 From Cambridge, Massachusetts, it's The Cube, covering MIT Chief Data Officer and Information Quality Symposium 2019, brought to you by SiliconANGLE Media. Welcome back to Cambridge, Massachusetts, everybody. You're watching The Cube, the leader in live tech coverage, where this is The Cube's two-day coverage of MIT CDO IQ, the chief data officer information quality event, 13th year. We started here in 2013. I'm Dave Vellante with my co-host, Paul Gillan. Vita Bawa is here. Bawa, sorry, Vita Bawa, did I get that right? It's close enough. The director of data governance at Raymond James and Althea Davis, the former chief data officer of ING Bank Challenges and Growth Markets. Ladies, welcome to The Cube. Thanks so much for coming on. Thank you. All right, Vita, talk about your role at Raymond James. Relatively new role for you, is it right? It is a relatively new role. So I recently left 5th third bank as their managing director of data governance and I've moved on to Raymond James in sunny Florida, and I am now the director of data governance for Raymond James. So it's a global financial services company. They do asset wealth management, investment banking, retail banking, and so I'm excited. I'm very excited about the opportunity. We've been talking all day and actually several years about how the chief data officer role kind of emerged from the back office of the data governance and the information quality and now has come front and center and actually we've seen full circle because now it's all about data quality against Althea as the former CDO, is that a fair assessment that sort of came out of the ashes of the back room? Yeah, I mean it's definitely a fair assessment. That's where we got started. That's how we got our budgets. That's how we got our teams. However, now we have to serve many masters. We have to deal with all of the privacy. We have to deal with the multiple compliances. We have to deal with the data operations and we have to deal with all of the new sexy emerging technologies. To do AI and data science, you need a lot of data. You need data rich, you need it to be knowledge management, you need it to be information management and it needs to be intelligent. So we need to actually raise the bar on what we do and at the same time get the credibility from our C-suite peers. So I think we no longer have the, we don't have luxury of being just a cost center anymore. We have to generate revenue. So it's about data monetization. It's about partnering with our businesses to make sure that we're helping to drive strategy and deliver results for the broader organization. So you got to hit the bottom line, either raise revenue or cut costs, directly that can be tangibly. Exactly, keep them out of jail, right? Save money, make money. Keep them out of the new, keep them out of jail. Like most CDOs, you did not study for this career path because it didn't exist a few years ago. So talk about your backgrounds and how you came to come into this role. Yeah, absolutely. So you talked about data kind of starting in the bowels of the back office. So I am that person, right? So I am an accountant by training. So I am the person who has done legal anti-controllership. I've booked journal entries. I've closed the books. I've done regulatory reporting. So I know what it feels like to have to deal with dirty data every single month then, every single quarter in, right? And I know the pain of having to cleanse it and having to deal with our business partners and having experienced that gave me the passion to want to do better, right? To want to influence my partner's upstream to do better as well as to take away some of the pain points, right? That my team was experiencing over and over again. It really was Groundhog Day. So that really made me feel passionate about going into the data discipline, right? And so, you know, the benefit is great. It's not an easy journey, but yeah, out of accounting, finance, and that kind of back office operational support was born, right? A data evangelist and someone passionate about this. Which makes sense, because you have to have data quality. Yeah, absolutely. You got to have consistency. You have to have a so-called single version of the truth. Absolutely. Because, you know, the regulators like for the financial reports to be accurate all the time. I'm about to say those regulators. Yeah. How about you? I came at it from a totally different angle. I was a marketeer. So I was a business major marketeer. I was working with the big retail brands, you know, the Nike's and the Levi Strausses of the world. So I came to it from a value chain perspective, from marketing, from, you know, rolling out retail chains across Europe. And I went from there as a line management position and all the pains of the different types of data we needed. And then did quite a bit of consulting with some of the big consultancies, Accenture. And then rolled more into the data migration. So dealing with those huge change projects and having teams from all over the world. And knowing the pains of what all the guys didn't want to work on, I got it all on my