Data Governance: Any “Dummy” Can Do It! with Dr. Jonathan Reichental, Author & Founder of Human Future

Hello and welcome to Data Radicals. In today's episode, Satyan sits down with FELLOW Data radical, Dr. Jonathan Reichenthal. Jonathan has penned several books in the Four Dummies series that make data transformation actionable for everyone. In this episode, he gives a step by step guide to implementing data governance, explains how to avoid common governance failures, and shares insights on the future of smart systems cities. This podcast is brought to you by Elation. The act of finding great data shouldn't be as primitive as hunting and gathering elation Data catalog enables people to find, understand, trust and use data with confidence. Active data governance puts people first so they have access to the data they need within workflow guidance on how to use it. Learn more about elation@ala tion.com Our guest.

Today is Dr. Jonathan Reichental. Dr. Reichental runs Human Future, a technology and education advisory firm. He is a professor and instructor at several universities, including the University of San Francisco, Pepperdine University, and Menlo College. Dr. Reichental served as chief information officer at both O'Reilly Media and the city of Palo Alto. He is the author of six books, including Smart Cities for Dummies and and most recently Data Governance for Dummies. Dr. Reichental, welcome to Data Radicals.

Well, thank you very much, Satchin.

So let's start with the most relevant topic to this audience, which is Data Governance for Dummies. What motivated you to write this book and why in the Four Dummies series?

Yeah, it's a great question. Back about four or five years ago, I had the chance to create a online video series on data governance. I did it for LinkedIn learning and it became actually very successful. Having been a technology leader for almost 30 years, I had a few things I could say about the topic. And of course, as a technology leader or as a cio, you're in that role. You're managing and governing data as part of your role. And so I was able to bring those experiences to the table as well as some of the formal frameworks and tools and things into that course. And later I had an opportunity to get a publishing deal with Wiley, the major publisher, and did Smart Cities for Dummies. It was a successful book and they were doing their own research on who would be a good candidate to write a book about data governance. And one day I got a phone call about a year and a half ago from my editor and he said, would you. We see that you've had a successful course and this something about this topic. Would you be interested? And I have to say, writing a Dummies book is Actually quite hard because it requires certain level of language, plus it's very structured and it was hard for me to write the first one. So I had to think about it deeply. I mean, they presented to me where the market was going. They said it's clear that data governance is quickly elevating in terms of priority for leaders in all types of organizations. And we see a strong demand for content and education around this space. If you write a book on this, it's going to be, it's going to, hopefully if you write it well, we'll have good, high demand. So that was convincing to me. I always want to be useful and to educate and reach a large audience. So I said, okay, I'm in. I just wrote it knowing that this was a very well respected brand and we could actually use the structure and style of it to make it easier for people to understand this important topic.

The branding is incredible because it takes topics that would be otherwise really hard to access and are difficult and really demystifies them and also just starts from a position of putting the reader into a place where they're automatically humble. And so it just, it's super disarming and very cool. So what is it about the structure of a Four Dummies book that makes it both so hard to write, but also so popular and accessible?

This is the most popular reference series of books ever created. So it's really quite a big brand. Well, if you pick up Three Dummies books and flick through them, you'll notice that they're very similarly organized. They're in parts, the parts of chapters and chapters have certain layouts. So you have the intro and then you have the sections. And all of that creates a lot of rigor for an author that maybe if you just wrote the book yourself or different brand or just wrote a book you wanted to write, you would make all those choices yourself. But no, you have to sort of conform to their template if you like. The other thing is they, when you work with the, with your editor and they're terrific editors, they push you to be very clear and action oriented. You can't do fluff. They're going to push back, they're going to delete sections. So it's actually good discipline for an author. It's not for everybody, of course. Some like to be a lot more elaborate in how they describe things. They want to incorporate more of their own personal style. I'll give you one quick story which kind of both proves and also disproves something I'm going to say, which Is when I was writing Smart Cities for them, the future of cities. One of the things I put in the sort of table of contents when I was. That's the first thing you do when you create a book. I had a lot of history, like the history of cities, the genesis of cities. And I sent it into my editor and they turned around and said, dummies books don't do history, we do right now. What does the person need to know right now? And so that's part of their thing. And in support of Dummies, I could say, I like that because there's no fluff. The person who reads the book gets what they need right now. But I pushed back and I said, I think people need to know the history of cities in order to understand cities today and where cities are going. And they actually allowed me to do that. They were accommodated my perspective, which was very unusual for dummies book to put historical context into it.

