 Hello and welcome to Data Diversity Talks, a podcast where we discuss with industry leaders and experts how they have built their careers around data. I'm your host, Shannon Kemp, and today we're talking to Anthony Ogman, the Convergence Platform Program Lead at AFI. Shannon Kemp, and I'm the Chief Digital Officer at Data Diversity, and this is my career in data, a Data Diversity Talks podcast dedicated to learning from those who have careers in data management to understand how they got there and to be talking with people who help make those careers a little easier. To keep up to date in the latest data management education, go to dataversity.net forward slash subscribe. And today we are joined by Anthony Ogman, the Convergence Platform Program Lead at AFI, and normally this is where a podcast host would read a short bio of the guest, but in this podcast your bio is what we're here to talk about. Anthony, hello and welcome. Hi, Shannon. Thanks for having me. So glad you were here. Okay, that's a very long title, Convergence Platform Program Lead. So what is that and what is it you do? Yeah, so it is as if I tried to find the longest title possible. It was really, you know, I've had a background for many years in consulting and finance and technology and all of this stuff, but I had been out doing consulting for a number of years and I had an opportunity through some contact that I had, a person I knew from way back, like in the financial industry days, 15 years earlier, where you'd been with ABD for a couple of years, working on this Convergence Platform. And what we're trying to do and what ABD is trying to do with this is, you know, we noticed that over the past several decades, as a pharmaceutical industry, we haven't gotten a whole lot better at finding the medicine. So if you look at where drugs fall off in the development cycle, like those percentages, like some will fall off really early, some will get to a stage three trial and some will actually eventually be approved, but those percentages haven't fundamentally changed. And we said, and some of our senior leadership said, you know, we should be doing better than that with all the advances in data and technology and how we can put these things together and work with it. We should be better at finding the right drugs earlier on in the process. And so they said, you know, we are going to invest in a large scale effort to transform how our organization, our R&D organization works with data, technology, each other to really try to move those percentages in a meaningful way, because that is really how we become more relevant as a business, we become more successful in finding new medicine. This is a big deal. And so when I was asked, I came here to lead the Technology Platform build out that will support that broader Convergence Initiative. So again, a lot of words going around, but it's about building out that infrastructure, that technology, that data ecosystem, that we can use all the data that R&D uses, which is a whole lot of data, and put it together in ways that scientists can have new ways of navigating it, finding new connections, making things possible from a research and development point of view. They just couldn't have done before. And so my team is building out that technology platform, which I think is the easiest part about this whole thing, like building technology, building data systems relatively easy compared to getting 12,000 scientists to do something different. Right, that's the real hard part in all of this. But for me, it's about putting into action what I've been talking about for years and years. Like, I've been working with Data Diversity a long time, I've been consulting a long time, I've been doing technology and business strategy work for a long, long time. And I wanted to have an opportunity to put it all into action where the contract wouldn't run out, where I could be there for the long term and build out a team and build out the success. And I couldn't have imagined, you know, I joined FB right at the start of the pandemic. And I couldn't imagine a better opportunity to do this in a place that really mattered. And so for me, having the opportunity to work in life sciences, work in finding new medicine, the context of COVID in a pandemic that still hasn't left us. To me, it was like, well, I'm gonna do this now. Like I had plans, I was doing my consulting thing and it was fine. But when they said, hey Anthony, use your help, I'm like, I'm in, let's do it. Like, I will regret this forever if I don't, let's just get going. So I mean, that's why I'm here now. But it's also been just so rewarding to be back on that industry side and have a new glimpse after many years doing consulting to relearn what it's like to be my client. Relearn what those challenges are day in and day out and what a client is facing when they're trying to do that. It'll eventually make me a better consultant one day. If I go back into consulting, I will know a lot more coming out of this experience with Abbie than I would have otherwise. And you touched on that a little bit. Abbie is a pharmaceutical company. That's right. We are Life Sciences Biotechnology Pharmaceutical Company known for Humira, known for Rin Vogue, Sky Rizzy. We now own Botox as part of our allergen acquisition. So Big Pharma based in the Chicagoland area grew out of Abbott Laboratories. So that's the, Abbie, I learned this once I started, Abbie's is Abbott