plate. So, but it put me in the position to be a really solid chief data officer. Somebody, I was at a, it was like, it was called like data chicks or something like that. And I snuck in, I was like the lone, I was like the lone data dude at this event. It's okay, no judgment here. But I was a judge. So, and one of the things that one of the CDOs said there, she was a woman obviously. And she said, you know, I think that, and the stat was there was a higher proportion of women as CDOs than there were across tech, which is like, I don't know, 15, 17%. And she posited that the reason was because it's like a thankless job that nobody wants. And so I just wonder as a woman CDO, your thoughts on that, is that? Well, first of all, we're the newest to the table, right? So you're the new kid on the block. Doesn't matter if you're a man or a woman, you're the new kid on the block. So, you know, the CFOs got the 4,000 year history behind them or her, the CIO, CTOs, they've got the 50, 60 years up on us. So we're new. So you have to carve out your space. And I do think that a lot of women, by nature, like to take on things big, to do things that other people don't want to do. So I can see how women kind of fell into that. But at the same time, you know, data is an asset. And it is the newest asset. And it's definitely misunderstood. So I do think that, you know, women, you know, we kind of fell into it, but it was actually something that happened good for women because there's a big future in data. Well, let's just be realistic, right? Women have a unique skill set. I might be a little biased, but we have a unique skill set. We're able to solve problems creatively, right? There's no one-size-fits-all solution for data. There's no accounting pronouncement that tells me how to handle and to manage my data, right? I have to kind of figure it out as I go along and pivot when something doesn't work. I think that's something that is very natural to women, right? And I think that contributes to us kind of taking on these roles. Creativity. Let's do a little survey here. So we hear that the Chief Data Officer function is defined differently at different organizations. Now, you both are in financial services. You both have a Chief Data function. Are you doing the same thing? Absolutely not. You know, this is data by design. I mean, I've been lucky. I've had teams that go the whole gamut, right? So from the compliance side, through to the data operations, through to all of the, like I said, the exotic, sexy, you know, emerging technology stuff with the data scientists. So I've had the whole thing. I've also had my last position at ING Bank. I had to, you know, lead a team of Chief Data Officers across three different continents, Australia, Asia, and also Eastern and Western Europe. So it's totally different than, you know, maybe another company that they've only got a Chief Data Officer working on data quality and data governance. So again, another challenge of being the new kid on the block, right? Defining roles and responsibilities. There's no one globally, universally accepted, definition of what a Chief Data Officer should do, right? Is data science in or out? Or analytics in or out, right? Security sometimes. Security, right? Privacy sometimes is in or out, right? Do you have operational responsibilities or are you truly just a second line governance function, right? There's a mixed bag out there in the industry. I don't know that we have one answer that we know for sure is true, but I do know for sure is that data is not an IT function. Well, okay, that's really important. It's not an IT asset. I want to say that it's not an IT asset. It is a information asset or a data asset, which is a different asset than an IT asset or a financial asset or human asset. But, and that's the other big change is that 10 to 15 years ago, data was assumed to be a liability, right? Federal rules are such a civil procedure. We got to get rid of the data or, you know, we're going to get sued. Number one, number two is data, because it's digital, you know, people say data's the new oil. I always say it's not. It's more important than oil. It's much more. You can only use in one use case. It's over and over and over and over. Reuse, reuse, perpetual, it goes on and on and on. And every time you reuse it, the value increases. So I would agree with you. It is not the new oil. It is much bigger than that. And it needs to, I mean, I know from some of my colleagues in the profession, we talk about barring from other more mature disciplines to make data management, information management, and knowledge management much more robust and be much more professional. We also need to be more professional about it as the data leaders. So when you're a little panel today, one of the things that you guys addressed is what keeps the CDO up at night. I presume it's data. No, no, no, it's our peers that don't get it. That's what keeps us up at night. I guess it's the sponsors that keep us up at night. So what was that discussion like? So yeah, I mean, it was a lively discussion. Great attendance at the panel. So we appreciate