Data Culture Eats Strategy for Breakfast | Dr. Jonathan Reichental

That's amazing. Those are some tough acts to follow. Wow. Thank you. Particularly the mayor and the singers and the dancers. This isn't— I'm not going to do any— I'm not going to sing or dance. You're safe. Okay, so I'm happy you're here. I'm happy I'm here. I'm very proud and delighted to be in Guatemala for the very first time. I'm having a good time. Thank you. Thank you for being great hosts. You've been amazing. When I return to Silicon Valley, I will tell the stories of Antigua, Guatemala in September 2023. Well, let's see. We'll get my presentation on the screen and Thanks for spending a bit of time with me. It's a great privilege to be able to speak to you as an audience and to share my insights. I'm going to start my presentation today talking about roads. Now, if this surprises you, you might be in the wrong event right now because this is very important for this story. I want to tell you about the importance of roads, and you probably know more than a lot of people how important roads are, right? Well, I went to work for a city about 10 years ago, actually 13 years ago now, I do the math, and I realized that, you know, these things really matter. People really care. If you want to know what a person thinks about their city, ask them, and they'll probably tell you something about the roads, right? If the roads are have holes in them, if they're gravel or dirt, or they're nicely surfaced. They're a big deal. Roads are a really big deal to cities. What I also didn't know is that there is a scoring system for roads, right? If a road is in really bad quality, it'll be given a low score, and if it's a perfectly brand new surface road, it will have a very high score. In fact, The score is from 0 to 100. 0 is really bad, 100 is really good. And every year, cities have to make decisions about what roads they fix, what roads they improve, right? And it looks a little bit like this, right? Some of you are smiling because you know the data that you sometimes work with looks like this, right? So many of us work with data that looks like this. You can't really make good decisions when you're presented with this. And this is how we've been doing it for a very, very long time. Right? What are we looking at here? We're looking at in the city that I was part of the leadership. This is the, you know, the geographic information. It's got the street, it's got the longitude and latitude. But I want to point you mostly Well, I can't do this. At the end to the score. And you can see these are actually pretty good scores, right? You got 71, 89, 78, pretty good scores. This is my town, which is, it's a nice town. And the mayor came to me, the mayor of City of Palo Alto came to me and said, Jonathan, can you help us be able to consume this data so that we can make better decisions Have more people involved in making the decision so we don't have to work with something like this. Because imagine this is just one page of many, many, many pages, right? Like, how do you make decisions like that? That's not 21st century. So in the tradition of Silicon Valley, I drew a little interface on a napkin. Because that's what we do. We draw the interfaces on napkins. And this is the actual picture that I drew about 13 years ago. This was not last week, by the way. This was 13 years ago I drew this picture. And you can see what I was doing. We'd have a picture of the road. We'd have the score. You could search for any street. Now you have this interactive application from being able to make better decisions. You could actually search your street, and here's really great, you could take your own photograph and upload it. So you could say, you know, my street's in pretty bad condition, maybe you want to fix that. So how are we going to do this? Now, there's two things that always happens in a government context. It does— I talk to people and governments all over the world. There's two things: it's going to be very expensive, And it's going to take a long time. It's going to be very expensive and it's going to take a long time. That's like saying no. That's a nice way of saying no. Well, they hired me to think differently. They hired me as an innovator to break through those barriers, those limitations. So I thought to myself, how can we do this differently? How can we do it so it doesn't cost a lot of money? And it doesn't take a lot of time. Well, we're quite fortunate in the city I came from. We have a big university called Stanford University, and they happen to have a pretty good computer science school. You may know this. And so I thought to myself, maybe I'll get some students to build this. So I went up to Stanford University one weekend when the students I knew were going to be, you know, playing some games and writing some software, and I said, Could you take this? And I'll give you the data. I'll give you all the backend data. Could you take this and build it? I'll give you a little tip here. Bring the mayor with you because the students will respond when the mayor is there. So I took the mayor with me. He's a great guy. And I said, you know, I can't— we're not going to pay you, but we'll feed you. We'll give you nice food and some drinks and, you know, try to build this. And over the next 24 to 48 hours, basically over the weekend, They took this paper napkin and a whole lot of data, because we could provide the data, and they built this. They built the solution in 48 hours. It didn't cost any money, and it actually went very, very fast. And this is a fully functioning application, exactly