 Live from New York, it's theCUBE. Covering Big Data New York City 2016. Brought to you by headline sponsors, Cisco, IBM, NVIDIA, and our ecosystem sponsors. Now, here are your hosts, Dave Vellante and George Gilbert. We're back, welcome to New York City everybody. This is theCUBE, the worldwide leader in live tech coverage. Kevin McIntyre is here, he's the data first strategy leader at IBM and he's joined by Nick Green, who is the director of BI and data management at Dell Hayes America. Gentlemen, welcome to theCUBE. Thanks for coming on. Thanks for having us. Nick, let's start with you. Dell Hayes America, what do you guys do? Sure, so we are a traditional supermarket retailer and so we are in the grocery business and we own two brands that people might be familiar with. One in the mid-Atlantic called Food Lion, which has a rich history and a strong presence in that area. We also have the Hannaford Brothers, which is further north in Maine, outside of Boston. And so those two are banners and like I said, I run data for both banners. I'm at Hannaford at least twice a week. Oh, great, that's great. Malboro Mass. Okay, and Kevin, your role is to help get clients to where they want to achieve outcomes, right? Yeah, absolutely. So I'm part of our global sales leadership organization and what we're announcing this evening around our DataWorks platform, we need a model in order to make our clients successful. So it's not just a focus on the technology, but the process, the strategy, the culture and everything that needs to be in place in order for our customers to be successful. So if I look at, if I want to make an analogy, maybe you want to start working out. You have a goal and you want to either gain some muscle mass, lose a little bit of weight. You can determine, hey, I'm gonna start running, I'm gonna go to local YMCA, maybe I'm gonna go to a really prestigious gym. Maybe you'll get the right outcomes doing that yourself. Running's not all that hard, going to the gym isn't difficult, but a personal trainer that comes in puts a diet plan in place, looks at the specific kinds of workout, the timing, making sure that you're motivated to do that. So Data First is kind of the personal trainer of the DataWorks platform that we are launching. So bringing in that expertise and the strategy and repeatable patterns through workshops and methods in order to help our clients really partner with us as we make them data-driven organizations. Gelhaze was an early example of this process. You guys kind of co-developed it and now you're taking that to market. Can we talk a little bit more about that? How did you guys get started and where did it start? Sure, so we can go back. I've been with the company for going on three years now and actually it goes back to, we wanted to do some experimentation with big data and this was very early on in IBM's kind of cloud journey and especially from a data perspective. And so it all started with, we wanted to really try and do some work around weather and sales information and understand if there's correlations between the two and that was really our first journey into this kind of big data space and leveraging the cloud because we knew as we're in the supermarket business, we're grocery retailers, we're not technologists. So for us to try and stand up complex Hadoop clusters or no SQL databases, whatever the case may be, we really don't have that engineering skill set. And so we wanted to move fast. We wanted to do things in a cost-effective manner. We reached out to IBM because they're a strategic partner and through that we stood up, this was again, before any of this really existed from a commercialization standpoint, we really partnered with them to understand what the offering was that we needed. And what it started with was I went to my client exec and I said, here's what we're trying to do and we have no idea what we're doing. Can you help us? And they really started pulling together resources from all over IBM to help us get that off the ground and we've just evolved from there. And that was two and a half years ago and we've continued to evolve, moved to a number of the different cloud offerings with BlueMix and some of the other new technology that's been rolled out. And at this point, I think we're probably one of the clients who are using most of the technology in the cloud space. And Nick, the problem you were trying to solve is you wanted to understand the relationship between weather and ultimately sales. Yes, exactly. Okay, and what did you find out? What did we find out? That's a secret. Yeah, it is kind of our secret sauce. Give us some general direction. There's a relationship. Well, you know, I think one of the interesting things about this is for us, it was, we have very strong retailers. We have people who understand our business inside and out and what this did was kind of affirm with data what they already knew. So it wasn't like we got these brand new insights. It was a great opportunity to try some new technology. So one of the things we learned is, and this may be revolutionary to everyone, but when it's hot, people tend to buy beer. So that was one of the insights that we had and they tend to stay away from things like veal. So these were two of our big insights that we had. But more from that, it was understanding how we could work with external data, internal data, glean some insights, leverage the technology, understand how to innovate fast within our company. We'd never done anything like this before. We went from just idea and concept to insights in a matter of weeks, which, if we were to try to do this on our own, it would have been months if we were lucky. Well, the interesting thing about that example is it's external data. It's weather data. The famous beer and diapers, I don't know when that was from the original data warehouse example, but it was- Yeah, for hurricanes. No, it wasn't just- No, that