 Hello and welcome. My name is Shannon Kemp and I'm a Chief Digital Manager of DataVercity. We are proud to produce this webinar series of Data Governance Studies for the Data Governance Professionals Organization. We'd like to thank you for joining today's DGPO webinar, Best Practices for Defining the Value of Data Governance. Just a couple of points to get us started. Due to the large number of people that attend these sessions, he will be muted during the webinar. For questions, we'll be collecting them by the Q&A section in the bottom right-hand corner of your screen. Furthermore, if you'd like to tweet, we encourage you to share highlights or questions via Twitter using hashtag DGPO. The slides and the recording for the DGPO webinar will be made available in the members-only section of the DGPO website at dgpo.org. Now, let me turn the webinar over to Bob from the Data Governance Professionals Organization to introduce today's webinar and speaker. Bob, hello and welcome. Thank you, Shannon. As a reminder, the recording for the webinar will be posted on the DGPO members-only section of the DGPO website in a few days. The DGPO is a community of data governance professionals whose mission is to share knowledge, content, best practices with its members to build a community of practice. Towards that goal, a group of individuals are working to expand our best practices information for the six areas that you see in the graphic on the lower left-hand side here. To learn more about the DGPO, I welcome you to visit our website at dgpo.org. If you notice here, we have our Best Practices Award that we just went through. We had the submission. And to honor those companies, we have advanced the DGP Data Governance Programs and the DGPO Award for the first Data Governance Best Practice Award this year. The award was given to the practitioners with the customer organization in recognition of the business value and technical excellence they have achieved in the design and implementation of outstanding data governance program. We had 18 submissions this year, and these companies were featured in the DGPO webinars throughout the rest of the year. Vanguard was selected as the winner in 2017 and two finalists, TIAA, which we have today, Michael and Donna Bradshaw. That is why I'm thrilled to have the privilege and honor to introduce today's speaker, Michael Nosia of TIAA. Just to let you know a little bit about Michael, he joined TIAA in November of 2004 and is currently responsible for developing and deploying business-led data and process governance capabilities and leading the development of FNA multidimensional vision, strategy and roadmap. In addition to these responsibilities, Michael oversees large-scale transformation programs focusing on strengthening and automating critical financial business processes, improving data quality and integration, and upgrading the finances, underground technology and infrastructure. He is also an active member of the company's Enterprise Data Governance Council. Without further ado, I'll introduce you to Michael, and Michael, we can get going. Are you there? Yes, I am. Thanks, Bob. Hi, Michael. I appreciate that. You saved me a bunch of time. Can everybody hear me? Can you hear me okay? Okay. Now, I don't have to introduce myself. I appreciate that. Did you turn over control with me? Absolutely, share my screen. As Bob alluded to, so thank you for giving me the opportunity to present to this rather large group today around some of the practices that we employ within the finance and actuarial area in terms of defining value from the data governance activities that we've been doing over the last few years. So we're going to talk today a little bit about what value is from our perspective, how we've kind of taken that concept of value, which can be very hard to define, and try to make it more tangible for senior leaders within our organization as well as kind of the general staff population to understand where data governance is and could add value to the work that they're doing in their operational areas. So from a disclosure perspective, we are a financial services company, so here's our standard disclosure. A little bit about TIA quickly, just for the folks that may not be familiar with us, we are a financial services company that's been around for just about 100 years. Right now we have over 13,000 employees and just short of one trillion in assets that we manage for over 5,000 participants and 16,000 institutions. We offer all manner of financial services from IRAs to 401K services, ed savings, et cetera. Our biggest market right now is retirement, managing retirement for colleges and universities and non-for-profit hospitals. So we're pretty well established in that particular industry. A little bit about the governance effort here that I've been leading for the last six years. So you can get a little more context around our discussion of value. So we've been at this about six years. We've made a lot of progress in a number of different areas around stewardship, policy, standards. We have dashboards and we're going to talk a little bit about that. We've done a lot of work around metadata and data quality, defined a lot of terms, touched a lot of different subject areas of data, trained a lot of people over those last six years. And the biggest news is we're still not even done yet. So it's very much a journey as people have probably said in the past and we are still on this journey. My goal ultimately is to get something that is more or less self-sustaining but we haven't reached that point yet and there might be another couple of years before we have enough coverage across the different areas of my organization to say that you can't learn sustainably. So let's jump right into kind of the presentation around value. So I'm going to try to do something here that might be a little bit different. Try to make it a little interactive and we'll see how this goes. So to put some context around