>> From Times Square, in the heart of New York City, it's theCUBE. Covering IMAGINE 2018. Brought to you by Automation Anywhere. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. We're in Manhattan, New York City, at Automation Anywhere's IMAGINE 2018. We've never been to this show. Pretty interesting, about 1,100 people talking about Bots, but it's really more than Bots. It's really how do we use digital employees, digital programs, to help people be more efficient, and take advantage of a lot of the opportunities as well as the challenges that we're facing as we keep innovating, I'm really excited to have our next guest. Jeffrey Immelt, the former chairman and CEO of GE, great to see you Jeff. >> Good to see you. >> Absolutely, last I saw you I think, was at Minds and Machines, and we're huge fans, >> A couple years ago, yep. >> Beth Comstock, I loved Bill Ruh, so you know, what a fantastic team. >> A great team. >> But here you are talking about Bots, and it's interesting because at GE you guys have been involved in big industrial equipment, as well as a huge software business, so you really figured out that you've gotta have software and people to really work with these machines. >> So you know Jeff, I really am a big believer that productivity is the key, and that we, we're seeing a bow wave of technology that's really gonna impact the workplace in a meaningful way. The reason why I like RPA, what we call Bots-- >> Right, RPA. >> Is because it can happen so quickly. It can happen across the organization. It has great productivity associated with it. So I kinda view RPA as being really one of the uh, let's say early wave technologies in terms of how to drive more automation and productivity in the workplace. >> That's funny, because people ask me they're like, what's the deal with some of these stock evaluations, is it real, and think back to the ERP days right, ERP unlocked this huge amount of inefficiency. That was a long, long time ago, and yet we still continue to find these huge buckets of inefficiency over and over. >> I think it's, I mean I think to your point, the early days of IT, really if you look at ERP manufacturing systems, even CRM. They were really more around governance. They were kind of connecting big enterprises. But they really weren't driving the kind of decision support, automation, AI, that companies really need to drive productivity. And I think the next wave of tools will operate inside that envelope. You know, ultimately these will all merge. But I think these are gonna get productivity much quicker than an ERP system or an MES system did. Which are really, at the end of the day, driven by CFOs to drive compliance more than operating people to drive productivity. >> Right, but what's driving this as we've seen over and over, that consumerization of IT, not only in terms of the expected behavior of applications, you know you want everything to act like Amazon, you want everything to act like Google. But also, in terms of expectations of feedback, expectations of performance. Now people can directly connect with the customer, with companies like they never could before, and the customers, and the companies can direct with their customer directly. Where before you had channels, you had a lot of distribution steps in between. Those things are kind of breaking down. >> I think that's for sure. I mean I think that's sure. I would say beyond that is the ability to empower employees more with some of these tools so you know, an employee used to have to go to the CIO with a work ticket, hey here's what I need. You know these Bots grow virally inside organizations. They're easy to implement. They're easy to see an impact very quickly. So I just think the tools are becoming more facile. It's no longer kind of a hierarchical IT-driven technology base. It's more of a grounds-up technology base, and I think it's gonna drive more speed and productivity inside companies. >> Right, so really it's kind of, there's always a discussion of are the machines gonna take our jobs, or are they? But really there's-- >> Jeff, I'm not that smart really I mean-- >> Well, but it's funny because they're not right? I mean, everyone's got requisitions out like crazy, we need the machines to help us do the jobs. >> Nobody has, nobody has easy jobs. The fact of the matter is, nobody has easy jobs. You know, a company like GE would have 300 ERP systems right? Because of acquisitions and things like that. And the METs not a complexity, manual journal entries, things like that. So to a certain extent these, this automation is really helping people do their jobs better. >> Better. >> More than thinking about you know, where does it all go some day. So I think, I think we're much better off as an economy getting these tools out there, getting people experience with them and, and uh, seeing what happens next. >> Right, it's funny they just showed the Bot store in the keynote before we sat down, and when you look closely, a lot of them look like relatively simple processes. But the problem is, they're relatively simple, but they take up a lot of time, and they're not that automated, most of them. >> One of my favorites Jeff, is doing a quote for a gas power plant would take eight weeks. Because now we have Bots, that can draw data from different data sources, you can do it in two and a half days right? So that's not what you naturally think of for an automation technology like this. But the ability to automate from the different data sources is what creates the cycle of time reduction. >> Right, and you're fortunate, you've sat in a position where you can really look down the road at some interesting things coming forward. And we always hear kind of these two views, there's kind of the dark view of where this is all going with the automation, and the robots. And then there's the more positive view that you just touched on you know, these are gonna enable us to do more with less and, and free people up to actually be productive, and not do the mundane. >> I think productivity, productivity enables growth. The world needs more productivity. These tools are gonna be used to drive more productivity. I think many more jobs will be technically enabled, than will be eliminated by technology. Clearly there's gonna be some that are, that are, that are impacted more dramatically than others. But I would actually say, for most people, the ability to have technology to help them do their day-to-day job is gonna have a much higher impact. >> Right. What do you think is the biggest misperception of this of this combining of people and machines to do better? Where do you think people kind of miss the boat? >> Oh look I mean, I think it's that people wanna gravitate towards a macro view. A theoretical view, versus actually watching how people work. If you actually spent time seeing how a Service Engineer works, how a Manufacturing person works, how an Administrative person works, then I think you would applaud the technology. Really, I think we tend to make these pronouncements that are philosophical or, coming from Silicon Valley about the rest of the world versus, if everybody just every day, would actually observe how tasks actually get done, you'd say bring on more technology. Because this is just shitty you know, these are just horrible, you know, these are tough, horrible jobs right? A Field Engineer fixing a turbine out in the, in the middle of Texas right, a wind turbine. If we can arm them with some virtual reality tools, and the ability to use analytics so that they can fix it right the first time, that's liberating for that person. They don't look at that and say, "Oh my God, if I use this they're gonna replace