WEBVTT
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Hello and welcome.
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I'm your host, Barbara Neshaw, and this is Inside Applied Data Governance.
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Whether you're just starting out in data governance or you've been working in the field for years, this podcast is for you.
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You will learn real-life lessons and practical advice from the people behind the Applied Data Governance Practitioner Certification.
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To learn more about the ADGP Certification Program, visit training.dataversity.
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Hello and welcome to Inside Applied Data Governance, a podcast where the practitioners who built the ADGP Certification Program share what real-world data governance actually looks like.
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I'm your host, Barbara Neshaw, and today we're talking to Jim Johnson, one of the key contributors to the ADGP certification, about obtaining stakeholder support and executive commitment for data governance.
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Let's jump right in.
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Hi, Jim.
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How are you doing today?
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I'm doing well, Barbara.
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Thank you.
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How are you?
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Doing wonderful.
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Wonderful.
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And I'm so excited to talk to you about this.
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Our subject today is actually one of my favorites about getting stakeholder commitment.
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I spent a lot of time doing that in my career as well.
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So I'm very excited.
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But before we get started on that, let's just tell our listeners a little bit about you.
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Why don't you start off with telling us about your background in data governance?
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Well, I really got my start officially in data governance when I heard the term data governance in, I think it was 2014 at a DGIQ conference.
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So I had spent my career and every job fixing things, making process better, making the data better.
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And it really never made sense to me until at that conference I realized holy cow, I've been doing this for a while, and it actually has a name now.
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So that was kind of exciting.
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Um, it all comes down to like, you know, standardizing things, uh, making your processes better, really building trust in the data and information assets.
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Um, my my approach prior to understanding DG was read the manuals, learn the tools, create standards, automate everything you can, and build trust and integrity in all of the data information.
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And then, of course, at the conference, I learned all kinds of other things like metadata, master data, and all these crazy terms that that started making sense to some of the problems I had encountered.
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I've been cross-sector.
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I've worked in uh pharmaceutical, banking, health insurance, quick service restaurants, healthcare, and most recently background screening.
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Every industry has something that you can learn and apply with to other industries.
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So that has been really valuable to me.
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Um, I've learned so much from each industry that I've taken all of that forward with all the other industries that I've worked in.
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Data's data, no matter what sector you're in.
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What changes is data governance, the scope and the art of applying it, which is why the applied part of this is so drastically important.
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Thank you very much for telling us a little bit about your background.
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And you just talked about it with the applied data governance um approach to it.
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How did you get involved whenever we started this certification program?
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So we're gonna go back to DGIQ again.
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So I think it was a couple of years ago, Tony and uh Shannon approached me at the conference.
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And I think Tony said, I, you know, I want to talk to you about a special project.
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And of course, you know, part of me is like, oh my God, I'm in trouble.
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And the other part's like, what's he talking about?
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So we ended up going out to the balcony at the catamaran here in San Diego, and we had a long conversation, and he started talking about, well, what do you think about building a body of knowledge?
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And what do you think about certification?
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And we had this back and forth.
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I was in from the moment he mentioned it.
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It's something I've been thinking about for a while.
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Ever since I obtained my CDMP certification, the thought in the back of my mind was, why don't we have a data governance certification?
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It makes us real, right?
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And the example I gave him was when I was in healthcare, a friend of mine who was the EDW architect for um the healthcare system that I was working at, he said, you know, I'm gonna, whenever you work with doctors, um I have one piece of advice where you should wear a tie.
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And we were casual, we were on the IT side and we weren't wearing ties to work.
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And I and I asked him why.
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And he said, the doctors take you more seriously.
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And so that's what certification does, right?
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It it helps make things more real.
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And as soon as Tony started talking about it, I said, I don't care how long it takes, I'm in.
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We need this.
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It's gonna help so many people in their positions, and it's gonna help executives and leadership and many organizations also realize that this is a real thing.
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And we need the credibility and the seriousness of your commitment to help us, which is again why stakeholder support is so darn important.
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Yeah, definitely.
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And I surely enjoyed working with you.
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And we spent a lot of time together on that certification program.
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Yeah.
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Um, you know, one of the things I think that makes ours a little different is the applied approach.
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Um, why do you think that was so important for this certification?
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Theory is the skill.
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It represents a perfect world, perfect conditions, perfect data, perfect behaviors.
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And it's almost like, you know, the demonstrations when IT vendors come in and they pitch their tool, the demo's perfect.
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I mean, that's not reality because you go to implement that tool and you realize that there's all kinds of challenges that are not represented in the perfect world.
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That's theory.
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It's it's a concept, it's perfect on paper.
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You can refine it indefinitely, but you don't really know whether it works.
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And then it's also retrospective.
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It's based on what we know, what we what we can observe, and what we believe is possible based on what we know and observe.
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So now let's talk about application.
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This is where it gets real.
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You walk out of the theory and you're in the real world, and conditions change, and data is messy, and people are challenging, and culture is strong.
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And you have to put theory to the test and see what works and what doesn't.
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And if it does work, how well does it work?
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And you discover gaps and assumptions and about your theory or your understanding of it, and then you start to troubleshoot everything in real time.
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And that's where the rubber meets the road.
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Application is all about perspective, it's creative and forward-looking.
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And without theory, it's guesswork.
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But with theory and this feedback loop that you create by trying things and learning from them, you're troubleshooting in real time.
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And that's really the true value of application.
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You can't learn that from a textbook.
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So there's a saying, I think it goes in theory, there's no difference between theory and practice.
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But in practice, there is, right?
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So if your data, I mentioned if you're a data or IT person, I mentioned earlier, you know, the perfect demos, that's theory.
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It's a vision.
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You can work towards it, but it's going to take you time.
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If you're not a data or an IT person, then it's very similar to a road trip.
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Theory is your perfectly planned map, your itinerary.
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The moment you hit the road, you have to react to anything that comes up: an accident, a detour, something in the backseat that has to go to the bathroom every hour.
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Learning from that on the fly is what application is all about.
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And this learning from experts all collected together makes that easier for everybody else that's in the same situation.
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That's a good way to describe it.
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And I like your car analogy.
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And that's really why our training that prepares you for the certification exam is so important because it really gives you all those examples and the videos and information from practitioners who are doing it on a day-to-day basis.
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So yeah, indeed.
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All right.
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Well, now let's jump into our topic for today: stakeholders and executive buy-in.
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Let's go here for the first question.
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You know, whenever we were originally, you know, you're thinking about what all should go into the body of knowledge, you know, why was it so important to include this?
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Key part about stakeholder um engagement and executive buy-in.
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Why was this so important?
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That what would have been missing if we didn't have it?
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So I think it's particularly important to everyone who works in an organization without a data and or data governance leader.
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So every time I'm at conferences or with my tribe of people, we're always troubleshooting how do I get started?
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What do I do?
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And that all leads to inevitably a question well, do you have a CDO?
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Because that's a person at the executive level of singular authority for all things something, right?
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So a CDO is data, maybe data governance.
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What do you do without it?
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You you do you're dealing with cultural challenges, politics, shifting priorities.
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And data governance, in essence, is organizational change.
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It influences change and improvement over the long haul.
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It doesn't directly impact sales or bring in revenue right away.
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So there's a lot of you know, consternation and and questioning that happens with data governance.
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And an executive leader can cut through a lot of the bureaucracy and the red tape and pave the way for at least awareness conversations, um, educational types of events to really get people more comfortable with the idea of how do we manage our data better.
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And I think it all comes down to if you're going to manage data as an asset, then you need to treat it like an asset and manage it accordingly.
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And so that's kind of new and different to a lot of people, even though we're familiar with it through finance and HR and supply chain and IT.
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But we're we're taking a slightly different approach to it.
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And it really, it really leaves us challenged with breaking through all of those, those, that that red tape and bureaucracy, basically.
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If we had excluded it, I think people, practitioners would be left with discovering and and and dealing with what I think is one of the top three reasons a data governance program fails.
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An executive sponsor can make it or break it.
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Having it can support success.
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Not having it, in my opinion, drastically increases the risk of failure.
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And one of the first things that a practitioner has to do is go find that executive sponsor.
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Um it's sort of like I think at one of the conferences we were asked a question of how would you describe it?
