 Hello and welcome my name is Shannon camp and I'm the chief digital manager of data diversity. We would like to thank you for joining the current installment of the monthly data diversity webinar series real world data governance with Bob Siner. Today Bob will discuss the role of data governance and a data strategy sponsored today by precisely just a couple of points to get us started due to the large number of people that attend these sessions you will be muted during the webinar. If you'd like to chat with us or with each other, we certainly encourage you to do so. And to note, zoom defaults the chat to send to just the panelists but you may absolutely switch that to network with everyone. And for questions we will be collecting them by the Q&A section or if you'd like to tweet, we encourage you to share highlights or questions via Twitter using hashtag RWDG. And to find the chat and the Q&A panels and if I click those icons in the bottom of your screen to activate those features. And as always, we will send a follow up email within two business days containing links to the slides, the recording of the session and any additional information request throughout the webinar. Now let me turn it over to David for a brief word from our sponsor precisely David hello and welcome. Thanks Shannon, I appreciate very much you guys having us here today and Bob I appreciate your presentation and the ability to sponsor very much looking forward to the conversation. I wanted to introduce myself and then just give you a little thoughts on from precisely and kind of the way we think about some of the topics that we're going to discuss here today so first a little bit myself. I'm the strategic services organization for precisely run that for about the last 13 years. Previous to that I run ran global data and analytics for Johnson and Johnson so I'm the very fortunate unique position have sat on kind of the customer side of the house and now on the other side of the house the strategic services organization is really the management consulting arm within precisely we really I think at a macro level help organizations design implement operationalize and ultimately optimize their data programs I'll tell you guys a little bit more about precisely as an organization as I wrap up but I wanted to talk about the topic today really the importance of the topic today. And really data governance being an integral part and really a catalyst for an overarching data strategy and you know it occurs to me that you know as we've been looking at the space and I've been in this space for many years four or five six years ago, you know we heard a lot of the analysts talking about there's going to be a billion dollars plus in global data infrastructure spend and there's going to be over $5 trillion in digital transformation investments and that's really come to fruition it's actually exceeded that right now and you know I talk personally about five or six CEO level executives every week and I can tell you what IDC says is absolutely right you know 83% of those absolutely want and really require their data organs their organizations to be more data driven and as it relates to kind of how they've instantiated that as part of an organizational construct you know I remember 345 years ago I would either chair host or I would attend a bunch of different CDO conferences and I would say about 7075% of those attendees weren't CDOs right they were data governance. You know data management managers directors, leaders of data programs but never at that executive level and now as you guys can see there's almost seven out of 70% or so seven out of 10 Fortune 1000 companies right now have CDOs. And that's a significant increase so really really critical concept here. As we talk about data integrity and we talk about data governance particularly as part of data integrity within a data strategy. One of the things that has been kind of opaque here for the past four or five years is what does data integrity really mean and we really used to work with organizations four or five six years ago or so data integrity was really around concepts around data consistency data accuracy data completeness etc very kind of control based type measures for data quality and data integrity. What that's really morphed into and it's really a synonymous with you know the instantiation of all these data lakes four or five six years ago very much a billed if you will come type mentality where we tried to homogenize all these different disparate data sets into a platform. More recently however things have been much more around context right and homogenization of not only the data but the user experience and our ability to actually interpret that data and use that data to make informed business decisions. And that's why beyond just kind of accuracy consistency context is critically important and as we think about kind of the topic today in governance, governing that information and that data is really a key catalyst and a key driver to getting at any value out of or even driving your data strategy for let alone having any efficacy with it. So, when we think about data governance specifically and we think about this categorization this definition of data integrity which is really be, you know, becoming prevalent across all organizations right now, governance in and of itself needs to change as well right so governance around accuracy and consistency tended to be very very control based. Now as we're using this information is homogenized information to make more informed more predictive more forward looking type of business decisions, we really need to apply different levels of governance to that data and we need to tie it to different value drivers within the organization. And precisely, what we like to do is really kind of imply a business first approach as we look at this data. And as we build our data strategies, and we build our data governance constructs commensurate with those strategies. It's really important for good organizations to prioritize the data that matters the most so when we look at kind of this diagram on the right hand side. Most organizations have between 20 30,000 different data elements across all their ecosystems the subset of that generally 68,000 of those are used to conduct this daily business operations so they're within our transactions within our systems and our interactions with our customers and our suppliers etc. A further subset of that information generally about 4 to 800 or so are used as part of our performance measurement framework right KPIs, PPIs, any other performance measures or metrics. And a further subset is generally in about the 200 range or so are your critical data elements that are really driving informed business decisions and really making a difference. What's important as you think about your data strategy and as you think about your data governance construct as part of that is we prioritize and we build the model based on the stuff in the middle, the information that matters the most. And why that's important is really the second bold point is because it's critically important to get some efficacy to link your data governance efforts to business goals and business objectives things at sea level and then minus one and minus two organizational roles really really care about. And then good organizations don't think they got it right when they walk in, right what they do is they have a construct they have a framework, and then they start to test drive that framework against value added use cases. And all those things together really drive and sustain ultimately that