>> Narrator: Live from Las Vegas, it's theCUBE. Covering AWS re:Invent 2017 presented by AWS, Intel and our ecosystem of partners. >> Hello and welcome back. Live here is theCUBE's exclusive coverage here in Las Vegas. 45,000 people attending Amazon Web Services' AWS re:Invent 2017. I'm John Furrier with Lisa Martin. Our next guest is Miles Kingston, he is the General Manager of the Smart Home Group at Intel Corporation. Miles, it's great to have you. >> Thank you so much for having me here, I'm really happy to be here. >> Welcome to theCUBE Alumni Club. First time on. All the benefits you get as being an Alumni is to come back again. >> Can't wait, I'll be here next year, for sure. >> Certainly, you are running a new business for Intel, I'd like to get some details on that, because smart homes. We were at the Samsung Developer Conference, we saw smart fridge, smart living room. So we're starting to see this become a reality, for the CES, every 10 years, that's smart living room. So finally, with cloud and all of the computing power, it's arrived or has it? >> I believe we're almost there. I think the technology has finally advanced enough and there is so much data available now that you have this combination of this technology that can analyze all of this data and truly start doing some of the artificial intelligence that will help you make your home smarter. >> And we've certainly seen the growth of Siri with Apple, Alexa for the home with Amazon, just really go crazy. In fact, during the Industry Day, yesterday, you saw the repeat session most attended by developers, was Alexa. So Alexa's got the minds and has captured the imagination of the developers. Where does it go from here and what is the difference between a smart home and a connected home? Can you just take a minute to explain and set the table on that? >> Yeah and I agree, the voice capability in the home, it's absolutely foundational. I think I saw a recent statistic that by 2022, 55% of US households are expected to have a smart speaker type device in their home. So that's a massive percentage. So I think, if you look in the industry, connected home and smart home, they're often use synonymously. We personally look at it as an evolution. And so what I mean by that is, today, we think the home is extremely connected. If I talk about my house, and I'm a total geek about this stuff, I've got 60 devices connected to an access point, I've got another 60 devices connected to an IOT hub. My home does not feel very smart. It's crazy connected, I can turn on lights on and off, sprinklers on and off, it's not yet smart. What we're really focused on at Intel, is accelerating that transition for your home to truly become a smart home and not just a connected home. >> And software is a key part of it, and I've seen developers attack this area very nicely. At the same time, the surface area with these Smart Homes for security issues, hackers. Cause WiFi is, you can run a process on, these are computers. So how does security fit into all of this? >> Yeah, security is huge and so at Intel we're focused on four technology pillars, which we'll get through during this discussion. One of the first ones is connectivity, and we actually have technology that goes into a WiFi access point, the actual silicon. It's optimized for many clients to be in the home, and also, we've partnered with companies, like McAfee, on security software that will sit on top of that. That will actually manage all of the connected devices in your home, as that extra layer of security. So we fundamentally agree that the security is paramount. >> One of the things that I saw on the website that says, Intel is taking a radically different approach based on proactive research into ways to increase smart home adoption. What makes Intel's approach radically different? >> Yeah, so I'm glad that you asked that. We've spent years going into thousands of consumers' homes in North America, Western Europe, China, etc. To truly understand some of the pain points they were experiencing. From that, we basically, gave all this information to our architects and we really synthesized it into what areas we need to advance technology to enable some of these richer use cases. So we're really working on those foundational building blocks and so those four ones I mentioned earlier, connectivity, that one is paramount. You know, if you want to add 35 to 100 devices in your home, you better make sure they're all connected, all the time and that you've got good bandwidth between them. The second technology was voice, and it's not just voice in one place in your home, it's voice throughout your home. You don't want to have to run to the kitchen to turn your bedroom lights on. And then, vision. You know, making sure your home has the ability to see more. It could be cameras, could be motion sensors, it could be vision sensors. And then this last one is this local intelligence. This artificial intelligence. So the unique approach that Intel is taking is across all of our assets. In the data center, in our artificial intelligence organization, in our new technology organization, our IOT organization, in our client computing group. We're taking all of these assets and investing them in those four pillars and kind of really delivering unique solutions, and there's actually a couple of them that have been on display this week so far. >> How about DeepLens? That certainly was an awesome keynote point, and the device that Andy introduced is essentially a wireless device, that is basically that machine learning an AI in it. And that is awesome, because it's also an IOT device, it's got so much versatility to it. What's behind that? Can you give some color to DeepLens? What does it mean for people? >> So, we're really excited about that one. We partnered with Amazon at AWS on that for quite some time. So, just a reminder to everybody, that is the first Deep Learning enabled wireless camera. And what we're helped do in that, is it's got an Intel Atom processor inside that actually runs the vision processing workload. We also contributed a Deep Learning toolkit, kind of a software middleware layer, and we've also got the Intel Compute Library for deep neural networks. So basically, a lot of preconfigured algorithms that developers can use. The bigger thing, though, is when I talked about those four technology pillars; the vision pillar, as well as the artificial intelligence pillar, this is a proof point of exactly that. Running an instance of the AWS service on a local device in the home to do this computer vision. >> When will that device be available? And what's the price point? Can we get our hands on one? And how are people going to be getting this? >> Yeah, so what was announced during the keynote today is that there are actually some Deep Learning workshops today, here at re:Invent where they're actually being given away, and then actually as soon as the announcement was made during the keynote today, they're actually available for pre-order on Amazon.com right now. I'm not actually sure on the shipping date on Amazon, but anybody can go and check. >> Jeff Frick, go get one of those quickly. Order it, put my credit card down. >> Miles: Yes, please do. >> Well, that's super exciting and now, where's the impact in that? Because it seems like it could be a great IOT device. It seems like it would be a fun consumer device. Where do you guys see the use cases for these developing? >> So the reason I'm excited about this one, is I fundamentally believe that vision is going to enable some richer use cases. The only way we're going to get those though, is if you get these brilliant developers getting their hands on the hardware, with someone like Amazon, who's made all of the machine learning, and the cloud and all of the pieces easier. It's now going to make it very easy for thousands, ideally, hundreds of thousands of developers to start working on this, so they can enable these new use cases. >> The pace of innovation that AWS has set, it's palpable here, we hear it, we feel it. This is a relatively new business unit for Intel. You announced this, about a year ago at re:Invent 2016? Are you trying to match the accelerated pace of innovation that AWS has? And what do you see going on in the next 12 months? Where do you think we'll be 12 months from now? >> Yeah, so I think we're definitely trying to be a fantastic technology partner for Amazon. One of the things we have since last re:Invent is we announced we were going to do some reference designs and developer kits to help get Alexa everywhere. So during this trade show, actually, we are holding, I can't remember the exact number, but many workshops, where we are providing the participants with a Speech Enabling Developer toolkit. And basically, what this is, is it's got an Intel platform, with Intel's dual DSP on it, a microarray, and it's paired with Raspberry Pi. So basically, this will allow anybody who already makes a product, it will allow them to easily integrate Alexa into that product with Intel inside. Which is perfect for us. >> So obviously, we're super excited, we love the cloud. I'm kind of a fanboy of the cloud, being a developer in my old days, but the resources that you get out of the cloud are amazing. But now when you start looking at these devices like DeepLens, the possibilities are limitless. So it's really interesting. The question I have for you is, you know, we had Tom Siebel on earlier, pioneer, invented the CRM category. He's now the CEO of C3 IOT, and I asked him, why are you doing a startup, you're a billionaire. You're rich, you don't need to do it. He goes, "I'm a computer guy, I love doing this." He's an entrepreneur at heart. But he said something interesting, he said that the two waves that he surfs, they call him a big time surfer, he's hanging 10 on the waves, is IOT and AI. This is an opportunity for you guys to reimagine the smart home. How important is the IOT trend and the AI trend for really doing it right with smart home, and whatever we're calling it. There's an opportunity there. How are you guys viewing that vision? What progress points have you identified at Intel, to kind of, check? >> Completely agree. For me, AI really is the key turning point here. 'Cause even just talking about connected versus smart, the thing that makes it smart is the ability to learn and think for itself. And the reason we have focused on those technology pillars, is we believe that by adding voice everywhere in the home, and the listening capability, as well as adding the vision capability, you're going to enable all of this rich new data, which you have to have some of these AI tools to make any sense of, and when you get to video, you absolutely have to have some amount of it locally. So, that either for bandwidth reasons, for latency reasons, for privacy reasons, like some of the examples that were given in the keynote today, you just want to keep that stuff locally. >> And having policy and running on it, you know, access points are interesting, it gives you connectivity, but these are computers, so if someone gets malware on the home, they can run a full threaded process on these machines. Sometimes you might not want that. You want to be able to control that. >> Yes, absolutely. We would really believe that the wireless access point in the home is one of the greatest areas where you can add additional security in the home and protect all of the devices. >> So you mentioned, I think 120 different devices in your home that are connected. How far away do you think your home is from being, from going from connected to smart? What's that timeline like? >> You know what I think, honestly, I think a lot of the hardware is already there. And the examples I will give is, and I'm not just saying this because I'm here, but I actually do have 15 Echos in my house because I do want to be able to control all of the infrastructure everywhere in the home. I do believe in the future, those devices will be listening for anomalies, like glass breaking, a dog barking, a baby crying, and I believe the hardware we have today is very capable of doing that. Similarly, I think that a lot of the cameras today are trained to, whenever they see motion, to do certain things and to start recording. I think that use case is going to evolve over time as well, so I truly believe that we are probably two years away from really seeing, with some of the existing infrastructure, truly being able to enable some smarter home use cases. >> The renaissance going on, the creativity is going to be amazing. I'm looking at a tweet that Bert Latimar, from our team made, on our last interview with the Washington County Sheriff, customer of Amazon, pays $6 a month for getting all the mugshots. He goes, "I'm gonna use DeepLens for things like "recognizing scars and tattoos." Because now they have to take pictures when someone comes in as a criminal, but now with DeepLens, they can program it to look for tattoos. >> Yeah, absolutely. And if you see things like the Ring Doorbell today, they have that neighborhood application of it so you can actually share within your local neighborhood if somebody had a package stolen, they can post a picture of that person. And even just security cameras, my house, it feels like Fort Knox sometimes, I've got so many security cameras. It used to be, every time there was a windstorm, I got 25 alerts on my phone, because a branch was blowing. Now I have security cameras that actually can do facial recognition and say, your son is home, your daughter is home, your wife is home. >> So are all the houses going to have a little sign that says,"Protected by Alexa and Intel and DeepLens" >> Don't you dare, exactly. (laughs) >> Lisa: And no sneaking out for the kids. >> Yes, exactly. >> Alright, so real quick to end the segment, quickly summarize and share, what is the Intel relationship with Amazon Web Services? Talk about the partnership. >> It's a great relationship. We've been partnering with Amazon for over a decade, starting with AWS. Over the last couple of years, we've started working closely with them on their first party products. So, many of you have seen the Echo Show and the Echo Look, that has Intel inside. It also has a RealSense Camera in the Look. We've now enabled the Speech Enabling Developer Kit, which is meant to help get Alexa everywhere, running on Intel. We've now done DeepLens, which is a great example of local artificial intelligence. Partnered with all the work we've done with them in the cloud, so it really is, I would say the partnership expands all the way from the very edge device in the home, all the way to the cloud. >> Miles, thanks for coming, Miles Kingston with Intel, General Manager of the Smart Home Group, new business unit at Intel, really reimagining the future for people's lives. I think in this great case where technology can actually help people, rather than making it any more complicated. Which we all know if we have access points and kids gaming, it can be a problem. It's theCUBE, live here in Las Vegas. 45,000 people here at Amazon re:Invent. Five years ago, our first show, only 7,000. Now what amazing growth. Thanks so much for coming out, Lisa Martin and John Furrier here, reporting from theCUBE. More coverage after this short break. (light music)