Life. So it's French Abbott Life. So that's where that name derived from. Nice. So I'm guessing that when you were very young, just a little boy, this was not what you dreamed of being when you grew up. Or is it? Like, what was your dream? What was it when you were? What did you want to be when you grew up? It's funny because I can absolutely point to an awareness in high school, especially, where I said, I never wanted to be, well, I wanted to be a professional baseball player. That didn't work out. But I also knew that I didn't have any interest in being like broadly famous or like come a movie star or anything like that. What I said is I want to know something really well. And I want to be a respected name in that place. When I come to a place where I do what I do, that I want to be known and understood and be able to talk about something knowledgeably and speak like I knew speaking and being part of that kind of community would be important to me. I had no idea what data management was or data governance or data leadership or any of that stuff was. So certainly didn't have the details worked out but could definitely trace what I do now back to those days, even in high school where I'm like, that's kind of the thing I want to do someday. Oh, interesting. So, when you were in high school, so then what did you decide, where'd you go after high school? So after high school, I went to a liberal arts school undergrad and I was always about business. Like I always wanted to help businesses be more successful in business stuff. And so like I went to undergrad, studied business, studied some computer science and stuff as well. Also was studying Japanese, which I've now forgotten all of, so don't even try. But I was studying a bunch of things. I was just interested, but at the time we're talking in the 90s, I was like, I didn't understand that you could be involved with technology but still fundamentally business motivated. I was just thinking if I do all this technology stuff, I'm gonna be sitting at a computer banging out code all day and that sounds like a sad life. That's not what I want to do. So I always had that kind of, I want to make it impact the business. I always want to make a connection there because that's what really matters in capitalism and in organizations. So I mean, when I graduated undergrad for a short six months, I was a stockbroker. I studied and I learned all the fun things. I had done some really cool finance classes in undergrad. Like, I'll do finance stuff. That sounds fun. And I'm like, I've always wanted to do some sales things, that's fine. So I did that. It got all the accreditation and like licenses and everything. And then it dawned on me. It was a lot less about, at least in the organization I was working with, there was a lot less about let's do an analytical model to determine what the best asset allocation would be and the best investment strategy or whatever. No, where I was working, it was like, here's the stock of the day. Here's the bond of the day. Find anyone you can to buy it. It was like, look for boiler room in its nature of it. But a super boring boiler room. It was like, look warm room is kind of where my stock for the day. But so I kind of realized, I'm like, this isn't for me. And literally, it turns out to be a long run of like, well reason, seemingly rash decisions. Like on a Friday, I realized I can't do this. This will not be my career. And then I quit on Monday. And the reason I did is that I couldn't go to people and say, hey, I'm gonna be your long-term financial advisor when I'm new. I'm like, I'm out of here, man. Like there's no way I'm doing this. So I just let it. I didn't know what was gonna come next. But what came next was maybe the most instrumental move in my career, which was I went to Morningstar, the mutual fund investment advisory firm, and found myself doing data analysis, it was the position with an electronic data analyst, which really quickly led to program. It really quickly led to doing things to bring data. In those days, Morningstar got its original start by getting net asset values and other data from mutual fund companies. And those mutual fund companies could be something like Vanguard, big stuff with big files and all this sophistication, or like literally some person in their basement office writing things down and sending them to you in the mail, like everything in between. And so, you know, Morningstar wasn't paying for any of this information, but they were just starting to publish about this stuff. So my job was to get that data, however it came into a database. And so we did that. And so that led to more programming and that led to more opportunities and that led to a couple other roles in the financial industry, where I was doing technology and data development. I had opportunities to be a programmer and did front end user interface stuff in the web. I learned a lot about technology throughout those days. And that eventually led, I was working at a trading firm and doing some really cool stuff around trade reconciliation, reporting, business intelligence was really the focus of a lot of the work that my team was doing, a lot of accounting automation and other things like that. I got an MBA in night school while I was there. And so a wonderful organization at the time it's no longer around, but really had an opportunity to live that dream of going to get an MBA and then had to work for a period of time. But