(upbeat music) >> Commentator: Live, from Orlando, Florida, it's theCUBE, covering ServiceNow Knowledge17, brought to you by ServiceNow. >> Hi everybody, welcome back to Knowledge17. This is theCUBE, the leader in live tech coverage. My name is Dave Vellante, and I'm with my co-host Jeff Frick at our fifth Knowledge. We go out to the events. We extract the signal from the noise. Seneca Louck is here, he's the Business Process Lead at Dow Chemical. A relatively new ServiceNow customer. Welcome to theCUBE, thanks for coming on. >> Thank you guys. >> Thanks for having me. >> So you said this is your second Knowledge. >> Seneca: It is. >> And, well how do you like Orlando? >> I like it, I like it. I'm here, in Venetian, >> Sunny? >> for next year, and so I'm a Vegas guy, so I'll be happy to get back there, but Orlando's nice. >> Dave: Where's home for you? >> Originally from New Jersey. Worked in Philadelphia for 15 years and relocated to Midland, Michigan, where Dow Chemical's headquartered. >> Dave: Fantastic, ah it's great, great country, Michigan. >> Absolutely. >> So, take us through your role, start there. What do you do, >> Sure. >> at Dow Chemical? >> So, I'm a Business Process Lead for Enterprise Service Management. We could go down the ITSM route, or we can go down the BSM route and we said, "Why pick one?" Enterprise Systems Management used to be the name. We actually elevated it up, Enterprise Service Management. We're the IT Operability focus on the end. >> Okay, and you said you went live, with ServiceNow, June last year? >> June 11th last year, we started with Incident Problem Change Config. We did Change Management, sorry, a month later. And then we did Service Request catalog, rolled out for the whole rest of the year. >> How long did it take you from sort of, when you said, "All right, we're doing this. "Start the project." To actually get, you know, MVP out? >> The cake. >> Yeah, the cake. (laughs) >> To get to the cake. >> And MVP's a really important thing. Minimum Viable Product. It was a hard lesson for us to learn. Quickly we realized that we're not going to be able to do everything we want to do in a first shot. So, we did focus very heavily on MVP. ServiceNow was good enough to make sure that they bred that into us, the importance of that. And so, we started in October, with workshops. We spent probably the first four or five months before we wrote one single line of code or configured one thing in ServiceNow. You know, a lot of that work was As-Is Process. Document it, understand it, uplift it, figure out what we want that To-Be Process to look like, and then figure out how the tool's going to deliver against that. >> Did you do some of that, I mean much of that came as part of the business case, and then you just refined it, is that right? >> The business case was really more on the value side. We didn't get into the specifics around process. We had a high level idea what we wanted to do strategically. Right? >> Yeah. >> Our guiding principles were really, Industry Best Practice, we like to think we're special. But really, the industry should know. Out of the box, ServiceNow, whenever possible. And to be honest, the out-of-the-box ServiceNow should reflect Industry Best Practice fairly well. And so that was kind of the coming in position for us. We deviated only when absolutely necessary and we really tried to stick to vanilla. >> So you minimized custom mods? >> Seneca: We really tried to do that, yes. There's times where we had to deviate of course. But we really wanted to look to see if ServiceNow had an answer, and if we could tweak what was already there, then great. There's only a handful of opportunities where we had to build something net new. >> And was that related to your ERP, or when did you have to build those custom mods? >> So, in places where we might have a concept that was to bring Legacy capability from a previous system. We knew we weren't going to cut and run from the old to the new. We had to kind of pull on some of the capabilities of that platform. So, the way you guys do category, sub-category, we did through classification. And so we had to customize a couple of tables to bring classifications over to bridge that gap. >> I see, okay, and then, so then you go live. Now was it a CMDB, a single CMDB across the organization? >> So, we have HP technology, where we had large investment. We wanted to keep that for discovery purposes and it enabled us to build one big tunnel between our CMDB and ServiceNow, so it made the integration go very easily. So, we really did two key integrations, a CMDB integration and an LDAP one to get our people data. Once that was done, we were on our feet, we were stood up and we were ready to start delivering processes. >> And the Service Catalog? >> Service Catalog was an interesting one because we had it spread out in a bunch of places. We had web forums, where somebody had customized a small, little web forum that that was actually making calls into our ticketing system to create service requests. We also had Request Center, which was brought in to try and solve that world of Service Request Management, but it only did it for Service Request. And we realize ServiceNow is going to do it end-to-end. >> Seneca, when you're thinking about your investments. I like to look at 'em as you get investments to run the business, some to grow the business and some to transform the business. And you're really sort of an IT-transform expert. How do you allocate that? Are those mutually exclusive? Do they sort of blend into each other and how much of your investment is transformation, and what does that all mean? >> Yeah, so it's tough because you've got guys that are on the run side, and I actually spent