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And everybody had to create an image or find an image that represented one person had, I think it was Atlas with a world on his shoulders.
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Another person had um the person pushing the proverbial boulder up a mountain.
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Um, and mine was hurting cats because it's like it's the real problem is people, right?
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And then my one of my best friends, uh professional colleagues, and a DGE practitioner for years described it as you're pulling the Titanic upstream all by yourself.
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And what you really need is an executive sponsor to be the captain, allow you to be the the navigator and work together and staff that Titanic so you can actually move it.
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That's great.
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I use that cat analogy myself, except for I said it was a feral cat.
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Yeah.
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Yeah.
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Untrained feral cats.
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Yeah, yeah.
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A little extra challenge.
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Um entry-level analyst to executive data leaders.
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Dataversity delivers the most comprehensive training in the industry, led by experts who are actually doing the work.
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Upskill with on-demand courses, earn exclusive certifications, and join a global community of data pros committed to driving real change at dataversity.net.
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You know, and you you alluded to this a little bit in your previously, but what do you think is the biggest thing that people misunderstand or underestimate about obtaining the executive commitment?
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I think there's two things that people misunderstand the most.
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One is that data governance is organizational change, and I talked about that.
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We have to change people's behaviors as it relates to data and how they interact with and use and manage data.
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Um, and you can't change behaviors until you change mindsets.
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And that's point number two.
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Data governance is essentially a people problem.
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It's people and process over tools and data.
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Um, I bucket everything in those four categories.
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And so if you understand that it's organizational change and we have to address the people aspects of it, it makes it a lot better.
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What we underestimate, in my opinion, is organizational data literacy.
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I've been doing this for 20 years.
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Don't tell me how to do my job.
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Yes, but doing things in Excel manually and then storing your Excel workbook on a file share with no password and sensitive data inside is probably not the best way to do it.
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So, data governance is going to help elevate organizational data literacy through training and education efforts around what it means to make data management better.
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So, in my college job, there was a facility across the street from my building that was a full-blown training center.
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And I've never seen this since.
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This was this was, um, I won't say when it was more than 20 years ago.
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Um, but they they they taught classes and things like word perfect when that was a thing, and you know, word processing and spreadsheets and different, you know, cultural and business kinds of things.
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And it I loved it, I took every class I could.
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I've yet to see an organization, unless they have a a really mature data governance program, have full-blown training around data, data management, and what it means to engage um and embrace data protection and all these other things that data governance governance brings to the table.
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So that's the value it brings.
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And if we don't if we don't correctly understand that and misunder or overestimate things, I don't think we're gonna hit the mark on any of it.
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Good point.
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Definitely.
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What does it actually look like?
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You know, you're again, this leads a little bit on from the your previous answers, but what does it look like to gain sponsor stakeholder support, you know, whenever you're really doing it, especially early on in the maturity of data governance within an organization?
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Yeah, early on is challenging.
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It's you you don't you don't have the visible signals to look for that are along the lines of formal committees and formal decisions and policies and processes to follow.
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It's it's very informal, it's relational, it's volatile.
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Um, it's a lot of conversations to get perspectives aligned and build trust.
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Um, if you get a green light to go do things and figure it out, that's more lip service.
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It's they're saying, like, okay, I there's something here that I kind of understand and trust, but I don't want to get too involved.
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So you can go off and do that.
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Um, but you might have shifting priorities and false starts.
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And so as you're engaging all these conversations, you have to also gauge the level of support and interest from these stakeholders.
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And so if they get excited and start asking questions or or you know, probe a little bit, that's good.
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If they uh their eyes glaze over and they go silent or they disappear altogether, that's not good.
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It's a lot of constant communication, emotional IQ, finding early adopters.
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And then those that are willing, you build the trust, get them to socialize uh everything that you're talking about.
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If you've got quick wins and efforts along the way, socialize that as well.
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Educate peers at their levels, as well as their direct reports down the reporting lines.
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And it's all about fostering awareness and support through communication.
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And you spend most of your time doing that.
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Yes.
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A lot of time talking and a lot of time explaining.
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Over and over again.
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Over and over again.
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Yes.
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What's one piece of advice that you would give?
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You've talked about a lot of different things, but what's one piece of advice you would give to game?
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So this is this is so hard because there's so much advice to share, right?
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Um I decided that you know what there's this really good I there's one technique that I've used several times that is actually really effective.
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And so there's it's a two-parter, and the advice actually comes with part two.
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So first one, first part is you as you're scoping and looking for stakeholders, ask them what keeps you up at night.
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And the ones that open up and start telling you truth about what really does keep them up at night, you're gonna get a boatload of understanding about how the company operates, what their challenges are, what you know, truly like, you know, they're lying at three o'clock in the morning wondering, how am I gonna do this for my job?
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And they're an executive, right?
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So how do you help them?
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So now we're gonna get to part two.
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Well, you could actually, if it's related to data and and and data management in any form, there may be ways that data governance can help.
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And so you can kind of inject in that conversation and say, hey, how about if I I've got some ideas, maybe I can go flesh some things out, maybe we can circle back in a week or two in and I might be able to help you.
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And if you get a green light, great, go do it.
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Now, here's here's the advice: don't come up with a hundred percent plan.
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You do not want to come back with anything that's a hundred percent ready to go, you what you envision being everything, because number one, it's not gonna reflect reality unless you've been at the company longer or just as long as the executive.
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But number two, if you ask them what am I missing, and they point anything out, you are now getting buy-in from the early, from the early part of this process.
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And they'll start to get more and more involved as you have this conversation.
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You might discover there's a few things that you're missing.
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And once you get that them on board with that, you can then go off and execute your plan.
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You're probably gonna be a lot more successful.
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And once they see that you mean what you say and you deliver, even if it's a small win, just one undeniable success, you you have now found a stakeholder.
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Oh, that's great advice.
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Really focus on those wins, get their buy-in, and then grow from there.
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Yep.
00:17:34.799 --> 00:17:35.519
Absolutely.
00:17:36.240 --> 00:17:42.000
So, what causes stakeholder support for data governance to remain passive rather than active?
00:17:42.400 --> 00:17:46.720
And what is the impact on the progress of data governance?
00:17:47.920 --> 00:17:50.079
So, gosh, there's so many reasons, right?
00:17:50.240 --> 00:17:55.680
I think probably among the most common reasons are no personal or professional risk.
00:17:55.759 --> 00:17:56.960
They just don't have any skin in the game.
00:17:57.039 --> 00:17:58.240
Success doesn't help them.
00:17:58.480 --> 00:18:02.960
Failure can't be tied to them, or maybe it could be tied to them, and they want to avoid that.
00:18:03.200 --> 00:18:09.759
So you got to find people that have some skin in the game, which means maybe a problem that you have in common or a problem you can help with.
00:18:09.920 --> 00:18:14.799
They could be overwhelmed, too many competing um goals, priorities, limited budget.
00:18:14.960 --> 00:18:18.559
Um, maybe they just don't have physical or cognitive bandwidth to help.
00:18:18.640 --> 00:18:20.960
Uh, maybe they don't understand or know how they can help.
00:18:21.119 --> 00:18:25.200
I ran into that a lot at the executive level because they're so far removed from the work.
00:18:25.279 --> 00:18:30.400
Um, it's kind of hard for them to connect the dots and understand why should I help you when all my problems are getting solved?
00:18:30.480 --> 00:18:31.599
You know, that kind of stuff.
00:18:31.759 --> 00:18:33.920
Um, they tend to default to passive observation.
00:18:34.000 --> 00:18:40.559
And so that's one of the signals that you might look for that wow, they're just I don't know, they they're they're they're very passive.
00:18:40.640 --> 00:18:42.160
How do you turn that around and get them active?
00:18:42.240 --> 00:18:46.079
That's you know, you got to understand what these passive uh signals are.
00:18:46.319 --> 00:18:50.000
I think the political exposure for a lot of executives is one of the top ones.
00:18:50.480 --> 00:19:01.119
If you're if you're supporting anything related to change, you may be sticking your neck out or going out on a branch to use borrow some cliches or rock of the boat, might as well throw that one in there as well.
00:19:01.279 --> 00:19:10.240
Um, if they're not 100% sure, they're gonna keep a little bit of distance, a little bit of protection, maybe have a back out or an exit strategy in case things go haywire.
