 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 Peter Burris. We're back, Gothen Villapa is here. He's with Capgemini, he's the Big Data Integration and Analytics Lead, leader at Capgemini. Welcome to theCUBE. Thank you, happy to be here with you. So, a lot going on this week at Big Data, you guys have one of the top SI's consultants in the world. What are you seeing as far as the transformation of organizations that become data-driven? What are some of the drivers that you're seeing out there? That's a good question, sir. A couple years ago, we started on this journey at Clatter about four years ago. When we started this journey on LinkedIn, you saw the poster that said Big Data's like teenage sex, everybody talks about it, nobody does it, right? The reality has shifted considerably. So, while the technologies evolve considerably over the last four years, the most important thing is most of our clients are feeling pressure from the disruptors in Silicon Valley. You see the Airbnb's and the Amazons and the Google applied pressures on traditional industries that didn't exist before. For example, a lot of our auto clients don't believe auto clients are the biggest threat, they believe Apple and Google and Amazon are the biggest threat, right? Because what our clients are afraid of, the incumbents that traditional companies are afraid of is they don't want to become a commodity manufacturer of components for a software company. They don't want, for example, GM manufacturing apart that Apple's putting the wrapper around selling and making the margin on. So, more and more tech is driving the industry to where GE made the announcement they no longer want to be known as an engine manufacturer, they want to be an IT company. Or a financial services firm. Or a financial services firm. And you see the same thing in pharma as well. We see the pharma companies don't want to be known as manufacturer of med devices, they want to own the service industry, move up the value chain and secure the revenue stream. So that's what's changing the industry as a whole and then big data central to the strategy of data-enabled transformation. So it's like the death, what was the article we saw yesterday who wrote that? The death of tech, it was Rob Thomas. The death of tech companies, it's now the rebirth of all companies are tech companies. All companies are tech companies and that's the future of all companies to be a tech company. And move from selling commodities to selling services and having invested interest in the outcome that the clients receive at the end of the day. Yeah, I once wrote a piece many years ago that suggested that we would see more non-tech companies generate SaaS and cloud applications than tech companies themselves. And while it still hasn't come true, there's evidence on the horizon that it very well likely will be a major feature of how companies engage their customers is through their own version of SaaS or deploying their own clouds for their own ecosystem and you can go back 30 years, 35 years and look at map top for example and the promise of what it meant to define and deploy standards that could integrate whole industries around data hasn't happened but we can see it actually happening on the horizon. What industries? You're still looking at things through industry lenses, right? Where do you see it happening before it's happening elsewhere? So the first place that happens naturally is tech because there are closes to it, right? To give you the classic example, I can go anywhere and buy an office license today. I have to subscribe to office, right? So what has done to Microsoft, it's changed the fundamentals of the balance sheet from selling perpetual licenses, getting revenue once and then having the prospect of not having a customer later to selling it over sustained period of time. So moving from one time revenue hits to perpetual revenue. So tech is where it's starting off. And even in tech, we're actually pushing the boundaries by working with some of our providers like Cloud Era and some of the other providers out there to move from a perpetual license model to as a service model. So what this enables people like us to do is to offer as a service to our customers because our customers need to offer as a service to their end users as well, right? So just like I gave you the example of GE because it's public knowledge, they wanna move up the spectrum of not selling an engine but leasing an engine to an airplane manufacturer and then owning the service's revenue on it, right? So when Delta, let's say that's leasing the engine is no longer owning a commodity, they're becoming asset-light, right? The companies like GE and other companies, when they become tech, they need to become asset-light as well, which means not owning the land, being burdened by land labor and capital, but as they get paid for outcome, they wanna pay for outcome as well. But somebody's gotta own the asset eventually. I mean, this is not a game of musical chairs where the asset owning music keeps playing and then it stops and somebody's got all the assets. Exactly. How do you see the global sense of how organization, how is this gonna get institutionalized? Are we just gonna have a few companies with enormous assets and everybody else running software? How do you think it's gonna play out? Good question. So Jeff Bezos was at a manufacturing company outside of Ireland recently and he pointed at an antique generator sitting next to the plane and said, back in the day, everybody had a generator sitting next to the company producing electricity. But today we have a big distribution plan and we get it off the grid, right? So to your point, yes. We see the scale and the price reduction coming from a few companies owning those pieces of assets. For example, it's almost impossible to compete with the Amazons and Googles of the world today because of the scale that they receive and the customers get the benefit of that. Similarly, you'll see the software, right? So software, you see the software companies owning the assets and title and leasing it back to the customer. So to your point, yes. We're moving to a model where it's more scalable and the price efficiencies that have passed on to the end consumer. So it has historically, in a more asset-oriented company, historically, if you take a look, for example, at Porter, Porter competitive strategy. So Porter would say, pick your industry. Where an industry is a way of categorizing companies with similarly procured and deployed assets. So you had, you know, Elmobile had a collection of assets and Hotelery had a collection of assets. So