the large majority of my career on the run side. So, I know what if feels like to be accountable for everything in production, regardless of how it got there. And so, I kind of oscillate back and forth. Right? If the hair's on fire and these guys are going to be dead by the time the project transforms next year's capability, there's no point in us waiting. We can't wait. So, we're bouncing in and out of transformation and dealing with, making sure operability can happen effectively, efficiently, and that these guys are around next year, and alive and well, so that we can deliver that transformational capability. >> You talked about MVP being kind of a new concept. I wonder if you could dig into that a little bit further. >> Sure, sure. >> Is that not kind of a process or methodology that you guys have done in the past, or was it a learning curve? >> So, it was a little bit of a learning curve. So, typically you know, we delivered the biggest SAP implementation in the history of the world. A billion dollars, 800 SAP systems. And it took us seven years. So, we didn't think a lot about MVP, we wanted perfection. And so we made sure that we got it. And it cost us dearly. But in the end, the results were good. In this case, we had to move fast. Right? We weren't going to be able to do it all. We knew the capabilities that you see, throughout this room, are incredible. We want to get to them. But we've got to get on to the platform first. And so, we really did hone in on trying to find, what is the minimum product that we need to get people moved over to the platform, and we'll increment from there. So, it was a little bit of a learning for us. It was a little bit of a culture change. And we kind of found that sweet spot between Agile and Waterfall, which I think we called it Wagile, or (laughs). Yeah, Wagile I think, >> Well, right. >> is the name. >> I mean your implementation >> coincided with the sort of DevOps craze, and Agile, but there's >> That's right, that's right. >> a place for Waterfall, right? >> There is, there is. >> Sometimes, you need >> that perfection. Other times, you need to break stuff and iterate. >> Absolutely. >> But so, that's interesting. You said you came up with sort of a hybrid. Sometimes, hybrids are scary. So, how did you sort of come to that point and how's it workin' for you? >> Yeah, so what we did is we front-ended a lot of the requirements. We spent, like I said, several months, just sitting and doing requirements. And then, we transitioned into two-week sprints. And we pulled out of the backlog, the requirements that we had captured in those months previous. So, that was kind of how we blended the two together. We're more a Waterfall shop but we were delivering a system of record. And so, in systems of record, we strongly believe that Agile can be dangerous. It's not necessarily the place to start. And so, we started with Waterfall, and we kind of ended with Agile. >> All right, okay, and so, what so far have been the sort of business impacts? Can you share that with us? >> Yeah absolutely, so first thing's first, we're getting consistency throughout our processes. So, many times, geographical differences or even within a geography, at a sub-activity level, people were doing things differently. So, first thing we had to do was Standardize Process. That gives us the ability to measure across the world, how that process is being executed. Whereas before, we couldn't do that one-for-one, we couldn't compare these things one-for-one. And so, now we have that vision, now we have that visibility, and we were a performance analytics customer from day one, so we started capturing data to baseline, to benchmark, from Go Live, until today, and we've got incredible data to go back then and do the continuous service improvement. >> And how much of the consistency and process was forced in your pre-deployment activities, where you kind of find, all right, we got to sit down and actually document this to put it into the system. Versus, now that you've got this tool in place, that you see the opportunity to continue to go after new processes. >> It varied, dependent upon area, so Change Management was actually not a bad process from a global perspective. On the flip side is, we actually implemented some case management capability for our Business Functions. Their processes were extremely deviated across geographies, across activities. And so it depends, but the bottom line is that before we talk about implementing on this platform, we got to talk standardization. Good news is the incident problem changed. It wasn't as much work. On the Business Process side, it was a lot more. >> How are you predominantly measured? Is it getting stuff done? Are there other sort of KPI's that you focus on? Is there one that you try to optimize? >> So, these days, we're actually operating in a little bit of a dangerous place because we're going through so much mergers and acquisition activity, that our success is, can we integrate a company in less than a year while we go on to do the biggest chemical merger in the history of the world? So, typically, we would be kind of looking at metrics, and KPI's, down at the process level. Right now, we're looking at, can I actually bring these companies together? So it's integrated. >> And not kill each other. >> And not kill each other. (laughs) That's right. That's not to say we're not doing the latter as well but I think we have to start with, can we get the big activities done so that we can figure out how to do the process improvement. >> Dave: Right. How about the show for you here? What's it been like? What are you learning? >> Yeah, so. >> Are you sharing? >> Dx Continuum I think is going to be the theme that I'm going