then when I was spring clear of those obligations, I went into consulting. Cause I said, you know, I've been so focused on this financial industry, you know, going way back to the stock worker, but then going to like doing data work for many years. I mean, at that point it was a decade. Then I said, you know, I'd like to go into consulting because I'd like to see other industries. I'd like to learn more about what goes on. I had the general business background from the MBA and the previous studies that I'd had, but I was really trying to fill in more of it. That's when I learned like data governance was actually a thing. I had been doing this for a long time, not knowing that there was a whole world of study around data governance and data management, data quality, master data, all this world that kind of came to me once I started my consulting career. And I had some really great mentors and some really, you know, great opportunities. And this is where like I started working with dataversities. When I was in my consulting career all of a sudden now, I need to get out there. I need to start learning much more than what I had been exposed to in individual businesses. Had to build out basic consulting skills too. And dataversity was where I found an opportunity to learn from the experts in this space. And then eventually, you know, not too long after I started attending dataversity events, started having the opportunity to speak at dataversity events first with individual sessions, eventually led to tutorials. And then led to a much bigger relationship with dataversity over the last many years where we've partnered together on training or on the book or on various events and things like that. And I've had so many opportunities to speak and learn and connect with folks through that. And I think that's really an important part of that journey for me is like I go back to what we were talking about with high school where I knew I wanted to be speaking. I knew I wanted to be getting out there as a thought leader in something. Now I found that something. And I always felt like very, and I know you've asked one question. I've been talking for like 20 minutes. But like, once I found that data world and dataversity was a big part of opening my eyes to all of that, I fully realized that I was doing and had found, relatively early in my career, found what my life's work was all about. And like some people go their entire careers and don't know what their life's work is all about. Never find that calling. And I found that calling. And so to me, it was about realizing, hey, this brings together the technology stuff I was interested in, the business stuff I was interested, all this data, new like things in technology, development, hot items, and things that people are interested in that's continued to grow. And so it was like, wow, I found this thing that keeps getting bigger and it's become something that just has defined what my entire career is about. And that for me is like, I know what my life's work is and I feel super fortunate that that's the case where I struggle and have learned through various things that I've done since I started in my consultant career is I struggle with context. Am I better off as a consultant? Am I better off as an entrepreneur or as an industry person or doing big programs like what we're doing at FBE? Or what have, and what I've kind of learned is just depends, just depends on what people need, what I can add value to and what matters in the end. And as I get older and older, things like FBE check a lot of boxes for me where what we're doing feels so much bigger than what I could ever do on my own. And that to me is something where I'm like, I don't know how long this lasts. I hope it lasts a while. And I hope that I am able to contribute to something that changes medicine and finds a cure. I mean, people are already finding new drugs through this platform that we're working on, doing science that hasn't existed before. And I have to role in that. Like, how cool is that? That's awesome. That's amazing, especially in this day and age, right? Yeah. With a robust catalog of courses offered on demand and industry leading live online sessions throughout the year, the Dataversity Training Center is your launchpad for career success. Browse the complete catalog at training.dataversity.net and use code DVTALKS for 20% off your purchase. And there's a piece in there in your career I know that you kind of missed that I want to touch on is you were a chief data officer? Yeah. Yeah. So where that was and how that kind of fit into the whole scheme is that I had started with one organization in my consulting career, which I will name as West Monroe Partners. I still think the world of them. But at the time, I had a young family. I didn't want to be on the road anymore. And I just didn't see a good path to doing what I wanted to do in the context of that organization. So I moved to another organization that was more locally focused. And so I didn't have to get on the plane as much. And I think that those models are evolving even now. But like at the time, it was more of a local model and that was good. But I had a client, which turned out to be the Chicago Transit Authority where I became the chief data officer. So there was a client where they had been doing a lot of work with data, but they didn't have a data analytics group. And it was actually the audit group, the chief internal