business stakeholder alignment and organizations that have done this have found that their time to value is 5x faster than otherwise. Now it's great to kind of have that concert but how do we pull this together and where do we really drive that relevance. So, as we think a lot about how we link our overall strategy to the things we're going to do from a data governance perspective which are kind of down the bottom right. We need to think in terms of the why in addition to the what in the how right so from a one to how perspective as we think about building these programs extending these programs are optimizing these programs. We think well what are we going to do we're going to build an organization or we're going to update or augment organization. And how are we going to do that we're going to have data stewardship roles data ownership models we're going to identify our critical data elements. We're going to build a governance framework and what are we going to do to drive that and how are you going to do that we're going to standards we're going to rule we're going to process standards we're going to trace ability. Back to the business processes and the key measures and from a tools perspective same type thing. The problem with that is is that's really not relevant to C level executives are really kind of mid level organizational or functional leaders. So what's important from a governance perspective and an overarching strategy perspective is that we take those what I call less visible enablers and we tie them to things at the C suite level, and their direct reports care about so C suite, folks that I talked to, they care about four or five six things and that's all they focus on. Below that I might care about maybe five, six, maybe 10, maybe 12 maybe 15 things as it relates to the processes I own the performance measures that are going to measure their efficacy or their success. It's critically important that we tie what we're doing from a data governance perspective through those critical data elements in the tactics we have to govern that data to things that at a strategy level. The executives and the organizational leaders are going to care about visibility and having that that that relevance is important, but it also pays dividends, right and I'm sure everybody on the phone here as a data leader has either been part of participated in or led projects where you've seen this cycle right so we have some sort of a business trigger whether it's a customer 360 initiative to digital transformation, a merger and acquisition and system upgrade, where we spend a bunch of time this kind of scrambled to get our data right, what we call kind of data ready generally to go live and what we find is, as we go live that data degrades almost immediately. So Garner will tell you that that data degrades at a rate of two to 10% per month, not per year but per month, right. So, your financial data and your supplier centric data may be in the low end of that scale, your customer, and certainly your product information is going to be in the high end of that scale. But as that data degrades eventually the organization has some sort of a call to action whether it's COEs or a lot of high touch mechanisms to get that data back up to where it was when we went live. And the problem is in the benchmark data will tell you is that takes anywhere between 18 and 24 months without a governance construct in place as part of that strategy. And the executives that signed up for this transformational initiative expected to get value pretty quick, right, and now if we're deferring that value or delaying that value 18 to 24 months. There's a lot of issues with that both from a social perspective and then from a financial perspective as well. What we found is, and Bob's going to go into some details on this, if you guys can think about a governance strategy employ some of those tactics as part of a program. Shorten that cycle and shorten that dip, any new program, any new change organizational change management and some sort of a dip. But by really putting some of the concepts in place that Bob's going to talk about we can really accelerate the time to value and we can really drive from programmatic perspective, significant savings so you'll see 25% reductions on average and implementation times and where you spend the most time and kind of your build and design phases and the front end of your testing phases, there's a 40% and 50% reduction, respectively in your development effort and then your rework cycles for your functional specs around data. So a lot of value Bob's going to kind of talk about here today and the way we address that is really a parallel integrated approach and I'll build this out for you guys in that it's great to have these kind of what I'll call top line level strategy components and the governance constructs that we think about aligning to those value drivers, you know, designing a data governance framework and decision tree to not only identify critical data elements but tie them to the business value drivers, then developing processes or or operating models with a complementary organizational structure to help have efficacy and then drive value from that and ultimately be able to measure that way we like to interact with our customers is we actually looked at like to look at a fact based way as well down the bottom and actually then take those critical data elements, operationalize them as part of the framework and decision tree to find governance strategies for those data governance elements, and then do some data profiling and analysis and enrichment that help validate and invalidate in some cases those metrics in the overall model. By having a parallel approach or one year time to value is a lot quicker and a lot faster but to your model up top that you're going to live into from a strategic perspective because it's much more informed, much more fact based. So again really looking forward to Bob's conversation here with you guys today, learning a little bit more as I always do when I listen to Bob, and you know happy to sponsor, you know very very proud to sponsor with the diversity as always. And just want to leave you guys with the fact that we have a lot of solutions and a lot of services, some of which I've given me a top line view of here today. You deploy these in over 12,000 customers, both large customers as you can see 99 and the fortune 100 but also it's not a one size fits all approach right so small medium size businesses also are going to be able to follow and get a ton of value from some of the things that Bob's going to talk about today so with that Bob I'm going to turn back to you look forward to the conversation I'll join you guys for the q&a. Thank you so much for this and thanks to precisely for sponsoring today's webinar and to help make these happen. And if you have questions for David or for precisely feel free to submit those in the q&a panelists. Again, as he mentioned he will likewise be joining us for the q&a portion of the webinar at the end. Welcome to our to our speaker for the series Bob Siner. Bob is the president and principal of kik consulting and educational services and the publisher of the data administration newsletter T Dan calm. Bob specializes in non invasive data governance data stewardship and metadata management solutions. And with that, I would give the floor to Bob to start his presentation. Hello, and welcome. Hi, can you hear me okay. You sound good. I'm really really good. Well, really, really happy to have all of you here today. Thank you David for a great presentation. There were so many