to leave here thinking, wow, these guys did the right thing with that purchase. So, you know the artificial intelligence, the machine learning, the data lakes, that we're going to be able to take all this data that we have and pump it out to you guys. And you're going to turn around and tell us an interesting story. You're going to tell me the questions that I would never even think to ask because you're going to be able to see into that data in ways that we never even dreamed possible. So, that's the big one for me. I've heard some rumors of some other things coming, but I shouldn't know about those and so I'm not going to say anything at this point. But right now, it's about the machine learning, the artificial intelligence. >> So, what other, I mean 'cause a company the size of Dow must be doing some interesting things with Big Data and Hadoop and AI. How does what you're doing or does what you're doing with ServiceNow relate to those sort of other activities? Is there sort of a data platform strategy? >> It's an interesting question. It's something that we're actually struggling with a little bit to figure out what that strategy is going to be. I don't think the larger organization expected so many opportunities to use analytics and to use machine learning against data sets that otherwise were, this is operation stuff, for the most part, right? We're starting to get into the business side a little bit but really, we were focused on running the business from an operations perspective. And so, all of a sudden, now, we're getting attention that we wouldn't have had otherwise, from the big players, you know. The SAP Business Warehouse, Business Intelligence guys. They've got 120 people delivering their reporting service. I got a guy half-time, that's helping me with my PA reports and we've got to figure out a way to either join our strategies together or at least meet in the middle because there's data that we probably want to share from each other. >> Do you have a Chief Data Officer on staff? >> We do not, that I'm aware of, actually. But I think it is , it's a very powerful role, but in our SAP world, they kind of act as that defacto person within our organization. But they're not very interested in what we're doing yet but they are starting to get the attention of us. >> It's interesting 'cause we talk a lot about IoT Now will bridge, you know, kind of the IT and the Ops folks. And it sounds like you're having that experience really specifically built around some of the processes that you're delivering in ServiceNow. To bring those two world together. >> Yeah, so while I mentioned machine learning and Artificial Intellience, that's actually right there, second on my list. The thing I came here last year and raised my hands and said I need the most is I need the ability to bring massive amounts of data onto this platform. Raw performance data, network data, server data, utilization data, end-user data. I want to be able to bring it into this platform so that I can use it to correlate events and incidents and problems. And so, the things that you guys are doing for IoT, to bring massive data sets in, are actually going to solve my problem, but I don't think it was necessarily what you were trying to solve. But I'm very happy for that. >> So, by the way, we're independent media, so we're (laughs) like third-party guys. >> Understood, understood >> It's these guys, ServiceNow. So, we just sort of unpack, analyze. What about if you had to do it again. What would you do differently? Obviously you would have, and you did, you embraced the MVP, other things? >> So, we took a very dangerous route in that we didn't have a team built. We didn't have a competency built. We took a system integrator and we went off and we went hog wild and we implemented it quickly, while we built the team, while we built the governance, while we built the competency center. If I could do it again, I'd have that team ready, staffed, you know, well-trained up front, so that we could learn as we went, a little bit more, be a little more autonomous and self-sufficient. >> Were you one of the 100 customers that John Donahoe met with in 45 days? >> I was not actually. >> And if you weren't, then what would you tell him in terms of the piece that he said, "What can we do better?" What would you? >> Yeah. >> So, the question came up yesterday, around releases. You know, should we do more, should we do less. I mean, we're actually struggling a little bit to keep up with the two releases per year. So, the biggest thing that I see is not making it a wholesale upgrade. If I could take parts and pieces from the new capabilities that are coming without having to go through the full upgrade cycle, you know, I think that would be huge for me. So that we don't have to spend a couple of months or we're hoping to get that down to one month. But this is our first one in production. So, we're going to spend three months getting this upgrade right. We're hoping to get it down to, you know, a couple of weeks to a month. But if I can take pieces and parts of the capability that's being delivered, and not have to take it wholesale, that would be the thing. >> Yeah, so that's interesting because Multi-instance is nice. You don't have to go on the SaaS player's schedule. But you want to keep current, you know, for a lot of reasons, with maybe, with certain parts of the upgrade. Yeah, okay, that doesn't sound trivial. (laughs) >> Yeah, it's not. >> Although I know they're thinking about it so it's come up, I've heard a couple of people at least mention that it's something that they have to think about. They may not actually go that direction. But at least that they're thinking about it, that tells me that they're exploring