 From Orlando, Florida, it's theCUBE. Covering ServiceNow, Knowledge 17. Brought to you by ServiceNow. Hi everybody, we're back. Welcome to Knowledge 17. This is theCUBE, the leader in live tech coverage. Chris Pope is here, he's with the office of the CSO, longtime CUBE alum, our friend. Good to see you again. You two guys, I think it's the fourth year now. This is the fifth. Fifth year. Yeah, cool, good stuff. So we're even up to, you move back home? Yeah, so my role is global. I'm quite fortunate to travel this planet and meet all our amazing customers around the world. But I think you would have seen in the keynotes and different things, IT's still core to what we do, but there's so many sort of strings to the bone now in terms of HR, customer service, the ITOM piece, security. And we still have building apps on the platform, which is a major part of what we do. So yeah, busy as ever, or more busy. And when you surround it by, you know, 15,000 and you close his friends, it's kind of a good party. So let's talk strategy a little bit. We've seen you guys execute on the strategy that you laid forth a couple of years ago. Right. You know, taking IT service management, bringing that through the rest of the organization. Seems like ITOM is really big and solid, but you got all these other pieces. I'm really personally really excited about the security piece. We've been talking HR now for a couple of years. That seems to really be picking up. The global 2000 is really rocking. So talk about the execution of that strategy and where you go from here. Yeah, I think, you know, it's fairly easy to launch a product, right? At the end of the day, the platform is there. We can do lots of different things. A lot of the challenges then come, you know, if you've got sales guys and field guys that have grown up in IT and selling ITSM, it's a different selling motion. You know, the way you talk to HR, the way you talk to customer service people, you know, who often sit truly in a business line and are not familiar with the IT stuff. So for us, it's been a lot about growing that organization. You know, 18 months ago, we turned the company upside down, went through a more sort of business line structure, aligned the product teams, aligned the field, and, you know, had product specialists and implementation specialists in the field so that, yeah, we've got a customer that's done ITSM, great, now let's do the HR thing. It's a different set of people that you talk to but also implement as well. So I think from that standpoint, you know, Frank always talked about flawless execution and, you know, that's what it's all about and that's what we've been able to achieve, that, yeah, we could, you know, go into any market at the end of the day, but the product's just a bomb part of it that helps a lot, but then, if you haven't got the right people selling it, the right people implementing it and supporting it, you're just going to fall flat on your face. So it's often not that we're late into anything, we do it at the right time for us and the customer and that then the field can just go and nail it on a scale that just really disrupts and obviously is wildly successful for us. Something that's relatively new, well, certainly new at this conference is all the talk about machine learning and AI and deep learning and, you know, we sort of stumbled into a service now during the big data ascendancy and we used to ask about data and is there a big data play here? And we'd sort of dance around that but you guys are going straight into AI. Talk about that a little bit and where it fits. Yeah, so again, you know, we could have done these things for a while, everyone's talking IoT and all these other things but again, what problem are we actually solving? Too often we think about how we solve with a solution without actually really understanding the problem we want to solve in the first place and you ever seen this morning from Dave, the certain use cases that we want to go after. I was fortunate, we ran a hackathon in February this year with a large customer and they looked at attrition and a problem for them as a company and they ended up using AI and machine learning to solve it whereby they linked, you know, the annual survey of employees not only to the performance data but also system data in terms of, you know, people being onboard and off-boarding and then based on how you responded to the annual survey they were able to predict within a certain tolerance you're a happy employee, okay, you had a bad year we'll take care of you or you're actually a poor performer you're not happy with a company, let's let you go because let's just shortcut that process and really focus on the people that we want to focus on. So, you know, a HR use case that no one's talked about with AI and ML whereas if you come it the other way, right, what's the problem we want to solve and then what do we already know? If you've got three years of employee data you can get a lot of learning from that quickly from a machine probably overnight versus if I ask you to go off and do it you'll probably come back with analysis in a couple of weeks and by the time you've done that it's already changed. So it's really about solving particular use cases in that space and certainly a lot of what I talk about with IT customers is saying, you know, his Dave, he works in the network team he's fairly good at what he does he's about to execute this change or something it may be as an overall team they're fairly successful but the service he's touching is a bit wobbly it's not been that great lately. Hey, there's a 72% chance that this thing might go wrong. That's going to raise a flag pretty quickly versus historically we've had change managers and so-called domain experts have that decision