the large discussion, we thought we might want to, I thought it would be a good idea. So can I see somebody not getting any audio, Shannon? Sorry, let me pause here. Can you hear me, Shannon? I can hear you fine. I will work with the individual. No worries about any technical issues. Just keep on going. Sorry, I just want to make sure everybody's here. So what I'd like to try to do here just for a couple of minutes is to start our discussion around value is do an auction. I'll try to keep it very simple. So what I want to do is I'm going to display in a second an item for auction and everybody on the phone has now been granted $5,000 with which they can use to bid on this particular item of value. What I would like you to do is you can plug your bid into the chat window which I can see and as we go along I will call out what the bids are and see where we end up. So like I said, I want to do a couple minutes of this just as an illustration of what the different perceptions of value could be. So our first item is Eric Jeter signed baseball. So for those of you who are baseball fans and I'm sure some of you aren't, he's a very famous baseball player played for New York Yankees for 20 years. He's in some exclusive clubs. He's got a lot of career statistics that are hall of fame worthy. This baseball comes with a genuine certificate of authenticity. So I see zero and not Yankees fan. That's okay. You don't have to play along. Everybody is Yankees fan. I see 1,000. I see 600. I see 950 and I haven't even set the opening price yet. This is wonderful. I see 450. Do I hear 1,200 since 1,000 is the highest bid here. So we'll jump right to 1,200. Anybody willing to pay $1,200 for this? Oh, 1,500. So I like. That's true. Red Sox fans with long memories. Absolutely. There's nothing else up for sale except for this baseball. So I see 1,501 has the highest bid thus far, $2,000. Thank you, Norman. So I hear 2,100. Anybody willing to pay 2,100 for this baseball? 2,500. Thank you, Wendy. Anybody willing to go higher than 2,500? 2,700? 3,000 and $1. Thank you, Lopsley. I don't know. That's a good question whether this is a real signature or not. 3,002. It's pretty high. All right. So Kurt jumped right to 5,000. So I think that would be the highest bid. So why go through this little exercise around bidding on something that has some perceived value? So if you look at the certificate of authenticity, to me that's probably a sealer. If I gave you a baseball and I signed it and said it was from Derek Jeter, but I gave you nothing other than just the baseball, I'm not sure we would get bids of $5,000 and people would max out their amount of cash that they have that I've granted to them. So the certificate of authenticity probably is like a form of governance, right? It's a structured authority. But in the absence of something that somebody has a good question, is it the real signature? Right? In absence of knowing whether or not that's a real signature, then you tend to doubt its reliability and how much value you're willing to put on this particular item. So that kind of leads us to what we'll call the definition of value. Did I just click off, everybody? I hope not. Here we go. So from a definition perspective, active value can be derived in several different ways. There's kind of the objective value, represents the replacement cost of the actual item. In this case, it's a baseball, right? You can pick that up in any local sporting that's store, and maybe it's, you know, $14.99. So that's objective value. Then you have the stated value, and you all didn't let me open up the bidding. Somebody jumped right in with $500 or whatever. And so that's a reserve price of the auction saying, I'm willing to start the bidding at, say, $500 to $600. And then you have subjective value, right? It represents what someone's willing to pay for or what somebody perceives that particular item to be worth. Right? It's the final price. It's the auction price, and in this case, it's $5,000. So, you know, why is it important to understand this? Defining value from a governance perspective, to be perfectly honest, is difficult. And I'm sure folks who are listening here may struggle at times to articulate to people why governance, why data governance is valuable to their organization, their particular area. Understanding the different types of value is an important piece to this whole equation because it's going to help you articulate value from different perspectives. So, based on my experience within our particular organization, value and benefits become meaningful from a stakeholders' perspective based on their perception, right? Based on what they think is valuable to them to find from their point of view, which it should always be. So, as you start to wrap your head around kind of different ways of looking at why data governance is valuable and how you might capture benefits of it, which help you illustrate the value, you have to be mindful from our perspective that value extends beyond dollar signs. I think a lot of times we get fixated on how much money did you save, right? Or how much cost did you avoid by implementing some good practices around how we manage data or implementing a policy that prevented people from doing certain things around data, et cetera. And so, as you look at what value means, you need to take into account something broader than just dollars. So, we have the obvious cost avoidance. We have cost reduction. We have things like increased revenue, right? So, sometimes data governance enables increased revenue. It also contributes to productivity improvement, which is another source of value. Or increased capacity, kind of the flip side of that coin. Customer satisfaction could be increased if you have better data. And also helps you reduce risk from our perspective and operational type of risk. So, these are all the sources of value that we tap into when we talk about value with our stakeholders. And in some cases, risk reduction