things that you talked about in the 10 minutes that you had that I'd love to just kind of expand upon. Thank you for having me to do that at another time we, we need to focus on the topic of this webinar but from everything that you said specifically focusing on critical data and critical data elements. It's a relevant subject for every organization that is looking to focus their data to implement their strategy incrementally from the fact that the governance enables and accelerates your data strategy and your data program. All of these things are really important. In fact, the whole topic of the role that data governance plays in a data strategy has become a really important subject to me. I am going to kind of jump into the slides I always begin the webinar by just telling people a little bit about about me in my background. One thing that I want to kind of point out that I kind of always wash over at the end is the work that I'm doing with Carnegie Mellon University. They're a conjunct faculty member with their chief data officer post graduate program and so much of the conversation and the education that's being provided to these either CDOs or aspiring CDOs. The numbers of CDOs are going up. Well, that's because company or universities like Carnegie Mellon are focusing on educating people in the role of a CDO or people who are aspiring to become CDOs. A lot of what they're teaching to the students focuses on putting together a good strategy. I've had the opportunity to guest lecture a few times in terms of data governance, but overall the program really focuses on helping organizations to set up data strategies. So just a couple of the things that I'm working on, things that I'm involved in. As you know, we've got this monthly webinar series on the third Thursday of the month. Next month, I will be talking about another really important topic. In fact, the backbone of anybody's data governance program, even from the things that again what David talked about with the operating model with the framework is roles and responsibilities. So I'm going to share with you an updated operating model of roles and responsibilities and how you might be able to use that to fit into the culture of your organization and take an approach to implementing data governance. Really taking an approach to implementing noninvasive data governance, which is something that I talk about quite a bit. If you're interested in learning more about noninvasive data governance. Please go and take a look for the book that I wrote several years ago called noninvasive data governance, the path of least resistance and greatest success. There are some learning plans that are available through diversity through the diversity training center that focus on noninvasive data governance, noninvasive metadata governance, and then specifically about business glossaries data dictionaries and data catalogs. I had the fortunate event of being able to speak at Enterprise Data World, which just wrapped up yesterday. I'll be speaking in June in person at the data governance and information quality West conference that's going to take place in San Diego, Shannon mentioned to my publication the data administration newsletter, please go out and check it out it's free. There's lots of great information from a lot of people around the country around the world, help you to administer and to manage your data better. My consulting business is called kik consulting and educational services, kik stands for knowledge is king, and the focus of my consulting business is to transfer best practice knowledge to my clients. I mentioned the Carnegie Mellon University gig. It is, it's fascinating to be working with chief data officers, and it's amazing to see that how many of them are really learning about what it takes to put together an effective data strategy. I'm going to talk about how to structure a data strategy in today's webinar I'm going to talk about the role that data governance plays in the overall data strategy. I will share with you a couple examples of layouts for a strategy but we're not going to focus our conversation on that we're really going to talk about data governance and how it needs to really come out and be stated in your organization's data strategy. I'm going to talk about how to address the old adage of people process and technology, and including those things in the data strategy, why data governance is an important piece of the data strategy. In fact, if you have a presently have a data strategy that doesn't heavily incorporate data governance and the operating model and the framework into it. You may want to reconsider because data governance kind of again since at the base of the many organizations models when it comes to implementing an effective data strategy. We'll talk about how to include governance in the strategy, and I'll share with you some examples of how some organizations have done that. So just want to reiterate real quickly that I'm not going to give you a lesson here on how to create a data strategy, you can go online you can go on the internet and find a lot of information structures for data strategies examples of data strategies. I'm really going to talk about how are we going to integrate governance into that and I oftentimes in these webinars start out with definitions, and I typically provide several definitions. I just want to start out with my definition of data governance for this webinar. And so data governance as I've, as I've been known to say is the execution and enforcement of authority over the management of data and data related assets or data related resources. And when I talk about the management of data and all the things David just shared with us about the data integrity and all the important aspects of data integrity. It really comes down to definition production and usage of data. I know this is a very strongly worded definition. But I like people to sit up and take notice when I provide a definition to them get them to scratch their heads and say well do we need to word it that strongly. At the end of the day, you know what you need to enforce authority over the management of data you need to find a way to execute that. And a lot of times, it's going to be to you need a strategy in order to do that you may need a policy in order to do that, but you know, let's stick to the strong definition of data governance and recognize that that's got to be an integral part of the of the data strategy that we're creating for organization. So I my slides are not moving. Sorry about that. Let's try that again. Weird things happening. Okay, so one of the things that I suggest to you is that you ask yourself this question about data within your organization and I'm talking about it holistically within the organization not just within a specific pocket of your organization. So the questions that you should really ask yourself are, are you executing and enforcing authority right now. Do you need to do that better. And do you have a plan for how you're going to do that. Well my suggestion is, is that you would incorporate governance into your data strategy or part of your plan for effective strategy in your organization. Take a look at how well you're governing presently and recognize that if there's room for improvement and you don't have it written into your overall strategy and your plan. It is something that you should be considering. So what did typical data strategies look like. Well again I kind of borrowed this from some of the things that are being taught in the CMU program that I just spoke about. There's really some major sections that go