other avenues to deliver capability. >> Dave: What's in the future for you guys? Where do you want to take this thing? >> Yeah, so our next big thing's going to be Event Management. So, we've got 45 different tools that are doing monitoring from purchase tools to somebody's script that's sitting on the mainframe that sends us an event, when some exception happens. And so we've built, you know, with a custom IT process automation tool, our Event Management framework. And it's integrated with ServiceNow. But at the heart of it is, there's some old technology, decade-old technology, that was my first entry into IT process automation. And so, as the person who built it, I'm going to be the one that ultimately unplugs it and hands it over to ServiceNow. So, for us, that's the next step for what we're going to do. >> Awesome, well listen, Seneca, thanks very much for coming to theCUBE. It's great to have you. Loved the knowledge. >> Thanks for having us. >> Dave: Rapid fire, you know, perfect for theCUBE, so thank you. >> Great, wonderful. >> Thank you, guys. >> Thanks for coming on. >> I appreciate it. >> All right, pleasure. >> All right, keep it right there, buddy. We'll be back with our next guest. This is theCUBE, we're live from Knowledge17 in Orlando. We'll be right back. (upbeat music)

>> Voice Over: From around the globe. It's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Okay. Welcome back everyone. To theCUBE's coverage of IBM Think 2021 virtual. I'm John Furrier, host of theCUBE. We've got a great segment here on the power of hybrid cloud and AI. And I'm excited to have Rob Thomas, Senior Vice President of IBM's cloud and Data platform, CUBE alumni. Been on going back years and years talking about data. Rob, great to see you, a leader at IBM. Thanks for joining. >> John. Great to see you hope everybody is safe and well and great to be with you again. >> Yeah, love the progress, love the Hybrid Cloud distributed computing, meets operating systems, meets modern applications at the center of it is the new cloud equation. And of course data continues to be the value proposition as the platform. And as you quoted many times and I love your favorite quote. There's no AI without IA. So you got to have the architecture. So that still rings true today and it's just so evergreen and so relevant and cooler than ever with machine learning and AI operations. So let's just jump in. IBM's announced, host a new products and updates at Think. Tell us what you're most excited about and what should people pay attention to. >> Maybe I'll connect two thoughts here. There is no AI without IA, still true today. Meaning, customers that want to do AI need an information architecture. There was an IDC report just last year that said, "Despite all the progress on data, still 90% of data in organizations is either unused or underutilized." So what's amazing is after all the time we've been talking John, we're still really just getting started. Then that kind of connects to another thought, which is I still believe that AI is not going to replace managers, but managers that use AI will replace the managers that do not. And I'd say that's the backdrop for all the announcements that we're doing this week. It's things like auto SQL. How do you actually automate the creation of SQL queries in a large distributed data warehouse? It's never been done before, now we're doing it. It's things like Watson Orchestrate which is super powers in the hands of any business user, just to ask for something to get done. Just ask for a task to get completed. Watson Orchestrator will do that for you. It's maximo mobile. So anybody working in the field now has access to an AI system on their device for how they're managing their assets. So this is all about empowering people and users that use these products are going to have an advantage over the users that are not, that's what I'm really excited about. >> So one of the things that's coming out as Cloud Pak for Data, AI powered automation these are kind of two that you kind of touched upon the SQL thing their. Cloud Pak is there, you got it for Data and this automation trend. What is that about? Why is it important? Can you share with us the relevance of those two things? >> Let's talk broadly about automation. There's two huge markets here. There's the market for RPA business process, $30 billion market. There's the market for AIOps, which is growing 22%, that's on its way to $40 billion. These are enormous markets. Probably the biggest bet IBM has made in the last year is in automation. Explicitly in Watson AIOps. Last June in Think we announced Watson AIOps, then we did the acquisition of Instana, then we announced our intent to acquire Turbonomic. At this point, we're the only company that has all the pieces for automating how you run your IT systems. That's what I mean when I say AIOps. So really pleased with the progress that we've made there. But again, we're just getting started. >> Yeah. Congratulations on the Turbonomic. I was just commenting on that when that announced. IBM buying into the Cloud and the Hybrid cloud is interesting because the shift has happened. It's Public Cloud, it's on premises as Edge. Those two things as a system, it's more important ever than the modernization of the apps that you guys are talking about and having the under the cover capabilities. So as Cloud and Data merge, this kind of control plane concept, this architecture, as you'd said IA. You can't have AI without IA. What is that architecture look like? Can you break down the elements of what's involved? I know there's predictive analytics, there's automation and security. What are the pillars of this architecture? What are the four concepts? If you can