as I had diagrammed it. And you might be thinking, well, where did all the photographs come from? Right? Google was kind enough to give us the photographs. Google has taken photographs of every street in the world, almost, right? Now you hear this story and you might think to yourself, well, that's cool, maybe we should build everything that way. Maybe that's the solution to all our problems, all our city problems. That's not the purpose. That's not what I think we can do. We can't build every solution that way. I tell you this story for two reasons. Two reasons. Number one, underlying great solutions to solve big problems problems is the data. You have to have the data, and we have the data. That's number one. Once you have the data, computer applications can be built over them, and you can make incredible solutions for problems. But the second thing, and this is really important for the theme of this event, got to think differently, you got to innovate. We did it differently, we got it done. We thought differently. I could have easily, after being told, you know, Jonathan, the solution is going to take 48 hours, the solution is going to take a long time, cost a lot of money. You know what I could have done? I could have said, okay, fair enough, thanks, bye-bye. That's not what you do when you innovate. You start asking questions. How might we do this? And it was so successful that I said, we're going to give all our data away And anyone who wants to solve the problem in our community, please do. And if you can actually make a business out of it, that's even better. And you see the actual picture of when the mayor and the council of my city declared that our city would be open for the world. And we started building all sorts of things. We found, for example, that our app for the community to report issues. We call it 311 in the US. You probably have something similar here. But a community member could get the app and sort of take a picture of graffiti or maybe trash on the street or something they don't like. They take the picture, the photograph then goes to city hall, somebody fixes it, and then we ask you, how did we do? How did we do? Well, what I thought about was behind this application You're going to guess what I'm going to say, right? Is a lot of data. So I took that data and I said, what would happen if we put that data on a live— take that data near real time, put it on a schematic of the city so we could see what was happening real time? And that's exactly what we did. You see the actual heat map here of what's happening in the city of Palo Alto at any point in time. This was visibility that the mayor and the city council and city members had never had in the entire history of the community. They could see what was happening in every place, and they could fix it, but they could also see, are there trends? Are there trends to this? Now, I'm telling you these stories because they all have one thing in common, and that's data. Now, I was asked by a publisher about a year and a half ago, "Jonathan, will you write a book about data?" I said, "Well, I know, I think I know a little bit. I've been doing it for about 30 years. I've been a technology leader for about 30 years. Yes, I'll write a book about data." And then I spent another year writing it, and it came out a few months ago. But one of the questions at the very beginning of this project was, people would say, "Data is the new oil." And one of the things that I always like to do is to validate, check that sentiment. Is that true? Is data the new oil? That's like, wow, that's a big statement to make. Well, I got news for you. I did the research, and data is the new oil. In the 1800s, coal was powering the economies. In the 1900s into the 20th century, it was oil that was powering the economy. In the 21st century, data is the engine of growth. Data is the power for the 21st century economy. We have to identify that in every organization. Now, data is the most important asset you have because it has the greatest power to make the greatest difference. However, with that knowledge, most organizations are not ready and aren't acting on that insight. That's the big insight. If you came into my talk thinking that data is probably important, I want you to leave this talk thinking data is the most important thing in my organization. No matter what you do, whatever business you're in, if you're in the events business or you're a startup or you're in the telecom business, data is absolutely essential. Why has this happened? What has happened over the last few decades? Well, we entered the sort of third industrial revolution in about the 1950s. So, we're now into about 70 years of that and data has been the common thread. Digitalization, moving from analog to digital, creates an abundance of data. Sometimes though, we lose sight of how much am I actually talking about? How much data? Like, it's big data apparently. If there ever was an understatement, it's the term big data. We're actually in the zettabyte era. Right? Zettabytes. You might even not know this term. I didn't know this term for a long time. Zettabyte? What's that mean? Well, you know gigabytes and you know terabytes. You might even know exabytes. Right? But there's a few more and finally you get to zettabytes. It's a 1 with 21 zeros. It's big. A 1 and 21 zeros. From the start of civilization all the way up to today, we created about 120 zettabytes of data. Let me say that again so you understand. From the start of civilization right up to today, we created 121 zettabytes of data. A lot. We will do