>>Welcome back to the cubes coverage of H P S. Green Lake announcement. We've been following Green Lake and the cadence of announcements making. Now we're gonna talk about ransomware, ransomware become a household term. But what people really don't understand is that virtually any bad actor can become a ransomware criminal by going on the dark web hiring a ransomware as a service sticking, putting a stick into a server and taking a piece of the action and that is a really insidious threat. Uh, the adversaries are extremely capable, so we're going to dig into that with Omar assad, who's the storage platform, lead cloud data services at H P E and Deepak verma vice president of product Zito, which is now an H P E company Gentlemen, welcome to the cube. Good to see you. Thank you. >>Thank you. Welcome. Pleasure to be here. So >>over you heard my little narrative upfront. How does the Xarelto acquisition fit into that discourse? >>Thank you. Dave first of all, we're extremely excited to welcome Sir toe into the HP family. Uh, the acquisition of Puerto expands the Green Lake offerings from H P E uh, into the data protection as a service and ransomware protection as a service capabilities and it at the same time accelerates the transformation that the HP storage businesses going through as it transforms itself into more of a cloud native business, which sort of follows on from the May 4th announcements that you helped us cover. Uh, this enables the HP sales teams to now expand the data protection perimeter and to start offering data protection as a service and ransomware as a service with the best in class technologies uh, from a protection site as well as from ransomware recovery side of the house. And so we're all the way down already trying to integrate uh, you know, the little offerings as part of the Green lake offerings and extending support through our services organization. And the more of these announcements are gonna roll out later in the month. >>And I think that's what you want to see from it as a service offering. You want to see a fast cadence of new services that are not a box by a box that are applying. No, it's services that you want to access. So let's, let's talk about before we get into the tech, can we talk about how you're helping customers deal with ransomware? Maybe some of the use cases that you're seeing. >>First of all, extremely excited to be part of the HP family now. Um, Quick history and that we've been around for about 11 years. We've had about 9000 plus customers and they all benefit from essentially the same technology that we invented 11 years ago. First and foremost, one of the use cases has been continuous data protection. So were built on the CdP platform, which means extremely low RTO S and R P O S for recovery. I'll give you example there um, United Airlines is an application that cost them $1 million dollars for every hour that they're down. They use traditional approaches. That would be a lot of loss with Zito, we have that down two seconds of loss in case and the application goes down. So that's kind of core and fundamental to our plaque. The second uh critical use case that for us has been simplicity. A lot of customers have said we make the difficult, simple. So DRS is a complex uh process. Um, give you an example there. Hcea Healthcare Consolidated four different disaster recovery platforms into a single platform in Puerto and saved about $10 million dollars a year. So it's making that operations of having disaster recovery process is much simpler. Um the third kind of critical use case for us as uh, the environment has evolved as the landscape has involved has been around hybrid cloud. So being able to take customers to the platforms that they want to go to that's critical for us And for our customers an example, there is Kingston technology's so Kingston tried some competitive products to move to Azure, it would take them about 24 hours to recover 30 VMS or so with zero technology. They will get about all their 1000 VMS up in Azure instantaneously. So these are three use cases that were foundational. Built. Built the company in the tech. >>Nice. Thank you. Thank you for that. So simple works well these days, especially with all this complexity we have to deal with. Can we get into the secret sauce a little bit. I mean CdP has been around forever. What do you guys do that? That's different. Maybe you can talk about that. Sure. >>Um it's cdp based, I think we've perfected the technology. It's less about being able to just copy the data. It's more about what you do when things go bump. We've made it simpler with driven economies of scale lower and being platform agnostic. We've really brought that up across to whatever platforms once upon a time it was moving from physical to virtual or even across different virtualization platforms and then being able to move across to whatever cloud platform customer may want or or back >>to cbP continuous data protection by the way for the audience that may not know that go ahead. And >>one of the additional points that I want to add to the box comment over here is the the basics of platform independence is what really drew uh hp technologists into the technology because you know, one of the things we have many, we have the high end platform with the H B electra nine Kv of the electro six kids the midrange platform. Then we have a bunch of file and object offerings on the side. What zero does it University universally applies to all those technologies and along with, you know, as you pair them up with our computer offerings to offer a full stack but now the stack is disaster recovery capable. Natively with the integration of certo, you know, one of the things that, you know, Deepak talked about about the as your migrations that a lot of the customers are talking about cloud is also coming up as a D our use case for a lot of our customers, customers, you know, you know, as we went through thousands of customers interviews one of the, one of the key things that came back was investing in a D our data center which is just waiting there for a disaster to happen. It's a very expensive insurance policy. So absurd. Oh, through its native capabilities allows customers to do is to just use public cloud as a D our target and and as a service, it just takes care of all the format conversions and recoveries and although that's completely automated inside the platform and and we feel that, you know, when you combine this either at the high end of data center storage offering or the middle age offering with this replication, D. R. And ransomware protection built into the same package, working under the same hood, it just simplifies and streamlines the customers deployment. >>Come here a couple of things. So first of all historically, if you wanted to recover to appoint within let's say, you know, 10 seconds, five seconds you have to pay up. Big time. Number one. Number two is you couldn't test your D. R. It was too risky. So people just had it in, they had a checkbox on compliance but they actually couldn't really test it because they were afraid they were going to lose data. So it sounds like you're solving both of those problems or >>or you know we remember the D. R. Test where it was a weekend. It was an event right? It was the event and at the end of july that the entire I. T. Organizing honey >>it's not gonna be home this weekend. Exactly what >>we've changed. That is a click of a button. You can D. R. Test today if you want to you can have disaster recovery still running. You can D. R. Test in Azure bring up your environment an isolated network bubble, make sure everything's running and bring it and bring it down. The interesting thing is the technology was invented back when our fear in the industry was losing a data center was losing power was catastrophic, natural disasters. But the technology has lent itself very well to the new threats which which are very much around ransomware as you mentioned because it's a type of disaster. Somebody's going after your data. Physical servers are still around but you still need to go back to a point in time and you need to do that very quickly. So the technology has really just found itself uh appealing to new challenges. >>If a customer asks you can I really eliminate cyber attacks, where should I put my my if I had 100 bucks to spend. Should I spend it on you know layers and defense should I spend it on recovery. Both, what would you tell them? >>I think it's a balanced answer. I think prevention is 100% impossible. Uh It's really I'd say spend it in in thirds. You want to spend a third of it and and prevention a third of it maybe in detection and then a third of it in uh recovery. So it's really that balancing act that means you can't leave the front door open but then have a lot of recovery techniques invested in. It has to be it has to be a balance and it's also not a matter of if it's a matter of when so we invest in all three areas. Hopefully two of them will work to your advantage. >>You dave you you should always protect your perimeter. I mean that that goes without saying but then as you invest in other aspects of the business, as Deepak mentioned, recovery needs to be fast and quick recovery whether from your recovering from a backup disaster. Are you covering from a data center disaster a corrupted file or from a ransomware attack. A couple of things that zero really stitches together like journal based recovery has been allowed for a while but making journal based recovery platform independent in a seamless fashion with the click of a button within five seconds go back to where your situation was. That gives you the peace of mind that even if the perimeter was breached, you're still protected, you know, five minutes into the problem And, and that's the peace of mind, which along with data protection as a service, disaster recovery as a service and now integrating this, you know, recovery from ransomware along with it in a very simple, easy to consume package is what drew us into the >>more you can do this you said on the use the cloud as a target. I could use the cloud as an air gap if I wanted to. It sounds like it's cloud Native, correct? Just wrap your stack in kubernetes and shove it in the cloud and have a host and say we're cloud to No, really I'm serious. So >>absolutely, we we looked at that approach and that that's where the challenge comes in, Right? So I give you the example of Kingston technology just doesn't scale, it's not fast enough. What we did was developed a platform for cloud Native. We consume cloud services where necessary in order to provide that scalability. So one example in Azure is being able to use scale set. So think about a scenario where you just declare a disaster, you've got 1000 VMS to move over, we can spin up the workers that need to do the work to get 1000 VMS spin them down. So you're up and running instantaneously and that involves using cloud Native uh tools and technologies, >>can we stay on that for a minute, So take take us through an example of what life was like would be like without zero trying to recover and what it's like with Puerto resources, complexity time maybe you could sort of paint a picture. Sure. >>Let me, I'll actually use an example from a customer 10 Kata. They uh develop defensive fabrics, especially fabric. So think about firefighters, think about our men and women abroad that need protective clothing that developed the fibers behave. They were hit by ransomware by crypto locker. That this was before zero. Unfortunately it took they took about a two week uh data loss. It took them weeks to recover that environment, bring it back up and the confidence was pretty low. They invested in, they looked at our technology, they invested in the technology and then they were hit with a different variant of crypto locker immediately. The the IT administrators and the ITS folks there were relieved right, they had a sense of confidence to say yes we can recover. And the second time around they had data loss of about 10 seconds, they could recover within a few minutes. So that's the before and after picture giving customers that confidence to say yep, a breach happened, we tried our best but now it's up to recovery and I can recover without having to dig tapes out from some vault and hopefully have a good copy of data sitting there and then try that over and over again and there's a tolerance right before a time before which business will not be able to sustain itself. So what we want to do is minimize that for businesses so that they can recover as quickly as possible with as little data loss as possible. >>Thank you for that. So, Omar, there's a bigger sort of cyber recovery agenda that you have as part of, of green lake, I'm sure. What, what should we expect, what's next? Where do you want to take this? >>So uh excellent question point in the future day. So one of the things that you helped us, uh you know, unveil uh in May was the data services. Cloud console. Data services. Cloud console was the first uh sort of delivery as we took the storage business as it is and start to transform into more of a cloud native business. We introduced electra uh which is the cloud native hardware with the customers buy for persistent storage within their data center. But then data services, cloud console truly cemented that cloud operational model. Uh We separated the management from, from the devices itself and sort of lifted it up as a sas service into the public, public cloud. So now what you're gonna see is, you know, more and more data and data management services come up on the data services. Cloud console and and zero is going to be one of the first ones. Cloud physics was another one that we we talked about, but zero is the is the true data management service that is going to come up on data services, cloud console as part of the Green Lake services agenda that that HP has in the customer's environ and then you're gonna see compliance as a service. You're going to see data protection as a service. You're gonna see disaster recovery as a service. But the beautiful thing about it is, is choice with simplicity as these services get loaded up on data services, clown console. All our customers instantly get it. There's nothing to install, there's nothing to troubleshoot uh, there's nothing to size. All those capabilities are available on the console, customers go in and just start consuming Xarelto capabilities from a management control plane, Disaster recovery control plan are going to be available on the data services, cloud console, automatically detecting electro systems, rian Bear systems, container based systems, whichever our customers have deployed and from there is just a flip of a button. Another way to look at it is it sort of gives you that slider that you have data protection or back up on one side, you've got disaster recovery on one side, you've got ransomware protection on on the extreme right side, you can just move a slider across and choose the service level that you want without worrying about best practices, installation, application integration. All of that just takes control from the data services, cloud concepts. >>Great, great summary because historically you would have to build that right now. You can buy it as a service. You can programmatically, you know, deploy it and that's a game changer. Have to throw it over the fence to some folks. That's okay. Now, you know, make it make it work and then they change the code and you come back a lot of finger pointing. It's now it's your responsibility. >>Absolutely. Absolutely. We're excited to provide Zito continue provides the desert of customers but also integrate with the Green Green Lake platform and let the rest of Green Lake customers experience some of the sort of technology and really make that available as a service. >>That's great. This is a huge challenge for customers. I mean they do, I pay their ransom. Do not pay the ransom. If I pay the ransom the FBI is going to come after me. But if I don't pay the ransom, I'm not gonna get the crypto key. So solutions like this are critical. You certainly see the president pushing for that. The United States government said, hey, we got to do a better job. Good job guys, Thanks for for sharing your story in the cube and congratulations. Thank >>you. Thank you David. >>All right. And thank you for watching everybody. Uh this is the, I want to tell you that everything that you're seeing today as part of the Green Lake announcement is going to be available on demand as part of the HP discover more. So you got to check that out. Thank you. You're watching the cube. >>Mhm mm.