auditor who had hired me as a consultant there because what do auditors do? They're using it, they're finding information, they're analyzing it, they're trying to find patterns and stuff like that. That's what data people do. That's data analytics. But the problem was is that they're trying to do audits and all of a sudden everybody in the organization is like, hey, audit group, you do data stuff. Can you do some data stuff for us? So they were getting pulled in all these different directions. So like, Anthony, can you come in here and let us do audits again? Like, let me see what I can do. So we came in there and we started making some real strides in an organization that's all about data, who had very little data capability at the time. I just came in and started doing things that made sense to me. It's like, well, this data takes way too long to access and a lot of things break all the time when we try to run a report. Let's fix that. So we'd fix that. And then we'd get faster at the data. And then that led to them for a while while I was consulting there. They were like, Anthony, come here and do this full time. We can't have a consultant keep doing this in the long term. We usually come here full time. I'm like, no, I'm good. I don't need to do that. And then maybe I'm oversharing here, but then it came down to they're like, well, Anthony, I'll tell you, Shannon, this is the best way you ever want to hear a negotiation stuff when you're sitting with us. They're like, Anthony, just tell us what it takes. And I'm like, I'll get back to you tomorrow. So I came up with this list. And I'm like, I'll tell you what it takes. And I'm like, literally, I'm making fun of it now, but it's actually quite literally went through. I'm like, what would it take for me to take this position? What would it take for, because it's not even about me. It's what would it take for this position to be successful in this organization? And so I came back and I said, okay, well, you need somebody who can really create this data analytics in a serious way, in a real way. And I looked at the organization of like where the power dynamics were and how things were functioning and where the technology was and how the data folks were working, who had data skills and all that basically said, okay, here it needs to be a chief data officer title. And it needs to be that chief data officer title needs to be at the same level as the CIO. Because what I realized is that the CIO was gonna torpedo anything that that CDO would do otherwise. So I don't care where it reports. You have a report wherever they need to, as long as it's no less than where the CIO reported, which was the CFO, which actually was where we ended up having that position report. So it was like, and I was trying to be realistic because I'm like, I don't even know if I'm the right person for this role, but I'll tell you what the role means, right? And so you need to be at the same level. You need to have a team built underneath them. You need to have certain budgetary authority in certain ways to create technology to complement the core technology operations. And I needed a residency exception. That one was about me, because I didn't live in the service area at the time. And that was something where you could get a residency exception, but it was a big deal. And I'm like, I think this is a non-starter, but they saw what I was talking about and then I had enough of a track record of success of where we were going. They really wanted to keep that going. And it just wasn't gonna be sustainable as part of the consultant model. And so I tried to give them, whether it's me or somebody else, like here's what you really need to do here. And so they ended up talking through it or working through it and ended up working out so that I could take the position. It was unfortunate because it was a little bit short-lived because it was like a week later, I felt like, once I took the position, the mayor got reelected and effectively took the president of CTA at the time and moved him out to become chief of staff for the mayor first, but that only lasted like a month. And then they sent him to run Chicago Public Schools. And when that happened, he took the entire leadership team from CTA with him to Chicago Public Schools. And that really changed the dynamic of what my role would be at CTA. So I ended up sticking around for a little while, but it was clear that the new administration just didn't see the value of data the same way, didn't see eye to eye. And I really joined the organization because of that leadership team and the chief and general auditor that I've been working with, everybody was gone. And so I said, okay, it's time for me to go off and do something else, which led to some more entrepreneurial things and some consulting and that stuff, did get an opportunity to do some consulting work with Chicago Public Schools to kind of do it. It was really cool because their data challenges were totally different, but like amplified from what CTA was. And it gave me an opportunity, it kind of made CTA feel like a dress rehearsal for the big challenges of CPS. But I do think that that time between the work that I was doing in the public sector at CTA and then CPS, that really helped ignite in me a desire to do good through my life's work. Like you spend a decade in the financial industry making rich people richer. It's not as fulfilling as when you're helping people get to