Yeah. And I would imagine you do have the context. It makes the present a little bit easier to explain. So I think obviously it's great to know that there's some agency with the author. What part of Data Governance for Dummies was hard to write? Because most of the books that I've read on data governance honestly speak super conceptually about the topic. And I've certainly read books where I've left more confused about the topic than actually educated.

Yeah.

What did you find was hard about data governance to explain?

Well, I have had the same experience as you, and if someone did a search online for a book on data governance, they're going to find results, they're going to see that this topic has been written about. And in doing my own research, I bought several of them. But I recognize, much like you, a couple of things. Number one is some of the books were really complicated. Like they assumed that you had a lot of prerequisite knowledge on just computer science overall, and data science didn't like that because that wasn't going to work. Then I read some books which were so fluffy they didn't give you any advice. And it ended with saying, what do I do now? So I had two missions. I wanted to, in a book, write something that anyone could approach, to use your words from earlier, a book that was more accessible. And I wanted to be action oriented. So when you actually buy the book tomorrow, you could start building a program. I think the next point is it is a tough topic and it is a topic that, if you write it a certain way, can be boring. And I say that with with great love for this field and great love for data and computer science in general and the value it has in society. So I actually wanted to write a book that was engaging, that took you through a journey from creating a vision for your organization right through to measuring that and operationalizing an effective program. I wanted to write about the value of data governance to your business and your organization. I wanted to be able to convince the reader so they don't have to go out and google for hours and read all the academic journals and all the blogs and stuff they could read in just a few pages. Why is data so important? And why do you need to prioritize it and ensure it's better quality and you're making sure that it's secured and all the other stuff that goes with data governance.

And I guess maybe make that case here, because I think people obviously listening to the podcast believe it, but a lot of the value you get from it is speculative and in some cases unrealized. So how are they going to convince people to invest in this thing called data?

Yeah, it starts. One data point that I thought was very valuable is when leaders of organizations of all types were asked whether they want to prioritize being a data driven organization. It's over 90%. Basically, every leader wants to ensure that they can make better decisions using good quality data. Because that means if you can do that, you can go to market faster, you can target your customers in a more efficient way. It also means that if you're data driven, you protect the data that you have a responsibility to. You don't get into trouble. Data is important because you're often managing data on behalf of your customers and your stakeholders. And, and if that data gets breached, and we hear all too often about that, there are fines, right? There's monetary fines, there is bad publicity, right? It damages your brand. I mean, the consequences of not managing data well are exceptionally evident. Right? On the one hand, managing means you get better results. So we have real support that organizations that do data governance well get better results in the marketplace. They're more profitable, they grow faster, the data is really clear on that. Equally, organizations that are poor at data governance don't get that benefit, but they also have more breaches, they have more compliance failures. So when you add it up from the offensive data strategy, which is to know your market and grow your business, and the defensive, which is to protect your data and make sure your operations are efficient, couple those with really efficient decision making, timely, good, quality decision making, those are some very strong, compelling arguments. And leaders want to get there, they actually demand it. It's not me or the data governance person coming forward and saying, you ought to do this. They're asking, we want to do it. We simply don't know how to do it. And unfortunately, when we do it, we're failing far too often.

But it is one of those things that is perhaps important but not always urgent.

Yeah.

What in your experience brings it to become something that's urgent for an organization? How do people make that case?

Well, part of answering that question is what's holding leaders back? Why wouldn't they do it? If it's clear there are so many advantages that I've just described, why wouldn't they do it? So part of it is they don't know what it is. Data governance sounds bureaucratic and cryptic, and they don't actually tell me what that is. So there's an education piece to it. So they don't know. They think it's expensive and they're like, oh, my goodness, I have to invest more money in overhead. And number three is they think it's too much bureaucracy and too complicated. So there are these reasons why leaders want to be data driven, but they don't pursue data governance. And so you have to convince them around those limitations or things they see as restrictions. You have to say and have the arguments in place that actually data governance can be sized relative to your business. If you're a small, successful business or you're a small business, you don't need the same level of rigor as a highly regulated Fortune 500 company. You can deploy and see benefits from data governance very quickly without massive investment, without having to buy very expensive suites of tools. The entry point is actually quite low. But as you mature and you see the value, you can obviously buy more tools and you can train more people and expand the purview of data governance across your organization. One of the things I talk about in the book a lot is how you get started. And then don't start by trying to govern all your data sets on day one, that's a recipe for failure. Pick the ones that would have big bang results quickly, like maybe pick one or two. If we as an organization knew a little bit more about our customers and that was data that could be kept current and secured in the right way, we could make better decisions and move more fast, more quickly in the market. You go after things that are really important to you. So I think making the strong case why it's valuable, but then also helping break down those which are often sort of Mental limitations of cost and bureaucracy and overhead.