me." >> Right, right. >> They really need me to do all this stuff so, I think not enough people know how people actually work. That's the problem. >> It's a tool right? It's as if you took the guy's truck away, and made him ride out there on a horse I mean-- >> It's just a, it's just a, you know look-- >> It's just another tool. >> I remember sitting in a sales office in the early 80s, when the IT guy came out and installed Microsoft Outlook for the first time. And I remember sitting there saying, who would ever need this? You know, who needs spreadsheets? >> Right, right. >> I could do it all here. >> Yeah, little did you know. >> So I just think it's kind of one of those crazy things really. >> Yeah, little did you know those spreadsheets are still driving 80% of the world's computational demands. >> Exactly. >> Great, well alright I wanna give you a last word again. You're here, it's a very exciting spot. We call 'em Bots, or robotic process automation for those that aren't dialed in to RPA stands for. As you look forward, what are you really excited about? >> Oh look, I mean I always think back to the, to kind of the four A's really, which is uh you know, kind of artificial intelligence, automation, additive manufacturing and analytics. And I think if everybody could just hone in on those four things, it's gonna be immensely disruptive, as it pertains to just how people work, how things get built, how people do their work so, when you think about RPA, I put that in the automation. It's kind of a merger of automation and AI. It's just really exciting what's gonna be available. But this, this bow wave of technology, it's just a great time to be alive, really. >> Yeah, it is. People will forget. They focus on the negative, and don't really look at the track, but you can drop into any city, anywhere in the world, pull up your phone and find the directions to the local museum. Alright, well Jeff, thanks for uh taking a few minutes of your time. >> Great. >> Alright, he's Jeff Immelt and I'm Jeff Frick, you're watching theCUBE from Automation Anywhere IMAGINE 2018. Thanks for watching. (jazz music)

>> Announcer: Live from New York, it's theCUBE, covering Machine Learning Everywhere: Build Your Ladder to AI. Brought to you by IBM. >> Welcome back to Midtown, New York. We are at Machine Learning Everywhere: Build Your Ladder to AI being put on by IBM here in late February in the Big Apple. Along with Dave Vellante, I'm John Walls. We're now joined by Dinesh Nirmal, who is the Vice President of Analytics Development and Site Executive at the IBM Silicon Valley lab, soon. Dinesh, good to see you, this morning, sir. >> Thank you, John. >> Fresh from California. You look great. >> Thanks. >> Alright, you've talked about this, and it's really your world: data, the new normal. Explain that. When you say it's the new normal, what exactly... How is it transforming, and what are people having to adjust to in terms of the new normal. >> So, if you look at data, I would say each and every one of us has become a living data set. Our age, our race, our salary. What our likes or dislikes, every business is collecting every second. I mean, every time you use your phone, that data is transmitted somewhere, stored somewhere. And, airlines for example, is looking, you know, what do you like? Do you like an aisle seat? Do you like to get home early? You know, all those data. >> All of the above, right? >> And petabytes and zettabytes of data is being generated. So now, businesses' challenge is that how do you take that data and make insights out of it to serve you as a better customer. That's where I've come to, but the biggest challenge is that, how do you deal with this tremendous amount of data? That is the challenge. And creating sites out of it. >> That's interesting. I mean, that means the definition of identity is really... For decades it's been the same, and what you just described is a whole new persona, identity of an individual. >> And now, you take the data, and you add some compliance or provisioning like GDPR on top of it, all of a sudden how do-- >> John: What is GDPR? For those who might not be familiar with it. >> Dinesh: That's the regulatory term that's used by EU to make sure that, >> In the EU. >> If me as a customer come to an enterprise, say, I don't want any of my data stored, it's up to you to go delete that data completely, right? That's the term that's being used. And that goes into effect in May. How do you make sure that that data gets completely deleted by that time the customer has... How do you get that consent from the customer to go do all those... So there's a whole lot of challenges, as data multiplies, how do you deal with the data, how do you create insights to the data, how do you create consent on the data, how do you be compliant on that data, how do you create the policies that's needed to generate that data? All those things need to be... Those are the challenges that enterprises face. >> You bring up GDPR, which, for those who are not familiar with it, actually went into effect last year but the fines go into effect this year, and the fines are onerous, like 4% of turnover, I mean it's just hideous, and the question I have for you is, this is really scary for companies because they've been trying to catch up to the big data world, and so they're just throwing big data projects all over the place, which is collecting data, oftentimes private information, and now the EU is coming down and saying, "Hey you have to be able to, if requested, delete that." A lot of times they don't even know where it is, so big challenge. Are you guys, can you help? >> Yeah, I mean, today if you look at it, the data exists all over the place. I mean, whether it's in your relational database or in your Hadoop, unstructured data, whereas you know, optics store, it exists everywhere. And you have to have a way to say where the data is and the customer has to consent given to go, for you to look at the data, for you to delete the data, all those things. We have tools that we have built and we have been in the business for a very long time for example our governance catalog where you can see all the data sources, the policies that's associated with it, the compliance, all those things. So for you to look through that catalog, and you can see which data is GDPR compliant, which data is not, which data you can delete, which data you cannot. >> We were just talking in the open, Dave made the point that many companies, you need all-stars, not just somebody who has a specialty in one particular area, but maybe somebody who's in a particular regiment and they've got to wear about five different hats. So how do you democratize data to the point that you can make these all-stars? Across all kinds of different business units or different focuses within a company, because all of a sudden people have access to great reams of information. I've never had to worry about this before. But now, you've got to spread that wealth out and make everybody valuable. >> Right, really good question. Like I said, the data is existing everywhere, and most enterprises don't want to move the data. Because it's a tremendous effort to move from an existing place to another one and make sure the applications work and all those things. We are building a data virtualization layer, a federation layer, whereby which if you are, let's say you're a business unit. You want to get access to that data. Now you can use that federational data virtualization layer without moving data, to go and grab that small piece of data, if you're a data scientist, let's say, you want only a very small piece of data that exists in your enterprise. You can go after, without