was- It was guys who run out to buy diapers, grab a six-pack or whatever. And so, but that was mostly internal data. The world has changed. And so, okay, so what about the process around that, the people and the process side of that? What did you learn from this experience? Well, I think what's really great about the relationship we've had, and I think Nick's right, we have been working together for, I think a little over two years at this point, is that it just wasn't success in one area. I mean, that's a great application where they were able to look at that data and validate patterns or understand kind of the relationship between sales and weather. But we've also been able to work with them on new systems of engagement and new web and mobile applications for how their end users interact with their brand and really kind of come to work with their haze. And then also providing kind of next generation analytics around customer loyalty and then looking at other unstructured data. So what we're doing with Data First is that ability to be very tactical with the problem. Maybe we need to better understand how we're going to engage with our clients with the new system of engagement. So there's a problem and a specific outcome to that. So with this Data First method approach is helping them put together that executable plan to get them from where they are today to where they want to be in the future and understanding everything you need to know about getting there. The data movement, the security, the interaction, quantifying and qualifying the business value that comes out of that. So not just talking about feature function product, it's what is the process to make this a success for you as a client. And I think we've had tremendous success in being able to do that with Dell haze across different projects and now with them embracing our technology and being kind of this cloud first data-driven organization and thermarchy client for us. So with that experience we've had with Dell haze, we need to be able to really kind of package this up, put some structure and operationalize this method so we can work with hundreds and thousands of clients globally. And what I think is really exciting about this too is that I'm focused on making sure that we're not just bringing the IBM point of view to technology and becoming a cognitive business. We want to have kind of a community effect here where we can work with other partners both within IBM and outside IBM so they can bring in their credibility and their expertise in helping our clients become successful on this journey. So to start with a whiteboard and a bunch of people, who do you invite? It started with a mandate from the top. But really it was one of the things that we try to do is with IBM because again we see them as our partner is really we talk about business problems. We don't talk about technology. We go to them and say, look, this is what we're trying to solve from a business standpoint. And we have multiple use cases like that that we've implemented. And when we go at it from a business problem standpoint that may incorporate multiple pieces of technology, a single piece of technology, but it's about having an end-to-end solution. So when you think about an enterprise like ours or any company that has kind of grown up in a traditional, you make these capital investments, you depreciate those over five years and you do these sorts of things. Moving to the cloud and doing some of the things that we're doing now takes a dramatic shift. And I think just even from a financial perspective it's very different than how you used to operate. You would build this big business model in a business case with this ROI, make this huge capital expenditure to bring in the technology, struggle for months to try and get it stood up and then you hope to get the benefit out of it. What we're able to do now is really cut that cycle down and we really focus on what's the problem. We remove the technology piece from the equation because we just say, look, we want this on demand. We want to be able to stand this up when we need it, answer our problem and then see if new problems arise or we spin it down and we're good to go. So it's really changed the dynamic of how we really go to market with our partners. What was the mandate from the top? Was it accelerate cycle time? It's really what we've seen as a business is really a transition to thinking about data as a key strategic asset. So for us, I would say when I joined the company we really shifted from data being an afterthought to whenever we're embarking on any type of strategy we want to one use data to understand how the strategy is performing but also figure out where do we want to go strategically? So we really started thinking about data first and thinking how do we incorporate data, how do we utilize this asset more effectively? And that's really where my role started and so for me it was how do we get speed to value quickly? How do we get the outcomes, not focus on the technology? And that's really been the evolution. So it was understanding, you had an understanding of how you make money. How can we enhance that with data? It really was the task, okay? I'm curious about over time how the mix went from consulting with IBM about outcomes towards having internalized the process of that consultation into repeatable technology. In other words, from a pure consulting engagement where you went to them with a request for an outcome to when you could take problems internally and say, oh, we know how to solve that based on all the experiences we've had. Yeah, well I can say one of the things that we're exploring now is we've been working with big insights in the cloud and we've been working on a supply chain project. Well, one of my leads who's running that is seeing multiple opportunities to leverage that platform beyond what we're currently doing. Now, obviously being in the tech