>> Live from San Francisco, it's theCUBE. Covering IBM Think 2019. Brought to you by IBM. >> Welcome back to Moscone North, this is IBM Think 2019. You're watching theCUBE, I'm Stu Miniman, and we're going to dig into a segment talking about the cognitive enterprise. And helping me through that, I have one returning guest and one new guest to theCUBE, so furthest away from me, the returning guest is Jesus Mantas, who is the managing partner strategy for the digital platforms and innovation in the IBM Global business services. Jesus, welcome back. >> Thank you >> A little bit of a mouthful on the title. And Mani Dasgupta, CMO of the same group, the IBM Global business services. Thanks so much both for joining us. Alright, so cognitive enterprise. We're going to play a little game here first. Buzzword Bingo here, you know, can we talk about, what cognitive is, where you can't say AI, ML, platform, or enterprise in there. So do we start with the CMO first? >> Sure, I can go. Cognitive enterprise, those are two bing bing right there. What's your core competitive advantage, is what I would say. As a company, do you know why you exist? And once you get to that, how do you then take it to your clients, in a way that would help you grow, and sustain growth in the future. That truly is the future of a smart business, what we call the cognitive enterprise. >> So, Jesus, data is something we talk about a lot, at all the shows, we hear all the tropes about it's the new oil, the rocket fuel that are going to drive companies. You've got strategy and innovation in your title, I'd love you to build off as to where this cognitive enterprise fits in to those big trends of AI that we were talking about. Jinny was just on the keynote stage, talking about Watson, talking about all those pieces, so where does that fit with some of these megawaves that we're talking about. >> I think it's the way that we define this new, smarter organizations that use data to the fullest extent. And I think the way that we define it is, one is this reuse of data, your own data, the external data, and the way you aggregate it, the way that you apply AI or other things to use that. But the technology itself is a means to an end, it's not the end, so these organizations change the way the work flows, and they also train people to make sure that they understand how to operate in a world where they have more information and they can make better decisions with that data that they could before. All of that is what we are labeling. It's more than digital, it's more than AI. It is this concept of a cognitive enterprise. It's a smarter way to do what a company does. >> Okay, I'd love if you could give us a little bit of a compare, contrast. You know, the wave of big data was, there's massive amounts of data, we're going to allow the business practitioner, to be able to leverage that data. Was a great goal, unfortunately when we did research, at least half the time it wasn't really panning out there. Doesn't mean we didn't learn good things, and there weren't lots of great tools and business value generated out there. So, give us, you know, what's the same and what's different, as to this new wave. >> This is how do you make that data work for you, really. It is about, when you talk of data, you think of data that's out there, but 80% of the data today, is owned by you. And by you, I mean a business, right, you own your customers' data, you know your customer better than anybody else. So what do you really do with it? And we are at an inflection point right now, where these technologies that you just talked about, be it blockchain, be it internet of things, be it AI. You can truly bring the power of these technologies, to start making sense of that data that you own, and use it to create, what we call, your competitive advantage, your business platform. So, think about it, I can break it down. Would you just be a retailer of clothes? Or, would you be a fashion expert? And which one would have long-term success for you? Or if you think of a completely different industry, would you be an insurance provider, you sell insurance products, or would you be a risk management expert? That decision to be who you want to be, is really at the heart of the cognitive enterprise, and what we are proposing to the clients here. >> Alright, help frame for us your group, where that fits in. IBM sells hardware, software, has a huge services organization. What are the deliverables and the services and products involved in your group? >> Sure, we are the services organization of IBM, and one of the core reasons why we exist is to help our clients solve their toughest business problems. And so, if you think about it, you think about it as different puzzle pieces, but they don't quite always fit together. We exist to sharpen the edges, to sometimes round the edges, make it customized, make it right for you, so that at the end of the day, you're able to deliver results for your customers and be closer to them than ever before. >> The balance we look at in this multi-cloud world, it'd be nice if you have a little bit more standardization, but of course we know when we talk with businesses, every company is different and is challenging. So, where are the architectural engagements? What are the design criteria? Where is some of the hard work your group gets involved in? >> Yeah, I think we've been spending a lot of work and a lot of time on understanding how to get clients, most clients have done a lot of experimentation. But they rarely figured out how to get that experimentation into real production, at scale, with impact. So that's where we've spent a lot of the time. Fundamentally it has to do with, not only understanding Agile as a method, but being able to combine that with taking that journey all the way through to production, actually integrating with compliance requirements that, if you're in a regulated industry, you have to do, and do that in a way that doesn't become a digital island. I think what we have learned is, when companies see this big divide between, that's the legacy world and that's the new world you can never put those two together. So we came up with this concept of IBM Garage, which is the way in which our team, the services side, can actually bring it all together, and it gets massively enhanced and improved, with technology like containers, like Kubernetes, because now you can actually open up architectures, without reinventing them, and connect them with new technology, and do that synchronously. So you can basically be modernizing your legacy, you can be creating new innovation, in the form of new platforms, but you can do it at the same time, and as you do that through cycles, you also change the skillsets that you have in your company, because if you don't change that skillset, you're always going to have a problem scaling. That's what we do, that's what we help the clients do. >> Yeah, skillsets are so critical. Something we've been hearing over and over is, that whole digital transformation, this isn't some 18 to 24 month going to deploy some software, bring in a lot of consultants, they go and do it, hopefully it works and then they walk away. We're talking about much faster time frames, usually agile methodology, talk about