moving the data, just pick that data, do your work, and build a model, for example, based on that data. So that data virtualization layer really helps because it's basically an SQL statement, if I were to simplify it. That can go after the data that exists, whether it's at relational or non-relational place, and then bring it back, have your work done, and then put that data back into work. >> I don't want to be a pessimist, because I am an optimist, but it's scary times for companies. If they're a 20th century organization, they're really built around human expertise. How to make something, how to transact something, or how to serve somebody, or consult, whatever it is. The 21st century organization, data is foundational. It's at the core, and if my data is all over the place, I wasn't born data-driven, born in the cloud, all those buzzwords, how do traditional organizations catch up? What's the starting point for them? >> Most, if not all, enterprises are moving into a data-driven economy, because it's all going to be driven by data. Now it's not just data, you have to change your applications also. Because your applications are the ones that's accessing the data. One, how do you make an application adaptable to the amount of data that's coming in? How do you make accuracy? I mean, if you're building a model, having an accurate model, generating accuracy, is key. How do you make it performant, or govern and self-secure? That's another challenge. How do you make it measurable, monitor all those things? If you take three or four core tenets, that's what the 21st century's going to be about, because as we augment our humans, or developers, with AI and machine learning, it becomes more and more critical how do you bring these three or four core tenets into the data so that, as the data grows, the applications can also scale. >> Big task. If you look at the industries that have been disrupted, taxis, hotels, books, advertising. >> Dinesh: Retail. >> Retail, thank you. Maybe less now, and you haven't seen that disruption yet in banks, insurance companies, certainly parts of government, defense, you haven't seen a big disruption yet, but it's coming. If you've got the data all over the place, you said earlier that virtually every company has to be data-driven, but a lot of companies that I talk to say, "Well, our industry is kind of insulated," or "Yeah, we're going to wait and see." That seems to me to be the recipe for disaster, what are your thoughts on that? >> I think the disruption will come from three angles. One, AI. Definitely that will change the way, blockchain, another one. When you say, we haven't seen in the financial side, blockchain is going to change that. Third is quantum computing. The way we do compute is completely going to change by quantum computing. So I think the disruption is coming. Those are the three, if I have to predict into the 21st century, that will change the way we work. I mean, AI is already doing a tremendous amount of work. Now a machine can basically look at an image and say what it is, right? We have Watson for cancer oncology, we have 400 to 500,000 patients being treated by Watson. So AI is changing, not just from an enterprise perspective, but from a socio-economic perspective and a from a human perspective, so Watson is a great example for that. But yeah, disruption is happening as we speak. >> And do you agree that foundational to AI is the data? >> Oh yeah. >> And so, with your clients, like you said, you described it, they've got data all over the place, it's all in silos, not all, but much of it is in silos. How does IBM help them be a silo-buster? >> Few things, right? One, data exists everywhere. How do you make sure you get access to the data without moving the data, that's one. But if you look at the whole lifecycle, it's about ingesting the data, bringing the data, cleaning the data, because like you said, data becomes the core. Garbage in, garbage out. You cannot get good models unless the data is clean. So there's that whole process, I would say if you're a data scientist, probably 70% of your time is spent on cleaning the data, making the data ready for building a model or for a model to consume. And then once you build that model, how do you make sure that the model gets retrained on a regular basis, how do you monitor the model, how do you govern the model, so that whole aspect goes in. And then the last piece is visualizational reporting. How do you make sure, once the model or the application is built, how do you create a report that you want to generate or you want to visualize that data. The data becomes the base layer, but then there's a whole lifecycle on top of it based on that data. >> So the formula for future innovation, then, starts with data. You add in AI, I would think that cloud economics, however we define that, is also a part of that. My sense is most companies aren't ready, what's your take? >> For the cloud, or? >> I'm talking about innovation. If we agree that innovation comes from the data plus AI plus you've got to have... By cloud economics I mean it's an API economy, you've got massive scale, those kinds of, to compete. If you look at the disruptions in taxis and retail, it's got cloud economics underneath it. So most customers don't really have... They haven't yet even mastered cloud economics, yet alone the data and the AI component. So there's a big gap. >> It's a huge challenge. How do we take the data and create insights out of the data? And not just existing data, right? The data is multiplying by the second. Every second, petabytes or zettabytes of data are being generated. So you're not thinking about the data that exists within your enterprise right now, but now the data is coming from several different places. Unstructured data, structured data, semi-structured data, how do you make sense of all of that? That is the challenge the customers face, and, if you have existing data, on top of the newcoming data, how do you predict what do you want to come out of that. >> It's really a pretty tough conundrum that some companies are in, because if you're behind the curve right now, you got a lot of catching up to do. So you think that we have to be in this space, but keeping up with this space, because the change happens so quickly, is really hard, so we have to pedal twice as fast just to get in the game. So talk about the challenge, how do you address it? How do you get somebody there to say, "Yep, here's your roadmap. "I know it's going to be hard, "but once you get there you're going to be okay, "or at least you're going to be on a level playing field." >> I look at the three D's. There's the data, there's the development of the models or the applications, and then the deployment of those models or applications into your existing enterprise infrastructure. Not only the data is changing, but that development of the models, the tools that you use to develop are also changing. If you look at just the predictive piece, I mean look from the 80's to now. You look at vanilla machine learning versus deep learning, I mean there's so many tools available. How do you bring it all together to make sense which one would you use? I think, Dave, you mentioned Hadoop was the term from a decade ago, now it's about object store and how do you make sure that data is there or JSON and all those things. Everything is changing, so how do you bring, as an enterprise, you keep up, afloat, on not only the data piece, but all the core infrastructure piece, the applications piece, the development of those models piece, and then the biggest challenge comes when you have to deploy it. Because now you have a model that you have to take and deploy in