everyone who came out to support it, definitely full house. Ray review so far. Yep. Okay. So the thing that definitely keeps folks up at night, and I'm going to start with my standard, which is quality, right? You can have all of the fancy tools, right? You can have a million data scientists, but if the quality is not good or sufficient, then you're nowhere, right? So quality is fundamentally the thing that the CDO has to always pay attention to. And there's no magic pill or magic write potion that's going to make the quality right. It's something that the entire organization has a rally around and it's not a one and done, right? It has to be a sustainable approach to making sure the quality is good enough so that you can actually reap the benefits or derive the value right from your data. Absolutely. And I would say, you know, following on from the quality and I consider that the trustworthiness of the data. I would say as a chief data officer, you're coming to the table, you're coming to the executive table, you need to bring it all. So you need to be impactful. You need to be absolutely relevant to your peers. You also need to be able to make their teams in a position to act, so it needs to be actionable. And if you don't have all of that combination with the trustworthiness, you're dead in the water. So it is a hard act and that's why there is a high attrition for chief data officers. You know, it's a hard job, but I think it's very much worthwhile because this particular asset, this new asset, we haven't been able to even scratch the surface of what it could mean for us as a society and for commercial organizations or government organizations. To your point, it's not a technology problem. When Mark Ramsey was surveying the audience this morning, he said, you know, why have we had so many failures? And the first hand that went up said, it's because of, you know, relational data base. Yeah, right, right. And I wanted to say, it's not a technology problem. Exactly. It's a, it's a heart, mind, and hands. Absolutely. You can make an impact to your data landscape without changing your technology. You said at the outset how important it is for you to show bottom line impact. Right. What's one project you can cite that you've worked on or that you've led in your tenure that did that? You want to, okay. If we're talking about, for example, I can't say specifics, but if we're looking at one of the institutions, I worked at an insurance firm and we looked at the customer journey. So we worked with some of the different departments that traditionally did not get access to data for them to be able to be affected at their jobs. What they wanted to do in marketing was create actually new products to make, you know, increase the wallet from the existing customers. Other things they wanted to do was, for example, when there were problems with the customers, instead of customer, you know, leaving, you know, the journey, they were able to bring them back in by getting access to the data. So we either gave them insight, like, you know, looking back to make sure that things didn't happen wrong the next time, or we helped them giving them information so they could develop new products. So this is all about go-to-market. So that's absolutely bottom line. It's not just all cost-efficiency in products. Yeah, pipeline. And that's really valid, but, you know. Absolutely, so I'll give you one example where the data organization partnered with our data scientists to try to figure out the best location for various branches for that particular institution. And it was taking, right, millions of data points, right, about our current footprint, as well as other information about, right, geographic information that was out there publicly available, taking that and using the analytics to figure out, okay, where should we have our branches, our ATMs, et cetera, and then consolidating the footprint or expanding where appropriate. So that is bottom line impact for us. Wow, and I remember in the early part of the 2000s, I remember reading a Harvard Business Review article about gut feel Trump's data every time, but that's an example where no way. Nope. Never do better with the gut than that example that you just gave. Yeah, absolutely. Vita, I want to ask you a question. I don't know if you heard Mark Ramsey's talk this morning, but he sort of declared the data governance was over. And as the director of data governance, I wonder if you disagree with that. Never! Look, it's just like saying that I should stop brushing my teeth, right? I always will have to maintain a certain level of data hygiene. And I don't think that employees and executives and organizations have reached a level of maturity where I can trust them to maintain that level of hygiene independently. And therefore I need a governance function, right? I need to check to make sure that you brush your teeth in the morning and in the evening, right? I need to go for your annual exam to make sure you don't have any cavities that weren't detected, right? So I think that there's still a role for governance to play. It will evolve over time