 Live from Las Vegas, Nevada, it's theCUBE. Covering Knowledge 15, brought to you by ServiceNow. We're back, welcome to Knowledge 15 everybody. This is Dave Vellante, I'm with my co-host, Jeff Frick, the original. That's right. Cube Knowledge, a Cube team back together. Jeff, thanks for coming on. Carl Vanderpoles here, he runs the performance analytics business at ServiceNow. ServiceNow's first acquisition of Mirror 42 a couple years ago. Carl, welcome to theCUBE, good to see you again. Nice to, thanks for having me. Great. So how's it going? Lots going on here at this event, 9,000 people, new business units announced this year. You're in charge of one of them, the analytics, hot space. We met you a couple years ago and we were like, wow, what a great fit with ServiceNow. All of a sudden, acquisition, you're here, rocket ship, how's it feel? Yeah, it's feeling great. I mean, it's been a great ride ever since the acquisition. We got acquired July 1st, 2013. And it's been booming ever since. So, especially the loss to releases. Now that we're in platform, we see great adoption by customers and it's really taking off. So, it's amazing. You know, M&A in the technology business obviously is a core discipline and strategy of many companies. Some are good at it, some are not so good at it. It's interesting to note, ServiceNow acquisitions, you've got to be part of the ServiceNow framework. Yeah. Or it's not going to work. And so, there's a nice feeder system, a farm system, if you will, for ServiceNow. But so, I wonder if you could talk about, go back and talk about the acquisition, the integration and what that was like. Yeah, sure. So, one of the things that was pretty strange actually, normally if you do an acquisition, like you buy a product and you go start selling that product, well with ServiceNow, they got this one platform, one code-based vision. So, the question that I got during the negotiation and the talk was like, hey Carl, are you up for a rebuild? And I was, my first response was like, you kidding me? You know, we spent five years building a great product. And then they start explaining this whole benefits of being a platform, it's like, all right, sounds like a plan, so we did it. And so, we did the rebuild in platform. And that was actually great. Well, I think one of the best things that we deal with ServiceNow is, you acquire a company and you ask them to start building on your stack, your technology, which was not necessarily our technology. Mira42 was building a different technology stack. So, there was a big learning curve. And obviously, we didn't know the platform that well. My engineers didn't know the platform. So, what we did, what ServiceNow did is, we got a couple of the platform guys out of San Diego, relocated them to Amsterdam, embedded it in a team. And that basically cost for very rapid knowledge transfer. And allowed us to pull it off to rebuild the product in platform. And that was just great. I mean, the executive team is great. I think there's some kind of privilege by being the first acquisition. We were the first. So, there's a lot of attention on it. ServiceNow didn't want to make sure it obviously succeeded, being your first acquisition. So, I get to meet all the leadership people, which also kind of helps you after that period in order to get things done and get things moving in the right direction. So, here you are, small company. Very small. A larger company, not a total whale, but a larger company with a much bigger distribution channel. What kind of momentum have you seen post? Well, literally hundreds of customers, right? You know, we got acquired and we were a small company. Like you said, you know, the canals in Amsterdam, 20 people strong. And a couple of, you know, we just got started with ServiceNow. Basically, what happened was, when ServiceNow opened up their eco net for partners and they released the ODBC driver, it allowed us to start connecting to it. And we thought that ServiceNow might have an appetite for acquiring somebody in this space. But we didn't realize that it went that fast. It was really, really, really fast. We signed up all the partners. We were signing up partners or customers, but we didn't have that many ServiceNow customers yet and when the acquisition came. So, if you now look, you were two years out, right? Or year and a half out. And like I said, literally hundreds of customers in the Eureka platform have purchased performance analytics or rolling it out. And we're ramping up capacity in the field, which is the big challenge for us. You know, you get a couple hundreds of customers in one year and obviously you also need to have the consultants in the field in order to be able to support that. That's really what we're going for right now. It's like cranking up the capacity. You did have the time machine because Fred was on earlier yesterday talking about talking to Google and they completely rewrote their entire search code base. So, if you'd known, you would have said, hey, we're rewriting that thing. But it also kind of free you up to write it up the second time, right? Because it's a forcing function. So it gives you an opportunity to maybe rethink some things, fix some things, and really look at your application with really fresh eyes. Yeah, it was actually it was the second rewrite that we did because we started with Mirror42 as an on-premise normal software vendor. So we did the rewrite in the cloud and then we did the rewrite again in the ServiceNow platform. So you're absolutely right. You're going to get better every time you do it. So, and the power of the platform obviously is, you get a lot of stuff for free, right? We didn't have to worry about security layers. We didn't have to worry about integration interfaces. It's already there. So, I mean, there are