>> (lively music) (lively music) >> [Narrator] Live, from Fisherman's Wharf in San Francisco, it's theCUBE. Covering IBM Chief Data Officers Strategy Summit Spring 2017. Brought to you by IBM. >> Hey, welcome back everybody. >> Jeff Flick here with theCUBE alongside Peter Burris, our chief research officer from Wikibon. We're at the IBM Chief Data Officers Strategy Summit Sprint 2017. It's a mouthful but it's an important event. There's 170 plus CDO's here sharing information, really binding their community, sharing best practices and of course, IBM is sharing their journey which is pretty interesting cause they're taking their own transformational journey, writing up a blue print and going to deliver it in October. Drinking their own champagne as they like to say. We're really excited to have CUBE alumni, many time visitor Seth Dobrin. He is the chief data officer of IBM Analytics. Seth welcome. >> Yeah, thanks for having me again. >> Absolutely, so again, these events are interesting. There's a series of them. They're in multiple cities. They're, now, going to go to multiple countries. And it's really intended, I believe, or tell me, it's a learning experience in this great, little, tight community for this, very specific, role. >> Yeah, so these events are, actually, really good. I've been participating in these since the second one. >> So, since the first one in Boston about 2 1/2 years ago. They're really great events because it's an opportunity for CDO's or de facto CDO's in organizations to have in depth conversations with their peers about struggles, challenges, successes. >> It really helps to, kind of, one piece says you can benchmark yourself, how are we doing as an organization and how am I doing as a CDO and where do I fit within the bigger community or within your industry? >> How have you seen it evolve? Not just the role, per say, but some of the specific challenges or implementation issues that these people have had in trying to deliver a value inside their company. >> Yeah, so when they started, three years ago, there, really, were not a whole lot of tools that CDO's could use to solve your data science problems, to solve your cloud problems, to solve your governance problem. We're starting to get to a place in the world where there are actual tools out there that help you do these things. So you don't struggle to figure out how do I find talent that can build the tools internally and deploy em. It's now getting the talent to, actually, start implementing things that already exist. >> Is the CDO job well enough defined at this point in time? Do you think that you can, actually, start thinking about tools as opposed to the challenges of the business? In other words, is every CDO different or are the practices, now, becoming a little bit more and the conventions becoming a little bit better understood and stable so you >> can outdo a better job of practicing the CDO role? >> Yeah, I think today, the CDO role is still very ill defined. It's, really, industry by industry and company by company even, CDO's play different roles within each of those. I've only been with IBM for the last four months. I've been spending a lot of that time talking to our clients. Financial services, manufacturing, all over the board and really, the CDO's in those people are all industry specific, they're in different places and even company by company, they're in different places. It really depends on where the company's are on their data and digital journey what role the CDO has. Is it really a defensive play to make sure we're not going to violate any regulations or is it an offensive play and how do we disrupt our industry instead of being disrupted because, really, every industry is in a place where you're either going to be the disruptor or you're going to be the distruptee. And so, that's the scope, the breadth of, I think, the role the CDO plays. >> Do you see it all eventually converging to a common point? Cause, obviously, the CFO and the CMO, those are pretty good at standardized functions over time that wasn't always that way. >> Well, I sure hope it does. I think CDO's are becoming pretty pervasive. I think you're starting to see, when this started, the first one I went to, there were, literally, 35 people >> and only 1/2 of then were called CDO's. We've progressed now where we've got 100 people over 170 some odd people that are here that are CDO's. Most of them have the CDO title even. >> The fact that that title is much more pervasive says that we're heading that way. I think industry by industry you'll start seeing similar responsibilities for CDO's but I don't think you'll start seeing it across the board like a CFO where a CFO does the same thing regardless of the industry. I don't think you'll see that in a CDO for quite some time. >> Well one of the things, certainly, we find interesting is that the role the data's playing in business involvement. And it, partly, the CDO's job is to explain to his or her peers, at that chief level, how using data is going to change the way that they do things from the way that they're function works. And that's part of the reason, I think, why you're suggesting that on a vertical basis that the CDO's job is different. Cause different industries are being impacted themselves by data differently. So as you think about the job that you're performing and the job the CDO's are performing, what part is technical? What part is organizational? What part is political? Et cetera. >> I think a lot of the role of a CDO is political. Most of the CDO's that I know have built their careers on stomping on people's toes. How do I drive change by infringing on other people's turf effectively? >> Peter: In a nice way. >> Well, it depends. In the appropriate way, right? >> Peter: In a productive way. >> In the appropriate way. It could be nice, it could not be nice >> depending on the politics and the culture of the organization. I think a lot of the role of a CDO, it's, almost, like chief disruption officer as much as it is data officer. I think it's a lot about using data >> but, I think, more importantly, it's about using analytics. >> So how do you use analytics to, actually, drive insights and next best action from the data? I think just looking at data and still using gut based on data is not good enough. For chief data officers to really have an impact and really be successful, it's how do you use analytics on that data whether it's machine learning, deep learning, operations research, to really change how the business operates? Because as chief data officers, you need to justify your existence a lot. The way you do that is you tie real value to decisions that your company is making. The data and the analytics that are needed for those decisions. That's, really, the role of a CDO in my mind is, how do I tie value of data based on decisions and how do I use analytics to make those decisions more effective? >> Were the early days more defensive and now, shifting to offensive? It sounds