 Okay, we're back, this is Dave Vellante with Jeff Kelley. We're here live at IBM's IOD conference at the Mandalay Bay in Las Vegas. This is the second year for theCUBE where we've been at IOD, we go out to the events, like information on demand, we extract the signal from the noise, which is what everybody's trying to do with big data and analytics. Wes Hunt is here, he's the Vice President of Analytics at Nationwide Insurance. Wes, welcome to theCUBE. Thank you. Great to see you, thanks for coming on. So, tell us a little bit about your role at Nationwide, we'll get into your business a little bit. Well, Nationwide is a mutual insurance company. Since 1926, we've been selling auto insurance to our members, and we also sell many other products, homeowners insurance, commercial insurance, pet insurance, financial services products like annuities and life policies, mortgages. My role in the marketing organization is help us understand all of that customer data that we collect, and to draw insights from that and allow us to help take action to improve the relationships that we have with our members. So what's going on in your business? I mean, obviously there's a lot of new entrants, there's been a lot of pricing battles that I think you guys have tried to stay above the fray, but still, a lot of people say, oh, cheap insurance, great, I'll buy cheap insurance, and then it's, uh-oh, when there's a problem, but nonetheless, a lot of competition, a lot of pressures on your business, I wonder if you could describe those a little bit and talk about how you guys have responded. Sure. Well, the insurance category, the property casualty category is extraordinarily competitive. Many, many insurance companies, and we're all going after a fairly mature group of customers. What we seek to do is we seek to differentiate on service. Now, there are some companies who will differentiate on pricing, but our model is to differentiate on service, and we do that because we're a mutual insurance company, and we really focus on seeking to deliver great experiences for our members. So, yeah, so explain a little bit about what that means, service in an insurance context. Sure. Well, the insurance, the experience that consumers have with insurance tends to be low involvement, right? You'll sign up for insurance, and you'll get a bill once in a while, and then you might have a crash, and you need coverage. You need to be made whole. Well, the experience that we seek to deliver for our members is really to be proactive, to demonstrate that we know our customers, to care about our customers, and to be easy to do business with when they need to have service, and that's really where we focus our efforts. Yes, okay, so once a year, everybody's going to relate to this, right? You'll get a form in the mail, and it's okay, here's your coverage. All right, so when you say proactive, you mean, hey, maybe you should adjust that coverage, maybe you got too much here, not enough there, maybe rebalance the portfolio, can you do things like that today? Sure, so we look at what we describe as moments of truth, and through analytics, we've been able to determine which moments of truth matter for the members that we serve. And when you get one of those bills, for example, sometimes customers value a needs-based assessment to make sure that they're adequately covered if something, you know, poor would happen to them, and we use that as an opportunity to really reinforce our value proposition, which is being on your side. Now, how do you do that? Do you do that through the agent? Is that something that you use? Yeah, nationwide has a unique distribution model. We serve customers online through agent offices and through telephone call centers. What we seek to do is deliver that same great experience regardless of the channel that consumers like to do business with us. And so we work on not only analyzing data, but making sure we deliver data into the hands of those who are working with our members so they can deliver that great experience. So that consumer interaction occurs between the customer and the agent, back-ended by your infrastructure, your knowledge, your data, your best practice? There's a lot of data collected, and there's a lot of data that needs to be adjusted to make sure that we understand what it means, and then we simplify that and deliver it back to those who are working with our customers to make it easy to understand data insights, and they use that to deliver our service promise. What's the evolution of your analytics business look like over the past, let's say five to seven years? Where did it come from and where is it headed? Well, nationwide has always been on your side. Since 1973, that's been our jingle. And so we really are a member-centric company. But we had to do a lot of work to consolidate some back-ended systems that stored customer information and policyholder information and claims information, and we did that over the last five years. Really to focus on bringing a complete view of our customers, a 360-degree view of our customers, and understanding of the interactions that they've had across the different channels, and then we seek to analyze that information and identify areas where we can help deepen relationships. As an example, we want to make sure that consumers don't have to retell their story. Have you ever had one of these experiences, and it's consistent across many different consumer categories, but you're on the phone with one person, you have a problem, they can't help you, so they transfer you to somebody else, and what's the first thing you have to do? You have to retell your story, right? Well, you have to retell your story because the data isn't traveling along with the phone call. What we seek to do is really break down those barriers, put that information that's critical to the experience into the hands of those who are serving our customers, and in doing so, our customers get better service. Well, I imagine in addition to the different channels and touchpoints with customers, you've also got different lines of business. You've got home, you've got car insurance and other types of insurance, and I imagine I would guess that those had kind of developed in silos over the years, and that would be, I would imagine, part of the integration and kind of laying the framework for this analytics-driven culture is to bring those together to get that 360-degree view. Absolutely. We believe