a lot of things that we do need to worry about, but the power of the platform was very, very useful. So you were writing originally in a public cloud? Is that right? Yeah. Originally on-premises. Right. And then a public cloud. Yeah, on AWS. Basically, here it is, go. Right. Yeah. API, it's cool. Right. Developers love it. Developers love it and it's very cheap. DevOps. Right. But actually, the public cloud for ServiceNow customers, for some ServiceNow customers is a no-go area. So we knew that with Mirror42 on AWS, we would not be able to get to all the customer base because just the big banks will not do analytics on the public cloud, rightly so. So yeah, also in order to reach the entire customer base, and especially the big customers, the in-platform move was a good one. Well, that's interesting. So what was it like developing in the ServiceNow cloud comparative to the AWS piece? I mean, you had to worry about scaling in AWS. Well, I remember the first time I actually, we had these technology sessions at ServiceNow. I remember the first quarter I came in and we had a big team meeting with Alan's guys, Alan Lyman, and Pat Casey guys, and we got all the people in there. And the first thing that struck me was like, wow, what a brain power in this room. It was just literally amazing. People that are holding your back while you're building an application and you do not have to worry about scaling the database, right? You do not have to worry about failover or running the operations, monitoring, or anything. It's like, you build your app and obviously we're an analytics app, so a lot of data flows through the system, right? So scalability is always something you need to think about with analytics. But if you have that kind of guys holding your back on the platform, it's really an amazing experience. So I think we didn't have the feeling like we were alone on it. It's just like there was a lot of support and great guys, great brains. It was pretty easy actually. I wonder if we can shift gears a little bit and talk about analytics and how analytics has changed over time. And especially, we talked a little bit off camera about in-platform analytics versus maybe more of a traditional approach of having the data and then putting it into a different analytics tool. Talk about how that's changing and really how that's driving different use cases. And we talked quite a bit on theCUBE of getting that data, that information, that actionable insight down to people that are making decisions in real time and out of the hallowed halls of the data scientists who's just down the hall. Yeah, analytics is a buzzword, right? Everybody calls everything analytics. Oh, big data is the buzzword. Oh, big data. I always say I want a small summary. Small summary, very good. Sounds like a management nightmare, big data. But so analytics is a big thing. What we mean with analytics at Suv's now is really you want to be able, if you orchestrate your workflows in Suv's now, whatever process it is, right? The theme of this conference is everything as a service. So you want to optimize the process of delivering that service. And in order to do that, you got to crunch the numbers, figure out what's not working, where, how you can optimize that process, where things are getting stuck. And that needs to be done in real time, right? You do not want to have exporting that data or putting it somewhere else again and there's always a delay. And the other thing that why the ETL process doesn't work in our vision for the platform is, Suv's now is a platform, so you're constantly changing things, right? That's the flexibility of the platform. People write their own apps, customize the apps. Well, guess what? If I customize an app, I do that for a reason, probably because I want to store data that is really important for me. Probably data that I want to report off. Well, if you then also need to fix the ETL layer again and then fix your data warehouse again, it kind of gets change after change after change. If you do it in platform, you make the change in platform and the platform is aware of the change, we don't have that problem, right? So it's about being there in real time and not having to worry about keeping other systems that integrate, in sync and have to worry about all that stuff. And that's interesting in the context of kind of the agile world that we live in, right? And back in the day, people weren't changing the software that often, right? They were doing major releases every now. But now in the agile world, people are pushing out new code all the time. So that just must really exacerbate the problem that you're talking about. Yeah, exactly. And there is a use case for extracting and putting it in. I mean, we understand the service now that not all data of the entire enterprise is in service yet, right? But so for consolidated reporting, really after the fact, you're crunching your management reporting and there is a consolidation play and there will be a big data warehouse and you put the data in. But that's not what we're talking about here. We're talking about, you know, crunching the numbers in the operation analytics to make the people who have to do the work give them the power of analytics to make better decisions when they do their job. It's not at the end of the month after the fact reporting. So let's unpack a little bit what customers are doing with your product. So take us through a typical customer scenario. Maybe there are several, but just give us some examples so people can understand what we're talking about here. Yeah, so the majority of the customers is now using performance analytics really on the operational side of the house. So we're looking at incident problem and change data and the requests that are coming in. Really doing like backlog analysis. So, you