I want to come back to the kind of ten step program that you lay out, because I think that's really important and relevant and to your point, pragmatic. Before we do that though, describe what, like, what is your definition for data governance and where did you get it from?

Data governance is about managing data well. And it's everything that helps in support of that to create better quality data that gives you outstanding results in your business. One of the ways I think about this question is if you asked what organizations or how many organizations manage data, do they have data management in place? I would say every organization today there isn't a business that doesn't have tech at the center and as a consequence they're managing data. But then the next question is a simple question. You get completely different answer. Are they doing it well? Is it secure? Is it compliant? Is it actionable? Are you building your business on top of the rich insights you can get from the data that you have or can collect from the marketplace? And that answer is often, no, not as much as we'd like to, or I don't know. We've got a layer of processes and responsibilities that we can put in place and tools that can allow organizations to achieve those better results, to manage data much better than they do today. And depending on your vision, depending on your goals for data, for your business, that can be lightweight or it can be a significant investment. It all depends on what you establish as your vision for data governance.

One of the things that this is not intended to be a sort of gotcha question, but I did want to understand in your assumptions in the early part of your book, you mentioned that data governance is not data management, but you define data governance as managing data. So how is data governance different from data management and what is it mean to manage data?

Well, the key part of, you know, data governance is about managing data well. The well is the key word there. It's like doing it better than you're doing it and doing it much better and getting much better results. So data management, this comes up a lot. People actually do confuse the two terms, or they know what data management is, but they have no clue what data governance is. Data management is the action of working with data. When you manage data, where do you store it? You put it on a server. Where is the server? Do you move data? If you move it, what software do you use to move it? How do you process it? How do you secure it? What are the admin rights and things? It's really the action related to data governing is the sort of the rules, the policies, the approach you have to those actions. It's that layer above it. Who does that? Why do they do it? When do they have the rights to do it? So they are distinctly different. Now, governance is one of those things that exists informally, just as a nature of existing, but there's levels of it. There's the informal governance of yes, we store data on a server and the IT manager has access to it. You could say that's data governance. But is it correct and is it the right approach? Is it the right person? Is it the right level of access? And those things have to be defined and there's rigor in defining that. And it just goes from there.

So how does this start? I mean, now let's get back to the sort of ten step plans. Where do people most often, you know, real world example. What if I was to start the smallest possible way? What would that look like?

For me, the starting point is why are we doing this? What is the goal of data governance? So you have to establish that, and you need to establish that with a broad set of stakeholders. This is something that you need to bring in participation from across the organization, develop that vision. Is your vision for data governance to be an organization that by doing data governance you can grow by 10% over the next two years? Do you have some very specific goals like that or is it over the last five years, annually we get at least one major security breach, data governance. We want to reduce that either by half or eliminate it. Right. So you have some overarching vision for data governance and you get buy in. You've got to work hard as an organization to ensure that there's some level of alignment in that people know why you're doing it and those results that you would like to see happen. The next thing is you need a strategy. And one of the questions I always ask organizations is, do you have a current executable data strategy? Do you already recognize data as your most valuable asset or is it driving your business? Or do you think of data as a byproduct of what you do, as opposed to the asset that drives our business growth in the marketplace? And unfortunately, the reality is many organizations don't have any data strategy, which is all too common, or number two, they do have one, but it's not current and it's not being executed again. So you really need to have an active data strategy. In my book, I tell you, step by step how to create a data strategy, which is the supporting first of all, a much more enumerated way of achieving your vision, but then the steps and the projects and the efforts to get there. Now the question is data governance baked into that? Is that part of how you are executing upon your data strategy for your organization? The third part is you've defined it, you've got a plan. Now what are the roles and responsibilities? Who's going to do what? Now I get asked the question often, who's responsible for data governance? Is it like a data governance manager? Is that it? And the answer, sadly, I guess for folks, is that everybody is responsible for data in the 21st century. It's a key asset for your business and everybody has a role. Everybody is managing data in some way, whether it's putting an attachment on an email or accessing a data repository, maybe running a report, exporting data, sending that data to a client or something, we're all doing that. And if you ask that employee, do you know what your responsibilities are relative to that data? You might be surprised by the answer. They might say, I hadn't thought about it, I don't know. Then you have people who are deep in this. And for succinctness, I'll just mention one, which is this is also a question that is often asked and with a bad answer is who comes to work every day and cares deeply about important data sets? The answer often is nobody. Like company organizations don't think about data ownership near as often as they should. We call that role, sometimes the broad role is called a data steward, right? But it's also a data owner. And there can be different types of data owners depending on the organization. Some very big complicated businesses have full time data stewards for big sets of data, big sets of data sets. Others, it's in a smaller organization. It's just part of somebody's role. And you don't need data stewards for every single data set, right? Only for stuff that really matters. So there's that. And then fourth point is metrics. Like, now you're actually doing stuff and what are the results? Are you measuring the results of your data governance program? And two things can happen. One is yes, you have good metrics and you share those metrics with stakeholders. You say, look at this, in the last year we've been doing the following rigor and we're getting better results. But it also can go back and say we put data governance in place and it's having absolutely no effect, right? In which case you've got to change the data governance program or something's broken and Metrics will tell you that.