into a data strategy. There's going to be key assumptions, things that you're assumptions that you're working with to create your strategy. There's going to need to be focusing on the resources that you have in your organization. I'll talk about that a little bit more here in a couple minutes as to different types of resources that you want to plan for. You need that budget, there needs to be data governance doesn't necessarily cost a lot of money it really costs people's time and it costs effort. You're not going to immediately solve your data governance problem by and your overall data strategy by throwing money at it. So as part of your strategy you need to have an operational budget. You need to have an operational expense budget you need to have a capital expense budget. You need to make note of what some of your major project related budgets are as part of that strategy, you need a roadmap you need milestones. I always suggest and I share these oftentimes with my clients that you need a notional timeline, you need to make certain that your timeline is flexible enough that if something changes if there's been an industry changing event or altering an event or there's something that goes on within your business that we need to be able to slide our timeline a little bit. So having a notional timeline really makes sense when you're building an overall data strategy. Some organizations don't necessarily have an enterprise data strategy they have an enterprise data management strategic plan. And when, and if you recognize that while I went out to the internet and I started to look, and I actually looked from examples from several clients as to what do they include in their strategic plan, specifically related to data governance. They talk about the, the targeted business outcomes that you're going to receive from data governance, the impact and the value that having a formal data governance program is going to provide here organization. The business improvement discipline the value proposition initial deployment activities reference materials. A lot of those things are items that are incorporated into an enterprise data management strategic plan so if you look at the two of these. If you don't necessarily at this point have a construct for your data strategy. You might be able to pull the best from these two, these two types of documents or outlines that organizations use for strategic plans, and use for data strategies. So one of the things that we really want to focus this webinar on is how do we inject data governance into that data strategy, which means we really and what is a strategy is truly a plan. So if I use the words interchangeably in the webinar. It's not intentional but they, to me, and for the context of this webinar, they really mean the same thing. And if you have experience implementing data governance programs, you understand that at the core of your data governance program are the people in the organization in fact, I joke a lot that my friend Len Silverstein a good friend of data diversity has said, has said to me that we really shouldn't really shouldn't even call it data governance we should call it people governance, because it's getting people to you're really governing people's behavior as compared to the data that you're governing so. If you're going to inject data governance into a data strategy you need to focus on stewardship, you need to focus on the people that are defining producing and using data as part of their regular job and you need to for a formalize that level of accountability for the definition of production and usage, and you need a plan for doing that. So that's the first item that the first way that we can inject data governance into a data strategy is plan for stewardship. If you've attended my webinars or my presentations in the past. I know that I've talked a lot about the fact that potentially everybody in the organization is a data steward. If you define produce and or use data as part of your job. And you're being held formally accountable for how you define produce and use data, your data steward it's not something that you can opt into or opt out to or opt out of. Again data stewardship is not going to develop itself you need to plan for how you are going to get people to recognize themselves as stewards and to formalize the accountability for the way that people define produce data across the organization. So that's the plan for people. I'm going to share with you and I know David talked about an operating model of roles and responsibilities well I have a lot of clients that are now calling the pyramid diagram that I'll share in a couple of minutes. They're calling that their framework for data governance. You need to have structure for your program a lot of organizations will have an executive steering committee a strategic council tactical data owners and subject matter experts of the data operational people who are stewards roles for it and information security and privacy and all these other groups that are governing different things that different aspects of your organization, you need to plan for that structure. So how are we going to inject data governance into the data strategy, we need to at least at a very high level. You know we might not want to create that the whole framework or the whole operating model within the strategy itself, but we certainly want to outline that we're going to need executive support that we're going to need a strategic level level which is the ultimate escalation point sort of decisions can be made. Why these things keep going away from the screen. We also need to plan for process. And what are some of the processes that are that are emphasized in data governance. How are we going to prioritize to fix data problems to resolve data issues to address data opportunities, how are we going to escalate things to the appropriate level of the organization in order to make decisions. How are we going to address issues I always used to always just talk about issues now I talk about issues and opportunities, because there may be something that's not necessarily an issue but that you can get more efficient and effective that I call that an opportunity. You may handle it somewhat the same way, but you need to have process defined for how you are going to formally address issues and resolve or address opportunities. So you need to plan for stewardship as part of your data strategy plan for people plan for process, you need to plan for technology. There are so many technologies that are are being that we are seeing that are capable of really helping organizations to become better successful and how they, how they manage their data how they are strategic and how they manage their data. So as part of your data strategy in terms of data governance, think about the tools that you may need and plan for that technology do you already have a catalog tool in your organization do you need to acquire a catalog tool. Is it handling your business glossary data dictionary and data catalog or repository. You know so we need to make certain that is again as far as governance, we need to build plan for technology as part of the strategy and the last item I have here is plan for budget. Again I mentioned earlier you need to have operating budget you need to have capital budget for those things that you're going to acquire and bring into the organization. So, certainly one of the ways to inject data governance into a day of strategies to plan for all these things. There is the place to do that I mean if it makes sense if you don't have a strategy or you do have a strategy and