explain that. >> Yeah, let's start with the basics. So Hybrid Cloud is about you build your software runs once and you run it anywhere you want, any public cloud,any private cloud. That assumes containers are important to the future of software. We are a hundred percent convinced that is true. OpenShift is the platform that we build on and that many software companies in the world are now building on because it gives you portability for your applications. So then you start to think about if you have that common fabric for Hybrid Cloud, how do you deliver value to customers in addition to the platform? To me, that's four big things. It's automation, we talked about that. It's security, it's predictions. How do you actually make predictions on your data? And then it's modernization. Meaning, how do you actually help customers modernize their applications and get to the Cloud? So those are the things we always talk about, automate, secure, modernize, predict. I think those are the four most important things for every company that's thinking about Cloud and AI. >> Yeah, it's interesting. I love the security side is one of the big conversations in AIOps and day two operations or whatever it's called is shifting left, getting security into the Cloud native kind of development pipeline. But speaking of secure, you have a customer that was talking about this Dow Chemical. About IB empowering Dow zero trust architecture. Could you explain that deal and how that's working? Because that's again, huge enterprise customer, very big scale at scale, zero trust is big, part of it. What is this? >> Let's start with the basics. So what is zero trust mean? It means to have a secure business, you have to start with the assumption that nothing can be trusted. That means you have to think about all aspects of your security practice. How do you align on a security strategy? How do you protect your data assets? How do you manage security threats? So we always talk about a line, protect, manage back to modernize, which is how do you bring all your systems forward to do this? That's exactly what we're doing with the Dow as you heard in that session, which is they've kind of done that whole journey from how they built a security strategy that was designed with zero trust in mind, they're protecting data assets, they're managing cyber threats in real time with a relatively low number of false positives which are the issue that most companies have. They're a tremendous example of a company that jumped on this and has had a really big impact. And they've done it without interfering with their business operations, meaning anybody can lock everything down but then you can't really run your business if you're doing that. They've done it, I think in a really intelligent way. >> That's awesome. We always talk about the big waves. You always give great color commentary on the trends. Right now though, the tsunami seems to be a confluence of many things coming together. What are some of the big trends in waves you're seeing now specifically on the tech side, on the technology side, as well as the business side right now? 'Cause coming out of post COVID, it's pretty clear cloud-native is powering a new growth strategy for customers. Dow was one of them, you just commented on it but there's a bigger wave happening here, both on the tech theater and in the business theater. Can you share your views on and your opinions and envision on these trends? >> I think there's three profound trends that are actually pretty simple to understand. One is, technology is going to decentralize again. We've always gone from centralized architectures to decentralized. Mainframe was centralized, internet mobile decentralized. The first version of public cloud was centralized, meaning bringing everything to one place. Technology is decentralized and again, with Hybrid Cloud, with Edge, pretty straight forward I think that's a trend that we can ride and lead for the next decade. Next is around automation that we talked about. There was a McKinsey report that said, "120 billion hours a year are going to be automated with things like Watson Orchestrator, Watson AIOps." What we're doing around Cloud Pak for automation, we think that time is now. We think you can start to automate in your business today and you may have seen the--example where we're doing customer care and they're now automating 70% of their inbound customer inquiries. It's really amazing. And then the third is around data. The classical problem, I mentioned 90% is still unused or underutilized. This trend on data is not about to slow down because the data being collected is still multiplying 10 X every year and companies have to find a way to organize that data as they collected. So that's going to be a trend that continues. >> You know, I just kind of pinched myself sometimes and hearing you talk with some of our earlier conversations in theCUBE, people who have been on this data mindset have really been successful because it's evolving and growing and it's changing and it's adding more input into the system and the technology is getting better. There's more cloud scales. You mentioned automation and scale are huge. And I think this really kind of wakes everyone up. And certainly the pandemic has woken everyone up to the fact that this is driving new experiences for users and businesses, right? So this is, and then those experiences become expectations. This is the classic UX paradigm that grows from new things. So I got to ask you, with the pandemic what is the been the most compelling ways you seen people operate, create new expectations? Because new things are coming, new big things, and new incremental things are happening. So evolution and revolutionary