00:19:10.400 --> 00:19:12.880
Um, those are some of the impacts as well, right?
00:19:13.119 --> 00:19:17.039
They may start and then they may disappear, and then you you gotta start all over again.
00:19:17.279 --> 00:19:19.920
So it's good to look for all those things.
00:19:20.160 --> 00:19:27.519
Um, from the non-people standpoint, I think your pay slows, decisions grind on and on for weeks and weeks.
00:19:27.680 --> 00:19:28.799
We're still talking about the same thing.
00:19:28.960 --> 00:19:31.519
Three months later, progress starts to trickle.
00:19:31.759 --> 00:19:34.720
Um, folks in organizations emulate leaders.
00:19:34.880 --> 00:19:36.640
What leaders say and do, they follow.
00:19:36.799 --> 00:19:41.039
And if they see the sponsor doesn't care, then they're not gonna care and they're gonna have other priorities.
00:19:41.119 --> 00:19:43.039
It's not gonna seem relevant or important.
00:19:43.440 --> 00:19:48.559
And that's part of the reason that the progress will kind of slow, morale will drop as well.
00:19:48.720 --> 00:19:51.279
Um, you'll see the squeaky sweal start to get the grease.
00:19:51.359 --> 00:19:53.599
Um, the loudest voices get the budget, the priorities.
00:19:53.759 --> 00:19:55.519
Data governance is not at the table yet.
00:19:55.599 --> 00:20:05.599
And so you're gonna be put on the side burner or the back burner altogether, or you'll have sudden death where data governance is the first thing to get cut during layoffs or budget cuts.
00:20:05.680 --> 00:20:10.880
Um, and that's no fun because and that happens because there's nobody there to speak up or defend it.
00:20:11.119 --> 00:20:14.559
So all of these impact data governance in the short term and the long term.
00:20:14.720 --> 00:20:27.200
Short term means you're your program, you may have to restart, you may have to change direction, um, you have a lot of time and energy invested, and it seems not to matter, which could cause DG staff morale.
00:20:27.359 --> 00:20:36.960
And in the long term, it hurts the organization simply because you're not really elevating the the data literacy along the way, and you're starting over on that as well.
00:20:37.200 --> 00:20:43.839
So um passive is often time oftentimes the um death of a data governance program, in my opinion.
00:20:44.880 --> 00:20:45.119
Yeah.
00:20:45.359 --> 00:20:49.759
And that's a strong way to end that question answer because it it can be.
00:20:50.079 --> 00:20:56.000
Um, and we mentioned a little bit about this about communication and how important it is.
00:20:56.559 --> 00:21:02.480
How should governance leaders tailor their messages for executives versus the operational teams?
00:21:03.359 --> 00:21:05.200
Yeah, this is a really good question.
00:21:05.359 --> 00:21:09.119
And it really strikes at the heart of how important communication is.
00:21:09.279 --> 00:21:15.119
You have to tailor your messages to the audience and gauge how much they understand and don't.
00:21:15.279 --> 00:21:21.680
And you can mix a little bit, but there are some clear differences between executives and operational teams.
00:21:21.839 --> 00:21:28.559
Um, one thing that I use, or one approach I use rather, with executives is the 30-second elevator pitch.
00:21:28.640 --> 00:21:29.680
You got to get right to the point.
00:21:29.839 --> 00:21:41.599
It has to have enough context and detail to get them hooked and understand it and walk away thinking about it, but not be so in the weeds that they're lost and won't even remember the 30 second elevator pitch.
00:21:41.759 --> 00:21:48.480
Um, if you have a little bit more time, you can engage in um uh I think lean and agile have different ways of doing this.
00:21:48.559 --> 00:21:52.240
Um, in healthcare, I learned a process called S bar.
00:21:52.480 --> 00:21:55.680
It means situation, background, awareness, and recommendation.
00:21:55.759 --> 00:21:59.519
And so on one page, you say, here's what's going on, here's how we got here.
00:22:00.160 --> 00:22:04.240
Um, here's what you need to know about it, and then here are a couple options with the pros and cons.
00:22:04.319 --> 00:22:06.000
And I'm gonna tell you which one I think is best.
00:22:06.079 --> 00:22:10.480
And so you've laid out it's almost like a dis I think it's called a decision paper in some industries.
00:22:10.720 --> 00:22:17.680
You've laid out what they need to know, and everything that's relevant is right there, and they can go through all that.
00:22:17.839 --> 00:22:19.759
Um, so I would do that with executives.
00:22:19.920 --> 00:22:26.240
I actually have employed some of those approaches at my DG council meetings too, with with VP and CXO levels.
00:22:26.480 --> 00:22:27.920
Operational teams are different.
00:22:28.079 --> 00:22:29.279
You have to get in the weeds.
00:22:29.519 --> 00:22:35.119
These are the people that are living and breathing all of the workflows and the data movement, the data processes, et cetera.
00:22:35.279 --> 00:22:39.440
And so you have to create clarity of what exactly we're talking about.
00:22:39.599 --> 00:22:41.839
You have to link it to their day-to-day jobs.
00:22:42.079 --> 00:22:51.759
Um, you have to connect it ideally to leadership goals and plans so they understand the importance and the urgency of why we're we're we're asking them to do something.
00:22:51.920 --> 00:22:54.240
Um, and then they require tactical direction.
00:22:54.319 --> 00:22:55.680
You you can't have ambiguity.
00:22:55.759 --> 00:23:01.119
They will they will pick all of your your your verbiage apart, looking for flaws.
00:23:01.279 --> 00:23:03.920
There's a lot of pressure to get things done around them.
00:23:04.079 --> 00:23:08.480
Um, you have to be clear on definition of done or success criteria.
00:23:08.559 --> 00:23:11.680
Here's the problem, here's what it's gonna look like when we solve it.
00:23:11.759 --> 00:23:13.519
Um, do you have any questions and concerns?
00:23:13.680 --> 00:23:19.119
You got a kid glove, you know, white glove treatment them all the way through that conversation and get them comfy with it.
00:23:19.200 --> 00:23:21.200
Look for roadblocks, like what are you working on?
00:23:21.359 --> 00:23:23.920
What is gonna you know interfere?
00:23:24.079 --> 00:23:26.160
And some of this you can't even do face-to-face.
00:23:26.240 --> 00:23:29.119
You got to do it asynchronously because they need blocks of time to work.
00:23:29.200 --> 00:23:37.599
And so, can you can you craft it in email or put it in your ticketing system or get into an existing meeting and put it in the materials that are disseminated?
00:23:37.680 --> 00:23:40.480
You got to find ways to to accommodate that as well.
00:23:40.640 --> 00:23:48.720
And then keep them organized and actionable and you know, headings and formats so that they can quickly scan it because they are by far the busiest folks.
00:23:48.880 --> 00:23:52.799
If you're gonna give them a voluminous amount of information, you need to have it organized and clear.
00:23:53.759 --> 00:23:54.400
That's great.
00:23:54.640 --> 00:24:07.519
You know, it does boil down to a lot of our job is communication when we're working with stakeholders, executives, uh, anyone at any level, communication is on us to be able to speak to them in the right language.
00:24:08.000 --> 00:24:11.440
And I think that's so it get back to the art that we were talking about earlier, right?
00:24:11.599 --> 00:24:18.799
Data governance people get very adept at switching communication styles and content and messaging on the fly.
00:24:18.880 --> 00:24:23.440
Like you walk in thinking, oh, I got it, and I I prepared because I know it's gonna be an elevator pitch.
00:24:23.519 --> 00:24:26.799
And then one executive asks a question, you got to go do a deep dive for five minutes.
00:24:26.960 --> 00:24:28.400
So you cut you have to be prepared.
00:24:28.960 --> 00:24:29.519
Yes, you do.
00:24:30.960 --> 00:24:31.359
All right.
00:24:31.440 --> 00:24:33.200
Well, here's our last question.
00:24:34.160 --> 00:24:42.160
What signals tell you that a stakeholder is truly committed, not just verbally aligned, but really believes it.
00:24:43.680 --> 00:24:44.000
Yeah.
00:24:44.079 --> 00:24:47.759
So verbal, let's talk about what it doesn't look like and then we can jump into what it looks like.
00:24:47.839 --> 00:24:49.759
So verbal alignment is always conversational.