might be very important to the person I'm talking to at that moment. So, my job is to help articulate how implementing some good data governance practices will help them reduce their operational risk. In other cases, I might be talking about to somebody who cares about increasing the capacity or having their people be more productive. And that conversation is much different than the risk reduction one. That one's around saving people time and how they manage the data and making them more efficient in doing so, giving them some tools and some practices, et cetera. So, we try to look at it from a holistic perspective. And we try to identify the ones, the pieces of value that resonate the most with a particular organization. So, in our organization, we look at productivity improvement as a primary driver or a primary source of value. Then we look at increased capacity, risk reduction, and then avoidance, cost avoidance is kind of thrown in there as well. Because we're a support unit within our organization, data governance is not, we don't touch a lot of things where we can take cost out of the organization as we have better practices around how we manage data. But there's another component to the value discussion, and it's around certain enablers that you need to have in place to help realize some of the value around this particular cloud, things like, you need to have people educated and trained to some level, raise the competence of the organization. You need to introduce some standard ways of managing data, so that we call them data governance practices, and then obviously provide people with some tools. How to manage metadata, data quality dashboards, reference data tools, things that will help accelerate and make the management of the actual data more efficient and effective for an area or an organization. If you don't have those enablers, then it's a much harder road to travel to kind of extract value from the things you do around data governance. If we take a step back now and say, okay, so those are the different sources of value that we look at, but how does that come into being? Where do you start this discussion around value? A lot of times the value of data governance tends to manifest itself, at least in our organization in the form of the value proposition. What is your value proposition as a data governance organization? This is something that I'm sure most of you are familiar with. You can articulate, you can start the discussion around value with kind of a value proposition. Your value proposition may be, we don't ensure data is perfect. We provide the methods to easily and efficiently assure that data is fit for use. Maybe your value proposition centers around higher quality data. Or you could be developing a value proposition because cost avoidance, cost savings, and cost out is a real big focus area for your organization. So maybe your value proposition focuses around that. Or you could be a very risk focused organization like we're trying to get as TIA is focusing a lot more on risk. And your value proposition could be how do we help the organization minimize operational risk? So the question really to ask kind of as a starting point for value is, what is the focus? What am I here to support? Am I here to support increased revenue, the growth of the company, reducing operating expenses, becoming more efficient, et cetera. And when you figure that one out, then you can articulate that in some sort of short statement which helps you communicate with your stakeholders. That's the starting point for the conversation. And everything else that follows is evidence of how you're affecting this value proposition inside of that particular organization. Now, from our perspective, we've actually defined a pretty broad value proposition intentionally. But it gives us the ability, because it's so broad, it gives us a little latitude and some license to look at value benefits from a number of different dimensions. So we don't pigeonhole ourselves into cost reduction or cost avoidance from one of those that I mentioned earlier. Because we recognize we need to have the ability to communicate to different audiences and articulate that value in different ways. So our value proposition is pretty simple. If you're all familiar with years ago, BASF, big companies used to run commercials like we don't make X better. We don't make X. We make it better. And so we took a play on that and came over the value proposition that we don't make the business decisions. We try to make the decision-making process more reliable and efficient. That's very broad. It can mean anything. But from a data perspective, it gives us a focus on overall decision-making capabilities, which could include data itself. It could include information reporting, analytics, operational processing to get the data, et cetera. But it's really primarily focused on productivity, proven and cost avoidance. And that's what we sell or talk about most often to the stakeholders around the table. And when I say stakeholders in our organization, I'm specifically talking about the CFO of TIA and her direct reports. So that's our big stakeholder group of senior leaders. And when I talk to them, I talk to them about productivity improvement, cost avoidance, and risk reduction, is the other component of this. But getting from a value proposition to something that is more operational is challenging, because value propositions are very conceptual in their nature. That's intentional, kind of like a vision. We don't have time to... I'm not going to take you through the step-by-step approach, but I am going to talk about the big pieces or the big steps that we took to kind of take this value proposition and translate into something more tangible that we can share with our stakeholders and really operationalize. So when you start with the value proposition, the next step that we took was... and this was years ago when we first started, we defined our governance priorities