that again In the next 3 years. Right? Start a civilization today, today, 3 years. Right? A lot of data everywhere. And so the question that I pose to all of you to think about, no matter what you belong to, whether you belong to a city, an events company, telecom, agriculture, farms, medicine, pharmaceutical, whatever it is that you're into, Are you part of a data-driven organization? So think about this question. Think about if you are part of a data-driven organization. I guess the question that you may be thinking is, what does that mean? What is a data-driven organization? What does that actually mean? I'll give you a few examples. When you have a meeting, which we all do, It's the curse of business, is the meetings, right? All the time, meetings. Come to my meeting. Can I have a meeting? I have to go to a meeting. Everybody's like, when you have those meetings, are they— is there a lot of good information being elevated that is database, that is like, we did this survey, we asked these people, we extracted this information from a system? Are you being given real data in a meeting. If it's anecdotal, not so good. It should be based on real evidence, on real outcomes. Your leaders will know, and you are— many of you are leaders— will know if you have a data-driven organization if you're able to make better decisions. Because this is the toughest part about work. And it's particularly tough at the leadership level because that's what you do most of the time is you go to work and you make a series of decisions over the course of the day. And you're hoping that you have good data to make good decisions. Now, anybody who is in a leadership position, if you do get data, you know that decision you make is based on imperfect data. It's the best we can have. We never have perfect information. But if we can serve up good, timely, good quality, accurate data, leaders can make better decisions. Now, it's very interesting that most leaders want their organizations to be data-driven. Maybe not a surprise, right? Turns out 83% of CEOs want a data-driven organization. This is real data, right? 83% want their organizations to be this way. But the reality, the aspiration is different from what they're actually achieving. Only about 32% get there today. Look, those 32%, fair play to them, that's a great achievement. But there's a lot of companies that are not data-driven despite the fact that they want to be. You know what, when I look at this, what do I see? I want to know what the other 17% want. Do you not want your organization to be data-driven? What if not? Well, what do you want? I just think that's an interesting stat there. I think it's fair to say most leaders, let's say the majority of leaders, want their organizations to be this way because there's real risk in going with guts or going with no information whatsoever. The decisions we make today for the biggest problems we have in the world and all sorts of issues are highly complex and interdependent. We don't want our colleagues and leaders to be making decisions based on no reality, on what they believe it should be rather than the actual reality. Half of your employees, if you hire people, if you have people who work for you, are basing their decisions on gut. Would you be okay if your surgeon was half the time based on gut? Or if your, your pilot for your plane was making decisions that was based on gut? I don't think so. And we don't want our leaders in government either. We want them to be empowered with good information. So now the question becomes, how do we get there? How do we go from where we are today, especially those other 70% who want to be data-driven and can't get there? How do we get from today to that point? I did a lot of homework on this, a lot of research. I was like, oh yeah, you could, you could buy tools. You can even send people to university, get people to have certificates. That's very good and you should do that. But I'm here with you for a very short amount of time, so I'm going to cut to the chase. I'm going to tell you how to do it so that you have real value and you leave today with new insights. That's what this is all about. What you need to achieve the success and run a better organization is a data culture. It comes down to a data culture. Data culture is the human operating system of digital transformation. This is how we achieve success. What is data culture? What the heck is he talking about? It's like, get this guy off the stage, you know. Now, let's talk about the data culture. What is culture? Let's go there, right? Simply, culture is behavior. It's how our people behave every single day when they come to work. Or they work from home, whatever the arrangement is in your business, right? It's what they do on a habitual basis. They're what they do when they're asked to do something. It's even what they do when nobody's looking, right? And you know, as a consumer, what that looks like. If you go, if you're, if you go to Disney World or Disneyland or one of the Disneys in the world, if you've had an opportunity to do that, You'll notice very quickly a distinctive culture, how people work, how they do things. If you go to an Apple Store, notice how things are done. It's very unique. Or go to your favorite store, your favorite retailer, fashion retailer, whatever it is, and make a mental note of how they behave. That's their culture, right? Where does that come from? Well, it comes from each other for sure. Culture is formed right from birth, right through life. Everything you observe comes from religion, comes from science, whatever your belief