making which just creates tension in the organization, right? Well, why do you know better than me of what I'm doing? And this way we're saying, well, the machine tells us X you know, and the machine's trained over time on your performance. So let's use that to guide us and have a different conversation and more data driven and factual driven. How are people taking advantage of this capability and how do I engage? Do I, does it just show up in the platform? Is it something, a module that I apply? Yeah, so the plan is it actually sits in our platform BU, right? At the guts of the core where the orchestration engineers as well, right? So whether it's IT, HR, customer service security doesn't matter, it's in the guts of the platform which then means the BU's and the applications have to figure out how they leverage the capability. Not let's go and figure out what we do for AI. Well, we've got that in the core. What problem does security solve? What does customer service solve? You know, virtual agents on the service system. The core competency is there and then because it's in platform, if you come along and say, hey, we're going to build a new app on the platform that service now doesn't ship. Wow, it also has AI capability with it. That is a step change in what people can do and not another thing they have to go and figure out and source and understand. It's all there in the box, right? So the toolkit they have is very, very powerful and suddenly, you know, so we're looking to launch that at the end of this year probably in the K release. They've now gotten a complete machine learning capability tied to ITSM. You know, a HR talking about AI and ML, probably not but think of what they could leverage from it in terms of context, sentiment and, you know, how that information comes together, which is very tech space, right? In terms of surveys and appraisals and all those type of things. Massive learnings very quickly and what did they ever have to do? Upgrade to our next version. Super simple. So there's a lot of talk in the data world. You got the various personas. You got the data scientist, you got the data engineer, the quality engineer, even the application developer is becoming, you know, more oriented like John Furrier says, data is the new development kit. But your developers are different, right? You got a spectrum of low code, heavy code. Yep. You know, there's a dev ops craze going on. So how does this AI trend affect development specifically in the ServiceNow platform? Yeah, I think it gives us deep learning, right? What do our customers actually do? So if we look at sort of just from a, when we look at our customer instances, what are they doing? What are they changing? Not just the data that's going in the tickets or the requests, but what are they actually doing to the platform? What are they changing? Why are they changing it? You know, they write in scripts or they write in business rules. And for us, there's a selfish learning there. We can say, well, actually that might drive our next set of features or whatever, because if more than X are doing it, then surely it's a core competency we have. I think then when you go beyond that, you know, we get too sort of engrained in what the data is and it's massive, right? And the problem becomes very big. Whereas the machine and the learning can give you, right? Maybe it's just a 20% of the problem and we have to fix, not try and figure out the 100% and really focus down on what we want to solve, not necessarily how we solve it, but just figuring out the compute layer and do we put it here? Do we put it there? Do we go with this storage? That's the complexity. We're removing that complexity and decision making and just saying, well, if we give you the data or you give us the data or even we train on it, we learn it and we say, hey, here's five different options. What's the right one for you for the situation or problem that you want to solve at this point in time? Given another month, it could change, right? We all know that changes. And I think in the DevOps space, it's really interesting in terms of, you know, we're deployed quickly all the time iteratively. Well, that's great, but what are we learning every time and are we continually improving or do we keep doing the same thing every time and we're not actually getting better, right? You know, and that's kind of the definition of insanity. Right, right, you know? But you seem very effective at focusing on relatively straight processes that have huge impact that seem kind of below the surface of the things that people are focusing on and really deliver huge value in a process. I think, you know, the buzzword around IoT, right? You know, 22 bajillion devices or whatever it's going to be, right? So what, right? It's more about, you know, there's really four pieces of work that anything needs or does. It needs help, you need help. It needs to change or you change. You request something or you just need some knowledge, right? When you go to Amazon and shop and do things, you're only doing one of those four things. You just don't think of it that way, right? Because it's all done for you because they've learned over time. Every time, you know, Dave buys a speedboat, he also wants some life jackets or whatever it may be, right? That's already there, right? And all we're trying to do is get under the surface of that and boil it down to some simple concepts because too often we over complicate and over engineer in IT and once the honeymoon wears off of launching something new, we actually realize we only used 30% of the thing we had and then we're off like squirrels chasing another nut because that's the cool thing to do and you just end up with bloat wear and shelf wear across the organization. So you think, well, how do we