and goals, right? Seems like an obvious step. So we tried to take the essence of the value proposition and bake that into our priorities and goals, excuse me, that would span over a one to three-year period from the goals and objectives and the priorities, we translated those into metrics, measurements and metrics, right? And a dashboard that we can now start accumulating data to start shaping the conversation around value. So really, you're taking something from very conceptual on the left-hand side of value proposition and we tried to make it very operational and practical. So boiling that conceptual idea, the theoretical idea, into something that we can measure now and measure on a consistent basis across multiple components. So I'm going to kind of break these down for you separately. So let's take a look at step one. So we called the governance agenda and it's really our one to three-year look of priorities, goals, strategies of how we're going to support a particular organization. We've defined six different priorities. If you can read them, they're right there, very high level. But the important thing here is we tied each one of these back to the strategic priorities for finance and actual work of a group on it. So we have complete line of sight on, hey, assessing regulatory changes and the impact of different regulations on how we need to manage data goes directly to our strategic priority around maintaining our financial strength. Since we're a finance organization, it's one of our responsibilities. One of the hats we wear is to make sure that everything's accounted for, reported. We give good advice around how business decisions are made, et cetera. We also include in the agenda what we're going to do and how we're going to do it. So we talked a little bit about high level strategy and how we're going to assess changes or how we're going to drive data governance practice adoption. And for each one of these priorities within governance, we have a series of metrics and goals and targets for those metrics that we lay forward and we track on a consistent basis. So we try to have, as I mentioned, the line of sight to say, this is our value proposition. These are the things we're going to focus on. Here's how we're going to measure that. And it all ties back to the strategic priorities of FNA. Then from there, kind of drill into the scorecard a little bit. So the agenda is the thing that gives us our plan. The scorecard is what we use to track and report the value. So we have four basic components to our scorecard. The first is we track metrics around education and awareness. And these are important. It's a key enabler that we believe that you have to have a certain level of competency around your staff in general around how to manage data and what good practices are. And they have to have some awareness of that. So we have some metrics that we use to track that. It brings value to the organization through education and training. We also have a series of metrics where we track the progress, the impact that we're, or the progress we're making in different areas of FNA, implementing standard governance practices around, you know, how we define metadata and data quality and all the familiar disciplines from a data governance perspective and where are we affecting change in that. Then we also, on the bottom right, we look at the actual results of that. So here we track things like what's the quality of data look like, how many issues do we have open, how long does it take us to close those issues, the average aging, for example. We also look at productivity improvement. So we survey stewards, and I'll talk about that in a second, but we try to measure change in productivity because of implementing data governance practices. And the upper right is kind of an amalgamation of the other three quadrants around operational risk. Kind of, this is something we made up internally to say if I took all the things we're tracking in the other three quadrants and boiled those down and looking at it from a risk perspective, we calculate that. So those are the quadrants around our scorecard. And so let's dive into, let's show you a picture what the scorecard actually looks like. So we go through and we set targets on an annual basis for each of the metrics. We visit that every year with our stewardship community, and they buy into and improve it. We also publish the scorecard on a quarterly basis to share a point. I share that with the CFO and her directs. We talk about not every quadrant every time, but I focus in on that. So they have, this is available to them. And as I alluded to just before, we look at a lot of different, we look at a lot of different metrics, right? Because we want to articulate value from a lot of different perspectives. So you'll see awareness. So we're big around education and training, and we actually survey our employee population around their general awareness for data governance. And it's a metric that we track. And we do that twice a year, a random sample of folks. We also look at other metrics, like how we're doing against our metadata metric around defining terms and common language. We also look at critical data elements. We also look at productivity, as I mentioned before, how much improvement have we made from a productivity standpoint. We track progress against projects that we're working on, as well as subject areas that are covered by standard data governance practices. And then the operational risk, we aggregate all these metrics and weight them. And we come up with this risk rating. And so really what this is saying, the risk one is interesting, because it's on our F&A, financial and actuarial scorecard that we report to the enterprise. The operational data risk index is. And it's a metric that we look at and the way I describe it is this. So every organization has risk. We're all familiar with that. We have to document it. We have to have mitigations to it, et cetera. But one of