wanna talk to IT. They talk down to me like I’m stupid.

And and I think we come in and I did myself going to Davos saying, I’m going to introduce people to the idea of governance. And it’s not that me teaching me, teaching them. It’s how do I listen to what and and because that ag tech, I just I didn’t realize ag tech was such a big thing. It was fascinating to me.

I have to learn about ag tech before I can be in the room with them about how they govern the central data for watering sprinklers. Right? But we we we come talking at them. I think that’s half of it, and perhaps the other half is a lot of well, I I’ll stop there.

I think that’s one of the the big drivers of of we go into these rooms teaching people we’re not listening first, and maybe we have to take it down to notch with our our conversation and speaking real English. You know?

Well, the simple fact that we call it data literacy Yes. Is is is in and of itself a judgmental term.

Right? It it’s it’s it’s judgmental. What what it says is is that you don’t get it.

And what you’re what you’re telling me is, no. They do get it. And that we’ve got a major communication issue here, but we’ve also got a mindset issue here. Right? So it may be what what you’re suggesting, it may be, is that at some of these companies, the senior executives are getting it, and maybe they’re just speaking a different language. Maybe they’re speaking the language of the business. Maybe they’re encoding their descriptions of their needs or their requirements.

And what they’re saying is is I need governance. I need governance. I need governance. And what we’re hearing is maybe something else. Right? Or or maybe we’re not even understanding it because it’s not being spoken in the language of data.

And what you’re suggesting is we need to a good solution here is to speak the language of business and that maybe we can connect the dots if we actually start speaking the language of of the business. I I I couldn’t I couldn’t agree more. I’ve got you I don’t I don’t wanna hurt my book, but I’ve got I’ve got multiple chapters on my book about why this is important, how the idea of literacy is judgmental, but more importantly, how that mindset would would would put you in a position of talking at and down to somebody instead of speaking with somebody. So in these conversations, you you you you kind of, like, got the Oh my god. They wanna talk about governance.

When you went into detail in some of these conversations, what did what did it look like? What what did you what did you hear? Right? Is it is it we need to do this for AI? I need to do this for compliance. I need to do this for my regulators in the EU. What what were what were what’s the next layer of the the cake that you were hearing about?

You know, that’s interesting. I think it’s and I will say the cake didn’t go as deep to your point. Folks know that and I hear this all the time from what I do talk to my clients. I know I need it.

What is it? Could somebody explain it to me in simple terms? Right? And I was not there last year at the World Economic Forum, and no surprise, you don’t have to be at the World Economic Forum to know that there’s a lot of AI hype.

And I think last year, it was all AI, all, you know, unicorns and roses. And this year felt a little more, okay. Now I actually I have to do this, or they’re seeing the it it was it was more that I I get it. How do we manage this data?

In fact, one of the speakers I really like this quote. Was gonna steal. He’s like, all AI is is math on top of data, and so you gotta get the data right. But there aren’t people you know, I I I mentioned before that the the platform vendors, the database vendors, or the the data platform vendors, and the AI vendors there, but their message is really simple.

You know, we have a platform to put your data on. We can make your data sync. We inherently sometimes when we have our covers and I do it myself. Well, to start governance, there’s an aspect that’s data quality, but, really, that’s not the same as metadata quality.

And then we have master data, which is not the same as metadata, and they’re like, out of here. Getting a coffee. Right? And so how do we it is nuanced, but maybe we have to simplify our I I can’t picture even myself.

We don’t have the billboard. When you walk down the promenade on on Davos, it’s interesting. They close all the stores. I didn’t know this.

So if you own a a friend of mine lives, is a Swiss person that lives in the town next door, he was telling me this. If you own, like, say, a shoe store in in the Davos Promenade, you can only lease for eleven months because they take your whole store and they fill it with snowflake or Anthropic or something, and they they literally it becomes, you know, the Anthropic store now. It’s not, your shoe store. Right?

So you walk down the promenade, and they all have a really nice pithy sign. AI to lose the business. I can’t picture what I just said on the side. Well, it’s nuanced.

We have metadata, which is not the same as master data, which needs lineage, is not the same as the semantic layer.

We have to be better at our messaging and keeping it simple and driving it to the business because none of our people, the master data, the metadata, the any of that were on the it was again, they had the quick simple message, but the business was asking for it. They’re like, I know this more than that. I tried it. Like, last year, I bought into the AI hype.