your current infrastructure, which is not easy. Because you're infusing machine learning into your legacy applications, your third-party software, software that was written in the 60's and 70's, it's not an easy task. I was at a major bank in Europe, and the CTO mentioned to me that, "Dinesh, we built our model in three weeks. "It has been 11 months, we still haven't deployed it." And that's the reality. >> There's a cultural aspect too, I think. I think it was Rob Thomas, I was reading a blog that he wrote, and he said that he was talking to a customer saying, "Thank god I'm not in the technology industry, "things change so fast I could never, "so glad I'm not a software company." And Rob's reaction was, "Uh, hang on. (laughs) "You are in the technology business, "you are a software company." And so there's that cultural mindset. And you saw it with GE, Jeffrey Immelt said, "I went to bed an industrial giant, "woke up a software company." But look at the challenges that industrial giant has had transforming, so... They need partners, they need people that have done this before, they need expertise and obviously technology, but it's people and process that always hold it up. >> I mean technology is one piece, and that's where I think companies like IBM make a huge difference. You understand enterprise. Because you bring that wealth of knowledge of working with them for decades and they understand your infrastructure, and that is a core element, like I said the last piece is the deployment piece, how do you bring that model into your existing infrastructure and make sure that it fits into that architecture. And that involves a tremendous amount of work, skills, and knowledge. >> Job security. (all laugh) >> Dinesh, thanks for being with us this morning, we appreciate that and good luck with the rest of the event, here in New York City. Back with more here on theCUBE, right after this. (calming techno music)

>> Announcer: Live from Washington DC, it's the Cube, covering .NEXT Conference. Brought to you by Nutanix. (electronic music) >> Welcome back to .NEXT everybody. This is the Cube, the leader in live tech coverage. We go out to the events and extract the signal from the noise. My name is Dave Vellante, and I'm with my cohost, Stu Miniman. This is day two of .NEXT. Dr. John Bates is here. He's the CEO of TestPlant, and author of Thingalytics. Sir, welcome to the Cube. >> Thanks. >> Nice to have you on. >> Nice to be here. >> Thingalytics, everybody's talking about things. >> This thing, that thing, the refrigerator, the iode things. What's Thingalytics? >> Well, things, i.e. connected devices, sensors and so on. They're not very interesting unless you actually do something with them. So you search through all that data that's coming out for the opportunities and threats to your business, for example, and then you act on it, while you've got time and perhaps, beat your competitor. So, Thingalytics is about smart, big data analytics, and the internet of things coming together. >> Okay, and what's the premise of the book? >> Well the premise of the book is, you know, everybody thinks, I mean if it's one message from it, it's IoT is not so hard to get into. So get started. You know, start small, and here's some lessons of how you can do it. And here's some stories from different industries of how thought leaders, you know, like Coca Cola, or GE, or many different companies, Medtronic, in different industries have actually got started and really been extremely disruptive in what they've done. >> And is this getting started, is this all for companies, or are you seeing individuals that can also participate? >> You know, I do have a chapter in there about the Smarthome. So, obviously that's the aspect where the individual is going to come. But you know, I think it's really the real winner in this will be the industrial and the enterprise, Internet of Things. I guess that the key message is for business leaders. >> Do you think that given that there's, the internet of things requires things, and there's so many things that are installed by these big, industrial companies that the whole IoT thing will be maybe less of a disruption than it will be an evolution of companies like GE, and Siemens and Hitachi, and guys like that. Is that a reasonable premise, or will we see a whole new wave of companies? Certainly we'll see startups come in, but will they attack these big industrial giants, that have been around for a hundred years? >> You know, this is a really great question, and I think that, at the moment, the opportunity is in the hands of the big buyer. You know, keynoting at .NEXT, Bill McDermott coming in to do his presentation. I sold my IoT platform company to SAP. And why, for example has SAP got an amazing opportunity? Because they've got all these applications, they've done an amazing job of taking ERP and adding a whole load of applications: financial planning, supply chain, business networks. But those applications model the real world. But they're not connected to the real world. So what happens when you take a model of a financial model about the value of a factory or a mine, and connect it to the real world. Suddenly, it's not theoretical. It actually is calculating in real time, the value of those assets. The supply chain is really about that. So, SAP is an unbelievable opportunity. IBM has an unbelievable opportunity. GE has an unbelievable opportunity. But it's going to be how they execute, and is someone going to come in, and do something unbelievably disruptive we haven't even thought about. So, those guys need to make all the running right now to really protect themselves. >> I wonder if you could comment on this. I see some of the execution risks as what Jeffrey Immelt said, "I went to bed an industrial giant," "and woke up a software company." >> John: (laughs) Yes. >> Wow, it's hard to be a successful software company. So, is that one of the many execution risks? Are there others? >> I think you're absolutely right. I mean, if you take GE for example, my friend, Bill Ruh. He's the chief digital officer, the CDO of GE Digital. >> Dave: We know him, yeah, sure. >> Yeah, he's awesome. Completely new business, but it's really hard. I think that's taken longer than they expected to build up that Predix platform. And are they going to be the people, it depends what business you're in. If you're the business of buying aircraft engines, then rather than buying an aircraft engine, you want to buy engine as a service. So that's the kind of the thing that maybe you'll buy from GE, or maybe it's one of GE's partners and GE provides the infrastructure. But I think they've learned that's really much harder than they thought. And I think everybody's sort of discovering that. It's not so much the thingalytics, I've realized, it's the thingonomics, the economics of the internet things. That's the really important thing to get right. >> We actually worked with GE when they were coming out with the Industrial Internet, and we did a lot of interviews. There's some of these barriers that we're going to hit along the way. As a matter of fact, at Wikibon, our team that works on it, they call it the Internet of Things and People because there's so much that needs to happen to be able to move forward. Some of them are just old industrial things, some of them are regulations, some of them are the mindsets. How do you see some of these, what do you see as some of the major barriers, and how do we knock them down to be able to accelerate this even more? >> Absolutely. Well, first, you're absolutely right. One of the key barriers is a cultural barrier, or a, oh, that's just too hard, getting back to why did I write