where they need to, to get to doctor's appointments, to get to their jobs. And then at Chicago Public Schools, educating the next generation, it doesn't get much bigger than that. Human health is a pretty big deal too. And so that's where like, and I don't know that I could ever spend a lot of time doing things that I don't think are super important for the world. And as I get older and older, that becomes a bigger and bigger importance to me and what my life's work is about. Like how can I do this weird thing that I do and help somebody as much as possible? Of course data, the use of data is set up just for that too, for when we use for anything. Visit dataversity.net and expand your knowledge with thousands of articles and blogs written by industry experts, plus free live and on demand webinars covering the complete data management spectrum. While you're there, subscribe to the weekly newsletter so you'll never miss a beat. Okay, so having stood up a CDO office and having such an extensive career in data, what is your definition of data? So my definition of data, I could throw a few different lenses at it, but I think the most important is data's the closest thing to truth we have in our organizations. And in that vein, it's what teaches us about what our organizations have done, what our organization's opportunities are, where our organization's assets are, and really helps drive the kinds of change we need to make as businesses to be successful in our markets. And I find it fascinating because the other piece to that, well, the truth piece I think is first and foremost, I'm also amazed at the notion of data as an asset because how many other assets, when you use data, what happens, right? When you use data, ideally two things happen. One, you do something of value to your business. You're starting to drive some sort of activity or change that helps your business improve at what it does, right? The second thing is you create more data. So the more you use data, the more you create data, the more data you have to use the more benefits your business can have. And I'm like, we've solved cold fusion with data. And so I'm fascinated by this whole thing because what other asset do you create more of the more you use it? And that's where I'm fascinated when I think about the work that I'm doing in FB and what we're trying to do is so much of our effort isn't around creating the data in the first place. A lot of our data comes from external sources, some comes from internal sources, some comes from what we then build on top of, right? So to me, it's about thinking through the long game of how do we take these different component pieces, start stitching them together, starting to combine them, starting to do things on top of that to create more data that we then can pass to others who can use that to do other things. And like if we can create ecosystems that do that and you create these feedback loops that keep reinforcing it, then I have to believe that truth grows and our potential is unlimited because that's the natural evolution of that loose calculation. So that to me is, to me, that's the essence of data. So we can get into the ones and zeros of it, literally, but like to me, the data truth and scale and dynamics of that, that's what fascinates me. It keeps me fascinated about data after doing this for so long. I love that reference to Cold Fusion. It's the first time I've heard it, I love it. I think that should be built to everyone's definition because it's so true. So Anthony, do you see the importance of data management and the number of jobs working with data increasing or decreasing over the next 10 years and why? Yeah, I mean, I think that data management is becoming a bigger and bigger need. You just look at like, and I thought about this a lot lately, like I mean, we both have phones within arm's reach right now. And as does literally everyone who's listening to this, probably on their phone. And we're masterful data consumers. We are masterful at taking information in, focusing around social media, this and all this stuff, you know, shopping and you know, whatever. And what I've realized is that just because we're masterful data consumers, we have these high expectations of what data should be able to do. We see it in our business life or in our personal lives constantly, right? But that masterful consumption does not magically lend itself to the creation of data capabilities in a similar way. That's a different area of emphasis. That's a different area of work. And that takes real effort and real substance behind it to create those things that we're constantly using. And so in our businesses, we don't have the kinds of capabilities today in most cases that we do in our personal lives. It didn't used to be that way. It used to be the opposite back in the day, but now because data is so prevalent in our personal lives, we expect that in our business, but we don't know how to make it. So how do we change that? And I think that's where these data management roles, they may not always look like the data management roles we're accustomed to seeing today. I think we see a greater push out to more federated governance, more things being decided at the end state and being loosely collaborated upon and connected to then bubble up to other areas. I don't know that we've even really seen the beginning of creating those reinforcing loops that I was talking about. I think we're still in kind