>> Live from San Francisco, it's theCUBE covering the IBM Think 2019, brought to you by IBM. >> Welcome to the redone Moscone Center here in San Francisco. I'm Stu Miniman with my co-host, Dave Vellante. You're watching theCUBE's wall to wall coverage of IBM Think 2019. >> Happy to welcome back to the program, a CUBE alumni Stephanie Trunzo, who's the Global Head of IBM Cloud Garage. >> Stephanie, thanks for joining us again. >> Yeah, yeah, great to be here. >> Good to see you. >> So, you're one of the IBM boomerangs. >> So you've worked for IBM before >> Indeed, that's right. and you're back now. So tell us a little about, we've had some interviews about the IBM Cloud Garage but tell us about your role, what you are doing. >> So I was with IBM for 13 years. >> I left and started a company called Point Source. >> We were a business partner and we did a lot of work in mobile and digital transformation and I sold that company and I kind of thought, "Well what's next?" and this opportunity presented itself. >> And it's perfect because the Cloud Garage is taking a new approach to how we interact with our clients from an IBM perspective and a lot of it is very similar to what we did at Point Source which is take this digital transformation, digital agency approach to looking at business outcomes first. >> Yeah, so one of our favorite topics, you know, cause it's a buzzword for a few years but when we talked to companies, I mean it's real. >> A few years back it was like, right, >> I'm doing a mobile app. I'm doing things like that. >> Bring us inside. It's a spectrum and every company is different but tell us what digital transformation means to the costumers that you're working with and how IBM and the Cloud Garage is helping them along that journey >> Yeah >> You know it's funny that you say that. Digital transformation can feel like a buzzword, right? >> And I think it's because there's so many things that are broader than just digital about transformation. So we talk in the Cloud Garage about guided transformation as a way of helping our clients not only think about how do they take Legacy applications, how do they take a new modern approach to their technology? How do they apply digital to processes that they already have in place? >> But also think about culture, new ways of working. >> Those aren't necessarily digital topics but we think about it as a guided transformation approach, meaning, can we teach along the way? >> So we're not just helping our clients see rapid outcomes and develop MVPs but are we helping them also learn along the way? >> So clients are really looking for people to help them, coach them on making decisions, bring expertise to the table so that they also have sustainable frameworks and you know, they're skilling people up in these new modern technologies as well. >> So digital transformation, of course, it is the buzzword of the day but every CEO you talk to is trying to get digital transformation right. >> So, what do you think some of the common ways in which people are pursuing the right path of digital transformation and maybe the question is what's perhaps some of the mistakes that people are making? >> Yeah, yeah, so I think if we think about it from the side of some challenges or mistakes or you know maybe missteps that people have along the way, is probably not spending enough time focusing on users, you know, taking the time to take a real outside-in approach. What is necessary to interact with your clients differently? >> What are the new capabilities that you could be offering? But instead of just daydreaming about all of the cool stuff that technology could do, really grounding it in an understanding of what your users want, what your users need, the data that will help inform those decisions. So I think that that's one misstep, is that people get excited about new technologies and so often it's like a solution looking for a problem and so we try to help make sure that we're really identifying business outcomes and what are the things that they want to test, to learn more so it's real iterative learning. >> And I think something you said is also really important, getting it right. >> What does that mean? >> Getting it right, it's a journey, it's this evolution so I'm not sure you ever hit a stage were you say, "Ah-ha, I've done it." (laughing) But more you can identify milestones where you can learn and apply that learning to keep evolving. >> Yeah. Often when we talk to users, the long pole to tent that transformation is that application portfolio. There's some stuff that can move pretty quick and we've seen that happen in the industry but boy, there's some stuff that I shoved it into VM and I kept it running five or 10 years longer than I should. >> How are companies doing along that line? >> How do we help get, because that's one of the challenges for users is, "Ugh, I have to use this horrible application." >> Yes. >> "That just can't move this at the speed that we need it to." >> Yeah, so when I talk with clients about this, one of the things that we often discuss is that you look backwards at your legacy architectures or your systems, like, core systems that take forever to migrate and often they were architected with time, not intention, right? So one microdecision after another took place over 10, 15, 20 years and your architecture, it reflects that. So I think that Cloud offers this really unique opportunity to look at your architecture going forward with an intentional mindset. So, kind of resetting the clock on all those architectural decisions that have accrued over a time. And I think that one of the aspects of getting people moving, even on the sticky projects, is breaking it down to consumable pieces. So one of the things we do in the Cloud Garage is help our clients figure out how to identify an actionable MVP. A minimum viable product that we can show quick success against. They've got a hypothesis they need to test. Let's just take one application, let's take one work load, and let's move that and see what happens. So we're going to do that learning, we're going to test that hypothesis and that starts you down a path that's a little quicker. >> How do I engage with the IBM Cloud Garage? >> If I'm interested, how do I get started? Is it a set of services? How does it all work? >> Yes, so we have 15 locations globally so they're built for purpose, built for activity spaces around the world. You can come into one of those spaces and we can do a tour, we can do a framing workshop which helps identify business opportunities, that first piece, the first step in the journey and get you moving really quickly. >> We also will do a couple different kinds of models if one of those locations doesn't work for a client or isn't a good