pick your industry based on your knowledge and what kind of returns you like it to get. Pick your position in that industry and then decide what games you're going to play using the five factor analysis that you did. But it was all tied back to assets. So if the world's getting less asset-oriented, hard assets, how does, what does that do to competitive strategy? It's a good point. So the hard assets are getting commoditized. The value comes in what you can build on top of the hard assets, which is your IP, right? So the soft assets of IP and software is what, it's where the value is going to be. So there's a lot of pressure on hard asset companies, like, you know, you see many companies getting up the server market because they can't compete with the Amazon and the Google. Right? Because they can wide label and manufacture all this stuff. The differentiation is going to come in the software. That's the reason companies like GE and the other pharma companies and automobile companies want to become tech companies because that's where the margin is, that's where the differentiation is. It's no longer in the tangible hard assets, but it's in what you can do with them. Well, and it says data is going to be one of those differentiators and the big assets. So what, so everybody in theory has to become data-driven, maybe in fact, has to be data-driven. Data is their asset, is the differentiator. You've pointed out many times, all this digitization, it's data. Digital equals data. So our basic proposition is that increasingly the whole notion of being a digital business is about how you differentially use data to create sustained customers. So let me build on that for a second and say that there's this term in economics known as asset specificity, which essentially is the degree to which an asset is applied to a single or limited numbers of uses. Programmability reduces asset specificity. So if we go back to the airline engine example, GE added programmability to an airplane engine and was able to turn it into a service. Uber was able to add programmability to a bunch of consumer cars and was able to turn it into a ride-sharing capability. What does that say about the future of an industry-oriented approach to conducting business if I am now able to reconfigure my asset base very quickly and the industry is based on how my assets are reconfigured? What does that say about the future of industry? So in my opinion, I don't think the future of industry is going to change because you're still going to have a specialization based on the domain you're selling through and the expertise that you have. So it's a customer-focused industry definition, it's not asset-based industry definition. The hard assets are going to get commoditized and get moved out to a few specialty players, but the differentiation is going to be on how you serve the customer and the type of customer that you serve. So what are the headwinds you're seeing in terms of customers getting to this data nirvana? What are the challenges that they're facing? So Peter Drucker is, there's an attribute of Peter Drucker but regardless of who said it, culture eats strategy for breakfast, right? So we work with retailers all the time who understand that they face an existential threat from Amazon. However, that culture prevents them from being like Amazon. It prevents them from experimenting, it prevents them from failing fast, it prevents them from acting together. For example, a lot of our customers want to have an omnichannel strategy, right? It is a seamless commerce strategy, but then they have a silo for the stores, they have a silo for the call centers, they have a silo for the web, but they don't act together. So culture is one of the biggest barriers we're seeing in enabling that journey. Tech, we know the tech works. Two years ago we're doing technical POCs, today we're not anymore, we know the tech works, right? So get over it. So it's a culture and the attitude and the ability to change how you go to market, that's to me the biggest challenge. But is it also financed because hard assets still are associated with a rate of amortization, depreciation, and out utilization. There's expertise and whatnot built up around that and this becomes especially critical when you start thinking about the impedance mismatch between agile development and budgeting, for example. So how do you anticipate that not only culture has to change, but also the way we think about finance or is financing disciplines end up being part of the culture? So you're absolutely right. So financing discipline has to be part of the culture. To give you an abstract example, back in the day when we did a data warehouse or a data project, we do a huge, let's say for lack of an argument, $10 million project. Today we're doing 40, 50, 50,000,000 projects, right? So agile has gone from fixed scope where you laid out a two-year project with an end in mind and by the time you achieve that end the requirements have changed and the business has moved on to achieving small objectives. So we're consuming it in chunks. You're going from fixed scope to a fixed budget. So I've got a certain allocation that I need to use and I prioritize it on a regular basis on how I want to consume that basis that I have. So it's almost a subscription. Are you going in a basically almost a subscription basis going to a customer and saying, here's the outcome. We will achieve that outcome over a period of time. You'll sign up to achieve that outcome over a 12 month period and we'll consume that budget in 12 month increments? First and second, in any given period you can reprioritize the outcome that you want to achieve. So during the journey for 12 months if you realize something new, you have the flexibility to change, let me take out this chunk of work and do something else so I have the flexibility. So you can redefine the outcome. So it's almost like, I don't know if you call it this. I'd be interested to know what you guys call it. But it's almost like a subscription to outcome business model. Exactly. Service as a service. We call it sprint as a service. The service as a service. We call sprint as a service is our defined model of how to go to market around that is we know to sprint ahead what we're going to deliver. Everything else is indicative, right? Because not everything that we do has to succeed. That's a mindset change that our customers need to realize. We believe the biggest reason clients fail is because failure is not an option. It's that they put so much behind it when they fail, it's catastrophic. Because careers fail and not the project fails. Exactly. You