capabilities. Can you share some examples and your thoughts? >> We've collected a decent bit of data on this. And what's interesting is how much AI has accelerated since the pandemic started. And it's really in five areas, it's customer care that we talked about, virtual agents, customer service, how you do that. It's employee experience. So somewhere to customer care but how do you take care of your employees using AI? Third is around AIOps, we talked about that. Fourth is around regulatory compliance and fifth is around financial planning and budgeting. These are the five major use cases of AI that are getting into production in companies over the last year that's going to continue to accelerate. So I think it's actually fairly clarifying now that we really understand these are the five big things. I encourage anybody watching, pick one of these, get started, then pick the second, then pick the third. If you are not doing all five of these, 12, 18, 24 months from now, you are going to be behind. >> So give us an example of some things that have surprised you in the pandemic and things that blew you away. Like, wow, I didn't see that coming. Can you share on things that you've seen evolve? Cause you're a year ahead of the business units of Cloud and Data, big part of IBM and you see customer examples. Just quickly share some notable use cases or just anecdotal examples of just things that jumped out at you that said, "Wow, that's going to be a double-down moment or that's not going to be anymore." Exposes, the pandemic exposes the good, bad and the ugly. I mean, people got caught off guard, some got a tailwind, some had a headwind, some are retooling. What's your thoughts on what you can you share any examples? >> Like everybody, many things have surprised me in the last year. I am encouraged at how fast many companies were able to adjust and adapt for this world. So that's a credit to all the resiliency that they built into their processes, their systems and their people over time. Related to that, the thing that really sticks out to me again, is this idea of using AI to serve your customers and to serve your employees. We had a hundred customers that went live with one of those two use cases in the first 35 days of the pandemic. Just think about that acceleration. I think without the pandemic, for those hundred it might've taken three years and it happened in 35 days. It's proof that the technology today is so powerful. Sometimes it just takes the initiative to get started and to do something. And all those companies have really benefited from this. So it's great to see. >> Great. Rob, great to have you on. Great to have your commentary on theCUBE. Could you just quickly share in 30 seconds, what is the most important thing people should pay attention to and Think this year from your perspective? What's the big aha moment that you think they could walk away with? >> We have intentionally made this a very technology centric event. Just go look at the demos, play with the technology. I think you will be impressed and start to see, let's say a bit of a new IBM in terms of how we're making technology accessible and easy for anybody to use. >> All right. Rob Thomas, Senior Vice President of IBM cloud and Data platform. Great to have you on and looking forward to seeing more of you this year and hopefully in person. Thanks for coming on theCUBE virtual. >> Thanks, John. >> Okay. I'm John Furrier with theCUBE. Keep coverage of IBM Think 2021. Thank you for watching. (soft music)

(soft music) >> Voice Over: From around the globe. It's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Okay. Welcome back everyone. To theCUBE's coverage of IBM Think 2021 virtual. I'm John Furrier, host of theCUBE. We've got a great segment here on the power of hybrid cloud and AI. And I'm excited to have Rob Thomas, Senior Vice President of IBM's cloud and Data platform, CUBE alumni. Been on going back years and years talking about data. Rob, great to see you, a leader at IBM. Thanks for joining. >> John. Great to see you hope everybody is safe and well and great to be with you again. >> Yeah, love the progress, love the Hybrid Cloud distributed computing, meets operating systems, meets modern applications at the center of it is the new cloud equation. And of course data continues to be the value proposition as the platform. And as you quoted many times and I love your favorite quote. There's no AI without IA. So you got to have the architecture. So that still rings true today and it's just so evergreen and so relevant and cooler than ever with machine learning and AI operations. So let's just jump in. IBM's announced, host a new products and updates at Think. Tell us what you're most excited about and what should people pay attention to. >> Maybe I'll connect two thoughts here. There is no AI without IA, still true today. Meaning, customers that want to do AI need an information architecture. There was an IDC report just last year that said, "Despite all the progress on data, still 90% of data in organizations is either unused or underutilized." So what's amazing is after all the time we've been talking John, we're still really just getting started. Then that kind of connects to another thought, which is I still believe that AI is not going to replace managers, but managers that use AI will replace the managers that do not. And I'd say that's the backdrop for all the announcements that we're doing this week. It's things like auto SQL. How do you actually automate the creation of SQL queries in a large distributed data warehouse? It's never been done before, now we're doing it. It's things like Watson Orchestrate which is super powers in the hands of any business user, just to ask for something