 Live from Las Vegas, it's theCUBE, covering IBM Think 2018, brought to you by IBM. Hello everyone, welcome to theCUBE, I'm John Furrier. We are here in Las Vegas for the CUBE coverage of IBM Think 2018, it's theCUBE Studios live coverage, all day long, three days our third day, our next guest is CUBE alumni, and he chooses as the general manager of Watson, customer engagement, I've been on so many times, I don't know, eight, 10, a lot, you're a VIP, great to see you. Thank you, good seeing you John, I'm really enjoying hanging out with you guys. So we'd love to hear what you're up to, because you always have your finger on the pulse here at IBM, take a minute to explain the group that you're in, Watson customer engagement, that's kind of a nice bumper stick, but there's a lot to it, you're doing now. There is. It's large, it's got billions of dollars in revenue, give us the numbers, run the numbers for us, size, people, products, all in 30 seconds, now go. It's an exciting space, so Watson customer engagement is really the Watson business applications that are relevant for marketers, merchandisers, digital commerce leaders, as well as supply chain professionals. So my team really develops the software, both for on-premises and SaaS, for everything from digital marketing experiences, personalized marketing, campaign management, to managing next generation of interactive sites, and shopping sites to understanding customer journeys and journey analytics, supply chains, and BB collaboration, so it is a pretty broad breadth of about 21 solutions and offerings that span many industries and many countries. Well, you have your hands in a lot of great stuff across the board, but I think the big news today was the blockchain announcements. You guys feature a solution on stage, this is hard news, so explain, talk about the hard news, you have an announcement, it's on stage, it's blockchain related. Yep, absolutely. So my team has been working on creating more analytics in our supply chain solution. So one of our solutions is called supply chain insights, which really is about adding visibility to disruptions and being able to apply analytics to, let's say, management response, incident management, then we're thinking about our supply chain business network. So that is a separate offering that we have, which is about 6,000 clients are on it, with 400,000 trading partners. We do 8 million transaction documents a day in terms of this trading network. What we did was we announced a shared visibility ledger for any of our clients and partners in the supply chain business network. So we're adding blockchain to that as a way to ensure that transparency, as well as speed of operation. So we're really excited about it. And security, huge. So supply chain, blockchain, value activities, all this stuff, this is where blockchain shines, because this is a core competency of IBM for generations. I mean, providing applications for value chains. And so this is interesting. So just to get the clarification, the product is on preview. Yeah, it's a technology showcase that we're doing right now that we prototype and we're going to make it available as an offering that's called shared ledger for any client that's actually on our supply chain business network today. And what's in it for them? How do they implement it in the vision of the product? They already have a product. They bolt it on, just a new offering. Yeah, so if they already have it, they'll get access to, let's say, a visibility layer. So the shared ledger will allow you to see where in the process your transaction document is. So let's say you're in the area of consumer and merchandising and moving goods in transit. So knowing when a box actually left a particular warehouse, is it in transit or not? And did it actually deliver on time? There's a lot of parties involved in all of that. And paperwork and manual process, data entry. You got it. Now you have the actual stamped records of who's touched it when and whether or not with IoT instrumentation too, of when things have moved or not. So this brings up the conversation we've been having on theCUBE around the inefficiencies now going to be abstracted away with things like blockchain and AI. Yes, absolutely. Use cases that you're seeing that jump out at you'd like to share that can highlight that and also the AI side analytics that's your wheelhouse. Blockchain's emerging. This is the innovation sandwich. AI on one hand is bread and then your blockchain and data's the meat. Well, you know, especially in areas like supply chain where small bits of optimization, meaning a 1% improvement or resolving invoice and settlements have such huge ripple effects downstream. So there was a great example in terms of our maresk work and global trade and blockchain is food shipments in particular and food safety and being able to resolve the source of where the original food, whether it was grown or harvested and being able to do that in seconds, not weeks, right? Going through that paperwork. So there's huge opportunities there. We've, we're excited because we're now adding in not just AI capabilities, but we're also adding in collaboration capabilities into that which then allow groups of people to interact together in time just in moment to address alternative decisions and routes. So. Any, I want to get your personal perspective on something. We've had so many conversations in the past around, you know, points in time, show messaging and products you're announcing. It seems like this showed IBM thing with all the everything coming to under one big tent. You see visibility now on unit economics of value. You're starting to see the path towards solutions for customers. It's not as foggy as it was once was. How do you explain that? You've seen this evolve and Jamie Thomas and I were talking earlier about, you know, we've made some investments and best it's now paying off. What's really happening here? What's the big aha moment? Where all this is kind of crystallizing right now? Well, a couple of things have happened. You know, IBM's gone through, we've gone through our own transformation. If you think about even four or five years ago, the mix of our portfolio to what it is now, less than I would say, three billion of our revenue basis was in the mix that we have now. And if you think about our fourth quarter earnings that even as we enter first quarter, like we had I think over 46%, 46 to 48% of our portfolio tied to what we call our strategic imperatives. And that's a huge transformation. So part of that is a couple of things. One is we said, look, this world of AI leverages and consumes a tremendous amount of data. And we want to make sure that you're protecting your data set. So we want to be thoughtful about how you engage strategically. So let's have your strategy. Let's make sure you understand your data. We want to protect you in that. We want to actually enable you to curate, train, harvest the insights from that. We want to make sure we leverage your expertise. So your people, your talent. So augmenting them with capabilities that are like workflow oriented, task management, self discovery. And then most importantly, delivering platforms, multiple platforms, quite frankly, over time that learn, right? Learn, interact, and evolve and can integrate these data sets and already give our clients speed. So that's what's been great about here is we're actually getting to share our own transformation story, but also our portfolio has evolved across strategy, data, and platform. It's mature and it's clear line of sight on some value. What's the big bets that you could look back on in the past five years