for sure, right? As you know, the landscape changes, but I think there's still a role right for that governance function. That wasn't my takeaway, Paul. I think he said basically enterprise data warehouse fail, master data management failed, the single data model failed, so we punted to governance and that's not going to solve the enterprise data problem. That was my takeaway. That was one leg in the stool, right? It's one leg in the stool. Yeah, I think it was really what he was, I would sum it up as monolithic data storage approach failed like that. And then our attention went to data governance, but that's not going to solve it either. Look, data management is about 12 different data capabilities. It's a discipline. So we give the title data governance, but it means it's all different things. And I think that if we're more educated and we're more apt and we have more confidence on what we're doing on those different areas, plus information and knowledge management, then we're way ahead of the game. I mean, knowledge graphs and semantics, that puts companies at the top of that corporate inequality gap that we're looking at right now, where companies are five and a thousand times more valuable than their competition. And the gap is just going to get bigger considering if some of those companies at the bottom of the gap are, just keep on doing the same thing. I agree, I was just trying to get you worked up. Oh. But you did. But that, but that, but that. You got me worked up. It's going to be a different kind of show. But at that point you're making up the, Microsoft, Apple, Amazon, Google, Facebook, top five companies in terms of market cap, they're all data companies. They've surpassed all the financial services, all the energy companies, all the manufacturers. And Alibaba, same thing. Oh yeah. They're doing the same thing. They're coming right up there. And they're all doing the whole knowledge, the knowledge approach. They're doing all of this stuff. And that's a much more comprehensive approach to looking at it as a full spectrum. And if we keep on in the financial industry or any industry, keep on just kind of looking at little bits and pieces, it's not going to work. It's a lot of talk, but there's no action. We are losing, right? We know that fintechs are infringing upon our territory. If Amazon can provide a credit card or lend you money or extend you credit, they're now functioning as a traditional bank would. If we're not paying attention to them as real competitors, we've lost the battle. That's a really important point you're making because it's all digital now. And it used to be you'd never see companies traverse industries. And now you see Apple, Pay, and Amazon, and healthcare. And government organizations teaming up with corporations and individuals. Everything is free flowing. So that means the knowledge and the date and the information also needs to flow freely, but it needs to be managed. And then get something out of it. Now yeah, you're actually the whole realm of privacy and security. And regulations, right? Regulations for the non-right traditional banks who are doing banking transactions. Do you think traditional banks will lose control of the payment systems? If they don't move with the time, they will. If they don't. I mean, it's not something that's going to happen tomorrow, but there is a category of bank called challenger banks. So there's a reason. Even within their own niche, there's a group of banks. I mean, not even just payments, right? Think about cash transactions. Like if I do a money transfer, am I going to my traditional bank to do it? Or am I going to cash app? Yeah. I think it's interesting, particularly in the retail banking business where one banking app looks pretty much like the other and people don't go to branches anymore. And so that brand affinity that used to exist is harder and harder to maintain. And I wonder, what role is data play in reestablishing that connection? Well, for me, right? I get really excited and sometimes annoyed when I can open up my app for my bank and I can see the pie chart of my spending. They're using my data to inform me about my behaviors. Sometimes a good story, sometimes a bad story, but they're using it to inform. That's bringing, that's making me more loyal to that particular institution, right? So the more they can do, I can also link all of my financial accounts in that one institution's app. And I can see a full list of all of my credit cards, all of my loans, all of my investments in the one stop shopping. That's making me go to their app more often versus the other options that are out there. So I think that, right, we can use the data in order to endear the customers to us, but we have to be smart about it. That's the accountant in you. I just choose to not look. You can afford to not look, I can. Thank you so much for coming on. It was really a great segment, I appreciate it. Thanks for riding us off. Yeah. Thank you for watching everybody. We'll be right back with our next guest. Right after this short break, you're watching theCUBE from MIT in Boston. Cambridge, right back.