our goals from a data governance perspective is to not have the risk operationally be rooted in bad data. I'd rather have the risk be we have a completely manual process to execute this particular important operational function. So that's what the risk is based on. It's not because the data in that manual process is of poor quality, right? So that's what we try to measure here and articulate to people. So let me give you a couple of examples. So here's a couple of examples on the left of some of the metrics that we use. We track the percentage of F&A staff that we've trained each year. We also look at, as I mentioned, the overall awareness from a governance standpoint. We run from a training and education perspective. We run a series of, we have a curriculum that we've built out for stewards and the general F&A population that takes them through kind of the very basics of data governance and more awareness and more awareness of what it is to what our data governance practices to all the way to kind of a boot camp day and a half to two days of hands-on how do I define terms, right? How do I build a data catalog? How do I understand and identify critical data elements, et cetera? Training's always been well received. Right now we're well over 100 people that we've trained. It's not just within F&A. We've also trained our IT partners that support us from a data management perspective on the IT side. They've attended boot camp as well, as well as a lot of the enterprise folks who participate in different areas of the organization. They've also come into our training. So that's just a couple of examples of kind of how we take the value proposition down to some specific metrics. Now from a result and impact perspective, the one I'm highlighting here is productivity improvement on... but I'll talk about overall systematic data quality. So we measure data quality for a lot of the source systems that we use here in finance. Not everything is kind of systematically monitored. So right now our metric is just focused on those things that we can gather automatically, as they say. And we use a homegrown data model for the data quality, and we use OBI, Oracle's Business Intelligence Tool for dashboarding and things like that. But from a productivity standpoint, one of the big things that we talk about is reducing the amount of data assurance work. Every time somebody touches the data to fix it, scrub it, reconcile it, clean it, is a lost bit of time they can't spend doing something else. So when I said our value proposition focuses on productivity, it very much does. We want to provide people with a standard way of doing something that helps them do it more efficiently and the right tools to help kind of accelerate that. And we measure it because the data assurance in any organization is a tax. We'll call it a data tax. In our organization, it's sometimes 30% of people's time. And we're just one function. Our function's got about right now probably a little over 700 people. So you're talking, you do simple math, that's millions of dollars in lost productivity because people are just fixing data. So our goal is to have them spend less time on that. We'll never eliminate it completely, right? That's not realistic. But it's one of the things we focus on and it's a big opportunity cost for us. So we survey the stewards around how much time they spend doing those things. And we do that on an annual basis. And then we look to see where we've actually worked with folks on implementing standard practices and we use that to measure improvement in their productivity. And right now we're seeing about, on average, 8% to 10% productivity improvement when we've gone in and worked with different areas to implement a standard set of practices. So those are just a couple of examples of how the scorecard kind of enumerates our goals and objectives and tie-staff, our overall functional goals and objectives as well as our value proposition. So that's kind of where we end up. And like I said, one thing that's important to note is this is not a static thing. We sit down purposely every October through December and we revisit, not our value proposition, because that should endure the test of time, but we revisit our goals, our objectives, our priorities, our strategy, our metrics. And over the last six years, we've evolved the scorecard kind of the end result of how we measure things numerous times, right? Because like a lot of you, we're learning as we go and some things don't make sense, some things are too hard to measure, some things don't actually enumerate the value that you're looking for. But if I contrast this with other parts of our total company, you know, some of the things we focus on, the productivity improvement and cost avoidance aren't as important as improving the customer experience or taking costs out of the operations that support our customers, which is very much a focus for that. So other areas could be focused on things like return mail, right? It's an easy one. We get, I don't know, thousands upon thousands of return mail. And each time it comes back, it costs us money. And the reason why is we might have, most of the time, bad address. So there's a master data issue. So governance for the operations group focuses around how do we improve master data in order to reduce the amount of return mail, thus saving the company real dollars off our bottom line. And there's different examples around that, you know, around the organization, how every group might focus on something different. And it's the same old scooper the folks on this call, right? What we focus on may not be something that's important to your organization, but you got to find that thing. And then you got to figure out how do I measure that and how do I articulate it. Very important from a business perspective, right? What's the business impact of that and how can I translate the data I get and the things I see into something that would resonate with the business. So