Thingalytics. And I think it's a question of people have just got to get started, not try and boil the ocean, and try and get some successful projects going. But definitely there's a cultural thing, and you just have to get those people together that think differently. And there's a reason why this new role of the Chief Digital Officer was created, but you can have many Chief Digital Officers throughout your company, just sort of get them together with that thought. One of the other things I can bring up that is really, really hard and why I went from being in the core of the IoT platform world into a company that's a software testing company, when you're going to launch this stuff, how do you, de-risk it, how do you make sure, in this world where there's all these sensors at the edge, all these strange mobile devices on the front end, and the cloud in the middle, how do you make sure you test that? It's a really complicated distributed architecture, that requires completely new technology. You don't even own the code, so how do you test that? So there's a whole load of issues there, but I think you have to put at the heart of it, think differently, think digitally. >> So what's the company you sold to SAP? Tell us about that. >> So the company's called Plat.One, and it was one of the leaders in platforms, software platforms, to enable Internet of Things application. So the idea is that you're going to build an Internet of Things application. You could start and hardwire, start writing some code and hardwire against all these devices and sensors, but then you start shipping your applications. What about if you made the wrong decisions? What about if you spent years just writing all the integrations to your factory floor, or your logistics networks? So, there's a whole load of common protocols out there, in machine to machine, and they call it a new Internet of Things protocols. Plat.One, new and could talk to all these protocols and make machines talk to each other. It could virtualize that, so that you disconnect those protocols from the application you write. So you're modeling things like, in a Smart city, truck and streetlamps, rather than bits and bytes. So then when you change the implementation from one city to another, you're future-proofed. And then graphical tools to model and plug them together, and a platform that manages microservices at the edge and the cloud. So you're managing an adaptive platform that you can place logic, depending on what it is. And that enabled SAP to rapidly roll out ITOs. >> And your company had customers? >> Yeah, a lot of customers, people like, you know, a great customer, Pirelli. Pirelli, obviously a tire manufacturer as you know them, but what they can do, if they plug sensors into their tires and have telematics boxes on tops of trucks or vehicles, suddenly they can go to the fleet management markets and sell them big data analytics because they know where the trucks are, they know how they're being driven, and what's more, rather than selling you a tire, they could lease you a tire as a service because they can track it, they know how much use you've got out of it. Unbelievable new thingonomic models. So, that's an example, flextronics, T-Systems, we had a whole lot of interesting smart cities using it, logistics, manufacturers. So yeah, it was a great, but early stage company, and you have to ask yourself the question, can you, as a small company, win, or would you be better off partnering with an SAP with that unbelievable reach? >> One of the things, I've got a networking background, we hear all these new protocols and the maturity there, there's the security risk there. I hear the fleet of trucks that was like, oh wait, I might turn off these sensors or do something malicious. The surface area has just grown by orders of magnitude. How do we address this as the industry? What is some of the advice you're giving for this? >> You're absolutely right, 'cause when we were talking about the issues earlier, that's a corker, isn't it, you know, the security of it. And as a Tesla owner, it was great when hackers tried to hack into the Tesla and they couldn't. All they could do was make the horn go beep. Which you can do from your app on your phone, anything that was publicly there, but couldn't take control of the car. That was great, that was nice. But with all this highly distributed model, you've got to be able to have end-to-end security. So in Plat.One for example, we had the ability to have role-based, end-to-end security right from the application to the device. And that was part of the platform, so you got that for free. But you've got to make sure that's the case in your applications. >> What's the opportunity for jobs in the growing IoT economy? >> You know, IoT giveth and IoT taketh away. (Dave laughs) We're all thinking let's bring more jobs back to America, which is a political thing at the moment. But are these jobs are going to be replaced by robots? I mean, is there a global issue, which is, are these jobs going to be replaced by robots, and by algorithims? The answer is yes, but on the other hand, are more jobs going to be created? Are people going to become much more productive? So I think humans are going to become more productive, for sure, for things like smart factories, smart cities, and life's going to get better in smart cities, but yeah, we're also going to lose jobs. I draw an analogy to trading, financial markets trading, where we used to have traders in the pits waving pieces of paper, then it went to Bloomburg terminals where people entered their trades automatically, then it went to algorithmic trading and high frequency trading where algorithms run it. Still humans involved, but less and less. But the humans are more productive and more coordinated. >> Hey, what if we put a 30% tax on all IoT-related initiatives, that would help preserve jobs. (John laughs) So tell-- >> Wouldn't slow down innovation or corporate profit or anything like that. >> Hey, here's an idea for you, Since we're in Washington I thought I'd throw out some good ideas. >> (laughs) Yes, exactly, very topical. >> So, tell us about your software testing company, TestPlant. >> So, the reason I was really excited to join TestPlant is there's this new world, you put IoT together with the mobile world and the cloud world, and you have the world of digital. How do you make sure that in this new digital enterprise that everybody's going to compete in, that you're, how do you make sure you're doing well, and how do you make sure your stuff works, and how do you make sure you're beating your competitors? So, TestPlant's all about end-to-end testing of the digital experience. It's taking testing to a new level, 'cause if you think about testing, it used to be about, does your code work? Now, it's about, are you offering up an unbelievable, delightful digital experience to your customers, because testing now has become a profit center. It's the differentiator between you doing an amazing job of launching an app and getting five stars in the app store, or crashing and burning because something's gone down, or there's a usability issue or there's a problem. So that's what we do, we test applications using artificial intelligence through the eye of the user, we actually, our algorithms actually use the applications and connect to the APIs and can take control and automate the testing process and discover these business metrics and show customers what good really is. >> So John, you were the founder of Plat.One, is that right? >> So I was an early joiner of Plat.One, I was the CEO, I wasn't the founder, we have two amazing founders. >> Okay, but you helped do the initial