>> Announcer: Live from Las Vegas, it's theCUBE. Covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Welcome back to theCUBE's live coverage of ServiceNow Knowledge18 here in Las Vegas, Nevada. I'm your host Rebecca Knight, along with my co-host Dave Vellante. We're joined by Michael D'Ippolito. He is the VP of Run Services at Nationwide Insurance. He's coming to us straight from Columbus, Ohio. So thanks so much for joining us. >> Thanks for having me, appreciate it. >> So tell our viewers a little bit about what you do. What is Run Services? What do you do at Nationwide? >> Sure, yes. We are a part of what we call our infrastructure and operations group and we're really an enterprise services group. Basically in my resposibility, I have resposibility over our data centers, over what we call our enterprise command centers. Pretty much the eyes on glass, 24 by 7 operations that kind of keeps everything running. Also, I have resposibility for all our run processes. So our ITSM processes, both from a process ownership and a process management. So that's where ServiceNow really comes in. >> So we've talked about this before, Mike. It's just in terms of the insurance business. Some of the things that are driving that business. We always talk about digital disruption but it's really, the insurance business hasn't really been digitally disrupted. Maybe it's coming. Not maybe, I'm sure it's coming. But what's driving your business today and how important, important is the wrong word. How much of a factor is digital in terms of the decisions that you make on a day-to-day basis? >> Well, it's huge. You know, as you probably heard we're really at a big inflection point in the world today and we are going to be disrupted and we actually focus on how can we disrupt ourselves because somebody else is going to. It's just a matter of time until Amazon wants to get into the insurance business. >> Dave: That's right. (Rebecca and Dave laugh) >> We laugh but you know. >> No, I know they're planning it. >> They're selling groceries. You're not really competing with other insurance carriers anymore. You're competing with Amazon and Google for that experience, that user experience, that ease of use, that direct interaction. You know, when you think about it, home and auto insurance, it's kind of a commodity. It's like buying your gas and electric. So you've got to be able to create that direct experience to our members, to our consumers just like an Amazon would. >> We hear so much of these buzzwords at this conference but also just in general in the technology industry. Automation, streamlining, this emphasis on customer experience. How do these play in to your digital transformation in terms of what you're thinking about at Nationwide? >> Yeah, right now one of our big drivers is what we call the need for speed. Speed is everything right now in terms of staying competitive, coming out with features as fast as possible. And when you think about it, the only way to really get fast is you have to be automated, right? You can't be manual and fast. So really now we have to look at, how can we automate everything and how do we treat infrastructure like software, basically, like code. And we can roll out changes any time, any day, any hour, versus the old days when you had these big releases once a month of your applications. Those days are kind of gone. >> So I got to ask you about, I mean, one of the things that cloud brought was this notion of self-service. There's certainly pressure for customers to do self-service. You see that, they're going to comparison shop, they're going to pick their package, et cetera. So that's part of the disruption and then the other part is potentially on the actuarial side, the actuarial robots. What do you see happening there and how is that affecting your business? >> That actually is an interesting use case. That's probably where big data is really coming into play. So for example, in auto insurance, your rates change every six months and what we do is we look backwards and say how did you drive over those last six months? Did you have accidents? Did you have tickets? You know, et cetera, and then we price you accordingly. Well, now with the information, the data we can get out of your vehicle 24 by 7, we can price you every day. So we can look at basically what's called metered insurance or insurance by the mile that we use the technology to enable that kind of a pricing model. >> And I would imagine you're at the point where you can begin to predict riskier situations. >> Absolutely, and anticipate it just like they do in health care, right, so, you know, not much different but yeah, that's definitely a new thing coming. >> You're collecting all of this data. I mean and this is the thing about the collection of the data is the easy part really but it's really knowing what the data is telling you and then how to act on the data in the right way. >> Yes. >> So is it a lot of trial and error or how are you determining what insights are the actionable ones? >> Well, as you know, a very popular skill out there are data scientists. Data and analytics, that's huge right now. So getting people who have that skill to understand the so what from the data and to be able to make good decisions on it, and then how do you even automate that? That's a big field right now actually. >> We're obvioulsy ways away but you see it in the news pretty much every day. You go to Silicon Valley, you can't miss it. What's the conversation like around autonomous vehicles? Because everybody says, well the problem is who's liable if something goes wrong and then you see that big accident, the Uber situation. What's the conversation like internally around that? >> It's going to be here sooner than you think. It's already here. You're seeing it more and more. You're seeing every car getting smarter now. It's getting closer and closer. It's an inevitable future. We are going to have those. And so now we have to look at what is going to be the actual model around that? We'll figure that out. But as you know, in a lot of these industries, the technology has really been ahead of the regulation. When Uber came out, there were basically discussions about coverage and liability and all those kinds of things. So normally in any fast-paced technology, usually it leads and then the rest follows. It'll get figured out. >> And I think you will figure it out because you guys are good with numbers. (laughs) Insurance companies can always figure out the cost of insuring something, right? >> Right. >> Should we envision kind of a hybrid shared risk model between the consumer and the technology supplier? Or do you think it's all going to be in the consumer? >> Well, it's hard to say exactly but we know there will be some compression in insurance because of it. And really, you might get to the point where the software is what gets insured and not the person. >> Right. >> Right. So we're already talking to automakers about how do you insure the actual vehicle versus the person driving it because they're not driving it anymore. >> That's a shock to the 100-plus-year-old system, isn't it? (laughs) >> Absolutely. Again, it was a shock when people said, you mean we're not going to use horses anymore? >> (Rebecca laughs) Good point. Point taken. >> So you go through time and there's these big revolutions that happen and I think we're approaching one. >> Talk about the ServiceNow situation. We've talked about your journey before but maybe remind us of that, where you are, what you thought of the new announcements today, maybe give us an update. >> Yeah, we're excited. We've been on ServiceNow for almost three years. Over the last year, we've made tremendous progress in terms of, we have a program now called IT Simplification and a little shout out to my partner Rick Schnierer who is my AVP who runs the platform for us. They do a great job. I'm kind of like the business partner to them. Right now what we're doing is it's a focus on configuration management and we're slowly retiring legacy systems and repositories across the company into the one single source which is in ServiceNow. We're also really focused on hardware and software asset management. Getting an understanding of all the assets we own and constantly scanning the network to understand who's connecting in and if it's a threat, if it's a good guy or a bad guy, that's important. Very important right now. And then lastly, like I said, the need for speed. How can our operations side support this need for increased pace of development? Because once you put it in, it's got to operate, right? And it's go to run. >> So where are you at today? Mostly, so ITSM, doing SecOps or did I infer that or no? >> Yeah, we have all the ITSM in. Actually we're moving to Kingston this weekend. We're doing that upgrade. We are involved with the HR module. We're bringing in Workday as our platform in July and ServiceNow will integrate with that. We're looking at the portfolio management. So now that we have the ITSM under control, we're slowly looking at where else can ServiceNow play for us? Cloud's a big play for us so, you know, we're right now working with a cloud provider and then there's a lot of APIs and interfacing back into ServiceNow. So that's going to be important for us. >> And you're saying for infrastructure? Cloud for infrastructure? >> Correct. >> Or infrastructure's a service? >> Correct, right now, well, we focus on SaaS first. Anything that can be SaaS, we want to go SaaS. ServiceNow is a perfect example. Salesforce.com, all those kinds of SaaS solutions. Then IaaS and PaaS are also important, right? So right now, by the end of 2018, we'll only be about probably 10% external cloud and 90% on-prem, but three years from now, it'll be the other way around. We'll probably be 90% cloud. >> Awesome. >> What keeps you coming back to Knowledge? >> You know, it's just the, look at this crowd. >> I know, it's true. >> I mean, the networking, the peers you meet. It's been so great because you have that time of year where you can share ideas, share stories, and all that. Where ServiceNow is going with the platform is always so interesting and appealing. We're really interested in hearing and getting to that agent workspace which I think would be great for internal, like our help desk services. So, more automation inline with where we're going. We think it's a great platform for that. >> Rebecca: Great, well Michael, thank you so much for coming on theCUBE. It was great talking to you. >> Great, thank you. >> Thanks, enjoyed it, thank you. >> I'm Rebecca Knight, for Dave Vellante, we will have more from theCUBE's coverage of ServiceNow Knowledge18 just after this.

>> Voiceover: Live from Las Vegas, it's The Cube, covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Welcome back everyone to The Cube's live coverage of ServiceNow Knowledge 2018, #Know18. I'm Rebecca Knight your host, along with my co-host Dave Vellante. We have two guests joining us, we have Mitch Kenfield who is an Advisory Principal CIO advisory at KPMG, And Adrian Hubbard, Service and Process Manager at Linklaters, thanks so much for joining us. >> Thank you. >> Thank you. >> Adrian, I want to start with you. Can you describe for our viewers what was sort of happening, what was going on at Linklaters, sort of the inflection point when you realized you needed to step up your game in this arena, and just lay that our for our viewers. >> Yeah, I think, from Linklaters' point of view, we're very much, kind of, use the telephone more than anything else, it's very much a contact organization through voice. And we wanted to implement a platform that would engage the users in a different way, more to be self-serving, more chats, more routes to service, if you like. And we saw ServiceNow as the right tool for that. We did some due diligence, an RFP process, but that wasn't enough, we had to build a strong business case to make sure we were doing the right things. And that's where we kind of reached out to KPMG to see what they could offer us in this space. >> Talk more about your business, and-- >> So we're a global firm, we're kind of part of the magical circle, so there's four or five in that arena we call our strong peers. And yeah, as I say, fairness can be very challenging, their day themselves needs to be very efficient and very effective, and they don't always want to have to tell Serve. So one of our challenges is the more time they spend with us the less time they're billing their clients, which is obviously the revenue of the firm. But then when you've got 450 plus partners they all feel they want to run the firm in a way that perhaps is regional, office-based. So some of those challenges play into delivering service also. >> You talked about doing your due diligence, how did you go about that? What was the, what was your process? >> So we engaged with a consultancy firm to help us through the process. Through that, we worked out where do we want to get to, our vision. We short-listed some top-set firms, there was about three or four on the list that we knew met the requirement. So we then went through the process of the next layer down and series of workshops with each provider. Obviously, there was a cost model, we got supplier guys involved from a contract perspective, tried to get the best price. But I think deep down we always felt ServiceNow was the right fit for us. And I've been at Linklaters six years, when I first joined Linklaters that time ago, we went through the same process. We chose the different tool then, but ServiceNow was in the list and we really would have liked to have gone there six years ago. But I think ServiceNow have improved a lot during that time, and now was the right time for us to choose them. >> It was the one that got away, and now you've brought it back. >> Absolutely, yeah, yeah. >> So, Linklaters reached out to you, so then describe about, describe how you sort of shepherded them through the process? >> Yeah, so they had reached out in our London office, and I guess I had happened to be there and jumped on the phone with them, and first of all, when Adrian mentions about the culture of a law firm, so we are a consulting firm you know, consultants and tax and audit and finance folks, so we kind of understand that, it's kind of like the industry where everybody's the boss and nobody's the boss. So we jumped on the phone, and one thing that I mentioned as Adrian was describing, is that we see this space as an opportunity to truly change the way the technology business is running, and therefore change the ultimate business. >> Adrian: Yeah. >> And so, we tell our clients a lot, if you're just going to kind of implement, it might not be the right thing for you. But if you're ready to transform the way you run technology, and the way that supports the business, we think we can help, and we brought something to them that we call Powered IT, which I can give some details on, but just at the highest levels it's our view of an accelerated transformation that includes some technology components, but more than that includes operating models and process to say let's not reinvent things, let's bring to you what's good, and that way we can spend our time focusing on the specifics for you, to get you to the business result you're looking for, and that was kind of that first conversation we had. >> Sure. >> The word "agile transformation" is popping into my head. It's such a common theme today, but is it relevant to what we're talking about? >> Yeah, absolutely. So, I'll start, Adrian, and maybe you can give your perspective on it. When we bring our view, and again, we call it Powered just as a tag, but really what it is, it's an acceleration. It's the components from an organizational aspect's process, metrics, supporting ServiceNow with some kind of near-the-box configurations to add in to that. And then, to your question, it's how do we deliver that in an agile way, where you see it constantly. We don't take six months before we show something, you're seeing it regularly and we can course correct and tweak to say we have a limited amount of effort we can spend, let's spend that in that agile methodology for things that transform you sooner and get it done. Would you, what was y'all's reaction? >> Yeah, to add to that, so what's really important for me is that we hadn't worked with KPMG before although, we were talking early doors, we didn't know what this Powered IT was, what it would bring us. So we made sure we had a number of kind of pre-sales workshops, where I could see the product and they've got a very strong environment where I could see exactly was I was going to get at the end, which is important for me because there's always a risky element, going in with a new incumbent, it was going to be success of this, or not, and I had to be sure that we did the right risk assessment. So actually, to be able to be provided with that kind of out-of-the-box experience, because often you go into sales call, or into the RFP process, and then you come out the back end of it and actually you see, actually getting what you saw in that sales demo. So it's important that we did that extra look. So I think we're able to see the end product, if you like, and then through talking with Mitch and the team and the UK guys, we then knew what the approach would be, very agile and quite aggressive as well. We delivered end-to-end in 14 weeks, which, considering that it took us from the old tool to ServiceNow, it took us from the old way of working to a new way of working on day one. We switched the old tool off on day one. There was a lot going on, it was... you know, we had to really stick to scope, as well, to manage mistake holders. >> I'm interested in how you managed risk, because that's the one thing that popped into my head. When you transform and your business processes are affected you know, you want to move fast, but there are dependencies. So how did you identify those, how did you guys manage the risks? >> I think, in terms of... We were quite strong on what our service improvement plans were looking like, we knew that we needed a new tool, we knew the tool would unlock it, but we didn't know is the extras that KPMG would bring through the Powered IT. So it's more than just the tool set itself, it's actually the processes