00:24:49.839 --> 00:24:54.240
It's cheap praise, it's smiling and nodding, it's zero effort, zero risk.
00:24:54.319 --> 00:24:55.519
Maybe they don't even show up, right?
00:24:55.599 --> 00:24:56.720
So, okay, that's great.
00:24:57.039 --> 00:25:00.079
True commitment, in my opinion, becomes behavioral.
00:25:00.319 --> 00:25:08.240
So they put their money where their mouth is, they actually do things that show um or that show support or directly help you.
00:25:08.319 --> 00:25:15.039
So it could be they reach out proactively, um, they stay engaged, they ask a lot of really good questions because they want to know.
00:25:15.200 --> 00:25:27.519
Um, if you have anything that you're presenting as like a recommendation or a plan, the moment they start asking questions, they're already starting to think about how they're going to be able to articulate this to their people or relate to a problem they have.
00:25:27.759 --> 00:25:29.519
Those are all really good signs.
00:25:29.759 --> 00:25:36.400
Um, they will also spend their own political and other capital or resources at the organization.
00:25:36.480 --> 00:25:39.839
Um they're gonna allocate people, maybe they're top performers.
00:25:39.920 --> 00:25:44.079
Um, they're gonna remove roadblocks, bureaucracy, and the resistors.
00:25:44.160 --> 00:25:48.880
Um, they're gonna show engagement in in interactions with you and any sort of data governance forums.
00:25:48.960 --> 00:25:54.000
They come prepared, they drive discussion and ask questions, um, especially the tough and uncomfortable questions.
00:25:54.079 --> 00:25:56.240
That that's a really good sign of engagement.
00:25:56.480 --> 00:26:00.960
And what they're what they're sort of alluding to is this sense of shared accountability.
00:26:01.039 --> 00:26:13.359
If I'm doing this out in the open with you in front of other execs and maybe some VP and director level folks, I'm sort of early indicating that that I'm I want to support this.
00:26:13.440 --> 00:26:18.559
And I, if we can work through all this and get comfy with it, then I'm gonna walk out of here and I am gonna support you.
00:26:18.799 --> 00:26:28.160
Um, pay attention in non-DG meetings and forums too, because you'll see all these patterns and behaviors, and that's gonna help you figure out how to gauge culture and who supports what and who doesn't.
00:26:28.240 --> 00:26:38.559
And then if you can learn enough from all of that, you can actually factor that into your communications and your audiences uh before you even walk in and try everything that I just described.
00:26:39.039 --> 00:26:41.920
Wow, that's really a good way to end our podcast today.
00:26:42.079 --> 00:26:45.119
So it really breaks it down for people and makes it real.
00:26:45.440 --> 00:26:48.160
So thank you very much for joining us today, Jim.
00:26:48.240 --> 00:26:50.640
Um, this has been a great conversation.
00:26:50.799 --> 00:26:55.440
And thank you so much for everything that you did for the applied data governance practitioner certification.
00:26:56.079 --> 00:27:01.039
It was a pleasure to be here and to help with the certification and the body of knowledge.
00:27:01.119 --> 00:27:03.759
And what a delightful conversation I always have with you, Barbara.
00:27:04.400 --> 00:27:05.839
Thank you very much, Jim.
00:27:10.480 --> 00:27:20.880
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.
00:27:21.680 --> 00:27:26.880
Until next time, I'm Barbara Nishaw, and this has been Inside Applied Data Governance.
00:00:05.440 --> 00:00:06.559
Hello and welcome.
00:00:06.719 --> 00:00:11.919
I'm your host, Barbara Neshaw, and this is Inside Applied Data Governance.
00:00:12.080 --> 00:00:18.239
Whether you're just starting out in data governance or you've been working in the field for years, this podcast is for you.
00:00:18.559 --> 00:00:26.559
You will learn real-life lessons and practical advice from the people behind the Applied Data Governance Practitioner Certification.
00:00:26.800 --> 00:00:33.759
To learn more about the ADGP Certification Program, visit training.dataversity.
00:00:39.119 --> 00:00:51.200
Hello and welcome to Inside Applied Data Governance, a podcast where the practitioners who built the ADGP Certification Program share what real-world data governance actually looks like.
00:00:51.439 --> 00:01:04.959
I'm your host, Barbara Neshaw, and today we're talking to Jim Johnson, one of the key contributors to the ADGP certification, about obtaining stakeholder support and executive commitment for data governance.
00:01:06.480 --> 00:01:08.159
Let's jump right in.
00:01:10.560 --> 00:01:11.439
Hi, Jim.
00:01:11.599 --> 00:01:12.560
How are you doing today?
00:01:13.359 --> 00:01:14.400
I'm doing well, Barbara.
00:01:14.640 --> 00:01:14.879
Thank you.
00:01:14.959 --> 00:01:15.359
How are you?
00:01:16.000 --> 00:01:16.560
Doing wonderful.
00:01:16.959 --> 00:01:17.359
Wonderful.
00:01:17.519 --> 00:01:20.239
And I'm so excited to talk to you about this.
00:01:20.480 --> 00:01:26.480
Our subject today is actually one of my favorites about getting stakeholder commitment.
00:01:26.640 --> 00:01:29.040
I spent a lot of time doing that in my career as well.
00:01:29.120 --> 00:01:30.319
So I'm very excited.
00:01:33.760 --> 00:01:38.000
But before we get started on that, let's just tell our listeners a little bit about you.
00:01:38.560 --> 00:01:42.799
Why don't you start off with telling us about your background in data governance?
00:01:43.840 --> 00:01:51.760
Well, I really got my start officially in data governance when I heard the term data governance in, I think it was 2014 at a DGIQ conference.
00:01:51.840 --> 00:01:58.719
So I had spent my career and every job fixing things, making process better, making the data better.
00:01:58.799 --> 00:02:06.079
And it really never made sense to me until at that conference I realized holy cow, I've been doing this for a while, and it actually has a name now.
00:02:06.159 --> 00:02:07.519
So that was kind of exciting.
00:02:07.680 --> 00:02:15.199
Um, it all comes down to like, you know, standardizing things, uh, making your processes better, really building trust in the data and information assets.
00:02:15.520 --> 00:02:26.319
Um, my my approach prior to understanding DG was read the manuals, learn the tools, create standards, automate everything you can, and build trust and integrity in all of the data information.
00:02:26.479 --> 00:02:35.360
And then, of course, at the conference, I learned all kinds of other things like metadata, master data, and all these crazy terms that that started making sense to some of the problems I had encountered.
00:02:35.520 --> 00:02:37.360
I've been cross-sector.
00:02:37.520 --> 00:02:44.560
I've worked in uh pharmaceutical, banking, health insurance, quick service restaurants, healthcare, and most recently background screening.
00:02:44.719 --> 00:02:48.400
Every industry has something that you can learn and apply with to other industries.
00:02:48.560 --> 00:02:51.039
So that has been really valuable to me.
00:02:51.199 --> 00:02:56.879
Um, I've learned so much from each industry that I've taken all of that forward with all the other industries that I've worked in.
00:02:57.039 --> 00:02:58.879
Data's data, no matter what sector you're in.
00:02:59.039 --> 00:03:06.800
What changes is data governance, the scope and the art of applying it, which is why the applied part of this is so drastically important.
00:03:08.000 --> 00:03:10.719
Thank you very much for telling us a little bit about your background.
00:03:11.039 --> 00:03:15.439
And you just talked about it with the applied data governance um approach to it.
00:03:15.680 --> 00:03:19.280
How did you get involved whenever we started this certification program?
00:03:19.759 --> 00:03:21.919
So we're gonna go back to DGIQ again.
00:03:22.080 --> 00:03:29.120
So I think it was a couple of years ago, Tony and uh Shannon approached me at the conference.
00:03:29.199 --> 00:03:32.240
And I think Tony said, I, you know, I want to talk to you about a special project.
00:03:32.319 --> 00:03:34.719
And of course, you know, part of me is like, oh my God, I'm in trouble.
00:03:34.800 --> 00:03:36.479
And the other part's like, what's he talking about?
00:03:36.639 --> 00:03:44.879
So we ended up going out to the balcony at the catamaran here in San Diego, and we had a long conversation, and he started talking about, well, what do you think about building a body of knowledge?