of a linear one directional flow a lot of the time. We have data, we use data, we create some value, create some more data that probably doesn't go anywhere and now we're done. The more we create those loops, I think the more opportunity for roles not only that we see today, but way beyond that and how we nurture those data assets going forward. So I think it becomes a bigger part of every organization as we continue before. And what advice would you give to people looking into getting into a career in data management in any aspect? Yeah, I would say the first and foremost thing is to be curious to learn and think through. Don't just take anything quite at face value, try to really understand of where it's coming from. Recognize too that the data while we focus on like technology things or like analytics things, the real value of data comes from changing people's behaviors, changing business process. There's a lot of change and management of that change over time or the prioritization of resources and investments. Recognizing that the more we want to do, nobody owes us this in our company. Nobody says, hey, we've just been waiting for some data governance. Like that's literally never been said. And so what we have to do is realize it's on us. If we identify, hey, there's an unmet need in our business, it relates to data. And it relates to something that we might do with data. We have to learn enough about how business works to create a proposal or sell the idea or sell the platform, build the thing that makes it happen. And so I just would encourage folks to not close themselves off to learning some technology or learning some stale strategy or learning how to give a presentation or learning how to communicate or write or whatever it is that you find interesting or you find effective, wherever you are, do those things, find ways to connect them and you'll have your own approach that can be very effective as we build out more and more of these data capabilities across all of our businesses. Cause they're all heading that way. Like there's no business out there who doesn't have some sort of data today. And I think most businesses need data, need data excellence to be relevant going forward. Yeah, it's certainly indeed as we move into this digital world. So if I'm hearing you correctly, don't be afraid to continue to learn and follow your passion. Absolutely, well, and I've been told I am a passionate person when it comes to this. But to me, it's hard not to be passionate about these things. And if you're doing this work because somebody said, hey, this is a good idea, you should go do this. And your heart's not in it, don't do it. Life's way too short. I mean, if the pandemic's taught us anything, it's like you can't take anything for granted and if you're not following what you're passionate about, if you're not following something that you love, there's probably something out there that you do. Chase that down. Don't end up like looking back on your life saying, wow, I really should have done this other thing. You know, I just, I love data. I think data is great, I think everybody should do it. But like if you're not passionate about it, you know, follow what you are. Cause there was plenty of people that are passionate about data, but I just want people to have good careers, feel like at the end of it all, as we get older and we look back on our life's work, I just, you want to say, yeah, I'm glad I did that. No, it makes sense. So anything else you want to add, any more about your current role or anything we didn't get a chance to touch on? No, I would just encourage folks out there to really explore the non-obvious things. Like one of the things that I think about when these were recording this during a diversity event. And I just think about the role that data diversity has played in supporting my career, giving me an opportunity to explore these things and be able to speak and be able to meet people. I mean, that the amount of knowledge that exists at these kinds of events, whether they're diversity or otherwise, like explore those things, be curious. Like if that curiosity draws you to something, leave no stone unturned, you know? And that's where like with data, with data you turn over these stones looking for things that the downside is like, turn over a stone, you learn something, and then you realize, oh wait, 10 more stones, I'm gonna do that stuff. Much more to turn over. But it kind of grows in that way, but explore and try to enjoy it. Cause that's the thing, like if you can find that passion, you tap into something that, it's still work, let's not kid ourselves, there's still effort, there's still a job, but there's something more to it. And I think that finding that, finding what resonates for you is really the most important thing. Makes so much sense. Well, Anthony, thank you so much for taking the time to chat with me today, especially since I drug you out of the conference in order to do this, I really appreciate it. And thanks to all of our listeners out there. If you'd like to keep up to date on the latest podcasts and the latest in data management education, you may go to dataversity.net forward slash subscribe. Until next time. Thank you for listening to Dataversity Talks, brought to you by Dataversity. Subscribe to our newsletter for podcast updates and information about our free educational articles, blogs and webinars at dataversity.net forward slash subscribe.