So vision, strategy, people and metrics, those are the four steps that we reviewed so far.

Those would be the high level. Yeah, yeah, nicely summarized there.

It sounds like, I mean frankly, if you take those elements, vision, strategy, people and metrics, it sounds like it's like any other cross functional strategy that a business might run. We have within relation strategic initiatives and literally the way we define them are vision, mission, strategy, initiatives. And each of the initiatives have metrics and then each of those metrics have actions or projects as you pointed out, that try to use, or that what we use to, in order to be able to move the metric this. So it sounds very cross functional. What one of the things that I found with data governance, before you set up all of this infrastructure or before you set up this framework, which I think it is, it sounds like a fairly useful operational framework or organizational framework. What I find is that people, when they say we need governance, like we meet hundreds of people, thousands of people every year at elation through our salesforce. And often you hear these words, we need governance. And then you say, okay, let's go into that conversation a little bit more deeply. And the person says what we really need to do is prevent people from accessing the wrong data sets. And so what they really mean is data access governance. And often if you talk to a database vendor when they talk about governance, what they mean is data access governance. And then sometimes you say, what do you need governance by people? Then say, everybody's using the wrong data. We all have these definitions and none of the definitions comport. And really there, there's sort of a business glossary which is needed. And so there's all these kind of artifacts of governance. But people seem to say the word governance, but often they mean this very specific thing. And so the irony of this is like the semantics are really muddled when one of the big things about data governance is it's supposed to work out your semantics. How do, how does one resolve that or at least what does one do with it?

Well, let me say a couple of points within the four steps. One thing that I don't want to lose sight of that is you got to implement some stuff, right? And maybe that's during the executing on the plan, right? So you do, there will be tools like in the case of data governance, you may build out a catalog, for example, the glossary. So when wanted to just highlight that doing these steps, we don't lose sight of the fact that there's a build element in there too. Once some of these things are in place, they're operationalized. That's a key part here. I think your question though, fundamentally goes back to the beginning, which is, what is the point? What's the vision? What are you trying to achieve? And if you discover, talking to a leader, that in fact they just want to have better control over who accesses certain data sets, you'll optimize for that. But it does invite a bigger discussion about how you're approaching data. And again, you could say that it allows for a bit of a gap analysis. What are you doing well to get good data results? What are you doing not so well? Which one of them is the driver for this conversation? But are there other aspects that if you go after this, you'll actually achieve some other results with just a little bit more effort? So I don't mind the idea that early on you're going after some very laser focused objectives. I do think in the long run, though, data governance is not about a narrow target. You will build a better business if you hire all the right people, if you build the right products and deliver the right services, not by doing just one thing and doing it really well. It's a comprehensive approach to running a successful business. And I think data governance should be thought of in the short term as targeting some very specific things, but long term as a cultural shift in how you actually think about data and how you use data on the back end and in the front end of your business.

Part of your book is about knowing if your data culture is ready for data governance. I think this is actually an important idea, right, because you could be very early in this continuum where all you're trying to do is like block access to a data set that contains, you know, Social Security numbers. And that could be like your big goal and might be premature to call that data governance. When do you, what is it about your. When do you know that you're ready for this particular thing? Like, how do I know that I want, like governance with vision and strategy and the like, as opposed to just a couple of rules in place to go manage a database?