00:03:45.439 --> 00:03:47.120
And what do you think about certification?
00:03:47.199 --> 00:03:48.879
And we had this back and forth.
00:03:49.039 --> 00:03:50.639
I was in from the moment he mentioned it.
00:03:50.719 --> 00:03:52.319
It's something I've been thinking about for a while.
00:03:52.479 --> 00:03:58.400
Ever since I obtained my CDMP certification, the thought in the back of my mind was, why don't we have a data governance certification?
00:03:58.560 --> 00:03:59.680
It makes us real, right?
00:03:59.840 --> 00:04:13.199
And the example I gave him was when I was in healthcare, a friend of mine who was the EDW architect for um the healthcare system that I was working at, he said, you know, I'm gonna, whenever you work with doctors, um I have one piece of advice where you should wear a tie.
00:04:13.360 --> 00:04:17.120
And we were casual, we were on the IT side and we weren't wearing ties to work.
00:04:17.199 --> 00:04:18.240
And I and I asked him why.
00:04:18.319 --> 00:04:20.720
And he said, the doctors take you more seriously.
00:04:20.959 --> 00:04:23.600
And so that's what certification does, right?
00:04:23.680 --> 00:04:26.319
It it helps make things more real.
00:04:26.399 --> 00:04:30.079
And as soon as Tony started talking about it, I said, I don't care how long it takes, I'm in.
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We need this.
00:04:30.879 --> 00:04:39.279
It's gonna help so many people in their positions, and it's gonna help executives and leadership and many organizations also realize that this is a real thing.
00:04:39.439 --> 00:04:46.800
And we need the credibility and the seriousness of your commitment to help us, which is again why stakeholder support is so darn important.
00:04:47.920 --> 00:04:48.720
Yeah, definitely.
00:04:48.800 --> 00:04:50.319
And I surely enjoyed working with you.
00:04:50.399 --> 00:04:53.680
And we spent a lot of time together on that certification program.
00:04:53.839 --> 00:04:54.480
Yeah.
00:04:55.759 --> 00:05:00.720
Um, you know, one of the things I think that makes ours a little different is the applied approach.
00:05:00.879 --> 00:05:03.839
Um, why do you think that was so important for this certification?
00:05:04.240 --> 00:05:05.199
Theory is the skill.
00:05:05.279 --> 00:05:09.360
It represents a perfect world, perfect conditions, perfect data, perfect behaviors.
00:05:09.519 --> 00:05:16.560
And it's almost like, you know, the demonstrations when IT vendors come in and they pitch their tool, the demo's perfect.
00:05:16.639 --> 00:05:22.959
I mean, that's not reality because you go to implement that tool and you realize that there's all kinds of challenges that are not represented in the perfect world.
00:05:23.040 --> 00:05:23.920
That's theory.
00:05:24.079 --> 00:05:26.160
It's it's a concept, it's perfect on paper.
00:05:26.319 --> 00:05:30.319
You can refine it indefinitely, but you don't really know whether it works.
00:05:30.399 --> 00:05:32.000
And then it's also retrospective.
00:05:32.079 --> 00:05:38.879
It's based on what we know, what we what we can observe, and what we believe is possible based on what we know and observe.
00:05:39.040 --> 00:05:40.879
So now let's talk about application.
00:05:41.040 --> 00:05:42.079
This is where it gets real.
00:05:42.240 --> 00:05:50.800
You walk out of the theory and you're in the real world, and conditions change, and data is messy, and people are challenging, and culture is strong.
00:05:50.959 --> 00:05:54.000
And you have to put theory to the test and see what works and what doesn't.
00:05:54.079 --> 00:05:56.079
And if it does work, how well does it work?
00:05:56.240 --> 00:06:04.160
And you discover gaps and assumptions and about your theory or your understanding of it, and then you start to troubleshoot everything in real time.
00:06:04.240 --> 00:06:06.079
And that's where the rubber meets the road.
00:06:06.319 --> 00:06:09.680
Application is all about perspective, it's creative and forward-looking.
00:06:09.759 --> 00:06:11.680
And without theory, it's guesswork.
00:06:11.839 --> 00:06:20.399
But with theory and this feedback loop that you create by trying things and learning from them, you're troubleshooting in real time.
00:06:20.480 --> 00:06:22.879
And that's really the true value of application.
00:06:23.040 --> 00:06:24.800
You can't learn that from a textbook.
00:06:24.959 --> 00:06:31.040
So there's a saying, I think it goes in theory, there's no difference between theory and practice.
00:06:31.199 --> 00:06:33.600
But in practice, there is, right?
00:06:34.000 --> 00:06:40.000
So if your data, I mentioned if you're a data or IT person, I mentioned earlier, you know, the perfect demos, that's theory.
00:06:40.079 --> 00:06:40.560
It's a vision.
00:06:40.639 --> 00:06:42.639
You can work towards it, but it's going to take you time.
00:06:42.800 --> 00:06:47.360
If you're not a data or an IT person, then it's very similar to a road trip.
00:06:47.519 --> 00:06:50.560
Theory is your perfectly planned map, your itinerary.
00:06:50.720 --> 00:06:58.240
The moment you hit the road, you have to react to anything that comes up: an accident, a detour, something in the backseat that has to go to the bathroom every hour.
00:06:58.560 --> 00:07:02.240
Learning from that on the fly is what application is all about.
00:07:02.399 --> 00:07:09.680
And this learning from experts all collected together makes that easier for everybody else that's in the same situation.
00:07:10.720 --> 00:07:11.920
That's a good way to describe it.
00:07:12.160 --> 00:07:13.680
And I like your car analogy.
00:07:13.839 --> 00:07:26.800
And that's really why our training that prepares you for the certification exam is so important because it really gives you all those examples and the videos and information from practitioners who are doing it on a day-to-day basis.
00:07:26.959 --> 00:07:28.800
So yeah, indeed.
00:07:29.120 --> 00:07:29.439
All right.
00:07:29.519 --> 00:07:35.279
Well, now let's jump into our topic for today: stakeholders and executive buy-in.
00:07:35.759 --> 00:07:37.839
Let's go here for the first question.
00:07:38.079 --> 00:07:46.560
You know, whenever we were originally, you know, you're thinking about what all should go into the body of knowledge, you know, why was it so important to include this?
00:07:47.600 --> 00:07:52.560
Key part about stakeholder um engagement and executive buy-in.
00:07:52.800 --> 00:07:53.600
Why was this so important?
00:07:53.680 --> 00:07:56.000
That what would have been missing if we didn't have it?
00:07:57.040 --> 00:08:04.879
So I think it's particularly important to everyone who works in an organization without a data and or data governance leader.
00:08:05.040 --> 00:08:11.519
So every time I'm at conferences or with my tribe of people, we're always troubleshooting how do I get started?
00:08:11.680 --> 00:08:12.399
What do I do?
00:08:12.560 --> 00:08:16.879
And that all leads to inevitably a question well, do you have a CDO?
00:08:16.959 --> 00:08:21.519
Because that's a person at the executive level of singular authority for all things something, right?
00:08:21.600 --> 00:08:24.079
So a CDO is data, maybe data governance.
00:08:24.240 --> 00:08:25.199
What do you do without it?
00:08:25.360 --> 00:08:29.680
You you do you're dealing with cultural challenges, politics, shifting priorities.
00:08:29.839 --> 00:08:32.639
And data governance, in essence, is organizational change.
00:08:32.799 --> 00:08:35.600
It influences change and improvement over the long haul.
00:08:35.679 --> 00:08:39.759
It doesn't directly impact sales or bring in revenue right away.
00:08:40.000 --> 00:08:47.120
So there's a lot of you know, consternation and and questioning that happens with data governance.
00:08:47.360 --> 00:09:05.279
And an executive leader can cut through a lot of the bureaucracy and the red tape and pave the way for at least awareness conversations, um, educational types of events to really get people more comfortable with the idea of how do we manage our data better.
00:09:05.519 --> 00:09:11.600
And I think it all comes down to if you're going to manage data as an asset, then you need to treat it like an asset and manage it accordingly.
00:09:11.679 --> 00:09:18.639
And so that's kind of new and different to a lot of people, even though we're familiar with it through finance and HR and supply chain and IT.
