>> From Washington DC, it's theCUBE. Covering the ScienceLogic Symposium 2019. Brought to you by ScienceLogic. >> Hi, I'm Stu Miniman, and this is theCUBE's special coverage of ScienceLogic symposium 2019 here at the Ritz-Carlton, in Washington DC, about 460 people here, I'm told over 50% growth, from last year's event, the first time we've had theCUBE here, really excited to be able to dig in, with a number of the executives, customers and partners, and no better way, to kick off than one of the users, here at the event, actually coming here from across the pond, here to the district, happy to welcome to the program first-time guest, Nigel Wilks who's the Head of Global Tooling at Computacenter, based in the UK, Nigel, thanks so much for joinin' us. >> Hey, a pleasure. >> And joining him from ScienceLogic we have Clive Spanswick, who's the Vice President of Sales from EMEA, Clive thanks so much for joinin' us. >> Pleasure to be here. >> All right, so Nigel, set the stage for us, coming to the event here, tell me what brings you here, and tell us a little bit about Computacenter. >> Yeah sure, so, we're a relatively new customer to ScienceLogic so, I think, what, we signed two, three weeks ago? So, not deployed yet, but got great expectations. So, there's a lot of background research in the sessions. Finding about more what the additional capabilities that we can unlock, which will help drive our business further forward. So, Computacenter is a large IT provider, global. Based in the UK, as headquarters. My area of the business is in the Managed Services sector. So realistically, we're looking to reduce our cost to serve. Be more proactive for our customers, and, we've got great expectations of what ScienceLogic can do around those areas. Unlocking more automation, and eventually leading down the AI path. >> So Nigel, what I heard in the keynote is, some of the same themes I've been hearing around the industry, we are unparalleled as to how fast things are changing in the industry, there's just more complexity, there's more heterogeneous environments, for companies like yours, usually agility is one of those things that's coming to the top of the environment and oh my gosh, when I became an analyst about nine years ago, it was the tooling and management options out there where usually some of the things that customers would say are weak in their environment, and something I think I've heard for my entire career, so, maybe give us a little bit as to some of what you're hearing from the business side and how it makes sure that you can run your services faster and ultimately serve your customers better and how your look at, I don't know whether you call it AI Ops, but this whole space, fits into that environment. >> Sure, so-- >> Yeah. >> We've with probably a lot of organic growth within Computacenter over quite a short period of time. Also through acquisitions, we've got quite a fragmented tooling landscape globally. So, nearly two years ago, we kind of set on the journey to become more of a global entity, and certainly from my perspective a tooling landscape. Looking to consolidate those down, simplify our services, again helping reduce our cost base, and then leverage the automation stuff I talked about earlier. So, just going to ScienceLogic, we're moving away from some of the big names. And consolidating over 50 tools into the one ScienceLogic solution. >> Wow. That's great, let's bring ya into the discussion Clive, yeah, I heard in the keynote this morning, it was, the typical customer, it's at least 14 tools. >> Yes. >> That get consolidated down. I think back about five years ago, frictionless and simplicity were the terms that I heard. I talked to a lot of companies, it's like "Oh okay, yes I've got integrations I need to do "if I'm doing acquisitions, whether I be in, "if I'm in services of course that's there" But, you know, financial industries, and, heck, Cisco IT who I'm going to be talking to later, does an acquisition a month, what are you seeing, give us a little bit of the EMEA flavor and-- >> Sure. >> How what Nigel's saying, how is that resonating with your customer base? >> Yeah, absolutely Stu. So we see this a lot with the leading service providers now that are really being challenged by their customers to really extend their portfolio of services, over an ever more diverse range of technologies, and this is one of the big challenges that has driven tool sprawl over the course of the last seven to ten years, so simplification of the toolset, is really one of the key drivers to really deliver outcomes for efficiency, so a lot of the way we see modern service providers operating today really is all about automation, to get to better automation at a lower cost you have to drive simplification into the tool chain. So, we see this a lot with our customers across the region and indeed worldwide, that taking the tools landscape and really collapsing that into a much more simplified model is an essential ingredient to drive efficiencies that then in turn can be delivered to the customer as lower-cost services, so that's the real driving force that we see for customers today. >> Alright. Nigel, we'd love to hear, I know you've just gone through the process of choosing but, what are you looking for, are there specific business drivers, how will success be measured in your environment? >> Part of the process was, to look at what our business requirements were. And map those on through an RFI process. Of which ScienceLogic were one of the vendors that took part. So I think at the benchmark of everything we did, at the heart of the whole process, was that business requirements. Just making sure that whichever toolsets we selected, would go down that route. We never expected to have a single-vendor solution, which, fortunately we've got ScienceLogic which covers the majority, but with the partner ecosystem, some of those guys are here today. It kind of rounds it up for us. But moving away from our current providers, some of those, they present challenges to us as well. Tryin' to