It's a good one there. Yeah. There's always going to be a number of different triggers, right, for questions and actions. Often it will be, something's happening, there's a problem that's, you know, a phone call will happen to a vendor when you're having a problem, like, we're getting attacked. Help us. We fail in our compliance requirements every year. You help us with that. So sometimes you are responding to this problem. But there's a bigger question that leaders are asking now is, and we see, I saw that in the research that I did during development of the book is senior leaders of organizations have noted that obvious we're operating in a hyper competitive environment. Every day is a hustle. There's somebody ready to steal your client or build a better product. Leaders know that. Leaders know that they're sitting on tons of data that they don't use, that they're not taking advantage of the incredible insights that sit in those massive data sets that we all either have access to on the outside or contain as our IP internally. And they ask the question, how can we be more data driven? How can we make better data driven decisions? And those broader questions, I think are answered with a comprehensive approach to data governance. So in a way, later on I might think differently about your question, but right now I see the entry point is either a pain point or it's a bigger strategic effort. I have a statistic here which I think again is validated through research. You know, one of the reasons that drove the book was the publisher in their research recognized that there was increasing interest in the topic. Why? What's going on? We're in this period of a data explosion, right? The zettabyte era. Never has there been so much data of so much variety and velocity than ever before. And organizations are recognizing, they're also recognizing a more regulated world in which they operate, a world in which there are much more cybersecurity risks and one in which they want to be able to make timely decisions. And so the data point that I thought was most interesting was in the next 12 to 18 months, 30%, over 30% of organizations of all types of will make large investments in data governance. So they're being driven by this. The market in my view exists and it's been driven by those pain points or by a larger strategic initiative.

And so when you know that you're in this 30% group is when you've got enough social political will within the organization in order to make it happen. There's a sort of groundswell, as it were, within the organization. You mentioned that you cited another statistic in your book that 90% of organizations fail at their first attempt at data governance. Like that sounds horrible.

It does.

And what percentage of these 30% are on their first attempt versus their third?

That's a good. That second question is. I don't know the answer. Fair enough. The 30% includes those that are making greater investments and those that are making investments for the first time of all organizations. So that's a sizable change in the market's demand for data governance. I was alarmed also like you with that 90% failure on the first attempt. And of course if you could dig into it a little bit, I mean what, what is failure? Did the whole thing completely implode or did they not get, did they only get 50% of their what they were hoping for? What you find is it's almost case by case, but some of the themes are insufficient buy in. Right. The organization weren't all over it. Somebody was the CIO or the chief information security officer, maybe the CEO if you're lucky. But there wasn't buy in from across the organization. I think that's very, very that that comes out in the data. So there's that number two is leadership, right? Something that I write about quite a lot in the book is you have to have a passionate leader or leaders who drive this. During my career, much like yours, I imagine I've managed a lot of projects and technology projects and unfortunately statistics on this are pretty bad. There's a high degree of project failure in every type of organization. And the question is why? Why do projects so often not go over budget? They're late and they don't meet their needs. And the number one reason is leadership is a sponsor. And that means that that sponsor believed in the project 100% and remained engaged in the project right through the end, through to delivery. When that happens, the likelihood of success is much, much higher. Now data governance is a program and it needs a passionate leader who's going to run with it. And this is a sort of an executive sponsor. It's probably somebody from the C suite. They need to be involved throughout. The third one I would just say is we see this not only in programs like data governance and projects too is poorly defined outcomes. Did you, was it really clear what you were going to do and how you would measure it? And if people had different ideas, this comes with the misalignment problem and everybody did their best. They weren't all on the same page. The metrics might not be so great at the end. And then the outcome is we, we, we didn't achieve what we wanted to. This has been a failure.

It does map back to this idea that it's a strategic initiative. And like with all of these things, like any, any action, entrepreneurial action, business initiatives within a company, you know, it ultimately just comes down to like, do you know where you're going? Do you have the right people to get there? And do you define scope? Well, Enough to know how you're doing along the way. And metrics, of course. One thing that you know, it's come up with more than one cdo, but one, one chief data officer said to me, this is somebody who led data for a large contract research organization. And she, you know, she said to me, we don't actually call this data governance anymore. We call it data enablement, which I think in your book you refer to as sort of data governance has a PR problem. Talk a little bit about that. I mean, do you think there's any merit in marketing it as something else? Or is that just a. Is that just avoiding the issue altogether?