you're working to adjust it, make certain that you're planning for all of those things within that that data strategy. That's what they're teaching CDOs of the future CDOs of the present. I hear oftentimes, and I'm sure that all of you have heard the expression about people process and technology it's used to describe everything, everything in the world it seems and little did I know that the whole people process technology framework that was put together has been around for many years around for almost as many years as I've been around, well maybe exactly as many years as I've been around, but since the 60s. So, I want to talk a little bit about how do we focus on people how do we focus on process and technology, and how do we build the governance aspect of those things into an overall data strategy. So, I know you've heard the people talk about people process and technology is being the three legged table. If we pull one of these things out the table is going to fall over. We're going to talk here for a couple minutes about people process and technology, and how we can use it to improve the way our organization operates the efficiency of the employees the efficiency of the tools. Here's some other things that are typically talked about in terms of people process and technology. You know if you notice that you're not doing good in one area might become a choking point that prevents you from being successful in other areas. The PPT framework focuses on eliminating waste and increasing efficiency, efficiency, and reducing time to demonstrating value. I think some of the things David talked about in his session was, we can't say that it's going to take us six months to do things anymore we need to be more agile we need to be able to address data issues as they occur. We need to not have data as an afterthought we need to build data into our thought into our daily processes. It really requires a strategy in order to do that so let's talk about people so that the people are the human resources at your organization's disposal. Think about your organization, how many people do you know of that are really knowledgeable about the business who are sitting around waiting for things to do. You can probably count it on one hand or one finger or even less than one finger. People are busy. We don't have we're not going to be able to acquire a ton of resources hire a bunch of people in as resources typically. And you got to look at what resources and how much bandwidth people have in order to participate in your data strategy and to participate in data governance. I always say especially when I talk about non invasive data governance, let's just build it into what people do, rather than handing it to them as something that's brand new I always say, let's recognize people as being stewards, instead of assigning them to be data stewards. Because if you assign, I know when I get assigned something it immediately feels like it's over and above what I'm doing. I only have so many hours in the day to be able to do work and you throw all these additional things at me I'm going to push back. I'm going to work certainly going to need to prioritize those things that I need to, that I'm going to be working on so you need to look at the human resources that are available to you, or available to the organization and that's not even just from the standing up to the governance program perspective. That's the people in the business areas in the technology areas, they're busy to. We need to be cognizant of how busy they are, and not make it feel as though we're handing them significant additional work. Again, one of the core tenants of being non invasive is we're going to recognize people for what they do, rather than assign them to be data stewards. We, from the people perspective we need to have clearly defined roles and responsibilities, we need to have people with the appropriate skill set in certain parts of the organization. It's not necessarily a data governance issue but it may be a data strategy issue. You can put together the world's best strategy but if you don't have the people to be able to execute on the strategy. Then your strategy is not going to be effective. And when it comes from a process perspective these are the steps or the actions that are typically combined together to produce a particular goal. So we have a process we have an outcome of the role, it's really the how aspect of how we're going to govern data, or how we're going to do anything for that matter, really. But when it comes to data governance and the role that data governance plays in data strategy, we want to at least provide an aspect of how are we going to do this. One of those things is, let's talk about the people let's talk about the construct let's talk about the operating model. You know we want to focus on key steps. We want to make certain that we can measure our process see how we're improving as an organization. We want to make a benchmark now and say okay well we know that in order to request access to certain types of information, it takes weeks or it takes months, or those requests sit on somebody's desk and they don't get addressed. We need to formalize that process. We need to make certain that there's people that are held accountable for the different steps of the process, and that's really, that really focus on the process is going to become an integral part of how data governance is going to help your organization and really where it fits into the overall data strategy. So when it comes to tools again people process technology and tools. We need to incorporate the tool aspect into our governance program as well. Technology must fit the organization I always suggest, take a look at what you have now, see if you can leverage it. I thought there are a heck of a lot of great tools on the market that you should match your requirements to that will help you to enable your program. And oftentimes, you know, it requires that people kind of fit into the technology and that technology fits into the people. It really requires what I refer to, often as the data governance bill of rights. We need people to do the right thing at the right time with the right technology to provide the right results, you know, as often as we can. So people process and technology, they are integral parts of data governance, they're going to be an integral part of your data strategy as well. So, I want to address a couple of questions that I've asked before that I've presented before that I think really makes sense to present as part of this webinar. My data governance is an important piece of a data strategy. And, you know what I've presented questions that you can ask your stakeholders that if they answer the questions honestly, they're going to give you all the ammunition that you need to make data governance important. You need to have a plan you need to have a strategy for data governance incorporated into all the other data things data integration data integrity efforts that are taking place in your organization. So I want to share these three questions with you. The first one is, if you go out to your stakeholders, and you ask them what they can't do, because they either don't have access to the data, or they don't have the confidence in the data, in order to be able to do it. That's a pretty open question to your stakeholders. They're going to tell you they have challenges finding data accessing data. They have trouble understanding or really trusting the data that they have access to, they have challenges manipulating the data they have challenges, analyzing the data. These are the