 Live from Boston, Massachusetts, it's theCUBE. Covering IBM Chief Data Officer Strategy Summit. Brought to you by IBM. Now here are your hosts, Dave Vellante and Stu Miniman. Welcome back to Boston, everybody. This is theCUBE, the worldwide leader in live tech coverage. Stu Miniman and I are pleased to have Gene Kolker on a CUBE alum. He's IBM Vice President and Chief Data Officer of the Global Technology Services Division and Seth Dobrin, who's a director of digital strategies at Monsanto. You may have seen them in the news lately, gentlemen. Welcome to theCUBE. Gene, welcome back. Good to see you guys again. Thanks. Thank you. So, let's start with the customer, Seth. Let's tell us about what you're doing here and then we'll get into your role. Yeah, so, you know, the CDO Summit has been going on for a couple of years now and I've been lucky enough to be participating for a couple of years, a year and a half or so. And, you know, really the nice thing about the summit is the interaction with peers and the interaction and networking with people who are facing similar challenges from a similar perspective. Yeah, it's kind of a relatively new role and topic. One that's evolved, Gene, we talked about this before, but you've come from industry into a non-regulated environment now. What's that been like? So, I think the deal is that we were developing some approaches and we're getting some successes in a very regulated environment, right? And now, I feel with, and we were being client of IBM for years, right? Using the technologies approaches, right? So, and now I feel it's time for me personally to move on to something different and try to serve our, I mean, IBM clients irrespective of industry. I came from healthcare, but their approaches and what IBM can do for clients go across different industries, right? And doing it at scale, that's very beneficial, I think, for clients. So, Monsanto, obviously you guys do a lot of stuff in the physical world, you know, the digital strategy. So, what does that entail? What is Monsanto doing for digital? Yeah, so, you know, for as head of digital strategies for Monsanto, really my role is to, number one, help Monsanto internally reposition itself so that we behave and act like a digital company, so leveraging data and analytics. I mean, also the cultural shifts associated with being more digital, which is that whole, you know, kind of like you start out this conversation with the whole customer first approach. So, what is the real impact to what we're doing to our customers and driving that? And then, based on those things, how can we create new business opportunities for us as a company? And how can we even create new adjacent markets or new revenues and adjacent areas based on technologies and things we already have existing within a company? So, is the scope of analytics, customer engagement, digital experiences, all of the above? So, the scope is really looking at our portfolio across the gamut and seeing how we can better serve our customers and society, leveraging what we're doing today. So, it's really leveraging the reuse factor of the whole digital concept, right? So, we have analytics for geospatial, right? A big part of agriculture is geospatial. Are there other adjacent areas that we could apply some of that technology and some of that learning? Can we monetize those data? Can we monetize the outputs of those models based on that? Or is there just a whole new way of doing business as a company because we're in this digital era? Seth, we talked about a lot of the companies that have CDOs today are highly regulated. What are you learning from them? What's different kind of in your organization? It might be an opportunity for you that they don't have. And do you have a CDO yet or is that something you're planning on having? Yeah, so we don't have a CDO. We do have someone who acts as a, essentially he's a de facto CDO. He has all of the data organizations on his team. It's very recent from ONS Nano. And so I think in terms of from the regular, what can we learn from the other? It's about half financial people, half non-financial people are in the half heavily regulated industries. And I think on the surface, you would think that there was not a lot of overlap. But I think the level of rigor that needs to go into governance in a financial institution, that same thought process can really be used as a way to really enable more R&D, more growth-centered companies to be able to use data more broadly. And so thinking of governance, not as a roadblock or an inhibitor, but really thinking about governance as an enabler. How does it enable us to be more agile? How does it enable us to be more innovative, right? If people in the company, there's data that people can get access to via a known process of a known condition, right? Good, bad, ugly, as long as people know, they can do things more quickly because the data's there, it's available, it's curated. And if they shouldn't have access it under their current situation, what do they need to do to be able to access that data, right? So if I'm a data scientist and I want to access data about my customers, what can and can't I do with that data? Number one, does it have to be de-anonymized, right? Or if I want to access it in its current form, what steps do I need to go through and what types of approval do I need to do to access that data? So it's really about moving roadblocks