end up with all this sprawl? Well, you know, and keep feeding technologies that you just cannot keep up with. John Donahoe talked about some of the things that he learned on his, you know, customer tours, 100 customers in 45 days. It's pretty impressive. That's more than me. And you see a lot of customers. It's the new benchmark. Yeah, exactly. So one of the things that I heard and he framed it in his language, but it was basically, we want to move faster, make it easier for us. So what are some of the challenges, the headwinds that you see in terms of adoption and how are you guys addressing that? Obviously ecosystem is part of that, but. Yeah, I think we're over that tipping point of cloud, you know, being an option now and it's more that when are we going to get there? Not if are we going to get there for customers and you know, regulatory changes like in Singapore with the monetary authority now saying cloud's the way to go. You know, it's just the way to go now. I think for us, you know, we have a pretty aggressive release schedule twice a year. And I think with customers, a lot of them are now saying, you know, how do we get back in the box? How do we get market standardization? It's another big term we're hearing around, you know, well, when we did it back in the day, you know, two, three years ago, we did the changes because they were appropriate. Well, the products moved on and evolve so much. We can now leverage all the core because it makes sense to do so and we can focus on other problems. So I think for us, it's that listen and learn, right? And just wash your hands, repeat all the time. And the more we feed that back into our organization, we can only get better. I think the other side is you see the scale of what some of these customers are doing today. You know, I had Citigroup on a panel with me earlier. They're pushing nearly 3 million transactions a day on the platform. So over 21 million a week, 15,000 concurrent users a day. The learning you get from what those people do. I guess the transactions may be small, but when there's that many a day, and if you scrape 10% of them, you're going to get the learnings, right? So that's huge for us in terms of that. And then they all talk to each other, right? And they push us hard to do the cool things. And then we understand and we learn and we go from there. So I think for us, you know, it's, we'll never forget IT, you know, Frank, as you know, used to call them our homies, right? Just with a Dutch accent, which clearly I can't do, right? But they're the core, right? And becoming even more important now of, they're still accountable for many services, but the day-to-day responsibility may be farmed out, right? But they're ultimately accountable. So if you think about IT service management, they still own it and do it, but we're responsible service now for the day-to-day operational aspects of it, right? They're focused on the outcomes and the business value piece, not running servers and storage and technology and upgrades. That says Office 365 is the same example, right? So I think where we see that shift is, how do we keep them going up that value chain, but where they're relevant for these new things that are happening, you know, no one really, when you ask them what digital means, can really tell you what it is, right? But they've all got one, you know, right? So it's that kind of situation that you have to deal with. So I think, and you said it, right, we have a good way of boiling it down to the simple aspects under the layer and removing the complexity, but still getting all that value. Well, and then when you have transactional volume like that, there's just no substitute for scale and that really drives the machine learning and the algorithms and all the stuff that comes with scale, which is very, very tough to compete if you're not at scale. Absolutely, no, I agree 100%. I'm very excited about the security strategy when I first saw it and we started on Packet last year at Knowledge and the whole focus on response, things like automating a run book and these mundane tasks that people hate to do. I just think it's a huge opportunity for you, although I don't think many, most observers don't understand, you know, your position in that market. But I think it's going to explode over the next five, 10 years. Talk about, from a strategy standpoint, security or entrance into that market, where you see it going? I think, you know, the big thing, right, people get kind of wowed by all the blinky lights, right? And there's always bad news in security. Whoever gave you any good news, right? Nobody, right? There's kind of the news at 10, there's never any good news, right? So it's not if it's when something bad's going to happen. And I think what we found is, you know, these guys are buried in work, but the problem is they can't tell anybody about it. Right, because it's all highly secure and confidential and, you know, one word gets out, that, hey, these guys have got a problem, it's front page news, right? And they're spending more time deflecting than they are actually solving the problem. So for us, it was that signal to noise ratio, which isn't a new problem, but it's just worse because it's a security thing and it's from the outside often, right? So for us, you know, every day there's a security product and monitoring something that pops up and that's just a never ending task that we've got to integrate and we've got to bring that data in. But it's more about have we got a meaningful framework that then says to us, we can make sense of that, right? And that's where the intelligent automation comes in and is even more critical, right? In terms of security. So for us, but we still have to, you know, in the way in IT we have our fulfillers, security does