and the policies. So because we're able to look at those day one, we knew what the end product was going to be. And plus we went with the preferred Powered IT platform. What we didn't try to do was to impose our current way of thinking. We took the KPMG way of thinking, which was the less risky approach, it meant that we weren't customizing, which was a big danger for us, potentially. So we also knew it was fully supported, because KPMG have put this Powered IT module together, built with other clients as well, so we knew we were adopting best practices from other clients. But actually it was fitting, the way we needed to get to from our vision. I think the thing that made me a little bit nervous was we'd been through a number of maturity assessments over the years that said our processes were quite mature. Where we were weak, really, was some of the reporting, the visibility of performance. So again, but they were kind of the key things from risk assessment, let's make sure the key things we could see working. And then we knew the risk was less. But, you know, as always, when you engage with a new incumbent for the first time, we had to make sure that we met the team as well, that was also a key part for us, to make sure the people we'd be working with, from day one, we met them at the beginning. And they stayed throughout. So that was also very good for us. >> So, Adrian, I'm curious about your particular experience, and then Mitch, I wonder if you could chime in on other clients that you might see. You always hear, "You got to have buy-in from the C-suite, top down." But when you go change the operating model, I often hear, the senior management goes, and then the rest of the company's like, "Well, we got to run the business," and they're trying to catch up. >> Yep. >> Is that a common problem? How do you guys deal with that? >> I think our senior team have been in place, they've been very supportive. There hasn't really been an issue there. And a lot of the senior team also supported the decision to go ServiceNow, which is important for me. I have to say, not all parts of the IT organization thought it was the right decision, but we had to demonstrate that as we went through, and the series of workshops was important, early doors. So we made sure we engaged the right stakeholders, they felt part of the whole solution end-to-end. And yes, people tried to push the scope at times, tried to scope creep, but actually senior management were very good and supportive of me to stick to scope. Stick to what we've agreed to do, help me push back certain people when they became challenging. And because we stuck to that scope, we delivered on-time. The fear would've been, as you know, you customize, you go off track-- >> I think what we see, to your analogy and I think your degree, you have to have that senior commitment. There can't be a question of why. But what breaks down often is that kind of next layer of key managers and stakeholders that maybe didn't show up to that meeting, and you know, didn't, you know... And those are the little things that can kind of take it off rail. And to your question earlier about agile, the great thing about a well-executed agile methodology is not about doing agile configuration it's about doing agile business transformation. It's about having regular interaction points where those stakeholders are involved in the process. And every day they're in those sessions and they're seeing something, and they get the chance, and we connect together. And that's what gets you to the end of it, to where instead of just in 14 weeks, we deployed a technology that kind of feels the same way we used to work. You deploy a technology and people are doing things different, and that's a key aspect. >> Dave: Lot of repetition. >> A lot of repetition. >> A lot of overcommunicating-- >> And we tell our clients a lot, it's going to be a rough 14 weeks, because you're going to be involved. This isn't the old-- >> Adrian: You didn't tell me that. >> Well (laughs). It's not where you're going to give me requirements we're going to go away and build something and hope we got it right and you're going to say, like you said, "That's not, wait, I thought I was going to get..." We're going to be in it and the teams are working collaboratively, stand up meetings, and all those kind of things. And it can be interesting, and for many of our clients, it changes the way they think about programs, right? >> So how's it going? I mean, what's the business impact been? >> It's been really positive. Of course, it talks for itself, it's really good. The fact that you've got 20 thousand people here kind of demonstrates that, but it is the industry platform, and there isn't anything that comes close to it, if we're being honest. But in terms of where we are now, we are gaining a lot of benefit from the dashboards, the reporting. We've still got to make sure the quality of data is good, of course, but actually visualizing our performance is really powerful. But we've also introduced new ways of interacting with our user base, so chat is a big thing for us. We now have a user pool to what we want to market out to the firm. So we're trying to get away from the telephone as the first point of contact, and move into other contact areas, like the portal. So that's the kind of areas that we need to kind of market outwards. But we're about three months in from go live. So we're now kind of looking back on some of the improvements already that we want to make, so looking at how we're using it, working with teams on using it better. So the improvement cycle is kicking in. And we've already made some minor improvements, and there will be more to come. >> So you avoided custom mods-- >> Yes. - Which is very important because the allure of custom modifications, it's so attractive, and then you know, you get technical debt and stuck with it. What have you learned, if you had a mulligan, would you choose anything differently? >> Yeah, it's an interesting point, because I think one of the things we could've done better already was the training. Because what was really powerful about Powered IT, there was training material, we had to kind of adapt that for our own change process, of course. Understanding our culture and how training with Linklaters, isn't necessarily the same as perhaps other technology firms, where they're expected to sell flurn. Very much the model at Linklaters is kind of classroom-led training, that tends to be our culture. And we perhaps didn't do enough of that before go live. So yes, everyone went live day one, they could log a ticket, but they couldn't unlock all the other benefits that we were really trying to deliver. So I guess that training's one of those areas that you could always overdo, but I think I would go back and arrange training earlier, make sure people know the training's coming, make sure their diaries are free as well, because we're all busy people. But I think, yeah, I think for now, I think we did a good job in the 14 weeks, but I'd come back and look at training again. >> And when was your go live? >> We went live on the 12th of February, this year. >> Oh okay, and single CMDB is the vision, or goal, or? >> Yeah, so we went live with the CMDB, we're now able to populate that out, and everyone knows that can be a pain point. So that's one of the kind of evolutions we're going through now, but as I said, we switched off the old tool on the day one, so we had to make sure the customer-facing processes were working, that we could may control changes, problem management could deal with issues that reoccur. So all of that was in place, but actually we've unlocked the power of the tool for visibility, managing the tasks across teams is quite big for us, as well. But that whole transparency of data has really improved the way we work. >> Rebecca: Great. >> I think one aspect, to play on your question, there are certain aspects of the platform in that transformation that you may not do all, but you need to design an architecture right the first time. So on the CMDB, you might not have it all the way populated, but if it's not architected with a good CMDB data model, it'll catch up later on, to your point. And so, a lot of, I think, that effort is a certain amount of time you have to show value, and then you lay that groundwork, you start improving, and then you make the decision of if and when do we expand into new things. When do we move into new areas, outside of the core, and those kind of things. >> For you know this, Mitch, too, and one of... I'm going to comment, maybe you could... You could give me your observations, early on in the ServiceNow, before the big ascendancy, a lot of mistakes were made, in terms of companies not standardizing, getting the CMDB architecture right, for a lot reasons, you had politics, people were trying to slide it in. And now you see a much more consistent vision around CMDB, how to architect it, single CMDB, one throat to choke, essentially. >> Yeah, I agree totally, and I think if you look at the ecosystem of what this all is, you have to level set on it, it was drastically different from a platform perspective, and three or four years ago to now. And to your point, I think there were a lot of relatively quick implementations, if you will. And again, quick implementation is okay, as long as it's architected and thought through for the long term, and I think we're seeing in the market some implementations that maybe made some short cuts, if you will, but to your point, the things that you got to get right, you got to get the CMDB and the data model, that layer, right. You got to get the employee experience right. You only get one chance to set an employee experience. If you underwhelm, then you've lost that audience, right? Then they're like, "Eh, well, yeah," you know? And you only get one chance to have some transformation, and it doesn't have to be going from crawling to, you know, sprinting, but if you go from crawling and it feels kind of the same way, you lose interest in expanding the capabilities. So I think that's, we've all, you know, the ecosystem has learned from that, and there are some things that you've got to get correct, and what we try to do with our clients is try to say, "Hey, let's not argue about those things, right, let's not start with a whiteboard and argue about the things that should be the same for Linklaters, that should be the same for anybody." Let's get that 80% where it's, let's focus on the things that are specific to you and not deal with that common stuff. >> Right, capture their attention right away. >> Absolutely. And we use a term internally, and sometimes with our clients too, everybody knows the 80/20 rule, right? You do 80% of it, you just should stop, it's not worth the effort. We switch that, we say 20% is what makes it work for you. We should just power through the 80% that should be the same for everybody else, and the 20% that makes it work for you. How do you deal with employee experience in a law firm, right, where everybody are knowledge workers, that have all, that's very different than employee experience in a, you know, industrial manufacturing firm, right? So that's what matters and what makes it transformational to a specific organization. >> And you're in Jakarta, or Kingston? >> We're on Jakarta-- >> Yeah, okay. - Yeah. >> Great. >> And again, because it's delivered through Powered IT, KPMG do a lot of the testing, once the new version's available, it's their offer to us in terms of making sure it's fit for purpose for their Powered IT platform. And as been said, it's the 20% that we've configured for Linklaters is what we need to test. >> So we're big believers, and John mentioned it this morning of only stay one behind at most. We're big believers in we should help our clients learn what's in the new upgrade, and how it applies to them. So we've heard this week, there's some great things coming out with London, some new things in the experience, and some automations, and so on. So our job is to bring that to our clients with Powered, and say, "Yep, we're ready, here's what's in it, and by the way, here's what they've advanced, and here's what you should look to add, and let's have that ready for you." >> So, you keep people, at worst, in minus one-- >> Correct. - Is really your objective-- >> And our general advice to clients, is if you need to go to N, if there's functional new capabilities that change your business, go to N right away. If it's more just add-ons, stay at N-1, learn from the others, and keep advancing, but never go later than that, absolutely. >> And but, ServiceNow will allow you to be N-2, right? >> They will. Going forward, they're going to keep you more to N-1-- >> Dave: Pushing you along, right? >> Exactly. So you want to save just one release back and you want to make sure, and again, to use that term I used earlier, as long as you stay near-to-the-box, you know, and out-of-the-box, if you turn it on, you need to add it, get it into your environment, you need tailor it, right? But there's a fine line between staying close to that and doing way too much, and over-configuring, not even customization, just making it to where it's really complex, and that's where we try to keep our clients away from. >> Do they still do cakes, you get a cake? >> Yes. >> Had a good one. >> Yeah, we had a really good one on go live. Yeah, it's actually on LinkedIn so yeah, go and have a look. >> A bunch of law books, it looks really smart. >> It looks really good. >> Yeah, it looked very good. >> And it tasted great, too. (laughing) >> That's important. Adrian, Mitch, thanks so much for coming on The Cube, we had a great time. >> Thank you both. >> You're welcome, thank you. >> I'm Rebecca Knight, for Dave Vellante, we will have more from ServiceNow Knowledge18, coming up just after this. (music)

hey welcome back everybody Jeff Rick here with the cube we're at the mill pedis at an interesting event is called the auto tech council innovation in motion mapping and navigation event so a lot of talk about autonomous vehicles so it's a lot of elements to autonomous vehicles this is just one small piece of it it's about mapping and navigation and we're excited to have with us our first guest again and give us a background of this whole situation just Derick Curtin and he's the founder and chairman of the auto tech council so first up there welcome thank you very much good to be here absolutely so for the folks that aren't familiar what is the auto tech council autofit council is a sort of a club based in Silicon Valley where we have gathered together some of the industry's largest OMS om is mean car makers you know of like Rio de Gono from France and a variety of other ones they have offices here in Silicon Valley right and their job is to find innovation you find that Silicon Valley spark and take it back and get it into cars eventually and so what we are able to do is gather them up put them in a club and route a whole bunch of Silicon Valley startups and startups from other places to in front of them in a sort of parade and say these are some of the interesting technologies of the month so did they reach out for you did you see an opportunity because obviously they've all got the the Innovation Centers here we were at the Ford launch of their innovation center you see that the tagline is all around is there too now Palo Alto and up and down the peninsula so you know they're all here so was this something that they really needed an assist with that something opportunity saw or was it did it come from more the technology side to say we needed I have a new one to go talk to Raja Ford's well it's certainly true that they came on their own so they spotted Silicon Valley said this is now relevant to us where historically we were able to do our own R&D build our stuff in Detroit or in Japan or whatever the cases all of a sudden these Silicon Valley technologies are increasingly relevant to us and in fact disruptive to us we better get our finger on that pulse and they came here of their own at the time we were already running something called the telecom Council Silicon Valley where we're doing a similar thing for phone companies here so we had a structure in place that we needed to translate that into beyond modem industry and meet all those guys and say listen we can help you we're going to be a great tool in your toolkit to work the valley ok and then specifically what types of activities do you do with them to execute division you know it's interesting when we launched this about five years ago we're thinking well we have telecommunication back when we don't have the automotive skills but we have the organizational skills what turned out to be the cases they're not coming here the car bakers and the tier 1 vendors that sell to them they're not coming here to study break pad material science and things like that they're coming to Silicon Valley to find the same stuff the phone company two years ago it's lookin at least of you know how does Facebook work in a car out of all these sensors that we have in phones relate to automotive industry accelerometers are now much cheaper because of reaching economies of scale and phones so how do we use those more effectively hey GPS is you know reach scale economies how do we put more GPS in cars how do we provide mapping solutions all these things you'll set you'll see and sound very familiar right from that smartphone industry in fact the thing that disrupts them the thing that they're here for that brought them here and out of out of defensive need to be here is the fact that the smartphone itself was that disruptive factor inside the car right right so you have events like today so gives little story what's it today a today's event is called the mapping and navigation event what are people who are not here what's what's happening well so every now and then we pick a theme that's really relevant or interesting so today is mapping and navigation actually specifically today is high definition mapping and sensors and so there's been a battle in the automotive industry for the autonomous driving space hey what will control an autonomous car will it be using a map that's stored in memory onboard the car it knows what the world looked like when they mapped it six months ago say and it follows