This is a conversation I have on in multiple topics. My strength has been for a long time in the smart city space, the smart sustainable community space. That's where I really carved out a niche. And. But now I. My expertise and what I'm doing is much broader. But I would hear a lot from city leaders and all sorts of stakeholders that can we not use smart city as the term? Because it's just, it's throwing people off and are we a dumb city? And now we're a smart city type thing? And there's lots of jokes about that. And the reality is the market will often give the title and you kind of have to go with it. You don't get the opportunity to redefine the words. And whether you like them or not, could argue about the designation of metaverse or blockchain. These words are maybe poorly chosen. So look, I think there are going to be people and companies that despise the term data governance. Governance itself has this aura of negativity. It sounds like bureaucracy, but we're stuck with is what it is. What are you going to do? Right. I love the idea that within a business you could call it in your internal branding, data enablement. That's beautiful. But the topic is data governance and it's going to be like that for the foreseeable future.

Yeah. And you can use whatever euphemism you'd want to use, but you sort of get there. Are there new policy types that have come out to play or are there new things that actually people are doing in data governance? Or what are the trends of what people are really focused on today that they may not have been focused on three to five years ago?

As we enter sort of third decade of the 21st century, organization leaders aren't waking up and saying, I'm going to spend all my time today worrying about and spending my energy on that defense of those back office Things, right? That's actually a poor use of a CEO. I don't know if that's how you go about your business, but what you want to do is come to work every day and figure out how are we going to create better products, how are we going to reach more people, how we can grow a market, how do we continue to be relevant. And if you're not building operations and approaches to that, it's not going to be as valued. And what I say in the book very clearly from start to finish is this is all hands on deck data culture type thing, but it is driven by leadership, need and the sort of the core focus of the organization. If you're not a profit driven business, I totally get it. If you're a non for profit, even government, a lot of it is about quality and building trust with data, not so much about growing market. But if you're a private company and publicly traded, your goal is to is to increase shareholder value. Data governance has a very big role to play. What's different today in the third decade of the 21st century is the Zettabyte era is you have more data of more value than ever before and we have more tools, right? The tool set is much better. The engagement of artificial intelligence, for example, in data governance is a real phenomena. Today is a game changer. Finding patterns for you, being able to make sense of the signal and the noise, as they say, all of that has elevated capabilities within the data governance space, giving leaders more tools, more capabilities to drive that offensive capability. So I think actually it's a theme in the book, although the book cover is comprehensive, I'm very clear right through the end that if you only approach data governance as those back office things, I don't think that's a winning argument. That the winning argument is to say you get that that's really key, that's your baseline. But the real value in data governance is innovation and growth.

So some element of crawl, walk, run and some element of also making sure that you have your goals well specified. Let's move a little bit to the other topic where you have maybe as much if not more expertise, which is smart cities. You've written that book, I guess I assume primarily based on your experience as the CIO of city of Palo Alto. I've heard that term a ton, but I don't think I could ever describe for anybody what a smart city is and which cities are smart and which cities aren't. Can you tell us a little bit more about that topic and how that ultimately I'D love to bridge to why that got you to the world of data governance, but I'd love to just understand what a smart city is in the first place.