Now I’m finding and it wasn’t so much to answer your question. There was some regulation. People know they but it was more the inherent need. I’m driving my business on this.

Data AI is just math on top of data. How do I get the data right? Who can help me with that? Right? So I thought that was interesting.

We we we love to be pedantic.

Right? We just we just so I I came up with this this thing, and and and I have to give credit where credit is due because because the person who kind of crystallized my mind around this is a is a gentleman named Doug Laney, also well known in our space, wrote a wonderful book called Infonomics. If you haven’t read it, it actually is to me is the seminal work on on on how to quantify the business value of data. But thanks to Doug’s input, I came up with this this thing called the semantic pedanticism feedback loop.

And and how we we continue to feed on ourselves and we go into these downward spirals around all of these pedantic concepts that the business just doesn’t care about. I’ll give I’ll give you an example. Every time I post something on LinkedIn about unstructured data, all of not all. Not all. A material number of the comments are there’s no such thing as unstructured data. And I’m like, oh my gosh.

Could you not could you not have that conversation in front of the business? Right?

Well well well well, right. But that’s but that’s what we do. Exactly. Yes. Right? And if the business expresses something in a way that that that is like our kryptonite that we can’t that we can’t ignore, right, that we start to go down these pedantic downwards death spirals, then they’re gonna walk out of the conversation, and they they’re gonna think that we don’t get it.

So, you know, you’re in the business. What what from a skills perspective, obviously, what you said, first thing, business literacy. Right? Like, understand how the business works.

Does that mean that you need to be a PhD in ag tech? No. Probably not. But you do need to understand how the business works.

You need to understand how they speak. What if you’re hiring a consultant to go into this space, what are you looking for from a skills perspective? How do how do we need to train better or hire better in order to have these conversations?

No. Great question. Well, the first, even before training, is just personality. Will you listen first?

Right? Are you listening? Because I it’s funny. I do I’m getting nerdy already. But I one of my favorite success stories is I will answer your question, but I’m I’m doing the data person thing and going in a longer thing.

I I did a data modeling project at a water company. I knew nothing about water systems, and I was there for two weeks, did an enterprise model, asked the questions in the interview, did the readout of the data model. And someone came out later to me and said, where have you been? You clearly have been at this company for about twenty years and I’ve heard nobody explain how our business works better than you.

Like, two weeks. All I did was ask the questions the data model does. How do your pipes how do you you know, how do you regulate the water? How do you price the water?

I have it’s been a few years, so I can’t say it as well now. But and and that was the listening. So I think one is a personality. Listen first.

Ask the right questions, not the nerdy question because you can get, does a pipe have more than one fitting? Is that you know, what’s the cardinality of that? You can say it in a really nerdy way, or you can do it from a business context because that’s where the business will I my favorite comment around a data modeling workshop is me the pen. You start to say things like, can a customer have more than one account?

That sounds really nerdy, but then they’re like, right. They could have a brokerage account, a four zero one k account, and a oh, right. How do we manage that? And as soon as you get them in the conversation, that’s a data con they may not see it.

But as soon as they see it, they’re they’re gonna be bought into governance. And I hardly ever call it governance first. Right? But to answer your direct question, because I am probably too much of a data person and go in circles, I mean, a power combination is tech and an MBA.

A lot of my consultants have that. A lot of consultants don’t come from data at all. One of my best consultants was an accountant. It’s that same kind of thinking, and she customers love her.

I’m biased. My first degree was liberal arts, and I know at the time they told me that’s gonna help you. It’s gonna help you. And right out of college, it didn’t make as much.

It didn’t help me then. But that is more of a mindset, that that holistic thinking. And even if you weren’t trained with an MBA or trained with a liberal arts or English major or whatever, just that mindset of, am I listening first and and and listen with the business language? Because that is data.

And and I know I get proud when I make the make see, I just said it myself. When I engage with the business and their light bulb goes off, that that’s data, what they’re talking about, how they manage their accounts and their products and all that, then you’ve got them in. Same thing with my consultants sometimes.