skillset-changing. How do we help customers move fast and accelerate, because that's really the faster, faster, faster, it's just one of those driving things we hear. >> I was talking to one of the clients this morning, and what she said is, it's so helpful to have a framework, just to know where to start, and also to know, sometimes it's there in their mind, but they want to see it in front of them, how to break a problem down into smaller components, so that you can get to value faster, so we have actually a seven-step process, of the cognitive enterprise. So we start with, what is your core platform? In fact, Jesus coined this term, he calls it the digital Darwinism. Do you want to talk about the digital Darwinism, Jesus? >> Yeah, I think it reflects very well this urgency. In the analog world when most businesses are based on how clients choose you based on proximity, based on convenience, based on brand, based on trust, based on price. Even if you're not great at it, you have enough friction in an analog world, that the clients will keep coming. All of us and more of our things that we do every day, are in our phone, and they are digitally accessible, all of that friction disappears, and what happens then is, the people that are very good at something becomes, everybody goes to them, and the people that are not the best. I call it, they either thrive or they die very quickly. So in the digital world, being really good at something is a lot more important than in the analog world. You can survive being average in the analog world. Once you get to the digital world, it's transparent. Everyone will know, you're the best, you're not the best, and nobody would pick you if you're not the best, so it's really important to reconfigure yourself, and understand the trust and your brand, understand how digitally you translate what you are, and then make sure that your clients will keep choosing you in a digital world as much as they were choosing you in an analog world. >> I tell you, that resonates really well with me. The old line you used to hear is, if you want to get something done, give it to someone who's really busy, because they will usually figure out a way to do it. I spent a handful of years in my career doing operations, and what I did when I was in operations, when I talked to people in IT, is tell me next quarter and next year, do you think you're going to have more or less work more data to deal with, more thing thing, and of course the answer is, we all know that pace of change is the only thing that's constant in this industry. So, if I don't figure out how I automate, change, or get rid of the stuff that I'm not good at, we're just going to continue to be buried. Are there commonalities that you see, as success factors or how do you help measure, what are some key KPIs that customers walk out of, when they go through an engagement like this? >> Yeah, just carrying on from where Jesus left off, the second step is very close to what you were just saying. It's about the data and how you're using that data. So some of the key success factors would be, what is the output of it, and it's not in the proof of concept phase anymore. It is real-time, it is big, people are doing it at a grand scale. I think, Jesus, maybe we take it through the seven steps, and then the key success criteria comes right at you, right after that. So after you do the workflow, after you do the data for internal competitive advantage, we go to the next step, which is all about workflows. You want to talk a bit about that? >> Yeah, I think one of the advantages that artificial intelligence brings to companies is, the fact that you can now, I mean as a human, there is only so much data that you can ingest. There is a limit, and most businesses try to optimize what that is and how you make decisions. But, artificial intelligence becomes this aid that will read and summarize things for you. So now you can take into account, into workflows, massive amounts of information, to optimize, or even not having to do things you had to do before, at a scale that, as a human you cannot do. This idea of inserting AI into workflows is the real idea. I think we talk a lot about AI as a technology, but that's just a means to an end. The end is a workflow that is embedded with blockchain, with AI, with IOT, and then people that are trained to engage with those workflows, so you actually change the output. And I think that's the big idea, that step of, it is workflow that is embedded with AI, it's not just about the technology, it's the combination of the main industry, and the technology that actually creates that >> And where does it sit, right? Where does it sit? Your tech choices, the architecture choices are also important. And we joked about this, like if you really like Netflix, and you're watching something and something is coming up after three seconds, how does it know what you really like? But it does, but think about this. This wouldn't be possible on a 1950s television set. So you've got to think about what's your tech platform of choice, how do you upgrade that, and what's the architecture look like? >> I want to give you both the final word. Lots of users here at the show. What are you most excited about? Give us an insight on some of the conversations you've been having already. >> Amazing conversations so far. The really aha-moment was, people really like to share within their peer set, so this morning I was at the business exchange, and people were having conversations, but just to bounce it off someone, who is facing the same issues that you do, across different industries, was a really aha-moment, and we have the IBM Garage actually right behind us on the other side of Moscone. We set it up so that clients can come in, and unpack their problems, and we helped them think it through, used design thinking, help them think it through. We are hoping in the next couple of days, we get lots of brilliant ideas, come from the sessions like that, and really putting the customer at the core of what you want to do. >> It's a recurring theme of all the client conversations, this idea of, they all want the speed and agility of a startup at the strength and scale of an enterprise. That's what they're asking us, as the services organization of IBM, to do is, help us not just experiment, that was good before, not good enough now. Help us do that with agility, with new technologies, but we want it to mean something at scale, globally implement it, create an impact. And I think again, the way in which hybrid multi-cloud can play into that, the way in which IBM Garage can combine the legacy world with the new world and moving people into new platforms is a really exciting method and approach that is resonating a lot with clients. >> Really appreciate you both sharing updates and absolutely as you painted a picture, just as in 1950 we didn't have the tools to run Netflix, now in 2019, we have the tools for customers to be able to help build the cognitive enterprise and not only test but get into real-world deployment at a speed that was really unheralded before today. Thanks so much for joining. We'll be back with more coverage here from IBM Think 2019. I'm Stu Miniman, and thanks for watching theCUBE. (upbeat techno music)