through governance instead of putting them in place. Gene, I'm curious, we've been digging into, IBM has a very multifaceted role here. How much of this is platforms? How much of it is education and services? How much of it is being part of the data that your customers are using? So I think actually there are different approaches to these issues. My take is basically we need to think that we live in cognitive era, right? And data is a new natural resource worldwide, right? So data is a service, cognitive is a service. I think this is where IBM is coming from. And IBM is traditionally was not like that, but it's under a lot of transformation as we speak. So a lot of new people coming in, a lot of innovation happening as we speak along these lines of new times because cognitive is something really new, right? And it's just getting started. Data as a service is really new. It's just getting started. So there are a lot to do. And I think my role specifically, global technology services is largest by revenue unit at IBM is 30 plus billion entity, okay? And we support a lot of different industries basically going across all different types of industries. How to transition from IT offerings to new business offerings, service integrated services. I think that's the key for us. Is that, Seth, I'm just curious, where's Monsanto with kind of the adoption of cognitive? Where are you in that journey? So we are actually a fairly advanced in the journey in terms of using analytics. I wouldn't say that we're using cognitive per se. We do use a lot of machine learning. We have some applications that on the back end run on AI. So some form of artificial or formal artificial intelligence and machine learning. We haven't really gotten into what IBM defines as cognitive in terms of systems that you can interact with in a natural, normal course of doing voice and that you spend a whole lot of time constantly teaching. But we do use, like I said, artificial intelligence. So Gene, I'm interested in the organizational aspects. So we had Interpol on before he's the global CDO. You're a divisional CDO. You've got a matrix into your leadership within the global services division, as well as into the chief data officer for all of IBM. Okay, sounds reasonable. He laid out for us a really excellent sort of set of a framework, if you will. This is Interpol. You got to understand your data strategy, identify your data sources, make those data sources trusted, and then those are sequential activities and then in parallel, you have to partner with the line of business and then you got to get into the human resource planning and development piece. That has to start right away. So that's the framework, sensible framework, a lot of thought, I'm sure went into it and a lot of depth and meaning behind it. How does that framework translate into the division? Is it sort of a plug and play and or is there divisional goals that create dissonance? Can you sort of? So basically I'm only 100 plus days in my journey within IBM, right? But I can tell you that global technology services is transforming itself into integrated services business. So this framework you just described is very applicable to this, right? So basically what we're trying to do, we're trying to become, I mean, it was the case before for many industries, for many of our clients, but we want to transform ourselves into more, I would say, trusted broker to what they need to do. And this framework is helping tremendously because again, there are things we can do in one after another, right? Sequential order and things we can do in parallel. So we're trying those things to be put in an agenda for our global technology services unit, okay? And this is new for them in some respects, but in some respects, it's kind of what they were doing before, but with new emphasis on data as a service, cognitive as a service, major thing for one of the major things for global technology services, delivery. So cognitive delivery, that's kind of new type of business offerings, which we need to work on, how to make it truly once sense automated, in other sense, cognitive. And deliver to our clients some new value, add on value compared to what was done up until recently. What do you mean by cognitive delivery? Explain that. Yeah, so basically, in plain English, so what's right now happening usually when you have large systems, computer systems, IT systems, which are basically supporting a lot of industries, a lot of organizations, corporations, right? You know, it's really done like this. So it's people run, technology assisted, okay? And a lot of decisions, of course, being made by people, but some of the decisions can be simpler decisions, right? Decisions which can be automated, can be standardized, normalized, can be done now by technology, okay? And people gonna be used for more complex decisions, right? So basically, you're gonna turn from people run technology assisted to technology run people assisted, that's very different value proposition, right? So again, it's not about eliminating jobs, it's very different. It's taking of routine and automatable parts of the business, right? To technology and giving options and basically options to choose for more complex decision-making to people. That's kind of, I would say, the approach. So it's about scale. And scale too, of course. IBM, when Gershner made the decision to sort of reorganize as a services company, IBM