things that you're going to hear from people if you ask the stakeholders, what what the data is preventing them from being able to do that they have to do as part of their job, or where is it really taking significant chunks of their time to do it. What would you be able to do. This is question number two, what would you be able to do if you had access to the data and the confidence in the data to do it. I don't want to read through all of these items that are on the screen for you right now but you'd be able to do modeling and analysis, you'd be able to compare business, business across different domains and different time times and things like that you can have confidence in the reports. I said I wasn't going to read all those things to you but these are the types of answers that you can expect from people. If you asked them, what would you do in a situation where you, it's basically the utopia. If you had access to the data, and you really had confidence in the data to be able to do it. And then the third question really relates to the first two questions, which is, well what does data governance have to do with helping people to do things that they can't do right now, or doing things that they really love to be able to do, but they don't have the confidence and the data to do it. So, you need data governance to be able to execute and enforce authority, formalize accountability, protect data and prove quality, all of these things. Data governance is an important part of data management in general for your organization, every framework that I've seen every maturity model includes data governance as a critical aspect of an overall data strategy for an organization. So, how do we go about including data governance in the structure of the document. Well the best advice that I can give you is that you call it out. And again, I'll just kind of fall back on the things that are being taught to the, the present CDOs and the future CDOs is when they're putting together their data strategies that data governance needs to be an integral part of that strategy and we need to call out that as part of the data strategy, data governance is not an option. People can opt in and opt out of being stewards, they're stewards based on their relationship to the data. So, call out data governance in your data strategy. This could be a homework assignment for you, you go, if you do have a data strategy, go and look to see what part of your data strategy focuses on things like data governance. Data governance as the central component of the strategy makes certain that you define what model you're going to follow for data governance model being different from approach. When I talk about approaches I talk about command and control, traditional kind of field of dreams if you build it they will come approach and then I talk about the non-indasive approach. So you should define for you what type of model you're going to fall for your organization. Are you going to have a centralized model where one group is defining the standards, defining the guidelines and enforcing them out to the organization, or are you going to leave everything up to individual groups, you can really have a distributed model. Your strategy should define whether we're going to take a centralized distributed or a federated model. In a federated model there may be a central group that's defining minimum standards and minimum guidelines and handing those out to all the different business units which by the way they don't have authority over to tell them how to do certain things. They're providing the what and in a federated model, the business areas are determining how they're going to best follow the standards and the guidelines that are being set up by the federated model. So data strategy is the perfect place to define what your model is, what type of model you're going to follow for implementing data governance. And like I said I just kind of reiterating here again. Mention data governance throughout the strategy. I know that these teams in this CMU program that I'm working with they're presenting their strategies next week. So data governance is going to be a core part of their overall strategy. So plan for the plan for a formal program framework that includes the things that I consider to be the six core components of an effective data governance plan, a data governance strategy, and those of a formal data governance framework, and that would be the data itself. The roles I'm going to share my roles model with you quickly here in a couple minutes, the processes, the communications, the metrics and the tools, and the reason I'm telling you that, and you've probably seen this diagram before or if not, I hope it's helpful to you, if you can fill in every one of these blocks so I have those core components across the top, I have the different levels of the organization down the left hand side. You can fill in this framework to say, Okay, this is the data that's important to the executives. This is the data that's important to the operational people. Here's the role that the strategic level plays here are the processes that are important and the tools that are important to each of these levels. If you can fill in this diagram. You're really putting your arms around all those things that are necessary to implement an effective formal data governance program. And so oftentimes I you know here I just kind of highlighted those things the components across the top, the levels down the side. Those are critical parts of your framework, and then you might go ahead and I'm just providing an example of the of a filled in data governance framework and this one is specifically focused on being non invasive in the approach. I just kind of highlight the roles column. We've got leadership or steering committee like I mentioned earlier and you got a council at the strategic level you've got data owners and people who are subject matter experts. Again you could see how this document gets filled in. I want you to focus on the right hand side of this document or this diagram for a minute because I typically talk about the tools of the executives when it comes to data strategy and data governance is going to be policy when it comes to the strategic level and having a data governance council or advisory board or committee, whatever you call it within your organization, your charter becomes your tool. And then it goes all the way down and you keep following that column down you can see that we've got philosophy dictionary catalog repository we've got other tools that are enabling us to support our data initiatives in our data governance. And the highlight in this diagram is where the data strategy fits in and who is typically responsible for blessing the data strategy once the strategy has been developed, they're not necessarily going to create the data strategy themselves, but you're going to present the strategy to them. So the data strategy becomes a tool of not only the executive level and the strategic level but it can also have an impact on the tactical, the operational and the support levels of your organization. So when you're thinking about what tools, it's not always just the technology tools, like the data catalogs like the analytics platforms like the, the analytic tools and reporting tools. Some of those tools are artifacts, things that are important, one of those artifacts that are extremely important to having a successful data governance program to executing on an effective data strategy is having a strategy. So you don't necessarily have any guidelines for the actions that you're taking to develop