unlock data that's within the platforms, some of those tools are through acquisitions. So as much as you've got a brand name as part of a whole stable of tools, they don't inter-operate very well. And the beauty of going to ScienceLogic was, everything comes in together, even the partner tools, which allows us to really look at what we can do in the future. >> Alright, so, Nigel I've got the tough question for you. When I came into the show, one of the things that really struck me, is how data's at the center of what's important here, you know, when we look at companies, digital transformation often is a buzzword, but, we've really defined the difference between the old way and the modern environment is, how is data something that can actually drive your business, are you data-driven in your decisions, can you monetize data, what I heard in the keynote discussion is, data's such an important, not just the collecting but leveraging, and that's driving the intelligence, the automation. How much did that focus on data play into your decision, and can you give us a little bit of insight as to how your company looks at the role of data in the IT world today? >> Well, it's very important, that's quite a simple solution to that one. So for me, an infrastructure tooling perspective, being able to bring all the data into one place but contextualize it as well, means that we can then do some good stuff. Again, driving us down that automation path but from an end-user point of view we've got end-user analytics, that can open up a lot of different worlds for us, predicting what issues users have, rather than calling a service desk, theoretically, going further down the future, we'll be calling them to say, "I can see you've got a problem, "I can fix it for you remotely." Those kind of decisions that we can make from that data. But in my kind of space, the infrastructure tooling side, we need to go onto that AI Ops journey, and as you heard this morning, now, or at least a few weeks ago, to get there, it's like getting the data into a good shape, knowing what we want to do with the AI Ops moving forward. So, automation's a good candidate, that helps up achieve some of our objectives, reduces customers' downtime as well but, we've also got to be careful that we're not tryin' to automate resolution to poor behavior. >> Yeah >> Yeah, so, rather than fixing the root cause, we need to actually look at things and say, "Is this an incident-worthy event, "is this something that "we need to actually do something with, "or is it just an automation candidate?" And it's going to drive some of those behaviors for us. >> Clive, I'd love to get your viewpoint as to what you're hearing from customers, when I listened to the analyst this morning, he's like "You need to really differentiate "between that machine learning piece, "and the automation." Because any of us that've worked in operations environment, you can automate a bad process. >> Yeah. >> And data doesn't necessarily mean good information, so we need to manage those things a little bit separately, and that maturation of where customers are for both automation and intelligence, is a tough one, when they did a poll when your CEO was up on stage, nobody's fully, turn things over to the computers. >> Yep, yep. >> So, where are your customers, how are they thinking through the AIML, the use of data, and those pieces? >> So see, I think to be fair, a lot of customers today, AI Ops as we know is a relatively new term to the market, so I think a lot of businesses are struggling to recognize their own maturity, and I think, what we learned from this morning from Dave Link, our CEO, about how you characterize yourself on the journey to AI Ops maturity I think is a very valuable thing, and I think as I look at a lot of the customers and we saw from the poll earlier in the main session, that a lot of businesses today are fairly in the middle of maturity, so they're really at about the point of consolidating all the data in one place, the next big step of that of course is to clean that data up and contextualize it, so that you can start to leverage that data for the meaningful outcomes, and that's really where the smarts of machine learning and early-stage AI really start to play. We still, to be fair, still a long way off from the realization of full AI, but there are many pragmatic things that you can do, to get you very well level set, to take full advantage when those opportunities start to present themselves. >> Alright. So, Nigel, you're goin' through this process to really modernize your toolset you said you're replacing a whole bunch of things with the new one, what ultimately will this mean to your end-user customers? >> I think a more proactive service. Just dialing it back down to the simple things. If we simplify our service, we can have, from a business point of view, we can be consistent in how we deliver service globally. But from an end-user point of view. At the end of the day, most of the stuff is event-driven. End users typically find those out before systems do. Just from whole new cycles, reducing false positives and things. But it also means that, again, automation is being at the heart of what we want to try and achieve. We can automatically fix these things, so it's less downtime. And then hopefully we can just kind of prevent. Automation's great, but prevention's better. >> Yeah. How do you see your journey going forward, when you look at that automation, I mean I can't imagine you at a day one, your desk, putting everything in and everything's there, do you have a roadmap out there as to how you look at your deployment and how you're going to change things internally? Yeah. This, realistically, is going to be a catalyst to how we do things. So what starts off as a tooling replacement project, becomes that overall, we can do things global process. Working a little bit smarter than we have been before, doing things on a larger scale, but using common processes. That's quite a big shift in how we work now. But also means from our