that members are members of nationwide, and they think of themselves as members of nationwide. Not so much between one business unit or another, but they're served by the company, and so we really need to focus on making sure that all that data, where they've invested in us by trusting us with their data, is put together in a way that allows us to demonstrate that we know them, that we can care about them, and that in using that, we're easy to do business with. So you've got all these data sources, kind of, I guess you might call traditional data sources that you've been building over the years. What has been the impact of the so-called big data movement at nationwide? Are you looking to work with those types of data sources, outside sources, to serve your clients better, maybe social data to kind of be more proactive in finding issues with certain policy holders who might be airing their grievances on Twitter or wherever? What is the impact, or what is the work you've done in sort of the big data space? So we focus on a lot of data, different types of data sources. Certainly many of them are structured data sources, data about profile, customer profile data, customer preference data so that we honor preferences, data about the experiences that they've had with the company, and then we also are beginning to utilize some data sources like the social stream and to listen to customers and use that in our marketing research and to help make sure that we're responding when there's an opportunity or a need to respond through social media. Our focus is really to seek to understand the customers as well as we can, know them better than anyone else, and then use that information in a way that will help us demonstrate that, because at that moment of truth, the moment when a customer is delighted by service, that's when these big data and analytic investments come to life. And how do you decide what initiatives you're gonna pursue? What is the, do you have kind of a lab model essentially where you're looking for new use cases and you're testing things out with maybe subsets of customers? How do you actually get started with new types of analytics? Because we have a lot of practitioners who watch theCUBE and they're very interested in some of these use cases but really not sure where to get started. That's a great question. And so we focus on seeking to get rapid insights. We use methodologies similar to agile development methodologies where we seek to iteratively answer these questions. And in doing so, we get more rapid insights. Now, if you don't then tie that agile approach to a consistent set of problems to be solved, you could come up with a little bit of a scattered approach to problem solving. So we seek to define a research agenda and that agenda really guides how we execute our research. That agenda in the area of customer analytics where I work is really seeking to understand what are the interactions and that customers engage in or the company engages in that cause retention to be maximized. How can we create the most retention benefit as possible serving our members so they don't have to go and look for other insurance coverages? We also, and that agenda can last for multiple years because it's a very rich area of understanding. It's a complex product and it's one that we seek to really understand. We also have individuals who, based on the knowledge that our partners within the business who've learned what we can do, often come to us to then seek additional areas of investigation. And so we'll work with them to strive and find insights that are gonna drive business for us. GPS data brings some new opportunities for you. You've partnered with Ohio State Police to do bait cars, right? Maybe we could describe that concept which is a very cool idea. And also some insurance companies are saying, hey, voluntarily put this GPS in your car, prove your good driver and cut rates. I wonder if you could talk about those two trends. First of all, what are bait cars? So explain to the audience how that works. Well, so one of the areas of loss in insurance are individuals who are, engaging in fraudulent activities or are in theft rings that cause consumers who are honest and good consumers to have to pay more for their insurance. And so what bait cars do are to help the police catch those rings that are operating car theft or are focused on stealing cars or organized crime that's sort of supporting that. And so we support that through some of our claims safety initiatives. And it's a good partnership with us. Yeah, okay, so the idea is you're putting GPS and audio visual tracking within the car. The thieves don't know which car is a bait car. And so it makes them think twice. And maybe if you can avoid some of that theft then it's good for insurance rates where we operate. And then how about this trend of voluntarily putting a GPS in your car? Some people are concerned that, oh, maybe it's gonna raise my rates. How do you deal with that? What are you seeing as trends there? Well, we see that as a fairly significant trend in the personal auto insurance marketplace. And progressive is really the leader in that space. And others are following closely behind with the devices, telematics devices that individuals can use. And based on their driving behaviors can sometimes, oftentimes get better rates. That's a process where individuals opt in to that product. And so when they do, they are agreeing to demonstrate their driving record and use that. And then that's used in the pricing of the insurance car. So do you expect the model for that will be sort of almost like a pay-by-the-drink, I think a cloud computing, right? Over time, sort of adjust as you adjust your driving behavior, is that where telematics will ultimately take this? Well, we think that telematics is a growing area for us. And one that's, we're just seeing the earliest adopters right now. It will be here for a long time to stay. Yeah, I would suspect virtually that that would be, at some point it won't be an opt-in, it will just be the way things are done. And potentially moving into maybe a real-time insurance, wouldn't that be great where you don't have to pay for insurance in the days you're now using. Oh, your car. That's how you drive, right? You could change the entire industry in really an entirely new way of interacting with customers. So what are some of the more interesting things you're looking to do in the future? We've