raise? >> Yes, exactly, and I took it from an early interesting technology to the company that got bought by SAP >> Made it viable, and sellable, you're an investor, I heard you say. >> John: Yes. Okay, now you're an author, you're CEO now of an more established company, right? >> John: Yes. >> Jack-of-all-trades here, well, maybe that's not a fair term, but you do a lot of different things. What are your thoughts on which things you enjoy the most, where do you see all of this headed? >> Well-- >> Polymath is the word I was looking for. (John laughs) >> Well, I started off actually as a professor, a university professor, and I took some of my research and started my first company. I loved building a start-up from scratch, and taking that as a first streaming analytics or real-time analytics company, and I then spent over a decade as a C-level executive in public software companies. But I haven't had so much fun as what I'm doing right now. It's beautiful, it's sort of mid-sized, really great private equity, backers, the Carlyle group, so I love what I'm doing right now, it's definitely my favorite gig, so far, I think that's the nice sweet spot for me. >> That's great, well, John, we love having big brains in the Cube, Stu and I, and it rubs off a little bit, at least we think it does, so thanks very much for coming on. >> John: Thank you gentlemen. >> You're welcome, alright, keep it right there, buddy. We'll be back with our next guest. We're live from Nutanix NEXTconf, this is the Cube.

>> Voiceover: Live from Orlando, Florida, it's theCUBE, covering ServiceNow Knowledge17. Brought to you by ServiceNow. (upbeat electronic music) >> Welcome back to sunny Orlando, everybody. This is ServiceNow Knowledge17 #Know17. I'm Dave Vellante with Jeff Frick. John Donahoe is here as the newly-minted CEO and President of ServiceNow, fresh off the keynote, fresh off 49 days in. John, welcome to theCUBE, thanks for coming on. >> Thank you very much, it's great to be here. >> John: So how'd you feel up there? You had the theater in the round, you were working the audience, I loved how you walked on the stage and really got into it. How's it feel? >> Well, what I love about ServiceNow, is it's a community-based business and a community-based company. And so, we had 15,000 members of our community out there, and that community feeling is, I think, one of the real powers of the movement that's called ServiceNow and of the ethos of this company. So, I loved that, I fed off that energy. >> So, at the risk of some repetition, a little bit of background about yourself, a former Bain, former eBay CEO, you shared that with the audience. What is relevant about your background to the ServiceNow experience that you expect to have? >> Well, you know it's funny Dave, I spent the first 20 years of my career at Bain doing business transformation. And a lot of what I talked about today was digital transformation, that is, every company is trying to transform. And I spent the first 20 years of my career focused on that. And then we talked a lot about great customer experiences. Well, the consumer world and consumer-based applications like eBay, or PayPal, or many other consumer applications, are defining the new standards of what kind of easy, simple, intuitive experiences are possible. And employees are consumers at home and they're increasingly expecting the same kind of great experiences they have at home at work, and as customers of enterprises. And so I think you're going to see the world of consumer and enterprise converging. And so that's why I'm very excited about being a part of ServiceNow. >> So, you talked to the audience, as I say, about your background. You're a family man, you've got Four children. >> John: Yeah >> Jeff: Pictures on stage; which I love. You know, it really kind of goes with the folksy, you know, history of this company and the community base. Not too many people put their family photo up on the keynote. I thought it was great. >> John: Yeah, well, they're my bosses, so... (all laughing) >> Dave: Well, like you said, they make you humble >> John: Yeah. >> Dave: and you learn a lot from them, so... So I appreciated you starting that. I've got Four kids, Jeff's got kids, and so... >> John: That's great. >> Dave: And you're hosting a women in tech breakfast tomorrow, a real passion of ours, so, maybe talk about that a little bit. >> Well, I just think it's really, really important. And, people ask me: "Why do you think that way?" I think it's good business, right? At the end of the day, the ultimate thing we do to succeed in business is we need to attract, develop, and retain the very best people, >> Dave: Right. >> John: and by definition, 50% of the workforce is female. And so, to not be aggressively trying to cultivate that part of our team is to miss an opportunity. And doing it well is hard, but if you do it well, it could be a source of competitive advantage. So, I care deeply about it professionally, and then also personally as a father of a daughter, the question I ask men that have daughters and say: "Do you want your daughter to grow up and be part of a work environment that's even better than the one they would have been if they'd come at your time?" And almost all of us say, "Yes!" >> Jeff: Of course >> John: So, it's a responsibility we all share. >> So, I want to ask about your management philosophy. You know, I've heard the term, of course you have too, "benevolent dictator". You use the term, >> "servant leadership". >> "servant leadership". >> John: Yeah. >> Dave: Which starts at the customer on top. Explain your philosophy there. >> Well, it's a way I learned to lead early in my career; which is: that it's the opposite of a classic pyramid. Right, where the CEO's on top and everything's underneath. No, this is an upside-down triangle, where the reason we're here is to serve our customers, to serve our employees as they serve our customers, to serve the purpose and to the extent you can, to serve the communities in which we are part of. And my experience is that: building that deeply into the culture of a company breeds a level of commitment and a level of long-term orientation that's really important. And ServiceNow's had that from the beginning. Think about Fred Luddy embodied that. He was a brilliant technologist, and he said, "You know what, I'm going to recruit a CEO" "before the company goes public who has those skills." So, he recruited Frank, right? And Fred stayed involved. Frank embodied servant leadership. Frank could've stayed forever. Frank said I was the right CEO to serve this purpose from 75 million to a Billion Four. And then he started to looking for someone that's the right person to serve for the next generation; which is me. So this notion of stewardship, we're all here to serve our customers and try to make our purpose come alive over a long period of time. And I think it's the most enduring motivation and inspiration we can have. And it keeps the customer front and center. >> Well, so one of the first things you did in your first 100 days, you said you wanted to see 100 customers, you actually accomplished that in 45 days. So, first of all congratulations, first of all how'd you do that? (all laughing) >> Well, I went at a roadshow to 10 cities across the U.S. and just packed my days full of meetings with customers. And they were individual meetings, and we had some group meetings, some lunches and dinners. And those are some of the best because you get a conversation going. I had Four or Five, Six customers around a breakfast table or dinner table and we start talking about their issues. And, the dynamic in every situation was they would start sharing with each other. They would