geographical location. We'll also do pop-up Garages where we'll go to the client and work directly onsite with them. >> We've heard a lot about how Cloud fits into a lot of the digital transformation? >> What I haven't heard as much, but I would expect IBM is doing is how AI fits into that activity. >> Absolutely. Yeah, so in fact, I kind of lump that all together, to be honest, because part of the journey is identifying, again, if you're starting from business outcomes, you're working back to the technology solution so maybe the objective is to, you're in insurance industry and you need to develop policy quotes quicker. In order to develop that solution, that might necessarily involve us figuring out how to not only get their core systems to clouds so that they can extract data faster but also get more intelligent about underwriting processes so they can get quotes out quickly. So all of those technologies come into our process almost as a subplot to the business outcome that we're trying to drive for our clients. >> How much do you get involved in helping with the data strategy specifically? I mean, we think of the innovation sandwich that is data plus machine intelligence plus Cloud for scale, how involved are you in the data strategy? >> Is that part of the initiative? >> Absolutely. In fact, I think there's a really great symbiotic relationship and we see this pattern really often where clients will come to us because they want to do some application modernization as a starting point. >> As soon as we get into that conversation, you realize you actually need to modernize your data strategy as well. So there's a cyclical relationship and either entry point ends up involving the other, so if you're modernizing your data, what are you doing with it? You're probably surfacing it in an application, now we're back into an application discussion again. So we do definitely get involved in that and in fact, we have several offerings that are specifically geared towards data and analytics. >> Stephanie, about how long is a typical engagement? >> Is there an ending point or are there follow-ups that you have to make sure you're tweaking ... >> It never ends. It never ends. Yeah. (laughing) >> So, a typical engagement is we would start with the framing workshop I mentioned to identify the business opportunity. Design thinking workshop to take that business opportunity. Take all these great big ideas that people come up with and funnel it into something that's actionable. >> So take all the big ideas then and turn it into the one that we're going to pursue. >> And then an MVP workshop where we co-create with the client so we're teaching those skills, pair programming and working directly with them and a product owner to develop an MVP, test that hypothesis. And at the end, sometimes the MVP is something that is ready to roll in to production. >> Sometimes the MVP is something that leads to a learning that produces a second MVP. >> A typical engagement, end to end, for us, is probably around three months to get that first MVP and that's a pretty rapid pace to go the whole way from, and sometimes it's just as short as three weeks. So it just depends on the scope. But to go the whole way from identifying an opportunity and to testing it and having a real results, it's pretty fast. >> Are there specific KPI's that the customer can usually have coming out of that? >> Three months. That's a great window. >> You used to think about these engagements that used to roll out. >> Three years! >> It used to be more. >> Yeah, exactly. >> Yeah, so we do look at... >> It really depends on what it is that they're trying to achieve. But we do define success criteria upfront. Those success criteria then are the things that we're testing as part of the MVP process. And so at the end, you will have actionable results. You'll have information that you've learned from as a result of developing that MVP. >> Sometimes it's something like understanding whether certain security protocols internally can be met with moving a workload in a certain way. Sometimes it's actually about user conversion. So it could be a marketing goal. >> It really depends on what they're trying to achieve. >> Where do you want to see this go? I mean, obviously, you're riding the waves. Digital transformation, AI, data. Where do you see this going over the next two to five years? >> Yeah. So I think some of the fascinating things that we've been doing and the Garage is a great place because so much innovation is happening there. Our clients are kind of testing boundaries. So we get to see a lot of the pretty far, out-there things. >> We've had projects with blockchain tracking fish in streams like a farm to table scenario but marry that with Watson image recognition so we can tell what the fish is and digitally imprint an ID on it. The sky's the limit on the kinds of things that we can come up with and build an MVP for. But I think some of the stuff that I would see in the next few years is really more around what I'll say ambient computing. We're adding additional senses, it's no longer just sight. Now we have so much voice. >> There's all of these other ways that we are interacting in context. >> And so I think we're going to keep exploring this kind of ambient notion of the things that are going on around us, whether that's data, artificial intelligence, and forming things, and then incorporating that into how technology interacts with consumers, users, et cetera. >> You're really taking the notion of digital transformation to the next level. >> That's right. >> Say, sensing. >> Exactly. >> Acting on behalf of the brand. >> That's right. >> Injecting intelligence layer- >> You got it. >> Into that all. >> Exactly. >> Nice. >> Yeah. >> Alright. Stephanie, there's tons of users here at the show. Are there customer stories that people get to hear throughout the week? >> What highlights? >> Yeah, definitely. So, we really are big on storytelling because it's the easiest way to understand these things. Some of these technologies are difficult, you know. They're intense concepts. >> So we have a lot of our clients come and share their stories onstage. There's a keynote on Thursday where we're talking about how to take an idea to MVP and we've got several clients joining us to talk about the Cloud Garage and how we actually impacted their business so, yeah. >> Alright. Well, Stephanie, we really appreciate all the updates on IBM Cloud Garage. >> Yeah, absolutely. >> Congratulations. >> Thanks for having me back! Five years. Great. >> Alright. Well, we always love to tell the stories of what's happening at all the big shows. Help extract the signal from the noise. From Dave Vallente, I'm Stu Miniman. >> We'll be right back. Thanks for watching theCube.