system is, it all informs you, comes from your brothers and sisters, your parents, your friends, and informs you. And at some point inside your head right now, you have a set of values, you have a set of guiding principles that are your behavior. If you're going to be kind, honest, accurate, professional, all these behaviors are part of what form holistically in an organization a culture. Now, we asked a lot of people, how you doing on your digital transformation journeys? Everybody's talking about digital transformations, right? Everybody's talking about them. If you're You got to be in one of three states. You've done your digital transformation, your digital transformation is underway, or you're going to do a digital transformation. You have to be in one of those three states. Otherwise, in the third decade of the 21st century, you're on a trajectory towards failure. I'm telling you the facts. You better have a digital transformation because digital is the heart of every organization in the world. Every business is a technology business. So you have to then think about, well, how do we make our digital transformation work? And so we did this study and we asked people, how are you doing on your digital transformation journey? And a lot of them said, well, not so good. Well, the folks that were honest, right? They said, we're doing, we're doing okay. A lot of digital transformations, unfortunately, let's be really honest with each other, are failing. And then we're wondering why. Well, this, you know, maybe not enough money, maybe not enough leadership support, maybe a bad strategy. There's lots of reasons. The number one reason, number one reason, no data culture. That's an insight, right? If you are underway with your multi-million, maybe your multi-billion dollar digital transformation, and you haven't sorted out data culture, you're in trouble. Because that's the number one reason you will fail. Now, getting into a little bit more specificity here in the short amount of time I have, one of the areas I'd like to focus on is not data management, because you know what? We all do data management. We all store data, we all query data. Every organization does that. Does that mean you have a culture and you govern your data? No, it doesn't. That's sort of like the basics and everybody kind of does it. What you need now to do is layer on that the governance of your data, right? So that you can extract value from your processes and you can reduce the risk. Right? Sure. Look, if data is the most important asset in our organization, if it's the very heart of our success and we're collecting data from our customers, and we're creating data with our customers, and we're creating data inside, that's a heck of a lot of responsibility. Right? And as that data gets bigger and bigger, and it becomes more sensitive, it's a big responsibility. So we have to manage that risk. We do it in all sorts of ways. You're welcome to take a picture because I'm not going to talk about all these things. I drive you guys to sleep. But I illustrate here that this, this process of data governance is a science, and professions and work around this are very valuable to all sorts of organizations. If you're going to govern, if you— if I— if this has resonated with you, if it makes sense that data is important and your data is valued and you want to take more advantage of it, you better know where it is, what it is, who has access to it, how it's been used? Do you— can you answer these questions? Right? Yeah, this guy says yes. That's very, very— well, you're ahead of the game. You are ahead of the game. Most organizations don't really know what data they have. They don't know the quality of the data. And they don't know who has access to it. You got to figure that out. There's lots of ways that we can figure out how to access it. If you want your people to use data to make better decisions, to be able to innovate, give them the ability to find it, right? They need some form of search engine, some sort of what we call a data catalog. So make a catalog for them. Here is an example, an actual example of work that I did with my team when I was a leader at the city of Palo Alto. Here's what we call our open data portal. And you got your search bar there and you got your categories. So people could go in and search and find and use the data that they needed to get better insights and solve problems. And as I said earlier, to build solutions. When people have access to data, they could build new capability. They can solve problems that you don't have the time to or you can't afford. Here's an example of data that's around permits. Every city has permits. And so people wanted to know what's happening in my community. And they would use— it would be very difficult to find that out. So we opened up all the permitting information and developers built a front end where they could search based on an address, get a photograph, and actually get the state of the permits. Not only did they build a solution that the community wanted, it didn't cost anything to us as a government. But they built a business. They built a successful business that hires people, employs people. That's an economic boost from data. You get economics here. You can drive economic growth in your community by doing the things that I've spoken about today. You've got to establish a program around this, a data governance program. And just by a show of hands, does your organization have a data governance program? We got sort of. We got one hand. That's not a good sign, right? Well, I'm glad you came to