say, "Well, how are you addressing this?" And they'd starting saying they have similar issues, similar challenges, similar ideas of how they're going to address it. So, the power, that community power, I was seeing firsthand in smaller settings. And for me, it was just so energizing because our limitation of how quickly we can get better is well we understand our customer's needs, and also understand their feedback about where we can get better. >> Well it's interesting, you said you were a customer when you ran eBay... >> John: Yes. >> Jeff: of ServiceNow, so that's kind of some of your background knowledge of the company. When you went out on your tour, what were some of the things that surprised you that you didn't know even though you had been kind of a ServiceNow customer in the past? >> Well, I think what I hadn't fully understood was the power of the ServiceNow platform, and how it's getting pulled into new areas across the company. So, it's getting pulled to customer-facing applications, customer-facing processes like Ashley at GE is talking about. >> Jeff: Right. >> John: And it makes sense, right? I know at eBay and PayPal, we really worried a lot about how do we handle inbound contacts from our users. And password reset was the #1 inbound contact. (dave laughing) Well, password reset is a perfect process that can be handled in an automated in a self-help way; which is ultimately what the customer wants. >> Jeff: Right. >> John: And ServiceNow can help enable that. And so, as I was sort of surprised and delighted by how this platform is getting pulled into new use cases, that in many ways are back to what Fred Luddy imagined when he founded the company. The interesting thing is, Fred founded the company as a platform to serve all services, businesses, business processes across the enterprise. And then, but platforms don't generate revenue, They don't sell. So, he found an application: ITSM; which was the first application, and it took off. And so ServiceNow began to be known as the IT company. But that was never what Fred envisioned. It was a company that enabled and empowered IT to simplify and automate and transform the entire company. >> It's interesting, password reset. Because it seems like such a simple process. And it doesn't necessarily seem like a high-value process. But in fact, it's hugely high-value for the customer. It's hugely cumbersome in terms of the time it takes. So, to automate something that seems so simple as password reset, has huge implications in terms of efficiency inside and customer satisfaction on the outside. What a great example. >> Well, and here's what's so interesting about that example: Is, it touches multiple parts of the company. Because, people actually, your password is your security. And you could automate changing it in a way that was insecure. But, you've got to do it in a way that it's the convenience that we want to reset our passwords, but we want to know we're safe. And so, that password reset flow has to touch security, it has to touch engineering, it has to touch operations and customer support, it has to touch the customer's record, and so it's a classic multi-function, multi-discipline flow, but you want to make that easy and simple for a user, and yet also have them feel safe. Simple and safe is hard to do. >> John, you mentioned Ashley from GE, I want to talk about digital transformation. It's one of those terms you hear a lot at these conferences, sometimes it's amorphous, it's kind of like A.I. We'll talk about that if we have time. But Jeff, I love your quote. We follow GE quite closely, and Jeffrey Immelt said: "I went to bed an industrial giant," "and I woke up a software company one day." >> John: Yep. >> Dave: And you see this everywhere. So what is digital transformation to you and the customer's that you've been talking to? >> Well, here's, technology and software in particular on one hand is disrupting every company in every industry. I view that as a motivation. I view that as a wake-up call for all of us, including a software company. And, software is an opportunity. An opportunity to make changes and advancements at a pace and a magnitude that's been unparallelled in business history. So every company needs to define how they're going to use technology, how they're going to use software, how they're going to use digital capability to their advantage. To their advantage with their own consumers, their own customers, either industrial customer or a consumer in a consumer business, and how to use it to change the employee's experience and improve it. So, employees are spending time not on manual tasks; which now can be done by technology, but on higher value-added activities, and then how you can operate a global enterprise in an effective and efficient manner. And so, technology is an offensive weapon if you will, an offensive tool, is something that's on the mind of every CEO, and every company. And that's where they're looking for how do they have a few trusted partners. A few trusted technology partners that help them navigate their way through that, help them drive their way through, and that's ultimately what ServiceNow is. >> So these are big ideas, and they involve a lot of different constituencies within your customer base. Obviously, your IT peeps, as we like to say, but the CIO, who's role is changing, and also the line of business folks. So these are big, heavy lifts that you can't do alone. You've got to have an ecosystem to do that. When we did our first Knowledge in 2013, the SIs were a lot of companies frankly that we never even heard of. And now, you're seeing all the big SIs. I don't even want to name them because I'll forget some. But, your partner strategy is critical to achieving that vision that you just laid out, isn't it? >> Absolutely, Absolutely. Because it takes both of us. It takes our software and then their capabilities to help our shared customers, shared clients, implement the software, and do it increasingly in a way that is as configurable as possible; which means as minimum customization as possible, and also as quickly as possible. And our partner ecosystem's an essential partner in doing that. And there's the big SIs, and then also some of the smaller ones. I spent some time with customers in some smaller cities where they're saying having local capabilities, local teams, that were trained and certified on ServiceNow was really important to them. Often they end up being acquired by or joining the bigger SIs over time, but that sort of grass roots opportunity. Because that's also job creation. That's job creation in communities. I got to see how talented, computer-literate, software-literate people in different cities around the world are seeing an opportunity to create a livelihood by helping customers integrate ServiceNow in the most effective way. >> So two years ago, Frank Slootman in his keynote said that the CIO's role is changing and they're becoming business people. >> John: Yes. >> Dave: And kind of challenged CIOs, if you don't speak wallet you better start learning that language, the "lingua franca" of the business. So, you obviously agree with that. But, how is the CIO role changing, and how does it support other roles within the organization, that you're trying to apply ServiceNow to? >> Well, I have a really, Jeff, a really outside-in... Or, Dave, really outside-in...sorry about that. >> Dave: It's alright. >> John: I've had a lot of names this morning. >> Jeff: I'm sure you have. >> Dave: That's pretty good. >> John: Outside-In view of this. Which is through the eyes of the customer, alright? The CEO is thinking about: "Alright, I've got to serve our customers better," "I've got to