have a saying failure equals fire mentality. That's the culture that people refuse to fail. Until it's catastrophic, right? So I was having a conversation last week at Oracle Open World when theCUBE was there, great show, and had a really good conversation with a good competitor of yours who talked about how they were going to use machine learning in the contracting process by sweeping up all kinds of data and that would help them actually define the characteristics of what they were going to deliver, how much work was going to take, how much labor, what are the resources, and that they were able to again get rid of the $500,000 to $5 million part of the assessment or the assessment part of a deal, drive it down to $50,000 or less and in the process come up with contracts who are much more customer friendly. What other types of changes are happening in the services business as we do a better job of packaging intellectual property, whether it's this services of service or service subscription or whatever you mentioned, or even thinking about machine learning being applied to the contracting process. Sure, sprint as a service. Sprint as a service, sorry, thank you. And you asked a number of questions. The first thing, let me talk about machine learning and human task automation. So one of the biggest things we're doing today is learning to understand and automate human tasks. One of the biggest things we've seen supply chain companies, for example, is they don't have enough planners, right? So you hire a bunch of planners, you have different variations and skills. So we're taking the top 5% of planners, automating what everybody else does and letting them handle exceptions, right? And workforce automation and in many of those areas we're beginning to automate human tasks and letting the humans handle exceptions that a machine cannot handle. So machine learning is becoming fundamental to everything, not just contract negotiation, but actually enabling companies to scale in areas where they could never scale because they never had enough people to do it. And we're not just doing it externally to our clients. One of the things we're doing internally is we don't have enough big data developers. So we're beginning to use machine learning to automate a lot of our tasks that developers will do, industrialize a lot of it so we can scale in our delivery approach as well. Excellent. So come back to this event. You guys are here, you're on the floor. You know, we've been talking all week about, you know, Hadoop is kind of, you know, yesterday's news. Yes, yes. What are you guys seeing? Well, you know, because you got the, you got a big chunk of customers that said, all right, we're going to invest in Hadoop. We have the skill sets. And then a big chunk of them said, I'm not going there. And now they're sort of looking at new ways, whether it's cloud, whether it's smart. And a big chunk of customers just say, I do want to go there, but I'm having problems getting there. Yeah, right. We've got some serious challenges. So what are you seeing there and how is Cap Gemini helping them? Cool. So we did an analysis with Forester and one thing we'll say that 100% of our clients are going to Hadoop. It's not 95%. So everybody's going to Hadoop in one way, shape or form. Whether you go with the traditional distribution, go with an Amazon, Azure, whatever, everybody's going to Hadoop in some way, shape or form. Right. To address the reluctance, we spoke about the uberization of the industry, which is you have a contract, which is an outcome-based contract. So we go to our clients who have fears about moving to Hadoop and say, we'll take the risk, right? Let's write an outcome-based contract to move you guys into the new, because you know you need to go there. You're afraid to go there, so we'll take the risk. We'll shift the risk over to us and we'll move you onto Hadoop. The last piece is industrialization. So back two years ago, we designed code for every little thing that we needed to do. Today, we've automated a lot of our code generation from existing systems, from knowledge we've gained, including machine learning, so we're able to mechanize a lot of that code. Frankly, we did it because we had a developer shortage, right? So we started industrializing a lot of our IP assets and our learnings, but this is also helping our customers move on to the new world. It's improved the quality of a delivery. It's improved the velocity of a delivery. It's reduced the price, we're much more competitive. To give you an example in the BPO space, back in the day, we did labor arbitrage, right? But more and more, right? Like with our clients who use manual auditing, we're using machine learning to automate a lot of that. And that more than pays for the cost of Hadoop, right? So to answer a specific question, gone are the days of, hey, I want to get into Hadoop. The question is what business value can I achieve? How fast can I achieve it? And if you're afraid, can I take the risk for it? In that business value, historically, if I can use that term on such a nascent industry, but has been, the ROI has been a reduction in non-investment, right? I'm gonna lower the cost of my enterprise data warehouse. That was two years ago. Okay, so what is it today? Today it is, how can I reduce your marketing spend? How can I optimize your marketing spend? How can I improve the accuracy of your supply chain planning, right? So it's more in terms of directly delivering business value versus the cost reduction. Many of our clients say the cost reduction is irrelevant. Frankly, because a business case is so huge. To give you an example of one of our supply chain clients, their fill rate for orders is 60%, right? Which means they're a big manufacturer, they're only able to fill 60% of the orders that come through. That's because they're not able to plan where to deploy product and so on and so forth, right? So if you increase it by 5%, it's a $300 million annual business case. My $2 million data warehouse optimization, it's relevant, it's peanuts in a $300 million annual business case, right? So it's things like that that's helping machine learning and Hadoop evolve in the ecosystem. The cost reduction play is just a way to slide the infrastructure in it. You can do a lot more with it. When you're selling to CIOs and business leaders, that resonates. Yeah, absolutely. Great, we'll have to leave it there. Thanks very much for coming to theCUBE. My pleasure. Pleasure meeting you. All right, keep right there, everybody. We'll be back with our next guest. This is theCUBE, we're live at Big Data NYC. Right back.