along a pre-programmed route inside of that world a 3d model world or is it a car more likely with the Tesla's current they're doing where it has a range of sensors on it and the sensors don't know anything about the world around the corner they only know what they're sensing right around them and they drive within that environment so there's two competing ways of modeling a 3d world around autonomous car and I think you know there was a battle looking backwards which one is going to win and I think the industry has come to terms with the fact the answer is both more everyday and so today we're talking about both and how to infuse those two and make better self-driving vehicles so for the outsider looking in right I'm sure they get wait the mapping wars are over you know Google Maps what else is there right but then I see we've got TomTom and meet a bunch of names that we've seen you know kind of pre pre Google Maps and you know shame on me I said the same thing when Google came out with a cert I'm like certain doors are over who's good with so so do well so Eddie's interesting there's a lot of different angles to this beyond just the Google map that you get on your phone well anything MapQuest what do you hear you moved on from MapQuest you print it out you're good together right well that's my little friends okay yeah some people written about some we're burning through paper listen the the upshot is that you've MapQuest is an interesting starting board probably first it's these maps folding maps we have in our car there's a best thing we have then we move to MapQuest era and $5,000 Sat Navs in some cars and then you might jump forward to where Google had kind of dominate they offered it for free kicked you know that was the disruptive factor one of the things where people use their smartphones in the car instead of paying $5,000 like car sat-nav and that was a long-running error that we have in very recent memory but the fact of the matter is when you talk about self-driving cars or autonomous vehicles now you need a much higher level of detail than TURN RIGHT in 400 feet right that's that's great for a human who's driving the car but for a computer driving the car you need to know turn right in 400.000 five feet and adjust one quarter inch to the left please so the level of detail requires much higher and so companies like TomTom like a variety of them that are making more high-level Maps Nokia's form a company called here is doing a good job and now a class of car makers lots of startups and there's crowdsource mapping out there as well and the idea is how do we get incredibly granular high detail maps that we can push into a car so that it has that reference of a 3d world that is extremely accurate and then the next problem is oh how do we keep those things up to date because when we Matt when when a car from this a Nokia here here's the company house drives down the street does a very high-level resolution map with all the equipment you see on some of these cars except for there was a construction zone when they mapped it and the construction zone is now gone right update these things so these are very important questions if you want to have to get the answers correct and in the car stored well for that credit self drive and once again we get back to something to mention just two minutes ago the answer is sensor fusion it's a map as a mix of high-level maps you've got in the car and what the sensors are telling you in real time so the sensors are now being used for what's going on right now and the maps are give me a high level of detail from six months ago and when this road was driven it's interesting back of the day right when we had to have the CD for your own board mapping Houston we had to keep that thing updated and you could actually get to the edge of the sea didn't work we were in the islands are they covering here too which feeds into this is kind of of the optical sensors because there's kind of the light our school of thought and then there's the the biopic cameras tripod and again the answers probably both yeah well good that's a you know that's there's all these beat little battles shaping up in the industry and that's one of them for sure which is lidar versus everything else lidar is the gold standard for building I keep saying a 3d model and that's basically you know a computer sees the world differently than your eye your eye look out a window we build a 3d model of what we're looking at how does computer do it so there's a variety of ways you can do it one is using lidar sensors which spin around biggest company in this space is called Bella died and been doing it for years for defense and aviation it's been around pointing laser lasers and waiting for the signal to come back so you basically use a reflected signal back and the time difference it takes to be billows back it builds a 3d model of the objects around that particular sensor that is the gold standard for precision the problem is it's also bloody expensive so the karmak is said that's really nice but I can't put for $8,000 sensors on each corner of a car and get it to market at some price that a consumers willing to pay so until every car has one and then you get the mobile phone aside yeah but economies of scale at eight thousand dollars we're looking at going that's a little stuff so there's a lot of startups now saying this we've got a new version of lighter that's solid-state it's not a spinning thing point it's actually a silicon chip with our MEMS and stuff on it they're doing this without the moving parts and we can drop the price down to two hundred dollars maybe a hundred dollars in the future and scale that starts being interesting that's four hundred dollars if you put it off all four corners of the car but there's also also other people saying listen cameras are cheap and readily available so you look at a company like Nvidia that has very fast GPUs saying listen our GPUs are able to suck in data from up to 12 cameras at a time and with those different stereoscopic views with different angle views we can build a 3d model from cheap cameras so there's competing ideas on how you build a model of the world and then those come to like Bosh saying well we're strong in car and written radar and we can actually refine our radar more and more and get 3d models from radar it's not the good resolution that lidar has which is a laser sense right so there's all these different sensors and I think there the answer is not all of them because cost comes into play below so a car maker has to choose well we're going to use cameras and radar we're gonna use lidar and high heaven so they're going to pick from all these different things that are used to build a high-definition 3d model of the world around the car cost effective and successful and robust can handle a few of the sensors being covered by snow hopefully and still provide a good idea of the world around them and safety and so they're going to fuse these together and then let their their autonomous driving intelligence right on top of that 3d model and drive the car right so it's interesting you brought Nvidia in what's really fun I think about the autonomous vehicle until driving cars and the advances is it really plays off the kind of Moore's laws impact on the three tillers of its compute right massive compute power to take the data from these sensors massive amounts of data whether it's in the pre-programmed map whether you're pulling it off the sensors you're pulling off a GPS lord knows where by for Wi-Fi waypoints I'm sure they're pulling all kinds of stuff and then of course you know storage you got to put that stuff the networking you gotta worry about latency is it on the edge is it not on the edge so this is really an interesting combination of technologies all bring to bear on how successful your car navigates that exit ramp you're spot-on and that's you're absolutely right and that's one of the reasons I'm really bullish on self-driving cars a lot more than in the general industry analyst is and you mentioned Moore's law and in videos taking advantage of that with a GPUs so let's wrap other than you should be into kind of big answer Big Data and more and more data yes that's a huge factor in cars not only are cars going to take advantage of more and more data high definition maps are way more data than the MapQuest Maps we printed out so that's a massive amount of data the car needs to use but then in the flipside the cars producing massive amounts of data I just talked about a whole range of sensors I talked lidar radar cameras etc that's producing data and then there's all the telemetric data how's the car running how's the engine performing all those things car makers want that data so there's massive amounts of data needing to flow both ways now you can do that at night over Wi-Fi cheaply you can do it over an LTE and we're looking at 5g regular standards being able to enable more transfer of data between the cars and the cloud so that's pretty important cloud data and then cloud analytics on top of that ok now that we've got all this data from the car what do we do with it we know for example that Tesla uses that data sucked out of cars to do their fleet driving their fleet learning so instead of teaching the cars how to drive I'm a programmer saying if you see this that they're they're taking the information out of the cars and saying what are the situation these cars are seen how did our autonomous circuitry suggest the car responds and how did the user override or control the car in that point and then they can compare human driving with their algorithms and tweak their algorithms based on all that fleet to driving so it's a master advantage in sucking data out of cars massive advantage of pushing data to cars and you know we're here at Kingston SanDisk right now today so storage is interesting as well storage in the car increasingly important through these big amount of data right and fast storage as well High Definition maps are beefy beefy maps so what do you do do you have that in the cloud and constantly stream it down to the car what if you drive through a tunnel or you go out of cellular signal so it makes sense to have that map data at least for the region you're in stored locally on the car in easily retrievable flash memory that's dropping in price as well alright so loop in the last thing about that was a loaded question by the way and I love it and this is the thing I love this is why I'm bullish and more crazier than anybody else about the self-driving car space you mentioned Moore's law I find Moore's law exciting used to not be relevant to the automotive industry they used to build except we talked about I talked briefly about brake pad technology material science like what kind of asbestos do we use and how do we I would dissipate the heat more quickly that's science physics important Rd does not take advantage of Moore's law so cars been moving along with laws of thermodynamics getting more miles per gallon great stuff out of Detroit out of Tokyo out of Europe out of Munich but Moore's law not entirely relevant all of a sudden since very recently Moore's law starting to apply to cars so they've always had ECU computers but they're getting more compute put in the car Tesla has the Nvidia processors built into the car many cars having stronger central compute systems put in okay so all of a sudden now Moore's law is making cars more able to do things that they we need them to do we're talking about autonomous vehicles couldn't happen without a huge central processing inside of cars so Moore's law applying now what it did before so cars will move quicker than we thought next important point is that there's other there's other expansion laws in technology if people look up these are the cool things kryder's law so kryder's law is a law about storage in the rapidly expanding performance of storage so for $8.00 and how many megabytes or gigabytes of storage you get well guess what turns out that's also exponential and your question talked about isn't dat important sure it is that's why we could put so much into the cloud and so much locally into the car huge kryder's law next one is Metcalfe's law Metcalfe's law has a lot of networking in it states basically in this roughest form the value of network is valued to the square of the number of nodes in the network so if I connect my car great that's that's awesome but who does it talk to nobody you connect your car now we can have two cars you can talk together and provide some amount of element of car to car communications and some some safety elements tell me the network is now connected I have a smart city all of a sudden the value keeps shooting up and up and up so all of these things are exponential factors and there all of a sudden at play in the automotive industry so anybody who looks back in the past and says well you know the pace of innovation here has been pretty steep it's been like this I expect in the future we'll carry on and in ten years we'll have self-driving cars you can't look back at the slope of the curve right and think that's a slope going forward especially with these exponential laws at play so the slope ahead is distinctly steeper in this deeper and you left out my favorite law which is a Mars law which is you know we underestimate in the short term or overestimate in the short term and underestimate in the long term that's all about it's all about the slope so there we could go on for probably like an hour and I know I could but you got a kill you got to go into your event so thanks for taking min out of your busy day really enjoyed the conversation and look forward to our next one my pleasure thanks all right Jeff Rick here with the Q we're at the Western Digital headquarters in Milpitas at the Auto Tech Council innovation in motion mapping and navigation event thanks for watching

>> Announcer: Live from Orlando, Florida, it's theCUBE, covering ServiceNow Knowledge17, brought to you by ServiceNow. >> And we're back in Orlando, everybody, this is Dave Vellante with Jeff Frick, CJ Desai is here, he's the Chief Product Officer of ServiceNow, the newly-minted, 150 days in, CJ, great to see you off the keynote, fantastic job. >> Thank you, thank you, thank you. >> Very crisp, I was struck by your story about last October, when you were contacted by ServiceNow, you fired up the platform and started playing around and built an app. >> Yeah! (chuckling) >> And you found it was a good experience. >> It was a great experience, I'll tell you, Dave, from my standpoint, when you join a company that is built on a platform like ServiceNow, you want to make sure that you feel great about the foundational elements, because as always, you can build floors on top of a foundation, only when the foundation is strong. So ServiceNow always, I don't know if you know, but it started out as a platform company, and then they used the service management use case, and went deep in that use case, and then went to Operations Management and other products, as you know, and I just wanted to make sure that, hey, how easy it is, if I'm a customer, or if I'm in the product development organization, to create an app, and having that strong foundational layer, even simple things like, it's the cloud offering, first of all, you have a integrated development environment, you can start creating workflows, UI, all of that is so easy, and there's no headache of figuring out how to deploy the app, because it's right there, so you just publish it and you're done. >> Yeah, it's interesting, one of the first CUBE interviews we did at Knowledge was with Doug Leone, the famous VC, and he told the story of, he saw this, "What am I going to do with this?" And sent Fred away and said, "Build something on top of it," and that's what happened, but. But help our audience understand, CJ, because you talked about Jakarta today. >> Yeah. >> Now, Jakarta is a platform capability, and if we understand it correctly, we were talking about it earlier, the business units have to figure out, "Okay, how do we apply that capability "to our particular needs, and our customer needs," so explain that. >> Yeah, so ultimately, there are two things that happens in the products organization, right? First is, we do release this every six months, twice a year, so every six months, twice a year, and we go by alphabets, and we pick cities, just a fun factoid, we pick cities that go from North America or South America, to Europe, to Asia. So, H released last year, around this time, was Helsinki, after Helsinki was Istanbul, and then we have Jakarta, so are now in Asia, and then next will be Kingston, and the one after that is London, so you go alphabetically, and the reason we pick this city names in alphabets, we support our customers, because it's a multi-instance paradigm, n minus one and n minus two releases, so when you make, name of the cities, customers will have a conversation with me and say, "CJ, we went on Helsinki, we're upgrading to Istanbul, "or we're going to skip Istanbul, "and go straight to Jakarta," for example, so, first of all, that's our naming system that we use, every six months, you will see us talk about a specific release, and you heard from John yesterday, he was very clear in saying, "Listen, "our customers want to hear our roadmap, "they want to know what we are up to," and so we took that customer feedback to heart, and decided, why don't we just tell them what's coming in Jakarta? So Jakarta will be released this summer, and from a planning standpoint, Dave, to answer your question, we figure out first, what do our customers want, and is it in the applications that we talked about, like ITSM or CSM or security or HR, and for those applications to deliver the functionality, what do we need to do in the platform so that the functionality can be delivered? So the requirement process is a complex requirement process, the applications team will give requirements to the platform, customers also sometimes have requirements for the platform on scale, platform will build a functionality, applications team will build the features on top of it, so in Jakarta, which is coming out this summer, we have six new products, you saw some of them, software asset management and others, 30 major features, and that's close, so after