00:09:18.879 --> 00:09:21.360
But we're we're taking a slightly different approach to it.
00:09:21.440 --> 00:09:28.639
And it really, it really leaves us challenged with breaking through all of those, those, that that red tape and bureaucracy, basically.
00:09:28.799 --> 00:09:40.879
If we had excluded it, I think people, practitioners would be left with discovering and and and dealing with what I think is one of the top three reasons a data governance program fails.
00:09:41.279 --> 00:09:43.360
An executive sponsor can make it or break it.
00:09:43.519 --> 00:09:45.440
Having it can support success.
00:09:45.600 --> 00:09:49.440
Not having it, in my opinion, drastically increases the risk of failure.
00:09:49.600 --> 00:09:54.720
And one of the first things that a practitioner has to do is go find that executive sponsor.
00:09:54.960 --> 00:10:00.960
Um it's sort of like I think at one of the conferences we were asked a question of how would you describe it?
00:10:01.039 --> 00:10:07.919
And everybody had to create an image or find an image that represented one person had, I think it was Atlas with a world on his shoulders.
00:10:08.000 --> 00:10:13.120
Another person had um the person pushing the proverbial boulder up a mountain.
00:10:13.679 --> 00:10:19.039
Um, and mine was hurting cats because it's like it's the real problem is people, right?
00:10:19.279 --> 00:10:29.519
And then my one of my best friends, uh professional colleagues, and a DGE practitioner for years described it as you're pulling the Titanic upstream all by yourself.
00:10:29.600 --> 00:10:38.879
And what you really need is an executive sponsor to be the captain, allow you to be the the navigator and work together and staff that Titanic so you can actually move it.
00:10:39.279 --> 00:10:40.000
That's great.
00:10:40.159 --> 00:10:43.919
I use that cat analogy myself, except for I said it was a feral cat.
00:10:44.399 --> 00:10:44.480
Yeah.
00:10:46.639 --> 00:10:46.799
Yeah.
00:10:47.360 --> 00:10:48.799
Untrained feral cats.
00:10:49.039 --> 00:10:49.519
Yeah, yeah.
00:10:49.759 --> 00:10:51.279
A little extra challenge.
00:10:51.519 --> 00:10:56.799
Um entry-level analyst to executive data leaders.
00:10:56.960 --> 00:11:03.759
Dataversity delivers the most comprehensive training in the industry, led by experts who are actually doing the work.
00:11:03.919 --> 00:11:14.559
Upskill with on-demand courses, earn exclusive certifications, and join a global community of data pros committed to driving real change at dataversity.net.
00:11:17.120 --> 00:11:31.200
You know, and you you alluded to this a little bit in your previously, but what do you think is the biggest thing that people misunderstand or underestimate about obtaining the executive commitment?
00:11:31.519 --> 00:11:34.639
I think there's two things that people misunderstand the most.
00:11:34.799 --> 00:11:38.080
One is that data governance is organizational change, and I talked about that.
00:11:38.159 --> 00:11:44.320
We have to change people's behaviors as it relates to data and how they interact with and use and manage data.
00:11:44.480 --> 00:11:47.360
Um, and you can't change behaviors until you change mindsets.
00:11:47.440 --> 00:11:48.639
And that's point number two.
00:11:48.720 --> 00:11:50.799
Data governance is essentially a people problem.
00:11:50.879 --> 00:11:54.320
It's people and process over tools and data.
00:11:54.399 --> 00:11:56.639
Um, I bucket everything in those four categories.
00:11:56.720 --> 00:12:04.000
And so if you understand that it's organizational change and we have to address the people aspects of it, it makes it a lot better.
00:12:04.240 --> 00:12:08.720
What we underestimate, in my opinion, is organizational data literacy.
00:12:08.879 --> 00:12:10.320
I've been doing this for 20 years.
00:12:10.399 --> 00:12:11.600
Don't tell me how to do my job.
00:12:11.759 --> 00:12:21.200
Yes, but doing things in Excel manually and then storing your Excel workbook on a file share with no password and sensitive data inside is probably not the best way to do it.
00:12:21.360 --> 00:12:31.840
So, data governance is going to help elevate organizational data literacy through training and education efforts around what it means to make data management better.
00:12:32.000 --> 00:12:38.080
So, in my college job, there was a facility across the street from my building that was a full-blown training center.
00:12:38.159 --> 00:12:39.360
And I've never seen this since.
00:12:39.519 --> 00:12:43.039
This was this was, um, I won't say when it was more than 20 years ago.
00:12:43.200 --> 00:12:55.360
Um, but they they they taught classes and things like word perfect when that was a thing, and you know, word processing and spreadsheets and different, you know, cultural and business kinds of things.
00:12:55.519 --> 00:12:57.759
And it I loved it, I took every class I could.
00:12:57.919 --> 00:13:14.399
I've yet to see an organization, unless they have a a really mature data governance program, have full-blown training around data, data management, and what it means to engage um and embrace data protection and all these other things that data governance governance brings to the table.
00:13:14.639 --> 00:13:16.720
So that's the value it brings.
00:13:16.879 --> 00:13:26.960
And if we don't if we don't correctly understand that and misunder or overestimate things, I don't think we're gonna hit the mark on any of it.
00:13:28.240 --> 00:13:28.720
Good point.
00:13:29.039 --> 00:13:29.679
Definitely.
00:13:30.559 --> 00:13:32.240
What does it actually look like?
00:13:32.399 --> 00:13:47.840
You know, you're again, this leads a little bit on from the your previous answers, but what does it look like to gain sponsor stakeholder support, you know, whenever you're really doing it, especially early on in the maturity of data governance within an organization?
00:13:48.240 --> 00:13:50.000
Yeah, early on is challenging.
00:13:50.159 --> 00:14:02.480
It's you you don't you don't have the visible signals to look for that are along the lines of formal committees and formal decisions and policies and processes to follow.
00:14:02.559 --> 00:14:06.240
It's it's very informal, it's relational, it's volatile.
00:14:06.320 --> 00:14:12.000
Um, it's a lot of conversations to get perspectives aligned and build trust.
00:14:12.240 --> 00:14:16.639
Um, if you get a green light to go do things and figure it out, that's more lip service.
00:14:16.799 --> 00:14:22.399
It's they're saying, like, okay, I there's something here that I kind of understand and trust, but I don't want to get too involved.
00:14:22.480 --> 00:14:24.159
So you can go off and do that.
00:14:24.399 --> 00:14:27.919
Um, but you might have shifting priorities and false starts.
00:14:28.159 --> 00:14:35.840
And so as you're engaging all these conversations, you have to also gauge the level of support and interest from these stakeholders.
00:14:35.919 --> 00:14:40.799
And so if they get excited and start asking questions or or you know, probe a little bit, that's good.
00:14:41.039 --> 00:14:46.159
If they uh their eyes glaze over and they go silent or they disappear altogether, that's not good.
00:14:46.320 --> 00:14:50.720
It's a lot of constant communication, emotional IQ, finding early adopters.
00:14:50.879 --> 00:14:57.679
And then those that are willing, you build the trust, get them to socialize uh everything that you're talking about.
00:14:57.759 --> 00:15:01.039
If you've got quick wins and efforts along the way, socialize that as well.
00:15:01.200 --> 00:15:06.639
Educate peers at their levels, as well as their direct reports down the reporting lines.
00:15:06.799 --> 00:15:10.080
And it's all about fostering awareness and support through communication.
00:15:10.159 --> 00:15:12.159
And you spend most of your time doing that.
00:15:12.960 --> 00:15:13.440
Yes.
00:15:14.720 --> 00:15:17.440
A lot of time talking and a lot of time explaining.
00:15:18.000 --> 00:15:18.879
Over and over again.
00:15:19.120 --> 00:15:19.840
Over and over again.
00:15:19.919 --> 00:15:20.320
Yes.
00:15:22.000 --> 00:15:24.960
What's one piece of advice that you would give?
00:15:25.519 --> 00:15:30.480
You've talked about a lot of different things, but what's one piece of advice you would give to game?
00:15:30.799 --> 00:15:34.559
So this is this is so hard because there's so much advice to share, right?
00:15:35.039 --> 00:15:44.080
Um I decided that you know what there's this really good I there's one technique that I've used several times that is actually really effective.