your program. So I always suggest that it makes a lot of sense to develop a data strategy, incorporate data governance into that strategy. I talked about people process and technology, and I want to spend just a minute here talking about the planning for the formal structure, and where should that structure reside where you may have a document that defines what your operating model looks like. So to give your overall data strategy, you want to at least provide ticklers for people to so that they understand what it's going to take what type of formal structure, we as an organization need, in order to be successful with governing our data with applying responsibility with executing and enforcing authority over the management of data. And as I mentioned, you've got the executive level of strategic the tactical, the operational and the support level. And just happens to be that next month in this webinar, I'm going to be going through in great detail, each of the different levels of roles and responsibilities in this operating model. The clients have even started to call this their framework for data governance, I have the other framework I have that grid diagram that I just shared with you. So I don't typically refer to this as the framework. But it's certainly a core part of the framework because there is a roles column, and you need to have these things defined within your organization so please come by next month when I talk about the roles that are associated with an effective data governance program. And for formal resources, I mentioned it before, resources are not is not just money. It could be people it could be the amount of time that they have the amount of time that you have in order to hit specific goals for your organization. What budget budget is certainly one of those resources as well so plan for formal resources. Let's talk for a minute about examples of how data governance has been included in a data strategy so let's first look at it from the terms of organizations that do have a data strategy where does that data strategy come from or who has the responsibility for executing on that data strategy. David talked about how the numbers of chief data officers are growing and it is it's growing in leaps and bounds other organizations are having other universities are having programs. I think we're going to see an influx of chief data officers, or even chief digital officers and some organizations actually have both Carnegie Mellon has a programs focused specifically on chief digital officers. And it's funny how it kind of aligns with the things that we're talking about to the chief data officer. Chief data and analytics officer I'm seeing that title more and more these days, chief analytics officer CIO CTO or as a chief information or chief transformation officer. I mean that's where these strategies are coming from and the interesting thing about these groups. Oftentimes they have respective offices. For a while there I was seeing chief data officers that were one person shows but now more and more I'm seeing organizations take the role of the chief data officer and build an office around them. So, in organizations that have strategies these are the people that you're going to want on your side, the people that are going to need to support sponsor and most importantly understand what you're doing with with data governance and with the data strategy in general. So, for those organizations that don't have a data strategy or who aren't interested in creating a data strategy. Oftentimes, you'll see that there's a lot of charters from different activities that are taking place in your organization so rather than a top down approach. There's a ground level up approach, and that is having a charter for data governance a charter for data science and analytics access privacy literacy all those things. There are some organizations that don't have strategies are oftentimes kind of starting with charters focused on different areas, because these folks. The screen kind of froze again. These folks they don't have their own office these are these the people that are running these groups don't have committees don't have fellow colleagues and a lot of organizations. And that is that each of these different charters if they're written independently are going to behave independently. We need to bring these together we need to get these these charters if we're taking kind of the ground level up approach and have them partner together. So, oftentimes again in the strategy they include things like leadership the organization stewardship defining stewardship defining what's going to be necessary to administer and to execute the program, moving forward. The process perspective make certain that you're documenting what are the specific processes that data governance is going to focus on. Again, you don't have to go to into infinite detail about it but talk about the fact that some of the things that data governance will do. And some of the things that specifically the data governance council will do is prioritize things rank and arrange, which activities are going to take place. Now, later, never, you know, there's a matter of prioritization for your organization escalating things up. I showed you the operating model the pyramid diagram. There's an escalation area along the right hand side we need to make certain that we've set our organization up to be successful which means that we can't just agree to disagree. We need to have an escalation path, and we need to have an ability to make decisions and have a place where the buck stops, and where decisions need to be made and that's typically at this, the strategic level of the organization process structure for issue So, as I mentioned, I talked about the earlier resolution activities documentation metadata is extremely important part of an overall data strategy, it needs to be incorporated in the data strategy, also part of data governance. It's very difficult. Yesterday in my EDW session I talked about active metadata and data governance using a data catalog. Well, the data, the data catalog really becomes the tool that we use to not only activate metadata, but activate our data governance program. And other things that you might want to include within your data strategy or your privacy rules, your security rules classification rules, and your business roles. There's a lot of things that you need to consider and your data strategy can't be 100 pages. It needs to be a digestible document. You know, hopefully what I shared with you in this session just gives you an idea of some of the things that you might want to incorporate into your overall data strategy, how as it pertains to specifically the role of data governance in that data strategy. So what did I talk about today I talked about the structure. I shared some structures for delivering a data strategy, how to address the people the process the technology. Why it's important and what are some of the questions that we can ask to really get great answers to help to share why data governance is an overall important piece of your data strategy. How to include it in the poll in the structure of the policy and examples of how governance has been included in data strategies. And with that, I'm going to turn it back over to Shannon and see if we have any questions today. Thank you so much as always for another great presentation. And if you have questions for Bob feel free to put them in the Q&A and just to answer the most commonly asked questions. I will send a follow up email by end of day Monday for this webinar with links to the slides and links