Yeah, well, it requires a little bit of context building. It's 2023, the world is majority urban, okay? So we think we're at about 60% of all humans who live today live in a city. This is pretty new. Before 2008 it was like 41% rural. So what's that, what I say, 51% rural, 49% urban. So we shifted now to being an urban planet. And if you look out over the next few decades, we're growing our cities by about 3 million people per week. We'll add about 2 billion more people into our cities by the middle of the century and by the end, about 80% of all humans will be born and live out their lives in a city context. So in terms of the 200,000 years of Homo sapiens, the city phenomena is like just in the last 10 years or 20 years. So it's pretty new and it's happened fast and it's a very big deal because what happens in cities, that's where you work, it's where you have your home, it's where you get your drinking water and your food and your healthcare, right? It's where we are generating a lot of carbon. So cities are the biggest contributor towards the climate crisis, if you believe the scientific consensus. And if you look at many cities around the world, they work pretty good for what they do, but they fail a lot of people and they fail on a lot of levels. Just take something like transportation, right? I have the pleasure, I think, much like you as an executive, to travel around the world and visit lots of cities. And one thing that you'll see a lot is traffic, right? If it takes an hour and a half from the airport to a hotel to downtown in the city, and it's only 12 or 15 miles, I would argue, and I think no one would disagree, that's failure. We failed, right? Our road networks, our infrastructure has failed and is increasingly failing. Take another example, which is energy, right? As cities grow and people use more electricity, our appetite is increasing. And if we continue to harvest coal, gas and oil, we know where that will lead to. That's not a good future. We need to transition to renewables and non carbon energy, things like solar, wind, Geomass and others. And we're doing that. Actually, we're doing it at a rate that most people would be surprised about, the rate at which we're converting and deploying new gigawatts of energy. It's all happening in a city context. And lastly, I would say a lot of people's experiences living in a city, when they deal with a city issue like getting a permit or reporting a crime or wanting to get their road fixed or something, it's pretty bad. You often have to go to a place, fill out a form, figure out who to call. It's just ugly. And this is in a world where people would rather use their smartphone to do most of their services because that's what they do in their, in their private life and when they're working with non government organizations. So all those things matter. We're in an urban world and cities need to think differently and they have to solve problems differently without changing our decisions. Right? Without changing how we're doing stuff. The problem only gets a lot, lot worse, right? Because it's accelerating, urbanization is accelerating. So smart cities are all about confronting those issues head on, but with an innovation mindset, reinventing how we do stuff and using technology and data to change the game, to completely shift how we've thought about these problems. For example, the digitalization of government. Government is also going through a massive global digital transformation right now. And to give you just a dollar amount on it by 2025, two and a half years from now, the market potential for digitalization of government is about two and a half trillion dollars, 2.5 trillion with a T. Right. And so that's creating a large volume of new startups and what we call gov tech businesses. We're also seeing the big tech companies, everyone from Microsoft to Google to IBM and others, really ramp up their government offerings by completely rethinking. You have a new generation of city managers and mayors and council members who are now, they're Internet native, they understand tech and they can't understand that when they become leaders in government or they run for office, how poorly things run and how much is analog. In summary, the smart city movement is all about building cities that perform better using technology so that they can deliver better quality services to their communities and be more sustainable in some ways.

There's some parallels I think, between this kind of topic of data governance and this topic of smart cities, or at least I'm seeing some in how you narrate it. Do you think that's a fair observation? And what do you think is common between the two?

I do, I absolutely do. Look, data is core to the functioning of good cities. And if you think of a domain, a client base for data governance and Data management, cities and governments. This is probably one of the biggest around the world. Clearly, private industry is a big opportunity, but I think government is the bigger opportunity, frankly, because they have. They store and manage vast amounts of data, like colossal volumes, and they don't do it particularly well, and they don't secure it particularly well. And I say that with great love for my city colleagues. Great love. But you only have to look at what happened in Baltimore and Atlanta and cities all over the world where hacking and ransomware happens all too frequently, where city leaders don't have data to make good decisions, they use bad data. We just have terrible results. In a lot of our cities, there are great outliers, there's some amazing cities doing great work, but the use of data in a meaningful way, both the management side and the governance side, is poorly executed in our communities today, but represent a phenomenal opportunity for training, for vision, for tools, and done right can make a big difference to our communities.

Yeah. And the idea of a smart city, I guess, presumes that there is a smart way of doing things and that other cities have discovered what works and what doesn't work. I can imagine that in the world of cities, ironically also true, in the world of data governance, there are probably many cities who are like, no, this would never work. Here we do things differently, our culture is differently, our people are different. And I certainly hear that about data governance, that, oh, these policies are completely nothing to do with us. We're very unique. When does one know where you should learn from best practice versus, you know, what's truly idiosyncratic to you?

Yeah.

And how do cities navigate that?

Well, one thing I've learned working with cities on every continent, all over the world, is there isn't a playbook. You go in, they say, we're having trouble, and you say, here's the answer for you, that doesn't really exist. There are cities. And I kind of used the themes at the beginning of my little pitch here. There's transportation, there's energy, there's digitalization, there's sustainability. Those are four big themes. But when you kind of go a little deeper, stuff that matters to cities is very local. And so you have to go in and figure out all sorts of dimensions like culture, communities, culture, the geography of the city, the finances of the city, the economics. I mean, there's a lot of different things that come into play when you think about how do we build a smarter, more sustainable community and what problems are we trying to solve. So my book, Smart Cities for Dummies, it's been received really well, tries to be comprehensive and it does give a lot of examples. But it also recognizes that strategy is really important and the principles are important, like innovation, data use. Making the things that are important independent of where you are and what kind of city you are, are where I can bring value. And then if you want to actually make the change and bring me in to help with that, any type of organization, then we're going to have to get into the weeds, figure out the specifics.

Yeah, that idea that there's no playbook is interesting. I mean, it feels like a huge opportunity in both domains. You mentioned crypto, maybe just to touch on that. Are you thinking of working on a four dummies book for crypto? Is that in the offing or.