00:15:44.159 --> 00:15:47.440
And so there's it's a two-parter, and the advice actually comes with part two.
00:15:47.600 --> 00:15:55.440
So first one, first part is you as you're scoping and looking for stakeholders, ask them what keeps you up at night.
00:15:55.759 --> 00:16:12.240
And the ones that open up and start telling you truth about what really does keep them up at night, you're gonna get a boatload of understanding about how the company operates, what their challenges are, what you know, truly like, you know, they're lying at three o'clock in the morning wondering, how am I gonna do this for my job?
00:16:12.320 --> 00:16:13.519
And they're an executive, right?
00:16:13.679 --> 00:16:15.120
So how do you help them?
00:16:15.279 --> 00:16:16.720
So now we're gonna get to part two.
00:16:16.879 --> 00:16:25.279
Well, you could actually, if it's related to data and and and data management in any form, there may be ways that data governance can help.
00:16:25.360 --> 00:16:36.399
And so you can kind of inject in that conversation and say, hey, how about if I I've got some ideas, maybe I can go flesh some things out, maybe we can circle back in a week or two in and I might be able to help you.
00:16:36.480 --> 00:16:38.240
And if you get a green light, great, go do it.
00:16:38.399 --> 00:16:42.159
Now, here's here's the advice: don't come up with a hundred percent plan.
00:16:42.320 --> 00:16:53.840
You do not want to come back with anything that's a hundred percent ready to go, you what you envision being everything, because number one, it's not gonna reflect reality unless you've been at the company longer or just as long as the executive.
00:16:53.919 --> 00:17:04.559
But number two, if you ask them what am I missing, and they point anything out, you are now getting buy-in from the early, from the early part of this process.
00:17:04.720 --> 00:17:08.400
And they'll start to get more and more involved as you have this conversation.
00:17:08.559 --> 00:17:11.599
You might discover there's a few things that you're missing.
00:17:11.839 --> 00:17:16.960
And once you get that them on board with that, you can then go off and execute your plan.
00:17:17.039 --> 00:17:18.480
You're probably gonna be a lot more successful.
00:17:18.640 --> 00:17:27.519
And once they see that you mean what you say and you deliver, even if it's a small win, just one undeniable success, you you have now found a stakeholder.
00:17:28.319 --> 00:17:29.359
Oh, that's great advice.
00:17:29.599 --> 00:17:32.880
Really focus on those wins, get their buy-in, and then grow from there.
00:17:33.279 --> 00:17:33.599
Yep.
00:17:34.799 --> 00:17:35.519
Absolutely.
00:17:36.240 --> 00:17:42.000
So, what causes stakeholder support for data governance to remain passive rather than active?
00:17:42.400 --> 00:17:46.720
And what is the impact on the progress of data governance?
00:17:47.920 --> 00:17:50.079
So, gosh, there's so many reasons, right?
00:17:50.240 --> 00:17:55.680
I think probably among the most common reasons are no personal or professional risk.
00:17:55.759 --> 00:17:56.960
They just don't have any skin in the game.
00:17:57.039 --> 00:17:58.240
Success doesn't help them.
00:17:58.480 --> 00:18:02.960
Failure can't be tied to them, or maybe it could be tied to them, and they want to avoid that.
00:18:03.200 --> 00:18:09.759
So you got to find people that have some skin in the game, which means maybe a problem that you have in common or a problem you can help with.
00:18:09.920 --> 00:18:14.799
They could be overwhelmed, too many competing um goals, priorities, limited budget.
00:18:14.960 --> 00:18:18.559
Um, maybe they just don't have physical or cognitive bandwidth to help.
00:18:18.640 --> 00:18:20.960
Uh, maybe they don't understand or know how they can help.
00:18:21.119 --> 00:18:25.200
I ran into that a lot at the executive level because they're so far removed from the work.
00:18:25.279 --> 00:18:30.400
Um, it's kind of hard for them to connect the dots and understand why should I help you when all my problems are getting solved?
00:18:30.480 --> 00:18:31.599
You know, that kind of stuff.
00:18:31.759 --> 00:18:33.920
Um, they tend to default to passive observation.
00:18:34.000 --> 00:18:40.559
And so that's one of the signals that you might look for that wow, they're just I don't know, they they're they're they're very passive.
00:18:40.640 --> 00:18:42.160
How do you turn that around and get them active?
00:18:42.240 --> 00:18:46.079
That's you know, you got to understand what these passive uh signals are.
00:18:46.319 --> 00:18:50.000
I think the political exposure for a lot of executives is one of the top ones.
00:18:50.480 --> 00:19:01.119
If you're if you're supporting anything related to change, you may be sticking your neck out or going out on a branch to use borrow some cliches or rock of the boat, might as well throw that one in there as well.
00:19:01.279 --> 00:19:10.240
Um, if they're not 100% sure, they're gonna keep a little bit of distance, a little bit of protection, maybe have a back out or an exit strategy in case things go haywire.
00:19:10.400 --> 00:19:12.880
Um, those are some of the impacts as well, right?
00:19:13.119 --> 00:19:17.039
They may start and then they may disappear, and then you you gotta start all over again.
00:19:17.279 --> 00:19:19.920
So it's good to look for all those things.
00:19:20.160 --> 00:19:27.519
Um, from the non-people standpoint, I think your pay slows, decisions grind on and on for weeks and weeks.
00:19:27.680 --> 00:19:28.799
We're still talking about the same thing.
00:19:28.960 --> 00:19:31.519
Three months later, progress starts to trickle.
00:19:31.759 --> 00:19:34.720
Um, folks in organizations emulate leaders.
00:19:34.880 --> 00:19:36.640
What leaders say and do, they follow.
00:19:36.799 --> 00:19:41.039
And if they see the sponsor doesn't care, then they're not gonna care and they're gonna have other priorities.
00:19:41.119 --> 00:19:43.039
It's not gonna seem relevant or important.
00:19:43.440 --> 00:19:48.559
And that's part of the reason that the progress will kind of slow, morale will drop as well.
00:19:48.720 --> 00:19:51.279
Um, you'll see the squeaky sweal start to get the grease.
00:19:51.359 --> 00:19:53.599
Um, the loudest voices get the budget, the priorities.
00:19:53.759 --> 00:19:55.519
Data governance is not at the table yet.
00:19:55.599 --> 00:20:05.599
And so you're gonna be put on the side burner or the back burner altogether, or you'll have sudden death where data governance is the first thing to get cut during layoffs or budget cuts.
00:20:05.680 --> 00:20:10.880
Um, and that's no fun because and that happens because there's nobody there to speak up or defend it.
00:20:11.119 --> 00:20:14.559
So all of these impact data governance in the short term and the long term.
00:20:14.720 --> 00:20:27.200
Short term means you're your program, you may have to restart, you may have to change direction, um, you have a lot of time and energy invested, and it seems not to matter, which could cause DG staff morale.
00:20:27.359 --> 00:20:36.960
And in the long term, it hurts the organization simply because you're not really elevating the the data literacy along the way, and you're starting over on that as well.
00:20:37.200 --> 00:20:43.839
So um passive is often time oftentimes the um death of a data governance program, in my opinion.
00:20:44.880 --> 00:20:45.119
Yeah.
00:20:45.359 --> 00:20:49.759
And that's a strong way to end that question answer because it it can be.
00:20:50.079 --> 00:20:56.000
Um, and we mentioned a little bit about this about communication and how important it is.
00:20:56.559 --> 00:21:02.480
How should governance leaders tailor their messages for executives versus the operational teams?
00:21:03.359 --> 00:21:05.200
Yeah, this is a really good question.
00:21:05.359 --> 00:21:09.119
And it really strikes at the heart of how important communication is.
00:21:09.279 --> 00:21:15.119
You have to tailor your messages to the audience and gauge how much they understand and don't.
00:21:15.279 --> 00:21:21.680
And you can mix a little bit, but there are some clear differences between executives and operational teams.
00:21:21.839 --> 00:21:28.559
Um, one thing that I use, or one approach I use rather, with executives is the 30-second elevator pitch.
00:21:28.640 --> 00:21:29.680
You got to get right to the point.
00:21:29.839 --> 00:21:41.599
It has to have enough context and detail to get them hooked and understand it and walk away thinking about it, but not be so in the weeds that they're lost and won't even remember the 30 second elevator pitch.
