>> Interviewer: Live from Las Vegas, it's the Cube, covering IBM Think 2018. Brought to you by IBM. >> Hello everyone welcome to the Cube, I'm John Furrier, we are here in Las Vegas for the Cube coverage of IBM Think 2018. So Cube Studios, live coverage, all day long three days, this is our third day, our next guest, is Cube alumni, Inhi Cho Suh, she's also the general manager of Watson Customer Engagement, been on so many times I don't know, eight, ten, a lot, you're a VIP. Great to see you. >> Thank you, good seeing you John, I really enjoy hanging out with you guys. >> So we love to hear what you're up to, cause 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-- 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, no go. >> It's an exciting space. So Watson Customer Engagement is really a 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 SasS 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, so supply chains, and big big collaborations. So it is a pretty broad breadth of about 21 solutions in offerings, that span many industries and many countries. >> We you got your hands in a lot of great stuff across the board but I think the big news today was the blockchain announcements, you guys featured a solution on stage, this is hard news, so explain, so talk about the hard news, you have an announcement, it's on stage, it's blockchain related, >> Yup 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 were thinking about our supply chain business network, so that is a separate offering that we have, which is about 6 thousand clients are on it. With 400 thousand 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 operations, so we're really excited about it >> And security. >> And security huge. >> 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. >> Oh absolutely. >> I mean providing applications for value chains, 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've prototyped, 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, and the vision of the product, they already have a product, they bolt in on, is this 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. From 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 processing, 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 the Cube about the inefficiencies now going to be abstracted away with things like blockchain and AI. Used cases that you've seen that jump out at you, that you'd like to share, that can highlight that, obviously AI, I said analytics, that's your wheelhouse. Now blockchain's emerging, I mean this is the innovation sandwich. AI on one hand is bread, and then you got blockchain, and data's the meat. >> Well you know especially in areas like supply chain, where small bits of optimization, meaning a one percent improvement, or resolving invoice and settlements, have such huge ripple effects downstream. So there was a great example in terms of our Maersk 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'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. >> Inhi I want to get your personal perspective on something, we've had so many conversations in the past around points in time, show messaging, and products you're announcing, it seems like this show at IBM, with everything coming together 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 once was. How do you explain that, you've see this evolve, and Jamie Thomas and I were talking earlier about, you know we base an investments and bets is now paying off what's really happening here, what's the big ah ha moment, where all this is kind of crystallizing right now. >> Well a couple 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 even as we enter first quarter, we had I think over 46 percent, 46 to 48 percent of our portfolio tied to what we call our strategic imperatives. And that's a huge transformation, so part of that is a couple 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 work flow oriented, task management, self discovery, and then most importantly, delivering platforms multiple platforms quite frankly, over time that learn. Right, learn to interact, and evolve and can integrate these data sets, in order to 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 been sure and a clear line of sight on some value. What's the big bets that you could look back on the past five years and say wow, we made some big bets, these one's paid off. What were those big bets in your mind. You've been involved in a lot of deals I know, 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 better round big data. That is a huge bet, in terms of our analytics capability, and that is 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 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 and cyber security, we're seeing huge opportunities >> Data paid off big time. >> Huge payoff. 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 maybe 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, and blockchain. So what's the priorities for you going into the new business, you 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 five thousand people on the team, so small team (laughs) 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 challenged, because of not only the data sets, but the types of tools and the varied 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 you know 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's interesting because now you've got 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 affect 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 networks sort of effect. >> And their effects 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, it's 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 be published in the right media form, independent of the channel, or the navigation tools or assets. There's a lot here I'm excited. >> So final question for you, it's kind of a philosophical one, you can answer it or not. You know you always get the zingers from me, but the tools are changing too, so in these new emerging markets, where there's just not-- take finance for instance and say cryptocurrency, and software, the tooling's not there, you can't just stand up at a trading exchange, that's in these new token environments, or what these apps have. So 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? >> Well 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 in user education and enablement. We are actually adding a capability called Ask Watson, embedded in our software and services, especially our SasS 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 SasS 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, you know what they want to do 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 be to be 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 serviceability. 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 the Cube, it's been eight, nine years, it feels like in analytics years it's like 20. You look great, thanks for sharing your insights, on the Cube and congratulations on your new role, >> Thank you >> Thanks for stopping by the Cube. I'm John Furrier here in the Cube Studios, IBM Think 2018, back with more coverage after this short break.