as I close out, so we'll do a little recap. I'm a firm believer that dollars are not the most important or shouldn't be the only thing you focus on. Let me restate that a little bit. And it's very important to understand who your audience is and what they value most. And the way that we did it was we just asked the question. What would you find valuable? And some people said, I want you to resolve my data issues, i.e. I want the quality of my data to be better than it is today. Others, I don't want my people spending time managing data. Okay, so let's focus on productivity, right? So you ask the question, you're going to get some different answers, but that's okay. Now it allows you to game plan kind of how you want to track and manage the value around data governance. The second thing is it definitely needs to be linked to the business schools. That is to me an imperative. So you have to be able to, you should be able to say, here's the goal of our organization. Here's our priorities from a governance perspective. They align and supportive of, right? Because governance is a support function or operational thing. And then this is how we're going to manage and report back to you on how we're supporting that goal. To be honest, data governance is a conceptual thing, right? And when you say it, it conjures up all manner of definition for people. Some people don't even know what it is and other people have different views of what it means. And so you have the opportunity of helping to define what it means for your organization and that's kind of what we did here. And the third thing is say pay attention to the things that enable the value, right? So we focus a lot, as I said, on education and training as well as tracking the progress around the different areas of finance and action work that we're actually working on and putting standard practices in. It's important because the more educated and more competent you have kind of from a general sense, it's easier to work with people and they start to see why this is something that they need and want. It's always a push to start, but what I found over the last six years is as soon as you complete and give them something that's tangible, they tend to want more of it. And a lot of times they don't know they need it so you got to make them aware, right? You have to educate them about what it is so people have a common understanding. You need to support that with the right tools and we don't have a large budget and we have a small budget and what I mean by small is zero to buy tools. So we relied on the enterprise to help us enable some of the things that we're doing like metadata. But from a data quality perspective, that was something we built on our own through the backs of other strategic projects. We kind of piggybacked on things. But the reality is that you actually don't need a whole lot of money to kind of get to the point where you're demonstrating and articulating value. Sure, it'd be nice to have a data quality dashboard that can automatically update every day and show you where your problems are. But you know, you really don't need that. All you need really is an access database that you can load data into and write some SQL queries. And any business person kind of analyst could probably do that, right? So if you don't have a tool, you don't need to rush right out and get one. I would rather, my advice to folks is, establish all of these kind of foundational things. Figure out what you want to measure, what are your goals and objectives, what are your metrics. Then build it in something that you can control and then migrate it eventually once you've tuned it to some sort of tool. But if you don't focus on the enablers, sometimes it's hard to extract the value out of things. But if I say disregard everything I just told you, I won't say that. But at its core, one of the things that I believe and that we practice here, it's great to talk about the value and it's important that you articulate it. But what data governance really is, it's about shifting the culture of your organization, right? The mindsets and the behaviors of people and how they interact with the data. That is really one of the primary focuses. And by focusing on that, it helps us kind of extract value out of the things that we're doing. Because I can't stand there all the time and beat the drum of this is good stuff, this is good stuff. The more impactful thing is to have somebody that you work with say, this is good stuff, this is good stuff. And in order to get them there, they have to change. There's some change involved, right? There's a culture change on how we manage data. There's a mindset shift to this is good, not bad. I don't understand it now I do, right? This is beneficial. I want more of it. And so the enablers kind of tie into that. And if you ignore those things, I'm not saying you won't be successful, but the degree of success might not be as much as you want it. And every time I go and speak at different conferences, one of the questions I ask is, how many people are on their first iteration of data governance, second, third, fourth, fifth, sixth? I think my record was ninth iteration. And I'm not saying it's all attributed to this, but there is some element of that mindset shift, right? The behavior and people not focusing on that as much. And so we do deliberately focus on it and we track metrics against it because we think it's that important. So that's all I have. I think we're going to open it up. I've been monitoring the chat. There's a lot of questions. That's it. Thank you. Thank you for the time. And so we can open it up for questions, Shannon. Sorry. It was not prepared to be. Bobby, are you going to moderate? Let me just dive right in. So let me just kind of go through here. We've got some questions in. So how many staff members do you have on your DG team? We get that question a lot. People want to know how to structure their team. Sure. Right now I have three, not