became a global leader, if not the global leader, but a services business, hard to scale. You can scale with bodies, and the bigger it gets, the more complicated it gets, the more expensive it gets. So you're saying, if I understand it correctly, that IBM is using cognitive and software, essentially to scale its services business where possible, assisted by humans. Yeah, so that's exactly the deal. So, and this is very different value proposition to say compared to what was happening recently or earlier or with other players. We're not building you shiny and much more powerful and cognitive-empowered mousetrap. No, we're trying to become trusted broker, okay? And how to do that at scale, that's an open, interesting question. But we think that this transition from people around technology assisted to technology around people assisted, that's the way to go. So Seth, what does that mean to you? How does that resonate? Yeah, I think it brings up a good point actually. If you think of the whole litany of the scope of analytics, you have everything from kind of describing what happened in the past all the way up to cognitive. And I think you need to understand the power of each of those and what they should and shouldn't be used for. And a lot of people talk a lot about predictive analytics, right? And when you hear predictive analytics, that's really where you start doing things that fully automate processes, that really enable you to replace decisions that people make, right? I think, but those are more transactional type decisions, right, more binary type decisions. As you get into things where you can apply binary, or sorry, you can apply cognitive, you're moving away from those more binary decisions, those more transactional decisions, and you're moving more towards a situation where, yes, the system, the silicon brain, right, is giving you some advice on the types of decisions that you should make based on the amount of information that it could absorb that you can even fathom absorbing. But there still needs to be some human judgment involved, some understanding of the context outside of what the computer can gain. I think that's really where something like cognitive comes in. And so you talk about in this move to have computer run, human assisted, right? There's a whole lot of descriptive and predictive and even prescriptive analytics that are going on before you get to that cognitive decision, but it enables the people to make more value added decisions, right? So really enabling the people to truly add value to what the data and the analytics have said instead of thinking about it as replacing people because you're never gonna replace people. I think I've heard people at some of these conferences talking about, well, cognitive and AI is gonna get rid of data scientists. I don't buy that. I think that's really gonna enable data scientists to do more valuable, more incredible things than they could do today. We've talked about this a lot, Stu. I mean, machines through the course of history have always replaced human tasks, right? And it's all about what's next for the human and I mean, with physical labor, driving stakes or whatever it is, we've seen that, but now for the first time ever, you're seeing cognitive assisted functions come into play and it's new. It's a new innovation curve. It's not Moore's law anymore that's driving innovation. It's how we interact with systems and cognitive systems. And I think you hit on a good point there when you said in driving innovation. I've run large scale automated processes where the goal was to reduce the number of people involved and those are like you said, physical tasks that people are doing. What we're talking about here is replacing intellectual tasks, right? Or not replacing, but freeing up the intellectual capacity that is going into solving intellectual tasks to enable that capacity to focus on more innovative things, right? We can teach a computer to explain an area to us or give us some advice on something. I don't know that in the next 10 years we're gonna be able to teach a computer to innovate. And if we can free up these smart minds today that are focusing on how do we make a decision to how do we be more innovative in leveraging this decision and applying this decision, that's a huge win. And it's not about replacing that person, it's about freeing their time up to do more valuable things. You have a comment? Yes, sure. So for example, from my previous experience, right? In healthcare. So physicians right now, basically it's basically impossible for human individuals, right? To keep up with pace of changes and innovations happening in healthcare and biomedical areas, right? So in a few years, it looks like there were some numbers that estimate that in three days you're gonna have much more information for several years, produced during three days, what was done by several years prior to that point. So it basically becomes inhuman to keep up with all these innovations, right? Because of that, decision's gonna be not optimal decisions. So what we'd like to be doing, right? To empower individuals, make this decision correctly with alternatives, right? That's about empowering people. It's not about just taking, which can be done through these processes, all this information and getting routine stuff out of their plate, which is completely full. There was a stat, I think it was last year at IBM Insight, I