to get done. Just ask for a task to get completed. Watson Orchestrator will do that for you. It's Maximo Mbo. So anybody working in the field now has access to an AI system on their device for how they're managing their assets. So this is all about empowering people and users that use these products are going to have an advantage over the users that are not, that's what I'm really excited about. >> So one of the things that's coming out as Cloud Pak for Data, AI powered automation these are kind of two that you kind of touched upon the SQL thing their. Cloud Pak is there, you got it for Data and this automation trend. What is that about? Why is it important? Can you share with us the relevance of those two things? >> Let's talk broadly about automation. There's two huge markets here. There's the market for RPA business process, $30 billion market. There's the market for AIOps, which is growing 22%, that's on its way to $40 billion. These are enormous markets. Probably the biggest bet IBM has made in the last year is in automation. Explicitly in Watson AIOps. Last June in Think we announced Watson AIOps, then we did the acquisition of Instana, then we announced our intent to acquire Turbonomic. At this point, we're the only company that has all the pieces for automating how you run your IT systems. That's what I mean when I say AIOps. So really pleased with the progress that we've made there. But again, we're just getting started. >> Yeah. Congratulations on the Turbonomic. I was just commenting on that when that announced. IBM buying into the Cloud and the Hybrid cloud is interesting because the shift has happened. It's Public Cloud, it's on premises as Edge. Those two things as a system, it's more important ever than the modernization of the apps that you guys are talking about and having the under the cover capabilities. So as Cloud and Data merge, this kind of control plane concept, this architecture, as you'd said IA. You can't have AI without IA. What is that architecture look like? Can you break down the elements of what's involved? I know there's predictive analytics, there's automation and security. What are the pillars of this architecture? What are the four concepts? If you can explain that. >> Yeah, let's start with the basics. So Hybrid Cloud is about you build your software runs once and you run it anywhere you want, any public cloud,any private cloud. That assumes containers are important to the future of software. We are a hundred percent convinced that is true. OpenShift is the platform that we build on and that many software companies in the world are now building on because it gives you portability for your applications. So then you start to think about if you have that common fabric for Hybrid Cloud, how do you deliver value to customers in addition to the platform? To me, that's four big things. It's automation, we talked about that. It's security, it's predictions. How do you actually make predictions on your data? And then it's modernization. Meaning, how do you actually help customers modernize their applications and get to the Cloud? So those are the things we always talk about, automate, secure, modernize, predict. I think those are the four most important things for every company that's thinking about Cloud and AI. >> Yeah, it's interesting. I love the security side is one of the big conversations in AIOps and day two operations or whatever it's called is shifting left, getting security into the Cloud native kind of development pipeline. But speaking of secure, you have a customer that was talking about this Dow Chemical. About IB empowering Dow zero trust architecture. Could you explain that deal and how that's working? Because that's again, huge enterprise customer, very big scale at scale, zero trust is big, part of it. What is this? >> Let's start with the basics. So what is zero trust mean? It means to have a secure business, you have to start with the assumption that nothing can be trusted. That means you have to think about all aspects of your security practice. How do you align on a security strategy? How do you protect your data assets? How do you manage security threats? So we always talk about a line, protect, manage back to modernize, which is how do you bring all your systems forward to do this? That's exactly what we're doing with the Dow as you heard in that session, which is they've kind of done that whole journey from how they built a security strategy that was designed with zero trust in mind, they're protecting data assets, they're managing cyber threats in real time with a relatively low number of false positives which are the issue that most companies have. They're a tremendous example of a company that jumped on this and has had a really big impact. And they've done it without interfering with their business operations, meaning anybody can lock everything down but then you can't really run your business if you're doing that. They've done it, I think in a really intelligent way. >> That's awesome. We always talk about the big waves. You always give great color commentary on the trends. Right now though, the tsunami seems to be a confluence of many things coming together. What are some of the big trends in waves you're seeing now specifically on the tech side, on the technology side, as well as the business side right now? 