including myself. And let me preface, let me put some additional context on it. When I started, it was me back in 2010, 11. Then I added one person to the mix there. And then a couple of years ago, I hired another person. Then I inherited somebody. So now I have three. And I don't include myself in that because right now I'm not only responsible for data governance, but I'm also responsible for strategy and planning within the finance organization. I'm also the administrative function of our organization, as well as I just picked up continuous improvement, which is kind of our six sigma and lean first. We have a team around that. And I also own the PMO. So I wear like 900 hats. I used to count myself as, I would say four, but now I can't count myself. So we have three. I love it. Bob, I hear you there too. So we've got, let me go in first. I'm just trying to get caught up on the questions here. Is it suggested to start with the vision statement followed by the value proposition? Yes. And so I neglect to say that we do have that as well. We have vision. We have a mission statement. We have kind of a high level strategy statement or strategy map. And then we derived kind of the value prop from those things. But yes, that is correct. You should start with the vision. Everything should start with the vision. And so then how do you measure the education awareness success of your data governance scorecard quadrants? So each quadrant. So from an awareness perspective, we survey the finance and actuarial population, general population twice a year. We generally send out about 200 surveys. We get generally around 60% response rate. And we ask them a few simple questions around like, are you aware that we actually have a function dedicated to data governance to do you know who your steward is? And there's a number of other questions we ask. But from that we get to derive kind of overall awareness as well as some other metrics that we pull out of that data. So that's from an awareness perspective. From a training perspective, we do a running count every year of how many people have attended our formal training sessions. We also hold informal things, lunch and learns, and that type of thing. And we track attendance on that. Anything that we do, we track attendance. I have examples of the type of questions that are asked in the surveys that you've sent out. The one is the two that come to that I can think of right now are what I just mentioned before, which is are you aware that we actually have a function around data governance dedicated to this? That's number one of the questions. The other is, do you know who your steward is? Within your particular area or subject area? I can't think of the others off the top of my head. I'd have to, something I could take a note on and provide that back with you. I can put it as an appendix. Sure. And then back to the value statement. Can your value statement be based on employee interviews, surveys based off what they currently cannot accomplish with the data as opposed to starting them from the top management? Absolutely. Yeah. I mean, we decided that one of the first things I did when I took over that part was charged with starting this function was I went and met with a number of different people. I started with the CFO directs and interviewed them just to get a basic kind of buy-in, right? Like, do you think this is important? That was one of the questions I asked them. I also asked them what they thought it was, right, from their perspective. And then over the next several months after that, I talked to my peers within the organization and I got different perspectives. And then we kicked it off with stewards and that. And really, we do a lot of work. I wish I could take credit for all of this, but to be honest, we involve the stewards in a lot of things that we create here because I'm also a big supporter of people who participate in the process or have to adopt it and kind of manage it on an ongoing basis. So our policies, procedures, our standards, our scorecard, our goals, objectives, we're all driven. We guided them, but they were developed and driven by our stewardship community. You know, and we're certainly seeing, you know, the attitude of businesses turn around, but we still get a lot of questions about, you know, and there's a question here, you know, how do you pitch this value proposition ahead of starting the data governance program? You know, how do you bring this up to the exact, how do you get by off on getting a DG program going? Well, so you can't go, well, I was going to say, you can't go in cold, right? You actually have to do some, my advice is that you do some covert research on your own within your company, and you need some horror stories, unfortunately. Unless you're faced with a regulatory, like in the financial services industry, it is not a, look, I know all the big organizations have chief data officers, they have data governance, and I think a lot of that is driven by the regulatory environment, right? So you've got that big club out there. If you're not in a financial services industry or a heavily regulated industry like healthcare or something where you have regulations that are, mandate that you manage data, you know, you have to have good practices around that, et cetera, then I always say you need to collect a few horror stories that will resonate with people as a way of illustrating the value proposition, whatever your value proposition is. Because it's such a conceptual idea that people can't wrap their head around what it means until you translate into something tangible. Here's an example. So a couple years, a few years ago, our enterprise data governance was giving an update to the CEO and the executive committee around the progress. And one of the things they used to illustrate, this was the first time I think that they were kind of providing a big update. And one of the things they used to illustrate why this is important was a death