Jakarta, we're already in planning for Kingston. After Kingston, I think I'm going to announce it for the first time, will be London, so it's Jakarta, Kingston, London, are the three-- >> Yeah, so when we go to these events, a lot of times, at the keynotes, somebody will make a product announcement and you get a little golf clap, it always happens at ServiceNow Knowledge that you get somebody hooting in the audience, today, the hoot came for software asset management, they were the three high level things you talked about today, performance with UX, and performance, and then the vendor risk management, which is very interesting, we'll talk about that a little bit, and then the software asset management, the guy must've been an Oracle customer hooting and hollering. But so, give us the high level overview. >> Alright, so, here is the thing, right? Our buyer is IT organization, we started with IT. We love our buyer, and CIO, to all the organizations that support CIO, head of infrastructure, the portfolio management team, the business management within IT. And one of the things that we saw, and this is the requirement that we got is, when we talk to CIOs about how to make the IT organization productive, because IT, it's a tough job, man, it's a tough job, things go down, you're like, "Okay, of course, IT," and technology's such an integral part of our life that people are always looking at IT to make sure they deliver great technologies. So, IT budget, and every, debated this all the time, everybody talks about IT budgets, what's happening to IT budgets, how the IT budget is going up or down, are you asked to do more with less, there are so many examples I can use, but as per Gartner, 25% of the IT budget is on software licensing. Then there is hardware and all the other infrastructure and people-related cost. 25%, so if, and as you know, some of the vendors put you through a pretty complex audit process, so why can't we, our chief buyer is IT, why can't we give them a platform, or a product, that allows them to discover how many products you are using by vendor, Microsoft, Oracle, some of you examples you used, for desktop, it's Adobe and others, you use these products, are you really utilizing all the licenses you have, or are you potentially in overage so that you actually have a sense of where you stand with every vendor that you're using that makes up your 25% budget. We talk to financial customers, manufacturing industrial customers, these are billions of dollars of budget, 25% is still a big number, any improvement in that 25% could go a long way, and what CFOs do not like is when CIOs go and tell the CFO, "Hey, we didn't clear this audit, "or potentially these guys may sue us "for a contract violation," so we decided we are going to create a product that helps you get a good posture on what your licensing is, does that make sense? And that's why, you know, I also saw on Twitter, a lot of people love this idea that, hey, can we automate this software as a management process, discover what's being deployed, allow you to reclaim, and at the end, help you save the cost. >> And the other one was the cloud management platform, which again, similar type of situation, especially with all the freemium services, and test dev, and card swiping, that they can get unruly pretty quickly. >> In my last job, as you are aware, I was in infrastructure space, and one of the things in speaking to customers, always realized that hey, IT was not agile enough, we decided, for some customers, we decided to go and use some of the public cloud services, re-enter infrastructure, because IT could not keep up with our demands, and you go and speak to IT, they say there is so much going on that sometimes it's not easy for devops communities, in particular, that you pointed out, so much going on. So, IT felt like they were losing control, developers, whether they're application developers in IT organization or in business units, just wanted agility, and IT felt like if they cannot deliver that level of service, you had the share-to-IT functions going on in the departments, and with cloud, we acquired a company called iTapp about a year ago in April. The first year was all focused on re-platforming, like I said today, I think many times, I'm sure people got sick of listening to me, is, we are going to re-platform every acquisition that we make, and we usually buy technologies in our business so far. And we re-platform it, and now, IT gets the control back, once for, you know, you help the developers, devops people, sure, go and use public cloud, but IT will still have a single pane of glass that allows you to look at your resource mapping, utilization, understanding the cost and the usage, whether you are on public cloud service, or in private cloud service. >> Well, it's huge, because it's very unpredictable, and people often complain, "Oh, I get the cloud bill at the end of the month," but a lot of times, there's not just one cloud bill, it's many, many cloud bills, and what happens, you know, you remember this, in the downturn, a lot of CFOs said, "Go to the public cloud, "eliminate Capax" and then, when we came out of the downturn, lines of business said, "I got to move fast, "and this cloud thing seems to be working for me." IT seems to have really, you know, in previous big picture trends like this, mega trends, IT oftentimes has been sort of pushing back, you saw that with client server. >> Yeah, their security concerns, compliances-- >> And today, they're announcing, okay, we have to embrace cloud, or we're toast. >> And Dave, I'll tell you, there are customers, I mean, some very large customers in regulated industries who tell me that, "CJ, we are now cloud first, "before we decide to do something," I mean, that's a pretty big statement, cloud first, I mean, if you remember 2008, '09, '10, '11, '12, '13, that journey, and how customers were reluctant, and they're like, "I don't know, my data losing from here," and this and that-- >> Well, I got to bring this up, so, I was reading an article on SiliconANGLE, EMC World is going on, Dell EMC World this week, and Michael Dell basically made this statement in his keynote, "If you're a cloud first, "you could be in trouble because of the expanse," and so forth. I don't buy it. I think the other, I love you, Michael, but the value that customers are getting out of going cloud-first, maybe, yeah, maybe the bill at the end of the month is high, but the other residual effects on your business, the speed, the agility, the processes, you're seeing it, aren't you? >> I mean, I'll tell you straight up, there are customers that are asking us, because, you know, again, IT's our key buyer, and key customer, and we appeal to the IT department, and the CIOs, even at the CIO dinner the night before, people are embracing cloud. Now, they are on a journey, some of them have maybe mode few percent of their workload, some of them may have mode a little higher, but they're on some journey, and they're trying to balance when the cost pros out with the cons, or the cons out with the pros, but, can you give us some kind of control plane to manage our cloud resources, understand the usage, understand the billing, which we do for financial management, and tie-in with IT processes, because that resource life cycle, that VMU provision, right, that VMU provision in the cloud, what happens to the life cycle of VM, can you create an incident, can you close it out, that's equally important besides just saying, "Yeah, I'm going to move this particular workload to cloud." So I feel that customers are on this journey of some kind of combination of public and private cloud, and it doesn't have to be zero-sum game, infrastructure continues to grow, I don't feel like, okay, if you do this, that means you do not do private, or if you do private, that doesn't mean-- >> Certainly both, and containers are going to just exacerbate the problem. >> Right, and the demand for compute, store, and networking is not going down any time soon. >> I'll tell you, my role environment, so my team lends cloud infrastructure, so our platforms runs on cloud infrastructure, and you saw some of the elevated numbers, I mean, our growth, we are trying to invest in compute network storage ahead of our growth, so it's not, and we are a cloud service, so I always look at it as, this doesn't have to be zero-sum game, customers are expanding, they want the agility, like you said, the agility, the business is asking, "Can you develop this app faster, "can you give me what I need," is what's driving-- >> It's a topline game for businesses, Jeff, I just want to inject some of those numbers on your cloud, 50,000 instances, 150 million active users, and 10 billion transactions per month. >> Yeah. >> Yeah, but I want to get, it's funny you're talking about Jakarta and London, I remember when we were doing interviews around Dublin, which I guess was a while ago, but I'm curious, 'cause there's this other trade-off, and get your perspective, is in a devops world, in kind of a continuous integration and development world, people want to push code frequently. On the other hand, in an enterprise world, and we've talked to a couple of customers, they can only take it so much, and so you've kind of got this yin and yang, and you want to get stuff out, and there's patches, and this and that, and you're on a relatively aggressive for current enterprise release schedule, on the other hand, the trend is clearly, just keep pumping it out, pumping it out, pumping it out, how do you see that kind of sorting itself out over time with these big enterprise customers? >> I will tell you, from a technology standpoint, there is nothing that prevents us from doing more frequent releases, yes, we have to mature our product release processes, we have to mature our cloud operations and how fast we can churn the code. There is nothing that prevents us, technically, from instead of two releases a year, maybe do four releases, it doesn't! But our customers, and we talk about customers first, listening to customers, you saw John today, I mean, we want to listen to them, and they will tell us, that I was at a large financial institution in Boston two weeks ago, and, your hometown, and they told me that, "I cannot do every six months, "I cannot do every six months, CJ, "we usually skip a release," right? And so we are just listening for specific use cases around service management, the processes, customer-run, same thing with operations management, right now, six months about feels right, every six months, release, we do quarterly patches, where we do not release features in those quarterly patches, and for emerging products, like you saw customer service, they challenge security, the team did a great job, when I look at those releases, is it potentially can we push things fast? Maybe, but right now, I'm okay, based on customer feedback. If customers come and say, "I want every three months," I hope to see what does that mean-- >> Let me run something by you, I told Jeff I've been sharing cabs with practitioners all week, it's great to just have wonderful conversations, and one said to me, "I've asked ServiceNow "if they can give me more granularity in the releases," I said, that doesn't sound trivial, in other words, if I can selectively choose features, is that even technically feasible? >> I mean, this is the isolating the feature, micro-feature development, making sure your schema is abstracted enough, I mean, there are companies in consumer world who do that, and push code out really fast. I would say, right now, one of the requirements I do get is, we're on IT service management, we have been a customer of ServiceNow for a while, but on this other thing, say, customer service, or HR, I want to take the new features, so my IT service management is at, say, Helsinki, but I want to take the HR, like the onboarding you saw, the onboarding, which is in Jakarta. So does that mean I need to upgrade this thing to leverage the HR feature? The answer is yes, because it's all built on single platform. Now, I do not want to do where customers, we give them two instances, and then we do a back-end pipe integration, a connector, so you can be on Helsinki for ITSM, and Jakarta, that-- >> Architecturally-- >> That breaks our model, and I do not want to do that. There are companies who, say, reside in different tenant, and will give you one for, I do not want to do that. >> I wanted to ask you about this too, CJ, because, you have a dogma, you have your own cloud, you see a lot of SaaS companies now saying, okay, you see Workday, a little bit of Salesforce, certainly Infor, putting their applications on AWS, for example. You guys, very proud of your cloud, you have availability, and I think when you show availability numbers, you downplay it, actually, people don't understand this, you're talking about application availability, you're not talking about the server light-- >> No. >> Okay, so you're very dogmatic about your cloud, and this issue here, you won't do something that maybe is going to help one customer but is going to ruin the experience down the road for all, and that dogma, is that a valid, it's not a criticism, it's an observation, and is that a good thing? >> So I would say there are some design principles, or operational principles that we live with, and we are going to stick to them, like we talk about acquisitions and re-platforming, think about, Dave, you have somebody coming in, you acquire a machine learning company, really smart kids, really smart people, machine learning or data sciences, an art more than a science, and looking at prediction accuracies and things like that. Now you tell them, "Welcome to ServiceNow, "here's your badge, you just got onboarded, "it's great what you've built, "we are not going to sell that standalone, "you need to re-platform," which typically takes one year, "Before we can launch your product." That's a tough message. That's a tough message for an engineering team to hear, that now I have to figure out how does this platform work, I mean, if I had a magic bullet, I would tell you, if I can wave the magic wand, I'll say, acquire this technology in machine learning AI, combine that with our organic development, it's a re-platform and I have a toolkit that does this thing, and it is a re-platform, but that's not easy. So on these kind of principles, whether it's re-platforming, how we do the releases, how we look at the cloud, and I want to answer your public cloud question. Right now, as you know, we're active, active, I've seen your interviews in the past here, we're active, active, we have eight pair of data centers, 16 around the world, and we make sure with our multi-instance architecture, the availability of the uptimes are very high for our customers, and when they upgrade, we know, they can pull the upgrade, "I'm going, CJ, "from Helsinki to Istanbul, or Helsinki to Jakarta," and that's available, but, can we potentially look at moving our footprint, and renting infrastructure in a public cloud? I'll never say never, but right now, there is no need for it. >> No, you see it, and there are advantages to having your own cloud. I want to ask about your role as Chief Product Officer. Fred Luddy had that title, we were sort of joking earlier, Fred was a coder, the company brought Frank in for adult supervision, and so you're inheriting that title, but I sense that you're a different type of manager, what do you bring to ServiceNow? >> I'll tell you, first of all, Fred, Frank, and even Dan McGee, who had this role last year, he was here, I saw his interview, he's here today, phenomenal people, I mean, I have interacted with all three of them, Dan McGee helped me transition into my role, Frank hired me, and just great, great guy, and even with Fred, going through this user experience, how do I think about the user experience based on the persona, he's always there to provide input with lots and lots energy and feedback. So let me just tell you for, in less than 30 seconds, what my role is, right? My role is, I help platform team, and the cloud infrastructure team, that's lead by Pat Casey, who is doing CreativeCon tomorrow, I have individual application general managers that you saw some of them today, and I also have the customer support organization, and the user experience teams. So that's my overall responsibility, so it's the responsibility that Fred Luddy had til last October, and Dan McGee had til last December, combined into one. So, it's a big job, and it comes with a lot of responsibilities on behalf of our customers, you talk about high availability number, we help to make sure that we keep our cloud service up and running secure, but at the same time, bringing this innovation in platform and the applications is my job. So, I'd done, fortunately, when I started out of college, makes me sound old, I know, but when I came out of college, I worked for a company that was doing business applications for a long time, eight years there, and I worked in that applications technology team, I worked in the CRM applications, did things for financial applications, and I went on security software, understanding how you protect the applications you write, all the way from OS up to the application stack, and then I worked for a infrastructure company, as you know. So that gave me a really good feel on the entire stack, how do you scale that stack, and be maniacally focused on, what do customers want? I mean, I am very fortunate to have great customer relationships, many companies around the globe, I reach out to them, ask them, tell me what you think, tell me what we are doing well, so customer focus, having done product development for 20-plus years now, and understanding all the way from application stack to the underlying infrastructure, is where I can help-- >> Yeah, it's like a triple threat that you have, the product innovation, the enterprise class, security, and scaling, as you mentioned, very, very important. Alright, CJ, I love having you on theCUBE, you're a great guest, we could continue, but we got to leave it right there. Great to see you again-- >> Thank you, thank you so much, I really appreciate it. >> Alright, keep it right there, everybody, we'll be back with our next guest, this is theCUBE, we're live from Knowledge17, we'll be right back.