like it. That's a typical case where you use technology, initially, often to save money before you start to use it to create new value, new revenue streams. Is that consistent here? By answering that, you say they have to defend themselves sometimes when you would think it'd be patently obvious >> that if you're not getting on a data software defined train, you're going to be left behind. >> I think there's two types. There's CDO's that are there to protect freedom to operate and that's what I call, think of, as defensive. And then, there's offensive CDO's and that's really bringing more value out of existing processes. In my mind, every company is on this digital transformation journey and there's two steps to it. >> One is this data science transformation which is where you use data and analytics to accelerate your businesses current goals. How do I use data analytics to accelerate my businesses march towards it's current goals? Then there's the second stage which is the true digital transformation which is how do I use data and analytics to, fundamentally, change how my industry and my company operates? So, actually, changing the goals of the industry. For example, moving from selling physical products to selling outcomes. You can't do that until you've done this data transformation till you've started operating on data, till you've started operating on analytics. You can't sell outcomes until you've done that. It's this two step journey. >> You said this a couple of times and I want to test an idea on you and see what you think. Industry classifications are tied back to assets. So, you look at industries and they have common organization of assets, right? >> Seth: Yep. Data, as an asset, has very, very, different attributes because it can be shared. It's not scarce, it's something that can be shared. As we become more digital and as this notion of data science or analytics, the world of data places in asset and analytics plays as assets becomes more pervasive, does that start to change the notion of industry because, now, by using data differently, you can use other assets and deploy other assets differently? >> Yeah, I think it, fundamentally, changes how business operates and even how businesses are measured because you hit on this point pretty well which is data is reusable. And so as I build these data or digital assets, the quality of a company's margins should change. For every dollar of revenue I generate. Maybe today I generate 15% profit. As you start moving to a digital being a more digital company built on data and analytics, that percent of profit based on revenue should go up. Because these assets that you're building to reuse them is extremely cheap. I don't have to build another factory to scale up, I buy a little bit more compute time. Or I develop a new machine learning model. And so it's very scalable unlike building physical products. I think you will see a fundamental shift in how businesses are measured. What standards that investors hold businesses to. I think, another good point is, a mind set shift that needs to happen for companies is that companies need to stop thinking of data as a digital dropping of applications and start thinking of it as an asset. Cause data has value. It's no longer just something that's dropped on the table from applications that I built. It's we are building to, fundamentally, create data to drive analytics, to generate value, to build new revenue for a company that didn't exist today. >> Well the thing that changes the least, ultimately, is the customer. And so it suggests that companies that have customers can use data to get in a new product, or new service domains faster than companies who don't think about data as an asset and are locked into how can I take my core set up, my organization, >> my plant, my machinery and keep stamping out something that's common to it or similar to it. So this notion of customer becomes the driver, increasingly, of what industry you're in or what activities you perform. Does that make sense? >> I think everything needs to be driven from the prospective of the customer. As you become a data driven or a digital company, everything needs to be shifted in that organization from the perspective of the customer. Even companies that are B to B. B to B companies need to start thinking about what is the ultimate end user. How are they going to use what I'm building, for my business partner, my B to B partner, >> what is their, actual, human being that's sitting down using it, how are they going to use it? How are they going to interact with it? It really, fundamentally, changes how businesses approach B to B relationships. It, fundamentally, changes the type of information that, if I'm a B to B company, how do I get more information about the end users and how do I connect? Even if I don't come in direct contact with them, how do I understand how they're using my product better. That's a fundamental just like you need to stop thinking of data as a digital dropping. Every question needs to come from how is the end user, ultimately, going to use this? How do I better deploy that? >> So the utility that the customer gets capturing data about the use of that, the generation of that utility and drive it all the way back. Does the CDO have to take a more explicit role in getting people to see that? >> Yes, absolutely. I think that's part of the cultural shift that needs to happen. >> Peter: So how does the CDO do that? >> I think every question needs to start with what impact does this have on the end user? >> What is the customer perspective on this? Really starting to think about. >> I'm sorry for interrupting. I'd turn that around. I would say it's what impact does the customer have on us? Because you don't know unless you capture data. That notion of the customer impact measurement >> which we heard last time, the measureability and then drive that all the way back. That seems like it's going to become an increasingly, a central design point. >> Yeah, it's a loop and you got to start using these new methodologies that are out there. These design thinking methodologies. It's not just about building an Uber app. It's not just about building an app. It's about how do I, fundamentally, shift my business to this design thinking methodology to start thinking cause that's what design thinking is all about. It's all about how is this going to be used? And every aspect of your business you need to approach that way. >> Seth, I'm afraid they're going to put us in the chaffing dish here if we don't get off soon. >> Seth: I think so too, yeah. >> So we're going to leave it there. It's great to see you again and we look forward to seeing you at the next one of these things. >> Yeah, thanks so much. >> He's Seth, he's Peter, I'm Jeff. You're watching theCUBE from the IBM Chief Data Officers Strategy Summit Spring 2017, I got it all in in a mouthful. We'll be back after lunch which they're >> setting up right now. (laughs) (lively music) (drum beats)