I'm not doing a dummies book, but I can tell you I have a book coming out called Cryptocurrency, which is the equivalent of a dummy's book. It's about a 400 page book on the past, present and future of money. It's a comprehensive guide on the topic. It's not an advocacy book. I'm not a champion or promoter of crypto. I'm an educator on crypto. And the purpose of the book is to help everybody understand what is this? Is it actually a Ponzi scheme or is there something to it? I give you the facts, you make up your own mind. So yeah, thank you for asking the question. I know.

Oh, but come on, you have to have an opinion in the extreme of global revolution to Ponzi scheme, like having done 400 pages of writing. What is the answer to that question? Because I feel like, sure, you have people who are equally rabid on both sides.

You do it. Unlike the topics we've been talking about so far, this one is polarizing. It is. There's extreme views actually. So it is a fascinating. And it's fascinating why that is. That actually really makes me curious. I can say a couple of things high level. Firstly, I can concur that any participation in crypto, whether it's trading cryptos OR tokens or NFTs, those types of things, highly risky. I can first say that with without a doubt. So enter at ye own risk. There is no foolproof way of getting in, making money and getting out, highly risky. So I want to say that from the outset, do I believe there's a future for cryptocurrency? My answer is yes. I don't think as many people are deep in this topic, suggest that this is a novelty and it burns out after a few years. It'll crash and burn and it's completely nonsense. I don't take that perspective. I don't feel that through my research and work that's the evidence that I see. There's room for a lot of perspectives, by the way. Respect all perspectives in this. It's very early. It's a moving target for sure. As you can see. I'm really trying to be uncommittal here, but I think this is very. Look, it's a fair question to say what's my point of view. And I have to say that I do think it's here for the long term and what shape it takes and who dominates in the next five to 10 years. I think it's very open. I think we'll see some surprises about what takes and what doesn't. And it's a compelling topic. I'm. There's the crypto part and then related to blockchain, which I think is a completely different conversation, but that is also really fascinating to me. And we're early. We're early too on that.

Yeah. Before you take us out, give us one or prediction about the world of data governance or one expectation that you have for it based upon everything that you've learned over the last couple of years and researching the topic.

What would I say to that question? So I think probably a few years ago, having been involved in this topic to create this video series and doing some talks and things on the topic, it felt still kind of a niche topic. Maybe there was a very small group of progressive organizations that really got it and we're moving forward. My prediction is that this moves and has already moved, but is moving more aggressively into the mainstream. And within a few years it's not a matter of whether you should have a formal data governance program, but the fact that you will have some form of it and that'll be in all types of organizations. When you think about reporting requirements, particularly for public companies and what's required overall in reporting good operations, I think there'll be more demand on data governance results that we don't see today, but we already see more responsibilities relative to cybersecurity for the C suite and public companies. We also see more requirements now emerging out of sustainability and diversity having to begin to be reported. I think it's not the most news flash kind of answer, but the movement of the topic into the mainstream and much broader adoption I think is right ahead of us.

Well, I obviously agree a bit, given what we do here at Data Radical. Great to meet you again and thank you for taking the time. It is a really fun book and I have not made my way all the way through it, but I have progressed through it quite a bit and it's been really clarifying, really excellent work and thank you for taking the time.

Dr. Reichental, thank you very much too. I'm honored that you would read it and it would be helpful to you in your role as CEO of Elation. So thank you very much.

When attacking a hard problem, I often find that it's helpful to come back to first principles, break it down into its most essential parts, and then build back up again from there. Often we do data governance because we have to, or because someone else did it that way, or because that's the way it's supposed to be done. However, if you approach data governance, often a very confusing topic with lazy thinking, you're likely to come up with a very confusing output. People won't know the goals, and it's pretty likely that you won't be successful. So being a dummy about data governance can be pretty useful. Start with the why break the initiative up into critical parts and just ignore the rest. Jonathan's Data Governance for Dummies gives you the framework to do just that, with helpful tips to guide your journey along the way. Thank you for listening to this episode, and thank you, Jonathan, for joining. I'm your host, Satyan Sanghani, CEO of Elation and Data Radicals. Stay the course, keep learning and sharing. Until next time.

This podcast is brought to you by Elation. The role of Chief Data Officer CDO is more vital and challenging than ever before. Elation offers a vision for building a strong data culture that empowers people to find, use, and trust Data. Download the CDO's toolbox 7 Tips for Building a Successful and Sustainable Data Culture A white paper available at elation.com CDO Tools that's A L A T I O-N.com CDO Tools.