my talk. Imagine that I'm giving you the secret recipe right now to success with digital transformation, to increase your innovation quotient and to reduce your risk. That's pretty good, right? That's a pretty good little exchange we had here in the 30 minutes I've been with you, right? So you got to have a program around it, set some policies up, and then enforce them through the operation— operation even. That's a tongue twister right there, right? Who is this? You need to have Perhaps depending on the size of your organization, someone to lead this, a data governance leader. If you're a small organization, many organizations in here, my guess would be you're pretty small. It's part of somebody's role. You don't, you don't have to hire a whole team. Now if you're Claro or McKinsey or some of the bigger, you know, Visa, these companies have big data governance teams with leaders and, and lots of roles. Administering the data governance program because they want to innovate more and they want to reduce the risk. Now, one thing I would say to you, when you do this, when you do this work, people are going to push back. You know, this may be the most boring but most important topic that you need to know about. It's certainly the conclusion that I came up with when I was researching and then writing my book. Boring but important. We have to do that. It drives really incredible results though. When you ask people to be involved, you say, hey, you know what, we went to this presentation with this guy, you know, in Antigua, and he was talking about data culture, and he was talking about we got to put data governance in place, and I think we need to do it. Your teams are going to say, oh my goodness, not more bureaucracy, more paperwork, like This sounds like a lot of administration for very little return. So you're going to have a bit of a tough time. You got to sell this and all its values. How do you do that? Okay, people are going to push back. You're going to get a lot of resistance. That just comes with any initiative that seems to be game-changing or disruptive or bureaucratic. What you do is after a little while, well, only a few weeks have passed. Demonstrate accomplishments. So start to talk about what is going well. So you got to become great internal communicators. You can share this information with your customers too if you think it's important, but communicate internally all the success you're having with the data governance program. When people see that their effort translates to results, to good outcomes, They're more likely to be invested, to be more interested, more passionate about this topic. I wanted to kind of bring this to a close with a real big world example. I take you down to the country of Aotearoa, which is the new name for New Zealand. It's a place I go to quite often, I go there to work, it's a country I fell in love with. Amazing place. Small country in terms of people, landmass is decent-sized country. It's a modern, progressive, relatively wealthy country. They have a big national government doing all sorts of things— transportation, energy, public safety, water quality, all the things you'd expect from a national government. But what they discovered over many, many decades of the growth of this government and the growth of their programs is that they were not working together very well at all. Each department, whether you were Department of Transportation, the military, whatever the department was, they were doing well as silos, but they were not doing well talking across each other. If they did that, they would innovate more, they would deliver better quality services, people would have more insight, they would reduce the risk of the data they managed. So they rolled out a governance framework, a data governance framework. Complex, detailed, engaging. And very quickly they start to see results. The New Zealand national government started to change the game about what was possible when you share data across silos. It made people collaborate more deeply. They got better results. The community felt that there was more transparency. They reduced risk and they innovated more. Little twist I want to give you on this is the indigenous people of Aotearoa are the Māori people. The Māori people, amazing people, Māori people. And they have very deep beliefs about things, very different from a Western perspective, my perspective, American perspective, I guess. They believe that everything has a spirit within it, and they in fact believe that data contains a spirit. So Māori data has to be managed in a certain way if you want to respect the culture. And they certainly want to respect their indigenous culture and work together. You have to respect and treat data in a very special way, and they bake that into their data governance program with great success. With great success. So as I begin to wrap up here on this boring but important topic— I disagree. I agree. I think it's exciting. I'm always wondering, you know, I've been in business about 30 years. I'm always wondering, what are the things we need to do to have more success? And I ask people, what is the thing I can do in my, in my government, in my business, in my university? What can I do to build and have more better outcomes? And they tell me data culture. And I have the evidence now. If you do these steps, if you do only a little bit of what I shared with you today, your organizations will be more data-driven and you will have better, more successful outcomes no matter what business that you're in. With that, thank you very much. Thank you. Thank you.