know, I have a backlog right now. The goal to reduce that in, let's say, even 50% in four months. And then to figure out like with my current staffing, where am I going to end up in four months from now if I don't do anything, right? And if I add capacity, how much capacity do I need to add in order to hit that goal? You know, those are kind of the things that we're doing, but it's also really implementing continuous improvement cycles. And what we mean with that is you have efficiency key performance indicators like percentage of untouched incidents, you know. It happens in every organization that you throw something in a workflow and it get lost somewhere, right? We don't want that to happen. Or tickets that are being reassigned too many times. So it comes to requests, it's difficult, we don't know who the right specialist is, so we're going to throw it around the whole potato, right? And the customer is waiting. So those are kind of like really the performance indicators that you want to start zooming in on, not only as an absolute number, but as a percentage of the overall traffic that throws through your process. And then you drive that percentage down. So the best way to actually hit the SLA is to make sure people are working on the right stuff. And that's really where you can set the efficiency indicators. So those are good examples. And very often it's also used for fender management. So you outsource something to somebody else who want to track the performance of that fender over time. So those are typical use cases. Okay, so do I get, so think about the operational analytics. Do I get a sort of set of, the framework out of the box and then I can customize that because my KPIs might be different than others or is it pretty much standard? What are you seeing there? So that's a good question. What we ship with about 80 key performance indicators out of the box, which are the obvious ones. But we also, what also came with the acquisition is a community called kpi-library.com. Kpi-library.com has over half a million members and it holds over 6,000 templates for key performance indicators. Now it's something that we haven't done that much about with the acquisition yet. It's still sit there, it's the community is very life and active. But those templates, those 6,000 templates are related to any kind of business process or industry. So we obviously take the ones for IT and we started there, but we also have them for HR, for facilities, for legal and for any other industry. So those templates, you can actually use those templates when you're setting up and customizing, adding your own KPIs, you can use it as a source of inspiration, download the templates and start setting up new KPIs faster and faster. So that's how it works, I downloaded, it was all like an API. You pull it in, it's a template. And the other thing that we're doing now we're obviously seeing the HR and portfolio management, all the other applications that we're building, we're building out of the box content to come along with it. So you'll see us, we have an HR analytics to complement the HR solution. Project. Right, so that's what we started really with the operational ones because that's what the majority of customers obviously have, they use service now for instant problem change. And as we see more and more HR and more PPM, we're building those packages along. So HR makes a lot of sense as a leverage. And project especially, I mean they must, I mean everybody's got KPIs and project management. Things like earned value management, yeah. Yeah, right, so that's what I was going to say. And project is a little bit different and so I mean you're trying to connect to other sort of value metrics. Yeah, I presume it's highly customizable, I can set that stuff up, I can score however I want to score, I can tie it to my business objectives. Yeah, yeah, it's basically if the data lifts into service now, platform, you can snap surely, you can slice or dice it any way you want, there's a formula editor that allows you to calculate and do forecasting and write those business rules. So it's very customizable. So essentially the Tiger team that came up from San Diego helped you get into the service now platform so you can leverage the entire platform today. Yeah, out of the box. Yeah, we're very much, I mean if you think about analytics and reporting, because reporting is the other thing that I do, we were very much joined to the HIPAA platform. If I can't query it, I can't do anything with it. So basically two parts where it's visualizing data, which is we work very closely with Fred's group on the UI side and then we have analyzing and storing the big data numbers, which is very much the platform side. So those are the peer groups that I have and then the application teams, the teams of Dave Stevens are basically my customers because they want to enrich their apps with analytics or three for that matter. So those guys are my customers, they kinda use and they build the content as well. So on one end I'm building an app that we sell on the other end, I'm actually building capabilities for the other GM's. Really taking advantage of the whole platform kind of concept. Right, it's the better together concept. What about the Viz? We talk about the Viz, we do Tableau show, we talk about the Viz. So the visualization is pretty much everything you guys do in-house, right? Or do you connect to other visualization tools? Yeah, well what we do is we ship a bunch of center visuals that we have, optimized for time series. Well, we're also a platform again. So anything in PA and film analytics is built on top of a rich API set. So customers can take any kind of visualization engine or scripting language like D3 and start writing their own visualizations on top of those APIs. So we see