>> Man's Voice: Live from Orlando, Florida, it's theCUBE covering ServiceNow Knowledge17, brought to you by ServiceNow. >> Welcome back to Orlando, everybody. This is theCUBE, the leader in live tech coverage. We go out to the events, we extract a signal from the noise. My name is Dave Vellante, and I'm here with my co-host, Jeff Frick. This is theCUBE's fifth year covering Knowledge. We started in Las Vegas, a little small event, Jeff, at Aria Hotel, and it's exploded from 3,500 all the way up to 15,000 people here in Orlando at the Convention Center. This is day two of our three day coverage. And, we heard this morning, you know, day one was the introduction of the new CEO, John Donahoe, taking over the reins for Frank Slootman. And, actually it was interesting, Jeff. Last night, we went around to some of the parties and talked to some of the folks and some of the practitioners. It was interesting to hear how many people were saying how much they missed Fred. >> Right, right. >> And the culture of fun and kind of zaniness and quirkiness that they sort of have, and there's some of that that's maintained here. We saw that in the keynotes this morning, and we'll talk about that a little bit, but what are your impressions of sort of that transition from, you know, really the third phase now we're into of ServiceNow leadership? >> Right, well as was commented again last night at some of the events, you know, a relatively peaceful transition, right. So, the difference between an evolution and a revolution is people die in revolutions. This was more of an evolution. It was an organized handoff, and a lot of the product leaders are relatively new. We just saw CJ Desai. He said he's only 100 days ahead of where John is at 45 days. So, it is kind of a, I don't know if refresh is the right word, but all new leadership in a lot of the top positions to basically go from, as been discussed many times, from kind of the one billion dollar mark to the four billion dollar mark, and then, of course, onward to the 10. So, it sounds like everyone is very reverent to the past, and Fred has a huge following. He's one of our favorite guest. The guy's just a super individual. People love him. That said, you know, it's a very clear and focused move to the next stage in evolution of growth. >> Well, I think that, you know, Fred probably, I mean, he may have said something similar to this either in theCUBE or sort of in back channel conversations with us, is, you know, ServiceNow, when they brought in Frank Slootman, it needed adult supervision. And, Fred doesn't strike me as the kind of person that's going to be doing a lot of the, you know, HR functions and performance reviews and stuff. He wants to code, right. I mean, that was his thing. And, now, we're seeing sort of this next level of ascension for ServiceNow, and you seen the advancement of their product, their platform. So this morning, CJ Desai kicked off the keynotes. Now, CJ Desai was an executive in the security business. He was an executive at EMC, hardcore product guy. He's a hacker. You heard him this morning saying when he was at a previous company, he didn't mention EMC, but that's what he was talking about, I'm pretty sure. They use ServiceNow, and when ServiceNow started recruiting him, he said I opened up an instance and started playing around with it, and see if I could develop an app, and I was amazed at how easy it was. And, they started talking to some of the customers and seeing how passionate they were about this platform, and it became an easy decision for him to, you know, come and run. He's got a big job here. He run, he's basically, you know, manages all products, essentially taking over for Fred Luddy and, you know, Dan McGee as a chief operating officer even though he hasn't used that title 'cause he's a product guy. But, all the GMs report up into him, so he is the man, you know, on top of the platform. So, he talked this morning about Jakarta, the announcement, and the key thing about, you know, that I'm learning really in talking to ServiceNow over the years, is they put everything in the platform, and then the business units have to figure out how to leverage that new capability, you know, whether it's machine learning or AI or some kind of new service catalog or portal. The business units, whether it's, you know, the managers, whether it's Farrell Hough and her team, she does IT service management, Abhijit Mitra who does customer service management, the IT operations management people, the HR folks, they have to figure out how they can take the capabilities of this platform, and then apply it to their specific use cases and industry examples. And, that's what we saw a lot of today. >> But, it's still paper-based workflow, right? 'Cause back to Fred's original vision, which I love repeating about, the copy room with all the pigeonholes of colored paper that you would grab for I need a new laptop, I need a vacation request, I need whatever, which nobody remembers anymore. But, you know, at the end of the day, it's put in a request, get it approved, does it need to be worked, and then executed. So, whether that's asking for a new laptop for a new employee, whether that's getting a customer service ticket handled, whether it's we're swinging by doing name changes, it's relatively simple process under the covers, and then now, they're just wrapping it with this specific vocabulary and integration points to the different systems to support that execution. So, it's a pretty straightforward solution. What I really like about ServiceNow is they're applying, you know, technology to relatively straightforward problems that have huge impact and efficiency, and just getting away from email, getting away from so many notification systems that we have, getting away from phone calls, getting away from tech-- Trying to aggregate that into one spot, like we see it a lot of successful applications, sass applications. So, now you've got a single system of record for the execution of these relatively straightforward processes. >> Yeah, it really is all about a new way to work, and with the millennial work force becoming younger, obviously, they're going to work in a different way. I saw, when I tweeted out, was the best IT demo that I'd ever seen. Didn't involve a laptop, didn't involve a screen. What Chris Pope did, who's kind of an evangelist, he's in the CSO office, he was on... the chief strategy office, he was on yesterday. He came up with a soccer ball. Right, you saw it. And, he said >> Football. Make sure you say it right. He would correct you. (Jeff laughs) >> And, he said for those of you who are not from the colonies, this is a football. And then, he had somebody in a new employee's t-shirt, he had the HR t-shirt, the IT t-shirt, the facilities t-shirt, and they were passing the ball around, and he did a narrative on what it was like to onboard a new employee, and the back and forth and the touch points and, you know, underscoring the point of how complex it is, how many mistakes can be made, how frustrating it is, how inefficient it is, and then, obviously, setting up conveniently the morning of how the workflow would serve us now. But, it was a very powerful demo, I thought. >> Well, the thing that I want to get into, Dave, is how do you get people to change behavior? And, we talk about it all the time in theCUBE. People process in tech. The tech's the easy part. How do you change people's behavior? When I have to make that request to you, what gets me to take the step to do it inside of service now versus sending you that email? It seems to me that that's the biggest challenge, and you talk about it all the time, is we get kind of tool-creep in all these notification systems and, you know, there's Slack and there's Atlassian JIRA and there's Salesforce and there's Dropbox and there's Google Docs and, you know, the good news is we're getting all these kind of sass applications that, ultimately, we're seeing this growth of IPA's in between them and integration between them, but, on the bad side, we get so many notifications from so many different places. You know, how do you force really a compliance around a particular department to use a solution, as we say that, that's what's on your desk all the time, and not email? And, I think that's, I look forward to hearing kind of what are best practices to dictate that? I know that Atlassian, internally, they don't use email. Everything is on JIRA. I would presume in ServiceNow, it's probably very similar where, internally, everything is in the ServiceNow platform, but, unfortunately, there's those pesky people outside the organization who are still communicating with email. So, then you get, >> Exactly. >> Then, now, you're running kind of a parallel track as you're getting new information from a customer that's coming in maybe via email that you need to, then, populate into those tickets. That's the part I see as kind of a challenge. >> Well, I think it is a big challenge. And, of course, when you talk to ServiceNow people privately and you say to them, "Have you guys eliminated email?" Then, they roll their eyes and "I wish." (Jeff chuckles) But, I would presume their internal communications, as you say, are a lot more efficient and effective. But, you know, it's a Cloud app, and Cloud apps suffer from latency issues. And, it's like when you go into a Cloud app, you know, you log in. A lot of times, it logs you out just for security reasons, so you got to log back in and you get the spinning logo for awhile. You finally get in and then, you got to find what you want to do, and then you do it. And, it's a lot slower just from an elapse time standpoint than, actually not from an elapse time. So, from an initiation standpoint, getting something off your desk, it's slower. The elapse time is much more efficient. >> Jeff: Right, right. >> And so, what I think ends up happening is people default to the simple email system. It's a quick fix. And then, it starts the cycle of hell. But, I think you're making a great point about adoption. How do you improve that adoption? One of the things that ServiceNow announced this morning, is that roughly 30% improvement in performance, right. So, people complain about performance like any Cloud-based application, and it's hard. You know, when you even when you use, you know, look at LinkedIn. A lot of times, you get a LinkedIn request, and you go, "I'll check it later." You don't want to go through the process of logging in. Everybody's experienced that. It's one of those >> Right, right. >> Sort of heavy apps, and so, you just say, "Alright, I'll figure it out later." And, Facebook is the same thing. And, no doubt, that ServiceNow, certainly Salesforce, similar sort of dynamics 'cause it's a Cloud-based app. And so, hitting performance hard, as you say, the culture of leaving it on your desk. The folks at Nutanix, Dheeraj is telling me they essentially run their communications in Slack. (chuckles) and so, >> Right. >> You know, they'll hit limits there, I'm sure, as well, but everybody's trying to find a new way to work, and this is something that I know is a passion of yours, because the outcome is so much better if you can eliminate email trails and threads and lost work. >> Right. And, we're stuck now in this, in the middle phase which is just brutal 'cause you just get so many notifications from so many different applications. How do you prioritize? How do you keep track? Oh my God, did you ping me on Slack? Did you ping me on a text? Did you ping me on a email? I don't even know. The notification went away, went off my phone. I don't even know which one it came through its difficulty. The good news is that we see in sass applications and, again, it's interesting. Maybe just 'cause I was at AWS summit recently. I just keep thinking AWS, and in terms of the efficiency that they can bring to bear, that resources they can bring to bear around CP utilization, storage utilization, security execution, all those things that they can do as a multi-vendor, Cloud-based application, and apply to their Cloud in support of their customers on their application, will grow and grow and grow, and quickly surpass what most people would do on their own 'cause they just don't have the resources. So, that is a huge benefit of these Cloud-based applications and again, as the integration points get better, 'cause we keep hearin' it 'cause you got some stuff in Dropbox, you got some stuff in Google Docs, you got some stuff in Salesforce. That's going to be interesting, how that plays out, and will it boil back down to, again, how many actual windows do you have open that you work with on your computer. Is it two? Is it three? Is it four? Not many more than that, and it can't be. >> Yeah, so today here at Knowledge, it's a big announcement day. You're hearing from all the sort of heads of the businesses. Jakarta is the big announcement. That's the new release of the platform. Kingston's coming, you know, later on this year. ServiceNow generally does two a year, one in the spring summer, one in the fall, kind of early winter. And, Jakarta really comprises performance improvement, a new security capability where, I thought this was very interesting, where you have all these vendors that you're trying to interact with, and you tryin' to figure out, okay, "What do I integrate with "in terms of my third party vendors, and who's safe?" You know, and "Do they comply "to my corpoetics?" >> Right, right. >> And, ServiceNow introducing a module in Jakarta which going to automate that whole thing, and simplify it. And then, the one, the big one was software asset management. Every time you come to a conference like Knowledge, and you get this at Splunk too, the announcements that they make, they're not golf claps. You'd get hoots and woos and "Yes" and people standing up. >> Jeff: That was that and that was the one, right? >> Software SM Management was the one. >> Jeff: (chuckles) put a big star on that one. >> Now, let's talk about this a little bit because they mentioned in, they didn't mention Oracle, but this is a bit pain point of a lot of Oracle customers, is audits, software audits. >> Jeff: Right, right. >> And, certainly Oracle uses software audits as negotiating leverage, and clients customers don't really know what they have, what the utilization is, do they buy more licenses even though they could repurpose licenses. They just can't keep track of all that stuff, and so, ServiceNow is going to do it for ya. So, that's a pretty big deal and, obviously, people love that. As I said, 30% improvement in performance. And, yeah, this software asset management thing, we're going to talk to some people about that and see what their-- >> But, they got the big cheer. >> What their expectation is. >> The other thing that was interesting on the product announcement, is using AI. Again, I just love password reset as an example 'cause it's so simple and discrete, but still impactful about using AI on relatively, it sounds like, simple processes that are super high ROI, like auto-categorization. You know, let the machine do auto-categorization and a lot of these little things that make a huge difference in productivity to be able to find and discover and work with this data that you're now removing the people from it, and making the machine, the better for machine processes handled by the machine. And, we see that going all through the application, a lot of the announcements that were made. So, it's not just AI for AI, but it's actually, they call it Intelligent Automation, and applying it to very specific things that are very fungible and tangible and easy to see, and provide direct ROI, right out of the gate. >> Well, this auto-categorization is something that, I mean, it's been a vexing problem in the industry for years. I mentioned yesterday that in 2006 with the federal rules of civil procedure change that made electronic documents admissible, it meant that you had to be able to find and submit to a court of law all the electronic documents on a legal hold. And, there were tons of cases in the sort of mid to late part of the 2000's where companies were fined hundreds and millions of dollars. Morgan Stanley was the sort of poster child of that because they couldn't produce emails. And, as part of that, there was a categorization effort that went on to try to say, okay, let's put these emails in buckets, something as simple as email >> Right, right. >> So that when we have to go find something in a legal hold, we can find it or, more importantly, we can defensively delete it. But, the problem was, as I said yesterday, the math has been around forever. Things like support vector machines and probabilistic latent semantic index and all these crazy algorithms. But, the application of them was flawed, and the data quality >> Jeff: Right, right. >> Was poor. So, we'll see if now, you know, AI which is the big buzz word now, but it appears that it's got legs and is real with machine learning and it's kind of the new big data meme. We'll see if, in fact, it can really solve this problem. We certainly have the computing horse power. We know the math is there. And, I think the industry has learned enough that the application of those algorithms, is now going to allow us to have quality categorization, and really take the humans out of the equation. >> Yeah, I made some notes. It was Farrell, her part of the keynote this morning where she really talked about some of these things. And, again, categorization, prioritization, and assignment. Let the machine take the first swag at that, and let it learn and, based on what happens going forward, let it adjust its algorithms. But, again, really simple concepts, really painful to execute as a person, especially at scale. So, I think that's a really interesting application that ServiceNow is bringing AI to these relatively straightforward processes that are just painful for people. >> Yes, squinting through lists and trying to figure out, okay, which one's more important, and weighting them, and I'm sure, they have some kind of scoring system or weighting system that you can tell the machine, "Hey, prioritize, you know, these things," you know, security incidence >> Right, right. >> Or high value assets first. Give me a list. I can then eyeball them and say, okay, hm, now I'm going to do this third one first, and the first one second, whatever. And, you can make that decision, but it's like a first pass filter, like a vetting system. >> Like what Google mail does for you, right? >> Right. >> It takes a first pass. So, you know, these are the really specific applications of machine learning in AI that will start to have an impact in the very short-term, on the way that things happen. >> So, the other thing that we're really paying attention here, is the growth of the ecosystem. It's something that Jeff and I have been tracking since the early days of ServiceNow Knowledge, in terms of our early days of theCUBE. And, the ecosystem is really exploding. You know, you're seeing the big SIs. Last night, we were at the Exen Sure party. It was, you know, typical Exen Sure, very senior level, a bunch of CIOs there. It reminded me of when you go to the parties at Oracle, and the big SIs have these parties. I mean, they're just loaded with senior executives. And, that's what this was last night. You know, the VIP room and all the suits were in there, and they were schmoozing. These are things that are really going to expand the value of ServiceNow. It's a new channel for them. And, these big SIs, they have the relationships at the board room level. They have the deep industry expertise. I was talking to Josh Kahn, who's running the Industry Solutions now, another former EMCer, and he, obviously, is very excited to have these relationships with the SI. So, that to me, is a big windfall for ServiceNow. It's something that we're going to be tracking. >> And, especially, this whole concept of the SIs building dedicated industry solutions built on SI. I overheard some of the conversation at the party last night between an SI executive, it was an Exen Sure executive, and one of the ServiceNow people, and, they talked about the power of having the combination of the deep expertise in an industry, I can't remember which one they were going after, it was one big company, their first kind of pilot project, combined with the stability and roadmap of ServiceNow side to have this stable software platform. And, the combination of those two, so complementary to take to market to this particular customer that they were proposing this solution around. And then, to take that solution as they always do and then, you know, harden it and then, take it to the next customer, the next customer, the next customer. So, as you said, getting these big integrators that own the relationships with a lot of big companies, actively involved in now building industry solutions, is a huge step forward beyond just, you know, consultative services and best practices. >> Well, and they have such deep industry expertise. I mean, we talked yesterday about GDPR and some of the new compliance regulations that are coming to the banking industry, particularly in Europe, the fines are getting much more onerous. These SIs have deep expertise and understanding of how to apply something like ServiceNow. ServiceNow, I think of it as a generic platform, but it needs, you know, brain power to say, okay, we can solve this particular problem by doing A, B, C, and D or developing this application or creating this solution. That's really where the SIs are. It's no surprise that a lot of the senior ServiceNow sales reps were at that event last night, you know, hanging with the customers, hanging with their partners. And, that is just a positive sign of momentum in my opinion. Alright, Jeff, so big day today. CJ Desai is coming on. We're going to run through a lot of the business units. You know, tomorrow is sort of Pronic demo day. It's the day usually that Fred Luddy hosts, and Pat Casey, I think, is going to be the main host tomorrow. And, we'll be covering all of this from theCUBE. This is day two ServiceNow Knowledge #Know17. Check out siliconangle.com for all the news. You can watch us live, of course, at thecube.net. I'm Dave Vellante, he's Jeff Frick. We'll be right back after this short break. (easygoing music)