That same thing, a cardinality rule in the data model. Can a customer have more than one account? That’s really boring. It’s a line on a diagram. Once you really understand why that’s really important to the business, they might have different divisions, then accounts aren’t talking to each other, and and it’s hard to roll up the revenue across four zero one k’s and mutual funds. Right?

Then they get it too, and then their whole conversations are different. So, you know, listen first, and we put it actually in our methodology. Before you know the client, you read their annual report. Look.

My most of my consult they they joke with me. I know, Don. I read the annual report. I’ve read the annual report of a company that nobody else did, and then even the CEO was saying we wanna be data driven, and the data team hadn’t read that.

Like, did you know that your CEO wants to be data driven and listen to what they’re asking for? It’s just so that part of it’s even a methodology before you go to the client. Read their website. Read their annual report.

Look in the news with the you know? And and so we can all get that mindset of listening first, learning first, and then talking about the data and challenge yourself to say, how was data in that conversation?

Well,

what you just said reminded me of many instances when I was leading both data teams and product teams.

So I’m a bit of a weirdo. I’ve been a chief product officer in the past, and and now I’m a chief data officer.

And across both of those worlds, I’ve had people who work for me try to tell me the business doesn’t know what they want.

And and every time I hear that, that’s like that’s like on the soccer field when the referee pulls out the yellow card. Right? Wait a minute. Hold on a second. The you’re trying to tell me the business doesn’t know what they want.

I’m calling BS because they know exactly what they want. They just may not be articulating it the way that you need to hear it, or you lack the curiosity to probe deeper to to to keep going. Right? It’s like interrogating a witness, I would Right? Like, if you’re not getting the answers, you need to ask a question a different way. Right? Right.

Getting back to

the problem.

Being interrogated.

That’s the

magic too.

Because we can do that.

Probably the wrong

and they get freaked out.

Pro probably the wrong metaphor.

And interrogation, probably the wrong metaphor, but hopefully, you get my point. Right? Which is, you know, to keep asking the same question over and over and in different ways until until you get to the heart of the issue. But getting back to the qualities. Right? You you there’s a few that jump out.

One, curiosity. Right? We need to be more curious. Right? Two is problem solvers. Right? Like, analysts, like like, people who are kind of native like like, natively, like, enraptured by trying to solve complex problems where the problem is understanding what is being articulated to you.

Not necessarily the technical problem, but the business problem that is being articulated to you. Kinda like you you mentioned MBAs. Right? Like, sounds a lot like a a case study for an MBA.

Right? Like, here’s all the symptoms. Here’s all the things. Now tell me what you think is inherently going wrong with this business or maybe going right with this business.

So problem solver, curiosity, you said listen before speaking.

Like, those are all all those things, I think, if we do those things, I I I have a hard time seeing how AI takes our job, at least that job.

Do you agree?

Oh, no. We should be all set with AI because AI’s map on top of data. Right? So that and people are looking for folks like us.

And and for some folks, like, yeah. Maybe I have a I have a you know, I got a computer science degree. I didn’t go into the softer skills because I like analytics. You can still, like, point that analytical mind to a different just like you would debug your code or do the data lineage for data.

If you could do that mental switch, and I’ve seen techie people really thrive with that mindset, do that you’re already good at problem solving, but point that to the business. It’s the same thing or the five whys. Oh, because, you know, your your company’s master data, that’s a classic one that you can fix it with match merge rules. It’s often a business process change.

So why did the data get that? Who is using that data? And the more you can just it can still be fun in a different way and sometimes getting that light bulb from the tech folks saying, it’s the same skills you’re using just or a person. Why are they thinking that way?

Not like again, I’m not like you make it feel like you’re analyzing them, but but break that down. What are their motivations? And and you can do it in a very logical way. Why are they nervous about talking to me?

Why would they maybe not wanna do data? Right? And that can help. So it’s the same skills we have, just maybe applied to a different topic.

Well well right. And so the to me, this is the lesson to any kind of more technically leaning person in the data world, whether that’s an engine software or data engineer, data modeler, data data hyphen, anything where you’re leaning a little more technical, where you need to be learning is leaning is more on the business side and try to understand, okay. What are the ramifications for a business perspective? How is the business actually using the data? How is this driving downstream value?

Because if we automate, where we’re gonna automate is on the technical side, I would argue, where we won’t necessarily

Right.

Yeah. There’s rules. You the data rules.