too, right? And they've got work to do that is now a board level conversation, right? And what's your security posture that they have to report as part of their dear chairman letter and SEC findings every year, right? Particularly the banking system, right? And then the whole too big to fail, that's gone beyond that now to be, are you even secure? Let alone have you got money, right? So for us, it's a massive opportunity but the beauty of it is is when you get under the layer, they do a lot of the same things that IT does and others do in terms of form space workflow. They just call them different things and they have things like NIST, which is great, but they're still doing work, right? And that's what it's about. So nothing but excitement in that space. The customers love it and because the path to adoption is so quick and easy, particularly if they're an existing customer, it's upgrade, turn the thing on and go. Yeah, the time to value is very, very short. I was telling Jeff, I've been sharing cabs with practitioners all week. As I look at him, like, you can tell when somebody's a customer, right? Hey, you want to take a cab? Oh, great, thank you. It's now a shirt. Absolutely. So today I actually bow guarded from a customer, so thank you. But I was talking to one who was in compliance. Right. A key area. A lot of new requirements coming out for the banks. I think May 18, right, is GDPR. Yep, and PSD2. Right, and so that's going to be a big deal. How does service now affect those things? Yeah, so I think for us, you know, they're all big scary things, right? Coming out of the EU and the regulators. And I think the big thing with GDPR is, you have a problem, you've got 48 hours, right? And what they've said is, where you don't follow the rules, you're up to 10% of your annual revenue, is you're fine. Right, now you talk to a bank, that's a big number, right? 10% of the revenue. Yeah, so that's a big ticket, right? So then you start looking at that and what they can do, but when you think about how they do compliance, regulatory reporting, demonstrate controls, a lot of that's done in spreadsheets and emails today. So it goes back to our original ethos of what we do. Forms-based workflow with data. Now you can do some cool things with machine learning and AI to predict and get ahead of those things and do the attestations in a much simpler way. But if you are unfortunate to have a problem, then there's got to be a process where your CEO's basically going to come out and admit and report we have a problem. Now the other side of that is PSD2, which has a whole different level of complexity around APIs and the open banking project basically says, if I want to get an account with a fintech, and I've traditionally been with a big bank, you know, one of the traditionals, they have to give my data up within 48 hours using an API. Now how many core banking systems on mainframes and AS400s are there at rest API integrations that are inbound and outbound? Probably a big fat zero right now, right? So there's huge change coming for technology, but then you look at that, is this appropriate request? Who did it come from? Is it signed? Does it need to go through blockchain, right? And start bringing all those messages together. That's really complex for IT. Oh, and keep the lights on at the same time, by the way. So huge change coming in that area. But again, we're positioned from a work standpoint and a compliance reporting standpoint to help them do all that. There's a big tailwind for you. I mean, the penalty find posture is completely different because it used to be, the bank would say, listen, it's cheaper to pay the fine. We can negotiate it down, right? We'll be, right. Accept that risk, but if in fact this new world is enforced. It's huge. Yeah, that is huge. It's huge, yeah. 10% revenue, that's a big number. So what else are you working on? You know, Hackathon is a great example. You know, we've got 300 customers over there right now and partners building cool stuff. And there's everything from voice recognition to virtual bots to machine learning going on. They're using Cortana and Watson and we've got guys over there with Raspberry Pis. I mean, it's just mental, right? It's so cool what they do. So I do a lot of that, you know, still traveling around the world doing things. And then some of the other cool stuff, you know, working with our financial services customers. A couple of our partners working on sort of some industry or vertical specific things around sort of credit card risk, fraud tracking, those type of things. Really, you know, getting creative, doing cool things. Still doing ITSM, of course, you know, it's kind of where I grew up and cut my teeth. And you know, just trying to help them build their strategy, get over the hump and say, look, you know, where do you want to go? How do you align with us? And let's just move the needle ahead. So still out there killing the dinosaurs, you know, in the Soviet era, technology guys, you're welcome. We still have a lot to do, but you know, it's part of what we do and it's fun, right? You know, the technology is not a limiting factor for us. You know, people in process change is hard, but more are doing it. And as you see here, the big boys and girls of the world are really doing it now and setting the standard, which is only a good thing to drive us on. Yeah, if you can make technology a facilitator, it's just a, it creates a flywheel effect. So for you, both you and your customers, that's the interesting thing here. Chris Pope, always great having you on theCUBE. Thanks so much for coming back. Thanks guys, appreciate it. You're welcome. All right, keep it right there, everybody. We'll be back with our next guest of theCUBE. We're live from Knowledge 17. We'll be right back.