talked about kind of the telematics data. There's some other areas, to the extent that you can, I know you don't want to tip your hand to your competitors, but obviously you're in a very, very competitive industry. What are some of the ways you're looking to use data in the future that you think might give nationwide kind of a competitive edge? Right, so we believe in taking action on the insights that we develop. And so a lot of the opportunities that we have to identify areas of improvement really have to pass the threshold that, A, the organization is able to adopt those insights and act on them. And B, there's a willingness to do that. So much of our focus in analytics is really to understand and act on those insights. Where we're focused right now is really on retention. We're seeking to move in pretty rapidly into making sure our sales engine is operating as efficiently as possible. And then there's some, of course, there are always opportunities to find ways to improve through continuous improvement efforts using analytic insights to help drive that and become more efficient, making sure that we deliver efficiently with our members and operate at the cost that is as efficient as possible, as small as possible to meet our needs. And let's talk a little bit about IBM. We've seen actually quite a few customers today, both on stage and here on theCUBE. And most of them are talking about IBM as really a partner and less as a vendor. Working closely with IBM to kind of develop some of these new capabilities. Talk a little bit about your relationship with IBM. Not just the technology, but the relationship around actually building these capabilities that are really designed to deliver real business value. Well, we've worked extensively with IBM on the effort to build a 360 degree view of our customers. And that effort is not only in the hardware and software arena, but also in services. And so what we find is that to help solve a problem, we go and find the individuals who have great skills and deep knowledge. These are really enterprise class systems that are being constructed and they have to be available to 24, seven, hundreds of different sites and online. And so you have to make sure that the engineering is really strong. And we found that the effort that we've engaged in really helps when we had IBM help products do that and then the services team help us deliver that. You hear a lot about individualism and marketing to the individual consumer and your models as an industry are generally based on aggregated risk. As you go more toward the individual, how or if does that and how does that change your models of how you approach the business? The model is a really personal one. The pricing, of course, is based on pulling risks and the nature of insurance is that you're paying in so that you're gonna help others when they need it. And if you need it, then someone else has paid in to help you. That process is designed to make sure that you're able to meet those promises when you need to make them. I don't think that that's gonna change. The nature of that product, the insurance product has been around for a long, long time. And what's gonna happen is that increasingly consumers expect personalization. You expect personalization in your phone bill, you expect personalization on your cable bill and consumers have expectations of personalization that just naturally flow into the less tangible service categories as well. And we're seeking to get ahead of that curve and use that as a way to differentiate our value properties. So that's a data opportunity. It really doesn't change your back end business model. I think the business of insurance is pretty consistent and its structure is going to be here for quite a while. One of the things we've been talking more and more on theCUBE, especially given this whole big data theme, is information quality. I wonder if you could talk about that a little bit, specifically from an organizational standpoint, how prominent is the information quality discussion? Who's responsible for information quality? Do you have a chief data officer, for example, or a data czar, as some people like to call it? Well, we recognize that quality is important and quality, there's two parts of quality. There are the creators of data in making sure that we do that with good quality. At Nationwide, we focused on establishing standards for information that needs to be collected and to make sure that's put in places that are consistent with the standards that we define. And then we have to focus on quality of data for the use that you intended to apply an insight or data to an insight. And quality on the usage side is increasingly an important topic. What we find is that sometimes people have challenges in buying into quality. And so we seek to try and explain that as effectively as we can. Quality is one of those elements where an organization who values data will seek to make sure that the quality of that data is high. And we've made really strong strides at Nationwide improving the quality of data, not just in customer data, but across the board. And it's really helping us get better insights and faster insights and delivering that with confidence to those who are making decisions. Do you have a so-called data czar or a chief data officer? Are you it? We are, I'm not it. We are in the process of establishing a chief data officer role. And that should be something that's moving along here pretty soon. Do you think, maybe you can't talk specifically to Nationwide because you haven't decided yet. But I'll ask anyway, will that role report into IT? Will it be autonomous, separate, independent of IT? Do you have any opinions on how it should be organized? We think that data is an enterprise asset and that there's no one owner of data. We actually view that data are the artifacts of the business process that are executed. And therefore, there are many people who are accountable for the quality of that. And we also approach that with this idea that they're multiple sponsors. And so you have stewards of data and different teams or the stewards of different pieces of data. And we have those today. We established them a few years ago. We have stewards of customer data. We have stewards of product data. We have stewards of financial data. And we have, we have stewards of claims data. And those stewards really work together as a community to help make sure that those who are users of