space, big data has been a hot topic for a few years now and there was no way that I could go to both my business leadership and IT leadership and say, hey, I want to spin up a Hadoop environment and they look at me and say, for what? What we did is we saw a business problem and fit that business problem to the technology. Well, now that we have the technology and the capability in-house, we're learning as a team, we can understand how to use that same design pattern to address other business problems that are coming up or on the horizon and so that's how we're really leveraging the platform. We've done the same thing with the cloud and no SQL platform and we're doing that over and over again where we're seeing, we're using IBM to really understand how to get the technology up, how to start leveraging that for a very specific use case but now it's in our portfolio and now we understand how do we continue to expand that capability. Do you measure your maturity in terms of, I don't know, maybe the cycle time from initiation of project to completion of project or do you measure based on perhaps how much external skills you need to source to get it done? I think my boss would like for me to do that. I think for us what we're focused on is really just getting faster at turning around a solution to our business. Moving away from the challenges, the real engineering challenges of standing up a new database, there were times in this company or in other companies where it would take months to stand up a new database. Those are months that I'm not getting business value to my business partners. If I just simply remove that from the equation and focus on the business value, that's speed to market, that's speed to value, and that you can't really put a measurement on that because what we're really doing is shifting how we think about how we do projects. We've gone from a great example when we were redesigning foodline.com, we used our Cloudant database as the back end and we have project managers who would say, okay, we're working on the plan. How many weeks do you need to stand up the instance? We say it's a matter of minutes. All we have to do is contact our partners and they really could not understand, okay, then what do you have to do after that? That's it, it was an email. So it's changing how we think about planning, how do we think about execution, 100%. When you guys started working together, like who's involved? Who did IBM have to bring to the table and who did Dell Hayes bring to the table? What type of folks? There's more than IT people, obviously, and can you describe that? And so typically when we're kind of starting on a new project, there's a new business challenge and some outcome that Dell Hayes or any other client wants to achieve, it's really important for, I think, everybody to be aligned from the beginning. And when I look at it for what's gonna be a successful way to get started, you need to have your business users who is responsible for that outcome, who is going to get value from that outcome, someone who's technically going to deliver that and facilitate that outcome, and probably an architect who understands kind of the existing kind of lay of the land at that organization. And IBM brings in there our enterprise architects as well that understand how our technology all works together. We bring in a business value consultant who can speak the kind of the lingo of the business value, understanding kind of industry specific imperatives that are important to that organization and some technology experts. So we're able to understand, hey, this is the challenge you're facing today, this is where you want to go and we're gonna help you be put on that plan in order to get there through quantifying again the business value, understanding that outcome and being mindful of everything that needs to happen in order for that to become a reality and bringing kind of those repeatable patterns of deployment. So if they're looking at a new project where it's gonna take technology X, Y and Z to make that a success, well we can look where we've been successful in the past with other customers and hey, we've worked with technology X, Y and Z, this is how it's done, we've done this before, we've been successful, so put that to the side and we're gonna focus on the other things that's gonna make this really kind of come to life and drive the outcome that you're looking for. And it is about being data driven and insight driven and the fact that Del Hayes is looking at data as an asset and that is really what's gonna help them make better decisions and how they're going to engage and make money from their clients is just they're a great customer to work with because not all customers have that mentality and it's just been a great partnership. And Nick, this happened predominantly at Del Hayes America HQ or did you have samples that you brought in from the stores or retail locations? It was pretty focused on, we're a shared service within Del Hayes America but we have very tight partnership with our banners and so actually the president of Foodline was one of the sponsors for a lot of the work that we were doing from a data perspective because she has such a great understanding of the value of data and so she and I work very closely together. It was really through her that I got great insight on some of the big business challenges and then we kind of bring those back and say how do we best solve that? How can we answer those questions quickly? How do we build platforms that allow us to iterate really fast? So she had skin in the game. Oh, absolutely, she still does, absolutely. All right gentlemen, we have to leave it there. Thanks so much for coming on theCUBE. Really appreciate it. Thank you, thank you. All right, keep it right there. Everybody will be back with our next guest. We're live from New York City. This is Big Data NYC, data week strata plus a dupe. Right back.