sales forces perspective, they're selling the same thing, it doesn't matter which country they're in. It becomes more about delivery location, and a language. >> Great. Clive, give us a little bit as to, what are customers like Nigel, what should they expect once they've made the deployment, how long does that transformation take-- >> Sure. >> And what's the day one and then, three months, six months out? >> Sure, great questions. So the whole journey that we're exploring, with all of our customers, is this move to AI Ops and they've done really the support of the resilient digital experience for their customers. The journey itself is continuous. So, one of the big challenges that we know to be true in the space that we operate in, is the demand for constant change. So the idea and the process that we're going on with, with computer sensor is that, we will take you through a series of maturity stages, of crawl, walk and run. And then once we get them to run, it will be a case of continuous improvement and continuous development. We expect to get to the first break of that within the first quarter, we're going to be delivering instant value from the platform pretty much from the word go, but once we get into the process of business as usual, running the operation, it really becomes about the improvement of moving, from really the stages of helping them react better to incidents, and then moving into a much more proactive and predictive state, and then finally, the endgame of this of course, is to really get to the point of, automate to avoid the incidents happening altogether, and that really, I guess, is where we start to step towards the ultimate vision of AI Ops and the things that that can bring to bear. >> Alright, so, Nigel, I want you to take me inside your team, 'cause on the one hand we say, "I have a whole bunch of tools, "I'm going to simplify and I'm going to unify "and that's going to be great." And I'm sure there's many on your team they're like, "Ah, I hate this tool, and this one's a pain "and this and that. "But we kind of know how "to do everything that I'm doing today." So, one, give us a little insight as to, is there some of that clinging to the past, and, on the other hand, are there some things that, like, "Oh my gosh, I'm glad I will never have to do "one two or three ever again, "once I've gone through this process"? >> Great, great question, so, everyone has their favorite tool, or favorite bit of software. I think, internally, we've clearly got that challenge as well. But it's fair to say, the reverse is true, there's a lot of tools out there that the user base are more than happy to get rid of. But ultimately, I think as we've gone through the cycle with ScienceLogic, and certainly we've had some good workshops with the various user base, highlighting what's possible, we've had some really really positive feedback. I still expect challenges, change, change is a big thing, most people don't like change but, I think there's a great opportunity for people to, at the end of the day learn a new tool. Something different, something fresh. And also then, they can think about what the tool can do, how can we exploit it more, so, we're not locked into the model that we were in before, the tools that we'd use for years and we've worked in the same way. We've got an exciting journey to start looking at how we can derive better services, how we can simplify our services. How we can let customers self-serve, to a degree as well. So you know, I think it's an exciting journey that we're on. And I think it'll be good to come back next year and demonstrate where we are. >> I love that, I definitely want to talk about that, Clive, give you the final word on this. What final advice to you give him, he's made the decision, he's goin' onboard. Tell him, I'm sure, unicorns and rainbows and everything's going to be phenomenal, but, what are some of the things you hear from your customers as they roll things out, give him a little bit of the "Yay" and a little bit of the-- >> Sure >> Just "Hey make sure "we've educated everybody on this." >> Yeah, again, great question Stu. So, from working with our customer base, the big thing that we see is that this is a continuous journey. The journey doesn't stop. What we do is we make things progressively easier, and the opportunities to scale and standardize are almost limitless. I guess the one word of counsel I would give is that, one of the big things that we see, with any major transformation, we're talking about the automations we can deliver around monitoring but, with any transformation it is really how you start to shift the culture of the organization to work a way around the new ways of operating, and really winning the hearts and minds of the guys that this stuff is going to make the biggest difference to. So, we're talking in the first instance of course about the operational stakeholders and the key users, having them engaged, and really working that process to get the maximum benefit out of the platform. From there, really is about the improvements that they can achieve in customer experience and of course, as Nigel has already said, a lot of that is really centered around the opportunities it's going to present them to show real innovations, around their service portfolio and my guidance there would be, don't be shy to show the world of the possible, to your enterprise customers, because they are demanding more, and there is so much that they can do with the platform to really unleash super value to their customer base. >> Yeah I love that, the world of the possible, we understand all the stresses and strains put on business and IT today so, Clive, Nigel, thank you so much for joining us, Nigel we look forward to hearin' how things go, catch up with you in a year maybe. >> Pleasure. >> Of course, thank you. >> Alright, so we'll be here all day at the Ritz-Carlton in Washington DC, ScienceLogic Symposium 2019, I'm Stu Miniman and as always, thank you for watchin' theCUBE. 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