that happening as well. For this conference we build up a custom dashboard to follow all the social events, all the tweets every two minutes. And we also have a little example of pooling data from the stock market in. But those are all examples of how you can do custom visuals on top of the APIs. So what we ship is kind of like, well, this is the basic stuff, right? Time series and bars and donuts and what have you. But you can go really fancy with the APIs. Yeah, I want to shift gears a little bit, do a little research before you came on. You had an interesting piece on really historical time bounds for reporting, which were quarterly, monthly, and that was driven really kind of by the speed of reporting and the speed of the ability to get the information and put it together back from however long ago that started. And how really we shouldn't do that anymore because we have the ability to do it much quicker and in a much more logical way. I wonder if you can kind of share with the audience that I think it's pretty powerful. So actually if you think about business intelligence, then unfortunately not much has changed in the last 10 years. If you start asking customers or big organizations how do they do their management reporting? It's basically at the end of the month or at the end of the quarter we crunch the numbers and then we look back and we say it's like, oh, we didn't hit our targets or UP, we hit our targets, right? But it's really strange because we did that because it was so labor intensive to crunch the numbers more often, right? It was hard work. You got to pull the data in, you put it in a data warehouse, you got data analysts doing all the numbers, people questioning about data quality. Well, that's been going on for 10, 15 years and nothing has really changed and some of the organizations are still doing that. But if you look at systems like ServiceNow, you can crunch the numbers every day and instead of looking at the end of the month you can start looking at a rolling 20 day average every day, right? Which basically gives you the data of a month rolling forward and you can, every day you can already do the analysis, are we on track to hit our target? Or are we moving in the right direction? Are we moving in the right direction? And that obviously, if you start thinking about it that way, so I sometimes call it drop the calendar view, right? Start thinking about it's like, well, it doesn't really matter if it's Sunday, Monday or what does that mean? We've got a business who goes 24 seven, 365. What does the calendar mean, right? Doesn't mean anything anymore. I just take an X amount of time and I trend it over time. And I want to see if I'm improving, if my organization becomes more efficient. So we still have this whole concept of, calendaring and looking back, it's, I think. Because it's taxes. Right. That's right, right. But there's one thing to report your taxes and then there's another thing to manage your business and I guess that's really what the opportunity is. Carl, what are you typically replacing when you come in? Is it nothing? Is it spreadsheets? Excel, right, okay. Yeah, it's a lot of Excel and it's a lot of in-house. I mean, when customers move from HP or BMC and they go to the service now, in the past, they typically have done a lot of business warehouse kind of things with business objects or Cognos and the tools on premise even. And most customers know how hard that is. And they know it's like hard work to keep it in sync, to do all that stuff. So when we show them that this thing is building platform and they don't have to worry about it anymore, it's like, well, yeah. So that's one use case and the other thing is with VA, we see customers who jump on VA performance analytics, I should say, they save a lot of time in gathering the data and crunching numbers in Excel. So what's happening a lot is offloading the data to Excel and everybody's a data jockey in Excel, right? And we all do that, but I do that at a different time than you do that, so we're not looking at the same data set and therefore we draw this, not the same conclusions. So and that's really automating that process and not having to get that data out and basically doing it in platform is one of the big time-saves. All right, we're out of time, but I wanted to leave, have you leave us with final thoughts. Let's look ahead, put on your binoculars, if you would. We heard you talk about extending into other sort of modules and lines of business. We heard a lot about real time. What's the future hold for the performance analytics, specifically in the context of service management? Well, we'll continue what we're doing, so it's really about moving towards forecasting, predicting where you're going to go, but also making the analytics and we're already doing that, but we can do a lot more there, but making it really prescriptive, right? Telling people, not only allowing managers to analyze what they need to do and optimize the process, but basically make the process already, give that power to the agents itself. So when you're doing your work, the analytics will tell you in order to prevent that we're actually re-assigning tickets or sending it the wrong direction. So I think that the whole notion of doing that thing in real time, taking the historic data, mining the historic data and profiling the data, and then overlaying it with what you need to do right now, that's where we want to go, and that's where I see the future. All right, Carl, congratulations on the acquisition, the successful integration and the new role at the service now and all the momentum, so appreciate you coming to theCUBE. All right, thank you. All right, keep right there. We'll be back with our next guest. This is theCUBE, we're live from Las Vegas, Knowledge 15, right back.