to the recording, along with anything else requested. So and we'll invite David back in to join us in the Q&A here so diving in. Who is the author owner of a data strategy and lack of a CDO. Good question, there's not a single answer to that question, at least from my perspective, it could be any of those roles that I just talked about it could be a chief data and analytics officer it could be a chief transformation officer. I'm a chief operating officer I've even seen that when there is not a CDO in an organization. You know sometimes even the data strategy itself may call out for the need for a CDO. I don't know, David you have any different opinion as to who would be the appropriate person to kind of head up the data strategy in an organization if you don't have a chief data officer. I usually agree with kind of what you said I mean, I mean my experience is is that it's really, really is focused around the way the organizations aligned so it's a more financially focused organization and a call it action for data strategy and data governance is financially oriented. Sometimes it rolls up to the office of the CFO, whether you know a financial controller or the CFO themselves, and more operationally supply chain center organizations I agree it's somewhere in the office of the CFO, sometimes like a supply chain BP etc. In sales oriented organizations, you try to get like a CMO chief marketing officer those those roles, you know, tend to be in and out in and up right so they tend to be more transitional less stable tends not to be a good place where we don't like to see it. Transitionally is in the office of the CIO right because it really needs to be business facing business own to really get the followership and the efficacy from everything you're trying to lay out in your strategy. But really, you know that at some level just try to understand like who is the most to gain, who is the most to lose and who is followership across the organization. I would avoid organizational roles that tended to be siloed, you really want an organizational role that tends to be a little bit more enterprise focused globally focused, because most of the data you guys know tends to be cross functional. So that will be my guidance there. I wanted to add one thing to it so it's funny I with the alphabet suit that I talked about the CAO CDO CDO all of those types of things the one that I left out was the CFO. And what I find in a lot of organizations the executive sponsor of a data governance program is the CFO. And I will agree and so I want to add the CFO to the CDO CDO and all those different roles that the EIE that I just talked about, but I would agree with you about one thing though, I would agree that you know that the CIO is not necessarily the appropriate person for the data strategy to fall under. It doesn't mean that if you have lack of anybody else and if the CIO is truly going to take this on from a data perspective, and not from an IT perspective that it has to reside somewhere. So that's what I was to say, if you don't have anybody else but your CIO is the one that is implementing your data strategy, more power to them, because in order for there to be a strategy that's acted on, it has to be somewhere. And, you know, as long as the CIO and the strategy and the program is focused on the business and not focused on IT. And we don't give that perception that data governance and data strategy is strictly an IT thing. I think we're going to be we're going to be safe so the CIO could be there. Just, it might not be my first choice. Thank you so much. So I love this next question. What is the difference between data governance and data stewardship? Ooh, that's a good that so it's like somebody served me up a homerun pitch for me to do it. I'll start and then David to hear your comments as well. So I say data governance is the execution and enforcement of authority over the management of data, data related assets I mentioned that earlier. So that is the end result. That is what we need to do. We need to execute and enforce authority. People just to give you as an example, people that are using sensitive information they can't opt in or opt out of protecting sensitive information. That'll put the organization at risk. So they need this has to be part of what they do. And so stewardship is the formalization of accountability is the people aspect of the behavioral aspect of the of data governance it's getting people to do the right thing in the right way at the right time. Being held formally accountable so I look at data governance as being the program and the stewardship aspect as being the one of the steps or many of the steps that are necessary to implement effective data governance. And what do you think I totally agree Bob I mean I often use the analogy law and order right so governance is the order is stewardship and then to your point earlier and you know I've read your book as well. You know not a basic data governance means that you don't have to have a formalized role to have stewardship, accountability and responsibilities right so I tend to think of it that way governance being kind of the structure of stewardship being kind of the people to your point in the order around that law. I'm going to have to borrow the law and order thing I think that was really that really describes it right there's the law which is the execution and enforcement, and then there's the order which is how are we going to do this how are we going to activate the people of the organization. All right, we have just a couple minutes left so I'm going to ask for your elevator pitch answer on this question. How involved should the business managers being creating and driving the data strategy. And you want a quick answer to that. Okay, now we can do a whole event on it, but I think they should be involved I think they should be reading. They should be aware of the policy they should be, you know, looking at the looking I'm sorry looking at the strategy, and making certain that things that are important to them are at least considered as part of the strategy. So if you do this in a vacuum, how do you know that you're going to be matching what the needs of the business are going to be. So I say that they need to be an integral part they're not necessarily writing the strategy, but they're involved because they want to make certain that the things that are important to them are incorporated into the strategy. That's my thought David, you got a quick answer to that. Yeah, I would think about in terms of a racy right responsible accountable consultant is informed and informed I totally agree with you Bob I think they're more and kind of the consultant and informed side and maybe have some accountabilities depending on what their roles in the overall program. Oh, I love it perfect timing. And you know so many great questions that we didn't have a chance to get to you but to keep them coming in. I'm going to get this over to Bob and we'll get answers to you in the follow up email which again I will send out by end of day Monday, and the follow up email will include links to the slides links to the recording. I also have links and copies of Bob's matrices that you saw in here so those will go out as well. So thanks to precisely for helping for sponsoring today's webinar help making these webinars happen. I appreciate it thanks David for joining us today. And thanks everybody for being so engaged in everything we do love it as always. Hope you all have a great day. Thanks everybody. Thanks everybody thanks precisely thanks David. Yep, thank you Bob. Thanks Shannon take care now.