Yeah. Just imagine just imagine, like, we just imagine a world where we have fully automated the the the business analysis. I don’t see that happening in the short term.

Right? There is no single shot one query to rule them all to help to help where a bot can tell me how my business runs.

People are going to are going to have the deep knowledge and deep information and and the ability to infer and derive in a way that AI will never never do, at least in the short term, I think.

So so that’s interesting about career direction. But getting back to governance.

Get getting getting back

to governance.

One more thing what you just said.

Don’t wait.

I’ve had the same light bulb this well, AI jobs aren’t going away because we’re that semantics, whatever that needs. If you can automate part of it, it can scan documents and give you ideas, but that inherently is a people thing. And ironically, it’s the more AI automates, the more people in those and that’s what back to the Davos, it was a really cure and everyone said it’s not the sessions you go to. It’s those serendipitous people meeting.

And and when you said, did I believe what you said? I thought it was hype too. I said, yeah. You guys make it sound like Disneyland for nerds, like all these smart people just getting together.

But it it was that serendipity I’ll tell one story. Sorry. I I went to I did I’m not embarrassed to say I did not know a whole lot about quantum computing, which was another big topic. Right?

So I went to this session where there was this PhD who actually got the Nobel Prize in quantum computing to explain it. That person was very clear, summarized what they knew. Right? It was a very business centric presentation, so he does that very well.

But I’d said that in the line. I don’t know anything about quantum computing. And this lady said, would you like me to explain? And and proceeded to give, like, a fifteen minute summary of how it was manual.

Like, again, that business centric for people who don’t know it. And she got, like I don’t know if anyone’s old enough to remember that when EF Hutton talks, people listen.

But that people just swarmed around her. I found out later she’s one of the CEOs of one of these microchip you know, the the quantum computing chip companies just happened to be next to me. Right? So my point is that is a hyperscale getting really smart people.

I don’t know why they invite me, but really smart people together. And so AI just just funnels that. You don’t spend your time doing data lineage and reading. You know, you can summarize the documents.

So it doesn’t make people less important. It makes them more important. And those allows those serendipitous human to human connections. That’s where the magic happens, and I think we forget that.

And Davos, to me, like, light bulb. Right? That know, like, AI couldn’t have done that. Yeah.

I could have read the same thing she said, but it was the person and the engagement. And so that’s what we need to think with with the the data stuff and the data skills. People do wanna hear what we have to say. You have a seat at the table in the boardroom.

People are dying to hear what you have to say. That lady could have made her topic really boring. Quantum computing can be really nerdy.

We all were fascinated, right, because she said it in a really clear way. She didn’t talk down to us. She just explained it, and it was that human to human. If I had read it, I wouldn’t have gotten it as much as hearing her and her passion for the topic and all that.

So our nerdy passion, and I I tend to overdo it myself, is is our superpower. So AI doesn’t make our job go away. It elevates it, and it’s that but but you can’t hide at your laptop. You have to share it in a in a way.

You know?

So

So a couple a couple more critical skills there.

One, for lack of a better word, storytelling. Right? How do you how do you tell the story in a way in an using a narrative that is meaningful for your for your audience? Because I guarantee you, she was able to explain quantum without going deep on, you know, superposition and, you know, Schrodinger’s cat. Right?

I I can guarantee you she she would use very powerful language that was meaningful for her audience. So storytelling is one.

Humility sounds like another one.

Excellent. Yeah.

Humility sounds like another one. Like like because what you’re saying is is that these are some of the smartest people on the planet and the most influential people on the planet, yet there was a thirst for knowledge and there was a thirst for learning. That to me suggests humility.

And the ability to say, I don’t know certain things. You know, when I listen to the the Nobel Prize winner, he’s like, I don’t know a lot about this, but I’m really good at this, and we need to do that. And it’s hard, and it took me a long time in my career because I had to be at a place where I could say, do know a lot of things. So when I go to the ag tech CEO, I could say, I you know, humility, and that goes a long way. I don’t know this about your business, but I do know this from other industries, and I think it could apply.

It just it’s a much it’s a conversation than a non election.

Yeah. You know what I mean? It makes me makes me think of those old SNL skits of the unfrozen caveman lawyer. I don’t know if you ever watched Saturday Night Live back in the day. I don’t know anything about your moving flying machines, but I know that if you spill a hot cup of coffee on somebody left, they’re should get twenty billion dollars.