that data are served good quality information against which to do that work. So it's a team sport. Has to be a team sport. Absolutely. And so is it, is it, does that function sit within or do you think it will sit within the IT organization? I think it will. The governance data governance role is part of our IT organization. And it's supported by stewards are part of the business. And so that's where we get this partnership. And so that's actually a good point. I mean, where governance sits may oftentimes determine where the CDO fits. It's not always within IT. But when it is, it probably makes some sense. And you sit within the IT organization. I sit within marketing. Within marketing. Right. Okay. So the old bromide, the guys in marketing are going to spend more than the CIO and data. Well, we have a really extensive partnership with our partners in IT and the sponsors of the initiatives that we've talked about today are jointly sponsored between the chief marketing officer and chief information officer, as well as really strong partnership by the business unit presidents who are the ones who are benefiting and taking the risk of making decisions based on insights. Yeah. So the BU president ultimately, it's his or her P and L that's paying for the initiative, which I'm sure the CIO is happy about. They don't want to own that initiative. Right. So we seek to find those who are, are the decision makers? Because the decision makers are the ones who are going to benefit from these investments and make sure that they help sponsor the work. Of course, you have to do it with teams like the marketing team and the IT team to make sure that we're serving our teams effectively. This historically been a lot of tension between the lines of business and IT. No, you can't do that. You know, the whole clock computing comes about and how Amazon's trying to change the world. Swipe a credit card. Yes, you can. Yes, you can. How has that relationship evolved in nationwide? Did we talk to your personal situation between it sounds like you have a good relationship with IT, was it always that way? Did you guys have to go through some growing pains and what do you want to see from IT going forward? Well, the role of the relationship between IT and business is one where, and business defined as marketing or the sales teams or those who are owning the operations is an area that historically, so you could generalize and say is not always the best relationship. We seek to find common ground at nationwide and we seek to define who's accountable for different pieces of parts for their roles that individuals play and then we seek to bring people together. It's a very collaborative organization, the nationwide enterprise and by being collaborative, we're able to I think break down some of those historical barriers that many other firms either have experienced or are currently experiencing. We think that success has many fathers and so that's one way we approach our work. All right, Wes, last question we gotta run. So talk about Eurovision for the analytics group at nationwide, where you wanna see this going over the next five, seven years? Sure, we see analytics and data that supports analytics as really the enabler of executing our corporate strategy. And so we are seeking to make sure that we deliver great insights, ones that can help move the business forward and we do that in a way that's totally consistent with our mission and vision as an enterprise. Our vision is to stay on that path and that path is growing and we've gotta make sure that we're able to keep up. Of course, there are challenges with finding skilled resources and there are challenges with meeting the demands that come from individuals who have problems that need to be solved and our roles make sure that we're able to support and deliver those who are making the decisions in our business to help them drive forward. That's our focus. Awesome, actually, one more question if I may. For the younger people in the audience who wanna get into the data business, what would you advise, what kind of skill sets, maybe share some of your background, what makes a good person in your role, what kind of attributes? So we found that skills are one of the areas where we're concerned. So we need more talent than we have today and we believe at Nationwide that we need to grow that talent. So in 2008, we established a partnership with the Ohio State University to help us define individuals who are skilled in conducting analytic research and really to develop this talent pipeline that will allow us and Nationwide access to resources that are gonna help us drive the business forward. If you're looking at analytics as a career, I would emphasize developing skills in rigorous problem formulation. What I mean by that is strong critical thinking skills. This is not computer science, it's just good strong thinking skills. I'd balance that skill in critical thinking with the ability to communicate and synthesize information. These great analytics that are left on the, that are understood by those who have to use it are likely not gonna have same buy-in as great analytics that are understood. And then of course, there's a strong element of developing the skills to actually be a practitioner to develop those insights in a rigorous way that's going to be accurate. We believe at Nationwide that you have to have skills in computer proficiency and what I mean by that is you're going to have to be able to write some code. You have to have skills in quantitative methods that's statistics and other mathematical approaches to apply to the data. And then you have to have skills in understanding business process. So really at the heart of analytics is an understanding of what is the business that is being executed in your interpretation, how effectively that's working. And those three skills are really the skills that are found in many data scientists. Wrap that with problem solving and synthesis or visualization and what you find is a really well-rounded individual who will have tremendous opportunities to learn and grow and influence organizations over time. Yeah, that's great. I was thinking you were just describing the modern day data scientist. All right, Wes, thanks very much for coming to theCUBE. It was great to meet you. And I really appreciate your time. Okay, keep it right there. We'll be right back with our next guest. We're live in Las Vegas, IBM IOD. This is theCUBE.