saying, well, we made some big bets. These ones paid off. What were those big bets in your mind? You've involved in a lot of deals, I know, on the analytics side. What were the big bets that IBM made that's paying off right now? You know, I feel like I've known you almost eight, nine years now, right? Since you guys started on some of this. I would say, for example, our bet around big data. That is a huge bet in terms of our analytics capability and that it's a full spectrum. That is something that we've been investing in for quite a long time. And then when you think about the bet on Watson and AI and transforming not just businesses and business process, but actually transforming professions. We have Watson today operating in across multiple industries, like 20 different industries in 45 countries, multiple languages, multiple implementations, and it's getting better and better, whether it's healthcare, it's tax accounting, it's law. We're seeing, and cybersecurity, we're seeing huge opportunities. Data paid off, big time. Huge pay off. Cloud. Cloud is huge for every client because they're in different states of their journey. There may be certain application workloads that they want to manage themselves. There may be applications that they want and services that they want to subscribe to in the cloud, public, private, hybrid, we're having that dialogue. So I think everyone is on that journey now. So that's another huge bet. And then verticalizing the application sets. And so one of the things that I've got the opportunity to be a part of right now is really the business applications and how are we infusing Watson into our business applications. And leveraging the horizontal scale of cloud and everything else in the blockchain. So what's the priorities for you going into the new business? You've got a big organization, thousands of employees, or people work for you. A lot going on. What's the priorities? What is the focus? I've got about 5,000 people on the team, so a small team. Globally dispersed. We're working on a number of things, actually. And what's so exciting about that is we're thinking about personalizing AI at mass scale. So when you think about through the lens of a marketer, real-time personalization is becoming more and more challenge because of not only the data sets but the types of tools and the very tool applications you're switching context all the time. So we're providing ways to integrate and mix data sets. So our user behavior exchange data set really gives insights around consumer sentiment, behavior and context. The work the team has been doing around metropolts, hyper-local store and a city location data, mixing that with events and other activities and customer transaction data. So a lot on that front. The second category we're really focused on is next generation of embedding what I would consider cognitive services like search, headless search, so really understanding intent that's pervasive on other platforms. We're adding things also like embedded agents. So everyone's right now talking about they want to create chat bots and bots but they may be embedded in systems and they also may be embedded in different types of use cases, call center, so forth. So we're excited about that. And then obviously the supply chain area with blockchain. So we've got a lot. And the payoff in data is interesting because now you can have contextual relevance for things that are embedded like chat bots or whatever at the right time. And also if you think about the gamification opportunities data now in these network effect markets whether it's blockchain evolving into cryptocurrency and decentralized web applications, the commerce piece is going to be impacted. Your vertical integrations are going to be gamified. This is coming right down Main Street for IBM, isn't it? Well, and if you think about blockchain one of the biggest challenges is onboarding into a network. So what we're trying to do is one of the use cases is actually adding blockchain to existing networks. And so that once you're onboarded into a network you can connect to other networks. So a network of network sort of effect as you talked about. Is all data driven? It's all data driven. So membership and governance around blockchain is important. And then the other piece we're thinking through is use cases by vertical. So retail. So when you go through that lens and retail in terms of fashion is a very different lens than when you think through the business lens of retail banking, right? And our team is thoughtful about what does that mean in the next generation of content services? So how do you automatically tag images and surface them up for it to be published in the right media form independent of the channel or the navigation tools or assets? So there's a lot here, I'm excited. So final question for you is kind of philosophical one. You can answer it or not. You always get the zingers from me, but tools and the tools are changing too. So in these new emerging markets where there's just not, even if you take finance for instance, in say cryptocurrency and software the tooling's not there. You can't just stand up as trading exchange in these new token environments or what these apps have so that there's new tooling coming out. That's a concern. How are you guys helping customers get the tooling? Is that on your radar? Is that something you guys are talking about? You know, it's interesting that you bring it up which is technology adoption. I'm just going to call it in a broader sense because part of tooling is really about end user education and enablement. We are actually adding a capability called Ask Watson embedded in our software and services, especially our SaaS properties, such that, hey, I want to build a new email campaign. Well, what are my choices? And instead of reading through a traditional manual or having to go and find someone or watching a bunch of YouTube videos, what if Watson actually surfaced? Here are ways, here are some existing templates. Where would you like to start? And all of a sudden this kind of co-creation happens. So we're actually thinking of applying Watson embedded in our software and SaaS services to enable not just tooling, actually automatic assistance in the task in the moment. Yeah, no need to code. Insights is a service. Huge, customer insights is actually one of our top applications. So we're doing capabilities around journey analytics and customer experience analytics. So think about when you're any business person who's got a set of clients, what they want to do is as they express their brand, it may be done through email communications, it may be push notifications, there may be a SEO notification. And in that scenario, at what point does the consumer or the B2B struggle in actually fulfilling a transaction? Was it as they're zooming in and doing product comparisons? Was it as they were looking at post purchase service ability? We are able to actually understand and look at their journey as they travel through all these touch points. So we're actually doing customer experience analytics too. So for me, just coming from that data analytics background into this application space of so many domain practitioners. And these applications got to be real time. They got to have the data analytics. Inhi, great to see you. Thanks for coming on theCUBE. It's been eight, nine years. It feels like, you know, in analytics years it's like 20. You look great. Thanks for sharing your insights on theCUBE and congratulations on your new role. Thanks for stopping by theCUBE. I'm John Furrier here in theCUBE Studios, IBM Think 2018. Back with more coverage after this short break.