Anyway, I lost my track of thought because I’ve been down to SNL rabbit

hole.

Segue.

Yeah. Well, no. We we were we were talking about covers. I was listening to you speak, and basically what we were saying is and and this is gonna sound a little pithy, but that the AI advantage, as it were, for for us is to focus on our interpersonal skills and how to to relate to other people, how to understand other people, how to communicate with other people. Yet at the same time, so often when we get in these discussions about governance, what you hear is is that it’s a people problem.

Not a people opportunity, but a people problem.

Right? Well, it’s always people. Right? And I’ve heard this is, a zillion times. Right? Like, well, why why aren’t they following the rules?

Why aren’t they showing up to the committee meetings? Why aren’t they why are they doing dumb stuff in Salesforce? Oh, people problem. People problem.

Well, maybe it’s more of a people opportunity than than than a people problem. And that and that’s exactly what we we’ve been saying, right, which is listen more. Be be humble. Assume you don’t know.

Learn the business. Learn the process.

Well,

because you just summed it up.

They don’t come to the meeting and follow the rules. Gee. That sounds fun. I’m gonna go to a meeting, and I’ve I’ve been with a lot of these where some data person lectures me about a policy. I wouldn’t go back either. And I’ve had some success this year flipping the script because even that people are doing the wrong thing in Salesforce, what I find and I hardly ever use absolutes, like always or never, but I’ve never Right.

Right.

In my

thirty years of doing this, I did use a number, that that someone came to work and said, I wanna make the data bad.

People are trying to do the best thing amongst constraints. So I’ve seen crazy things. I’m gonna get nerdy, in a Salesforce or one of the big SAP, you know, that they have duplicate I’m getting into your world. Sorry about like, duplicate vendors, vendor a with a shipping address, vendor b with a mailing address.

No. We come in and they made they’re dumb. They did duplicates. Well, because the system wouldn’t let them create multiple addresses.

It’s a data problem, but we didn’t let and once I got it took me a few because that one happens a lot. Like, why were you doing that? And they’ll probably again show you a whole SOP and what they were trying to do or weird things you see in the data. Like, yeah.

We prefaced it with x six nine because that meant something because the systems weren’t working for them. And if you listen to them, they probably were really, really smart, but they’re not using our language. And they yes. They did this convoluted thing and going to say, great.

How can we help you take all that thing and make the systems work for you?

Oh my gosh. They’ll come to the meetings because you’re solutioning with them and listening because they’re not dumb people. In fact, a lot of the solutions they did to work around systems that didn’t work for themselves making the data bad were brilliant. We just didn’t listen to them.

So that’s one thing I’ve done that’s very impactful. Then they’re then they understand why they’re a data steward or a data owner because, oh, right. That’s my data I’m working with every day. And then some fun things.

We just started one with some we just started with, like, a a gripe session. What drives you crazy about data? And what’s interesting?

Well, well, these were people, like, regular people, and they’re like, you know and and they were using our language but with different words. There’s no drop down for state codes. You know, we only operate in Michigan, and and there so but I have to go through. So I just put Alabama every time because it’s at the beginning.

And if you could just make my life easier, like, us, that’s reference data. So they just gave me the solution right there with different words. Had I not listened and started and I’ve seen this, I go into the data governance meeting and give them a twelve slide thing of the and what ref how reference data is like, to your point, it’s not master data. Reference data is different, which is shoot.

I would have lost that person. But letting them talk and then we translate and say, that problem you have, we can solve. We even use the term reference data.

Right? And there was a whole bunch of those people that were already explaining the things they were doing that they wanted help with. And we very and now I always do that with my data governance meet. It’s kinda fun.

Everybody laughed, and they’re like, oh my gosh. That drives me crazy too. And we very quickly came to the top ten things we needed to fix in the business and, like, eight eight of the more mastered data things that were easily fixed. So that was a great example of collaborate.

I often call governance just collaboration because adults that most people are adults, and they wanna out trying to do something wrong or even like, oh, I didn’t know you needed that data downstream. Oh, I just thought it was a stupid field. Now I know why you need the weights and measures of a product because when you do tariffs, you need it. I didn’t know that.