'Cause coming out of post COVID, it's pretty clear cloud-native is powering a new growth strategy for customers. Dow was one of them, you just commented on it but there's a bigger wave happening here, both on the tech theater and in the business theater. Can you share your views on and your opinions and envision on these trends? >> I think there's three profound trends that are actually pretty simple to understand. One is, technology is going to decentralize again. We've always gone from centralized architectures to decentralized. Mainframe was centralized, internet mobile decentralized. The first version of public cloud was centralized, meaning bringing everything to one place. Technology is decentralized and again, with Hybrid Cloud, with Edge, pretty straight forward I think that's a trend that we can ride and lead for the next decade. Next is around automation that we talked about. There was a McKinsey report that said, "120 billion hours a year are going to be automated with things like Watson Orchestrator, Watson AIOps." What we're doing around Cloud Pak for automation, we think that time is now. We think you can start to automate in your business today and you may have seen the C QVS example where we're doing customer care and they're now automating 70% of their inbound customer inquiries. It's really amazing. And then the third is around data. The classical problem, I mentioned 90% is still unused or underutilized. This trend on data is not about the slow down because the data being collected is still multiplying 10 X every year and companies have to find a way to organize that data as they collected. So that's going to be a trend that continues. >> You know, I just kind of pinched myself sometimes and hearing you talk with some of our earlier conversations in theCUBE, people who have been on this data mindset have really been successful because it's evolving and growing and it's changing and it's adding more input into the system and the technology is getting better. There's more cloud scales. You mentioned automation and scale are huge. And I think this really kind of wakes everyone up. And certainly the pandemic has woken everyone up to the fact that this is driving new experiences for users and businesses, right? So this is, and then those experiences become expectations. This is the classic UX paradigm that grows from new things. So I got to ask you, with the pandemic what is the been the most compelling ways you seen people operate, create new expectations? Because new things are coming, new big things, and new incremental things are happening. So evolution and revolutionary capabilities. Can you share some examples and your thoughts? >> We've collected a decent bit of data on this. And what's interesting is how much AI has accelerated since the pandemic started. And it's really in five areas, it's customer care that we talked about, virtual agents, customer service, how you do that. It's employee experience. So somewhere to customer care but how do you take care of your employees using AI? Third is around AIOps, we talked about that. Fourth is around regulatory compliance and fifth is around financial planning and budgeting. These are the five major use cases of AI that are getting into production in companies over the last year that's going to continue to accelerate. So I think it's actually fairly clarifying now that we really understand these are the five big things. I encourage anybody watching, pick one of these, get started, then pick the second, then pick the third. If you are not doing all five of these, 12, 18, 24 months from now, you are going to be behind. >> So give us an example of some things that have surprised you in the pandemic and things that blew you away. Like, wow, I didn't see that coming. Can you share on things that you've seen evolve? Cause you're a year ahead of the business units of Cloud and Data, big part of IBM and you see customer examples. Just quickly share some notable use cases or just anecdotal examples of just things that jumped out at you that said, "Wow, that's going to be a double-down moment or that's not going to be anymore." Exposes, the pandemic exposes the good, bad and the ugly. I mean, people got caught off guard, some got a tailwind, some had a headwind, some are retooling. What's your thoughts on what you can you share any examples? >> Like everybody, many things have surprised me in the last year. I am encouraged at how fast many companies were able to adjust and adapt for this world. So that's a credit to all the resiliency that they built into their processes, their systems and their people over time. Related to that, the thing that really sticks out to me again, is this idea of using AI to serve your customers and to serve your employees. We had a hundred customers that went live with one of those two use cases in the first 35 days of the pandemic. Just think about that acceleration. I think without the pandemic, for those hundred it might've taken three years and it happened in 35 days. It's proof that the technology today is so powerful. Sometimes it just takes the initiative to get started and to do something. And all those companies have really benefited from this. So it's great to see. >> Great. Rob, great to have you on. Great to have your commentary on theCUBE. Could you just quickly share in 30 seconds, what is the most important thing people should pay attention to and Think this year from your perspective? What's the big aha moment that you think they could walk away with? >> We have intentionally made this a very technology centric event. Just go look at the demos, play with the technology. I think you will be impressed and start to see, let's say a bit of a new IBM in terms of how we're making technology accessible and easy for anybody to use. >> All right. Rob Thomas, Senior Vice President of IBM cloud and Data platform. Great to have you on and looking forward to seeing more of you this year and hopefully in person. Thanks for coming on theCUBE virtual. >> Thanks, John. >> Okay. I'm John Furrier with theCUBE. Keep coverage of IBM Think 2021. Thank you for watching. (soft music)