00:21:41.759 --> 00:21:48.480
Um, if you have a little bit more time, you can engage in um uh I think lean and agile have different ways of doing this.
00:21:48.559 --> 00:21:52.240
Um, in healthcare, I learned a process called S bar.
00:21:52.480 --> 00:21:55.680
It means situation, background, awareness, and recommendation.
00:21:55.759 --> 00:21:59.519
And so on one page, you say, here's what's going on, here's how we got here.
00:22:00.160 --> 00:22:04.240
Um, here's what you need to know about it, and then here are a couple options with the pros and cons.
00:22:04.319 --> 00:22:06.000
And I'm gonna tell you which one I think is best.
00:22:06.079 --> 00:22:10.480
And so you've laid out it's almost like a dis I think it's called a decision paper in some industries.
00:22:10.720 --> 00:22:17.680
You've laid out what they need to know, and everything that's relevant is right there, and they can go through all that.
00:22:17.839 --> 00:22:19.759
Um, so I would do that with executives.
00:22:19.920 --> 00:22:26.240
I actually have employed some of those approaches at my DG council meetings too, with with VP and CXO levels.
00:22:26.480 --> 00:22:27.920
Operational teams are different.
00:22:28.079 --> 00:22:29.279
You have to get in the weeds.
00:22:29.519 --> 00:22:35.119
These are the people that are living and breathing all of the workflows and the data movement, the data processes, et cetera.
00:22:35.279 --> 00:22:39.440
And so you have to create clarity of what exactly we're talking about.
00:22:39.599 --> 00:22:41.839
You have to link it to their day-to-day jobs.
00:22:42.079 --> 00:22:51.759
Um, you have to connect it ideally to leadership goals and plans so they understand the importance and the urgency of why we're we're we're asking them to do something.
00:22:51.920 --> 00:22:54.240
Um, and then they require tactical direction.
00:22:54.319 --> 00:22:55.680
You you can't have ambiguity.
00:22:55.759 --> 00:23:01.119
They will they will pick all of your your your verbiage apart, looking for flaws.
00:23:01.279 --> 00:23:03.920
There's a lot of pressure to get things done around them.
00:23:04.079 --> 00:23:08.480
Um, you have to be clear on definition of done or success criteria.
00:23:08.559 --> 00:23:11.680
Here's the problem, here's what it's gonna look like when we solve it.
00:23:11.759 --> 00:23:13.519
Um, do you have any questions and concerns?
00:23:13.680 --> 00:23:19.119
You got a kid glove, you know, white glove treatment them all the way through that conversation and get them comfy with it.
00:23:19.200 --> 00:23:21.200
Look for roadblocks, like what are you working on?
00:23:21.359 --> 00:23:23.920
What is gonna you know interfere?
00:23:24.079 --> 00:23:26.160
And some of this you can't even do face-to-face.
00:23:26.240 --> 00:23:29.119
You got to do it asynchronously because they need blocks of time to work.
00:23:29.200 --> 00:23:37.599
And so, can you can you craft it in email or put it in your ticketing system or get into an existing meeting and put it in the materials that are disseminated?
00:23:37.680 --> 00:23:40.480
You got to find ways to to accommodate that as well.
00:23:40.640 --> 00:23:48.720
And then keep them organized and actionable and you know, headings and formats so that they can quickly scan it because they are by far the busiest folks.
00:23:48.880 --> 00:23:52.799
If you're gonna give them a voluminous amount of information, you need to have it organized and clear.
00:23:53.759 --> 00:23:54.400
That's great.
00:23:54.640 --> 00:24:07.519
You know, it does boil down to a lot of our job is communication when we're working with stakeholders, executives, uh, anyone at any level, communication is on us to be able to speak to them in the right language.
00:24:08.000 --> 00:24:11.440
And I think that's so it get back to the art that we were talking about earlier, right?
00:24:11.599 --> 00:24:18.799
Data governance people get very adept at switching communication styles and content and messaging on the fly.
00:24:18.880 --> 00:24:23.440
Like you walk in thinking, oh, I got it, and I I prepared because I know it's gonna be an elevator pitch.
00:24:23.519 --> 00:24:26.799
And then one executive asks a question, you got to go do a deep dive for five minutes.
00:24:26.960 --> 00:24:28.400
So you cut you have to be prepared.
00:24:28.960 --> 00:24:29.519
Yes, you do.
00:24:30.960 --> 00:24:31.359
All right.
00:24:31.440 --> 00:24:33.200
Well, here's our last question.
00:24:34.160 --> 00:24:42.160
What signals tell you that a stakeholder is truly committed, not just verbally aligned, but really believes it.
00:24:43.680 --> 00:24:44.000
Yeah.
00:24:44.079 --> 00:24:47.759
So verbal, let's talk about what it doesn't look like and then we can jump into what it looks like.
00:24:47.839 --> 00:24:49.759
So verbal alignment is always conversational.
00:24:49.839 --> 00:24:54.240
It's cheap praise, it's smiling and nodding, it's zero effort, zero risk.
00:24:54.319 --> 00:24:55.519
Maybe they don't even show up, right?
00:24:55.599 --> 00:24:56.720
So, okay, that's great.
00:24:57.039 --> 00:25:00.079
True commitment, in my opinion, becomes behavioral.
00:25:00.319 --> 00:25:08.240
So they put their money where their mouth is, they actually do things that show um or that show support or directly help you.
00:25:08.319 --> 00:25:15.039
So it could be they reach out proactively, um, they stay engaged, they ask a lot of really good questions because they want to know.
00:25:15.200 --> 00:25:27.519
Um, if you have anything that you're presenting as like a recommendation or a plan, the moment they start asking questions, they're already starting to think about how they're going to be able to articulate this to their people or relate to a problem they have.
00:25:27.759 --> 00:25:29.519
Those are all really good signs.
00:25:29.759 --> 00:25:36.400
Um, they will also spend their own political and other capital or resources at the organization.
00:25:36.480 --> 00:25:39.839
Um they're gonna allocate people, maybe they're top performers.
00:25:39.920 --> 00:25:44.079
Um, they're gonna remove roadblocks, bureaucracy, and the resistors.
00:25:44.160 --> 00:25:48.880
Um, they're gonna show engagement in in interactions with you and any sort of data governance forums.
00:25:48.960 --> 00:25:54.000
They come prepared, they drive discussion and ask questions, um, especially the tough and uncomfortable questions.
00:25:54.079 --> 00:25:56.240
That that's a really good sign of engagement.
00:25:56.480 --> 00:26:00.960
And what they're what they're sort of alluding to is this sense of shared accountability.
00:26:01.039 --> 00:26:13.359
If I'm doing this out in the open with you in front of other execs and maybe some VP and director level folks, I'm sort of early indicating that that I'm I want to support this.
00:26:13.440 --> 00:26:18.559
And I, if we can work through all this and get comfy with it, then I'm gonna walk out of here and I am gonna support you.
00:26:18.799 --> 00:26:28.160
Um, pay attention in non-DG meetings and forums too, because you'll see all these patterns and behaviors, and that's gonna help you figure out how to gauge culture and who supports what and who doesn't.
00:26:28.240 --> 00:26:38.559
And then if you can learn enough from all of that, you can actually factor that into your communications and your audiences uh before you even walk in and try everything that I just described.
00:26:39.039 --> 00:26:41.920
Wow, that's really a good way to end our podcast today.
00:26:42.079 --> 00:26:45.119
So it really breaks it down for people and makes it real.
00:26:45.440 --> 00:26:48.160
So thank you very much for joining us today, Jim.
00:26:48.240 --> 00:26:50.640
Um, this has been a great conversation.
00:26:50.799 --> 00:26:55.440
And thank you so much for everything that you did for the applied data governance practitioner certification.
00:26:56.079 --> 00:27:01.039
It was a pleasure to be here and to help with the certification and the body of knowledge.
00:27:01.119 --> 00:27:03.759
And what a delightful conversation I always have with you, Barbara.
00:27:04.400 --> 00:27:05.839
Thank you very much, Jim.
00:27:10.480 --> 00:27:20.880
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.
00:27:21.680 --> 00:27:26.880
Until next time, I'm Barbara Nishaw, and this has been Inside Applied Data Governance.