don't know if this is exact numbers, but it was something like a physician would have to read 1,500 periodicals a week just to keep up with the new data innovations. I mean, that's virtually impossible. And so that's something that you're obviously pointing Watson at. I mean, but there are mundane examples, right? So you go to the airport now, you don't need a person, an agent, to give you a boarding pass. It's on your phone already, you get there, okay. So that's a mundane example. We're talking about significantly more complicated things. And so what's the gate? Is the gate creativity? Is it education? Because these are step functions in value creation. I think that's what the gate is is a question I haven't really thought too much about. I approach it, the thinking more from a, not so much what's the gate, but where can this add the most value? And so maybe a half thought about it, and the gate is value. And it's value both in terms of, the physician example where physicians look at images and I don't even know what the error rate is when someone evaluates an MRI or something. I probably don't wanna know, right? So getting some advice there, the value may not be monetary, but to me it's a lot more than monetary, right? If I'm a patient. And there's a lot of examples like that in other places that are in various industries that I think that's the gate is what's the value? You just hit on it, because you are a heat seeking value missile inside of your organization. So what skill sets do you have? Where did you come from that you have this capability? Was it your experience, your education, your fortitude? Well the answer is yes, to all of them. I'm a scientist by training. My background's in statistical genetics. And I've kind of worked through the business. I came up through the R&D organization within Monsanto over the last almost exactly 10 years now. And I've had lots of opportunities to leverage data and analytics to change how the company operates. And I'm lucky because I'm in a company right now that is extremely science driven, right? Monsanto is a science based company. And so being in a company like that, you don't face your question about financial industry. I don't think you face the same barriers in Monsanto about using data and analytics in the same way you may in a financial type company. Based on my experience, 50% of diagnosis been proven incorrect, okay? So 50% 50, half. So imagine you go to your physician twice, once you, an average, you're getting wrong diagnosis. We don't know which one by the way. So we definitely need some help as individuals, as human, we do need some help as cognitive. And it goes across different industries, right? Technologies. So if your server is down, you shouldn't worry about it because there is like system, robust system enough, right? So think about it, how you can do it at scale and then start to imagine the future which gonna be very empowering. So it used to be get a second opinion. And now the opinion comprises thousands, millions, maybe tens of millions of opinions. Is that right? It's that's right, exactly. And scale of data accumulation which gonna help us to solve these problems is enormous. So we need to keep up with that scale and do it properly, exactly for business, value proposition. Let's talk about the role of the CDO and where you see that evolving, how it relates to the role of the CIO. We've had this conversation frequently but I'm wondering if the narrative's changing, right? Because it's been fuzzy when we first met a couple years ago. That was still a hot topic. When I first started covering this topic, it was really fuzzy. Has it come in to more clarity lately in terms of the role of the CDO versus the CIO versus the CTO, Chief Digital Officer? Are we starting to see these roles? Are they more than just sort of buzzwords or gray areas? I think there's some clarity happening already. So for example, there is much more acceptance for Chief Data Officer, Chief Analytics Officer, Chief Digital Officer, right? In addition to CIO. So basically, the situation is similar to what was with CIOs 20 plus years ago. And CIO role in one sentence from my viewpoint would be how you can use an IT, leveraging IT, empower your business value proposition. With CDO, it's the same with data. How using data, leveraging data, your data and your client's data, you can bring new value to your clients and businesses. That's kind of, I would say, differential. Last word. You know, and you think, you know, I'm not a CDO. But if you think about the concept of establishing a role like that, I think the name is great because what it demonstrates is support from leadership that this is important. And I think even if you don't have the name in the organization, like in, like in Monsanto, you know, we still have that executive management level support to the data and analytics, our first class citizens, and they're important and we're going to run our business that way. And I think that's really what's important is, are you able to build the culture that enables you to leverage the maximum capability data and analytics? That's really what matters. All right, we'll leave it there. Seth, Jean, thank you very much for coming in the queue. Really appreciate your time. Thank you. All right, keep it right there, everybody. Stu and I, we're back. This is the IBM Chief Data Officer Summit. We're live from Boston, we're right back.