date. Right? Death date's important in the retirement business. We have to know when to start paying out benefits, who the beneficiary is, et cetera, et cetera. And if we had some inconsistencies in death date, we decided the way to approach that would be to use the Social Security's death index that they put out every month. And so because we did that, it saved gov the money probably. But the way you articulate that is, you know, we don't send checks to dead people anymore. Because now we have a better understanding of that. And because of that, you don't even have to tell people the number what it saves. They can do the math in their head. If we send out $10 billion in benefit payments a year and we get checks back, it's millions of dollars. So my advice is be a little covert, go out and talk to people, gather some horror stories that have some real impact, and use that as a way of articulating how governance can help in situations like this. I love it. You know, and there's several more questions. I don't know. We've covered some of it, but maybe you want to go a little bit more in depth too just about the roles of the current DG members that you have. And then, you know, the interaction of how you set up with the data stewards. Okay. Yeah, I could talk about that briefly. So the folks that report to me, you know, have titles are kind of immaterial. But their role is to work with data stewards and data SMEs or subject matter experts to implement a set of standard governance practices that we've defined around, you know, how you met a data management, data quality management, reference data management, business architecture, data architecture, governance and stewardship, et cetera. So that's their primary role. And I have two people that kind of support that. Now we have a different model. We don't, we now have a hybrid. We kind of waffle back and forth. Because we don't have a ton of money and we're not funded other than the people, we implement the practices on the backs of other strategic projects we have here in finance. So we work with project teams and we weave our activities into the overall project plan and it becomes a work stream in the project. And our IT partners kind of contribute to that as well. And so that's what my folks primarily focus in on. And we also do work on behalf of the enterprise, run some working groups. As far as stewardship goes, right now when we originally started, we only had about 15 stewards. We divided finance up into 16 subject areas of data, kind of these big blocks of discrete data subjects. But over the last couple of years, we've actually expanded that to now, we have over 60 different subject areas of data. And we have over 60 stewards. So we have one person kind of aligned to each one of those subject areas as a steward at that level. And then we have what we call functional stewards, which is the person that attends the committee meetings. And so for example, we have a steward from our corporate finance group. And underneath that steward, they might have 10 subject areas. And each one of those subject areas has a steward. And so we've trained all those people over the last year and half or so in awareness training and stewardship. We've had some specific stewardship training developed that we developed and delivered to them. But it's a pretty broad organization now. We meet with them every month. And then every quarter, we gather the entire group of 60 plus together on a quarterly basis. I think that's, you know, there's a lot of questions around lots of stewards, but no budget for tools. That's right. It's charm. I smile a lot. And my opening position with IT is, you're going to do this work for free, right? I love it. And what is, you know, what is your training and compass for the... So that's also evolved over the last four or five years. Right now we have a full curriculum for data stewards. And it starts with a one-hour orientation where we just say welcome to the family. And, you know, here, thank you for being voluntold that you are now a data steward, et cetera. And then we follow that up with a half-day training. And that training is focused on answering the question, what does it mean to be a data steward inside of F&A? And then if that data steward is going to implement data governance practices, they will go to a bootcamp training, along with their... anybody else they want to invite from their area. And that is focused in on... we have 20 different governance practices that we like to implement as part of kind of a standard package. And so we take them through the methodology around that. We take them through how to implement each one of the practices, and then we track their progress in implementing the practices over the course of a year. And we have a project plan, a work plan that they follow, et cetera, in doing that. And so all of that, we've tied all the training to CPE credits, so that's very important in the finance arena. And so we give out like 16 CPE credits for the training. And then for the general population of folks in F&A, we do a series of high-level, wise data governance important. What does it look like within F&A? What is stewardship? Who are your stewards? Just kind of that general awareness training for them. I love it. That brings us right to the top of the hour. Michael, thank you so much for this great presentation. And, Bob, thank you so much. Anything, Bob, you want to add before we close out regarding the DGPO? Yeah, and listening to him, I'm wondering why he wasn't number one. With the award we gave out, it's just excellent information. They said it was very close. They said it was very, very close. It really was. It really was. We're talking like one or two away. But I just want to reiterate thank you for an excellent presentation. Just to remind everybody that the slides will be posted on the DGPO members-only site. Again, thank you for your time. Thank everybody else for joining. We'll see you next time. Thank you. Okay.