retain our customers" "and serve our customers better." "And then I've got to tract and retain employees" as we've been talking about. "And I need the digital capability," "I need technology to help us do that." Their going to turn to the most technically-literate person in the C-suite to help do that. That's the CIO, right? And so the CIO by very definition has to play a broader role of partnering with the business unit leaders, with the functional leaders, to drive that end-to-end business transformation or digital transformation. And the CIOs that I met are ready to take on that challenge. They couldn't have done that before the cloud technologies that give them the ability to play offense. But these cloud technologies now cut across, they don't just sit in IT, they cut across all of the enterprise. >> Jeff: Right, right. >> John: And so, I would say there's almost this gigantic sucking sound, if you will, to use an old Ross Perot-ism, that IT and the CIO are being asked to play this role, be change agents, strategic change agents, across the enterprise. And they're ready to do that, but they do need to speak business in business terms, and business value, and business value means: Are we serving our customers better? What's our customer NPS? What's our customer response time? What's our customer retention? They need to speak employee value terms: What's our ability to retain our best employees? What's their satisfaction? And then of course they have to speak the business terms of efficiency, right? Are we being more productive and more efficient as we're serving our customers and as we're serving our employees? And so, the CIOs I met and the IT professionals I met, are asking for help to translate what they do into that business language. And the very best ones are doing it. And I think you'll see that trend continue more and more. >> And they've got to have automation, and they've got to have efficiency because their budgets aren't going up commiserately with their increased responsibility to drive this digital transformation. So they've got to wring that extra value out of the tools and processes and people that they have, and that's where you really help them quite a bit. I think I saw a quote the other day that someone went from 60 days to Two days in a business process, amazing. >> Well, and it's interesting because companies are investing more in technology than they ever have. If you take the broad technology spend, they're investing more in technology. But, they expect to get productivity and efficiency, not just out of IT, but across the entire enterprise. >> Jeff: Across the board. >> John: And that's the opportunity: More investment, greater productivity, greater value for customers and employees. >> You talked yesterday to the financial analyst about the sort of execution machine that you inherited. Personally, I think you have a great CFO, one of the best if not the best in the business. So I presume you're not going to be spending a lot of your time trying to restructure reporting and counting beans, no pejorative intended there. So, what do you bring to the organization? Where are you going to spend your time? And what are your main goals over the next mid-term and long-term? >> Well, as you said, I'm blessed. Mike Scarpelli, I think, is a world-class CFO and the best in the industry and I'm honored and thrilled to work with him. Same with Dave Schneider and Kevin Haverty who run our sales force. And now CJ Desai, our Chief Product Officer, Dan Rogers, we've got a really strong team. My focus is to have us continue our current momentum, continue the current execution that we're focusing on. But then, to begin to sort of chart a course for 2018, 2019, 2020, and beyond as we go from being a billion-dollar company, to a four, to five-billion dollar company, to beyond to a 10-billion dollar company. And the nice news is that it's building on top of this very solid foundation. As we evolve from being what has been an IT-focused platform company to be more of a digital transformation platform and company. And helping our clients, helping our customers, achieve their aims and their goals, and being one of the few trusted technology partners. Every company has a few trusted technology partners and we want ServiceNow to be one of those. And, to do that, you've got to be viewed as mission-critical and adding real value, both of which I think we are. >> Dave: So you could joke, you know, don't mess it up. >> John: Yes. >> Dave: Okay, and take it to another level; which really is kind of what seems to be your expertise. Bringing it into the line of business is talking to the CEO and other C-level executives. And actually, marrying the expertise of the CIO has cross-organizational purview, leveraging that capability and super-powering that. >> Exactly. Exactly. You know, it's interesting. If I were to look back on the last 15 years, the C-suite role that has changed the most in the last 15 years has been that of the CFO. 15 years ago CFOs were being counters. >> Dave: Yeah. >> John: Right? Today, as you said, as Mike Scarpelli and Bob Swan, my previous CFO at eBay and the best CFOs, they drive value across the enterprise. Right? They're almost COOs in their mindset. They work with business units, and they add enormous value. So that job has become significantly more important and powerful. I see the same thing happening with the CIO over the next Five to 10 years where the CIOs role with grow, and expand, and broaden. And that's exciting. >> Well, you know, one of the things, actually, you know, we come to these conferences, and there's obviously a lot of messaging, but we try to understand how that messaging actually fits with what customers are doing. One of the things that you guys are messaging this year is light speed. And so, when you talk about the CFO and the changing role, it brings up, to my mind anyway, light speed requires a new set of metrics, and listening to, like Scarpelli, talk yesterday, he's all over the metrics. And these aren't, you know, your typical, you know, EBITDA metrics, they are just a new set. Do you see that happening within, not only ServiceNow, but within your customer base, where the so-called, I'll call them, "light speed" metrics are emerging? >> Absolutely. I mean, you saw the example of Dave Wright going through the machine learning, and how the machine learning capability, when applied to the ServiceNow platform, applied to specific problems, helps you fix problems before they happen in an automated fashion. Imagine that, right? That's light speed. Dave said it so well on stage. (all laughing) That's even faster than light speed. And so, you begin to see, alright, how do you measure, in delivering a great customer experience, how do you measure the reductions of problems? How do you measure the prevention of problems that provides greater availability, greater reliability, greater consistency, of a customer's experience? Now, ultimately that measure will be in customer NPS or some other customer metrics. But, some of the subordinate metrics I think you will see a growing number of what I would call L2, L3 metrics, that is, a dashboard of how to run a great company around customers, employees, and financials. >> Alright John, I know you're super busy, we've got to leave it there. Thank you so much for coming on theCUBE and congratulations on the role, great keynote, and best of luck. We'll be watching. >> John: Thanks very much Dave, thanks >> You're welcome, alright. >> From me, congratulations. Keep it right there, buddy, we'll be right back with our next guest. This is theCUBE, we're live from ServiceNow, Knowledge17. Be right back. (upbeat electronic music)