>> Announcer: Live from Orlando, Florida, it's The Cube. Covering Service Now Knowledge 17. Brought to you by Service Now. >> we're back, welcome to Orlando, everybody, this is Service Now Knowledge 17, #Know17. I'm Dave Vellante with my cohost, Jeff Frick. Dave Wright is here, he's the chief strategy officer of Service Now and a long time Cube friend. Good to see you again, David. >> Good seeing you again, guys. So off the keynote, we were just talking about intelligent automation and what's new in your world. New way to work is really kind of the broader theme here, people are changing the way they work. So what is intelligent automation and how does it fit in? >> So what we did when we built intelligent automation is we wanted to come at it from a different angle. So we didn't want to build a product and then look for a solution that it'd work with, we wanted to go out and speak to people and see what are the challenges that they faced. So what we did was we came up with kind of four key areas where people wanted to be able to improve or do things differently. We wanted the capability to be able to predict when something was going to happen from an event perspective. We wanted to be able to use machine learning to be able to augment it. So to be able to perhaps order, categorize, or provide severity, or in the case of change, provide risk analysis. We wanted to be able to do that at a machine level rather than use a human triage level. Then people were coming back saying we feel we're doing a good job, but we want to understand if we're doing a good job, so that was the concept of expanding out the benchmarks program to include more and more benchmarks for people to see how they compared against their peers. And the final element was people wanted to set themselves performance targets, but then they wanted to understand when am I going to get to that target. So what we have to do then was augment the whole performance analytics suite to be able to do predictive analytics. So they're kind of the four core areas that sit in the intelligent automation engine. We can go into as much detail as you want around them, but it's pretty interesting. >> So help us understand, 'cause I get a little confused about, you know, when I hear something like a big announcement coming up at Jakarta, platform, but then I see bits and pieces hit the various products. Can you maybe set that up for us and help us understand. >> Yeah, so what'll happen is the benchmarking, the predictive analytics capability, and the ability to do predictive service usage, they will all appear in Jakarta. And then the actual ML side where we can do the auto-categorization, that will appear in the Kingston release. So by the end of the year, everything that's shown will be available. >> And it hits the platform and then the modules take advantage of that, is that correct? >> Yes, so what is happening at the moment is the initial use cases have gone through around IT. So it's IT looking at well how do we process events so that we can get a precursor to a bigger issue and predict the bigger issue. How do we categorize when someone comes in with an IT request or an IT incidence, how do we make sure it goes to the right people and gets the right categorization. And then what'll happen over time is we'll be able to use that for the security module, we'll be able to use it for customer service, for human resources, because it's all, in the same way we said, it's all a different type of service, it's exactly the same process to be able to categorize, to prioritize, to put a severity on something. And then more long term, we can use this technology to look at all kinds of different files on the system. >> And when you say IT first, it's ITSM and ITOM, is that right? >> Yes, ITSM and ITOM. >> Okay, and so good, I like this, this is a very practical example of, generally, AI, as people don't really know what it is. You're going to tell us that something's going to break before it breaks is usually the use case here. >> What we realized is because we can now start to look at time series data and analyze time series data, there's a few things we can do. So the first thing is we can do corelation, so we can start to link events together, so people didn't spend ages just trying to fix the symptoms, they could go right down to the disease and say well, this is what's causing everything else. The other thing we could build in because we could understand what normal looked like is we could build an anomaly detection. So normally, an event says hey, this has got a high CPU, or this switch has gone down. Now we could say this just looks weird. We've got an activity that never normally happens to this level, or it never normally happens at this time of day, or we've never seen this before on a Saturday. And we can actually generate an anomaly alert at that point. Now, the anomaly alert might be a precursor to a traditional alert where you might get. I think the example used in the actual keynote was we get a large number of user threads on a system, that's probably a precursor to high CPU. So once we've started to be able to do that correlation, the more and more examples you get, the more you can start to predict. So you can say as soon as I get that precursor, I have a level of confidence of when we're going to see the next event. So now you get a brand new type of incidence, you'll get an incident for a predicted failure. So the system will say I've seen this, this, and this, I'm 86% confident we've got two hours and we're going to lose this service. So the whole concept of this was how do you work at light speed. And my whole challenge was what happens when you do it before it happens, is that beyond light speed, it was very difficult to try and wrap your mind around it. >> The speed of light is too damn slow. >> Yeah, it's too slow, no one's going to wait for it. >> I did get a tweet back where someone said if you fix everything before it happens, we'll get no budget because everyone will say nothing ever happens. >> If a tree falls and nobody's around. And so there's a risk, sort of risk scoring algorithm in there that helps you say okay, this one is going to fail and you better take advantage of it. >> Yeah, so if you imagine seeing a precursor to something, you look how many times that precursor has caused that event, that allows you to give a degree of probability as to how likely you think it's going to happen. And it might be you decide to set a threshold and say look, if it's below 50%, don't bother doing it. But if it's above 70%, do it. Or if it's a specific type of issue, if it's something around security, and you're above 90% confidence, I want it flagged as a priority one issue. >> Yeah, but if it's my picnic wiki, so can you inject the notion of value in there, I guess the question. >> Dave: Yes, yeah, you can. >> I want to ask you about this categorization piece, even though it's coming down the road with Kingston. That's been a challenge for organizations in so many different use cases. I mean, the one I can think of, you know, is like email archiving and the federal rules of civil procedure, all that stuff when electronic records became admissible. And everybody sort of scrambled to categorize. But it was manual, they were using tags, it just didn't work, it didn't scale. So the answer was always technology to auto-categorize at the point of creation or use. But even then, it was complicated and the math kind of worked but you couldn't apply it. What's changed now and what's the secret sauce behind it? Was that part of the DX Continuum acquisition, maybe you can explain that. >> So we acquired DX Continuum, that gave us eight really bright math Ph.Ds who were data scientists, who could come in, who could look at data in a different way. But I think technology also drove it. So you've got the ability to have the compute power to be able to do the number crunching, but you've got the volume of data as well, I think the more volume of data you get, the more accurate it is. So we found if we're going to train auto-categorization, we need between 50 and 100,000 records to be able to get to a degree of accuracy. And then obviously, we can just keep on doing it again and again and that accuracy gets better and better over time. But even when we ran this out of the box on our system for the very first time before we'd rewritten it on the platform, first time we ran it through, it was 82% accurate straight off. Now, the real interesting thing about when you do something like categorization, it's almost as important what you get right as not guessing when you're going to get it wrong. So we wanted to be be very sure that they system would say I am 100% confident that this is where this is. But if I don't know it, I'm not going to guess. I'm not going to say well, it's 75% confident, so I'm going to say it's this. At that point, you want to say I just don't know. So these, 18%, for example, in this case, I don't know. And then over time, you get to reprocess the things that you don't know, and that percentage gradually goes up. So now, I think in-house, we're running into the 90% region. >> So the math, though, has been around forever. I mean, things like support vector machines and there are other techniques. What is it about this day and age that has allowed us to effectively apply that math and solve this problem? >> So I think what you get now, if you look at the DX Continuum technology used, I think it was five different methodologies for being able to interrogate. And it was neural nets, it was using base, but I think what gives you the big advantage is people have always taken live data and then tried to do this prediction. That's probably the wrong way to do it. If you take historical data and then run it, you just find out which one works. And if this algorithm is working the best for you based on the way you structure your data, then that's the algorithm you focus on. And that's exactly the way predictive analytics works. What we do is we were initially looking, saying okay, well we've got these three different models we can use. We can use projection, we can use seasonal trend lows, we can use AREMA with the auto-regressive moving average type solution. Which one are we going to use? And then we realized we didn't need to guess. What we could do is we could give the system historical data and say which one of these most accurately maps and then use that algorithm for that data set. Because every data set is different, so you might look at one data set where it's really spiky, so you don't want to use projection because if you choose the wrong points, your projection of them is effectively out. So it might be, in that case, you want to use STL and be able to smooth out some of the curves. So you have to, every time you want to do predictive analytics around a specific data set, you need to work out what mathematical model you need to use. >> So the data is then training the models and the models are your models, correct? >> Yes, yeah. >> And now you tell the customer, and I'm sure you do, that this is your data and your data is not going to be shared with anybody outside of your instance. But the model, the gray area between the model and the data, they start to blend together. Is there concern in your customer base about oh, I don't want the model that you train going to my competitors, or is this a different world where they feel as though hey, I want to learn, like, security. What are you seeing there? >> So this is the uniqueness that we, you don't get a generic ML where we look at everyone's instance and train across that. We can only train for your instance. And that's because everyone does things differently. You go to some companies where their highest priority issue is a sev-9, whereas another customer would have sev-1, so you've got people doing different implementations like that. But let's say I tried to do everyone's, and I went through and I said look at this description, this is a networking issue, so I'm going to categorize it as networking. And you haven't got a networking category, you've got networking infrastructure or networking hardware, then it fails. So I have to build a model that's very specific to your instance. So every time we do this, we'll build it for each customer. So it's kind of customized artificial intelligence machine learning models that sit within your instance. >> So my data, your model that you're basically applying for me and only me. Period, the end. >> Yeah, so we do the training on your data and we inject that model, which is your model, back into your instance. >> And now, the benchmarks, you guys have been talking about benchmarks for a while, this is sort of taken it to a new level. So how do you roll that out, how do you charge for it, what's the strategy there? >> So what people do is they effectively subscribe to it. So they're willing to share their data, we're at that point, allowing them, so it's almost a community issue, at this point, everyone is sharing data across the systems. Now, we added another nine benchmarks in the Jakarta release and now I think there's 16 benchmarks. Ive been mainly focused around IT and ITOM, but as we get more and more customers coming on in CSM and more on HR and more on security, we'll be able to start to introduce the whole concept of benchmarking those as well. But the thing you can do now is you don't just see the benchmark and how you perform, we can also use analytics to show how you're trending as well. So you might be better than people of a similar size or people in the same industry, but it might be that you're trending down and you're actually going to start to get close to being worse than them. So the concept here is you can take corrective measures. But also, it gives a lot of power to customers, not just to be able to say I think I'm doing a good job, but to be able to go to senior management and say this is how customers that look like us are currently performing. This is how customers in the finance sector perform. This is how customers with 100,000 people or more perform. And they can see look, we're leading in this, this, and this area, and they can see where they're not leading, and they can actually start to see how they'd address that. Or it might even be that you start to build relationships where they could say to their account manager who are the people who have got this best in performance type thing, could we meet with them, could we exchange with them? The evolution of this will be on the performance analytics side when we start to get to Kingston and beyond will be to be able to do not just the predictive analytics, but to be able to do modeling and to be able to do what-if. And the end goal is we've gotten to the point where we've got predictive, you want to get to the point where you get to prescriptive. Where the system says this is where you are, if you do this, this is where you'll get. >> That's what I was going to ask you, is it intuitive to the client, what they should do, and what role does Service Now play in advising them. And you're saying in the future, the machine is actually going to-- >> Yeah, could be able to say hey, well, if you want to, let's say you want to improve your problem closure rates, you could say well, when you look at other customers, an indicator of this is people have gotten much better first call incident closure. So what you need to do is you need to focus on closing first call incidents because that's going to then have the knock on effect to driving down the way you resolve problems. So we'll be able to get to that, but we'll also be able to allow people to actually model different things. So they could say what happens if I increase this by 10%? What happens if I put another 10 people working on this particular assignment group, what's the effect going to be, and actually start to do those what-if models, and then decide what you're going to do. >> To prioritize the investment to get the numbers down. It's interesting too, 'cause it's a continuous process, as you mentioned, it's this whole do the review once a year, do your KPIs. That's just not the way it works anymore, you don't have time. And to use the integration of the real time streaming data, which is interesting that you said not necessarily always what you want to use first compared to the historical data that's driving the actual business models and the algorithms. >> I think the thing about the whole benchmark concept is it's constantly being updated. So it's not like you take a snapshot and you say okay, we can improve and move here, you see if everyone else is improving at the same time. So there might just be a generic industry trend that everyone is moving in a certain direction. It might be that as we start to see more things coming online from an IOT perspective, I'll be interested to see whether people's CMDBs start to expand. Because I don't know if people have yet established whether IT is going to be responsible for IOT. Because it's using the same protocol for its messaging, how are you going to process those events, how are you going to deal with all that. >> So I guess it's the man versus machine, machines have always replaced humans. But for the first time, it really is happening quickly with cognitive functions. And one of your speakers at the CIO event, Andrew McCafee and his colleague Erik Brynjolfsson have written a book. And in that book, they talked about the middle class getting kind of hollowed out and they theorize that a big part of that is machines replacing them. One of the stats is the median income for U.S. workers has dropped from $55,000 to $50,000 over the last decade. And they posited that cognitive functions are replacing humans, and you see it everywhere. Billboards, the kiosks at airports, et cetera. Should we be alarmed by that? What is your personal opinion here? And I know it's a scary topic for a lot of IT vendors, but it's reality and you're a realist and you're a futurist. What are your thoughts, share them with us. >> People have different views on this. If you look at the view of executives, they see this see this as potentially creating more jobs. If you look at the workforce, I completely agree with you, there's a massive fear that yeah, this is going to take my job away. I think what happens over time is jobs will shift, people will start doing different things. You can go back 150 years and find that 90% of America is working farmland. And you can come now and you can find out they're like 2%. >> Not too many software engineers either back then. >> Not too many. Hard to get that mainframe in the field. What I think you can do is you can not just use AI or machine learning to be able to replace the mundane jobs or the very repetitive jobs, you can actually start to reverse that process. So one of the things we see is initially, when people were talking about concepts like chat bots, it was all about how do you externalize it, how do you have people coming in and being able to interface to a machine. But you can flip that and you can actually have a bot become a virtual assistant. Then what you're doing is you're enabling the person who's dealing with the issue to actually be better than they were. An interesting example is if you look at something like the way people analyze sales prospects. So in the past, people would have a lot of different opportunities they were working on. And the good sales guys would be able to isolate what's going to happen, what's not going to happen. What I can do is can run something like a machine learning algorithm across that and predict which deals are most likely to come in. I then can have a sales guy focusing on those, I've actually improved the skills of that sales guy by using ML and AI to actually get in there. I think a lot of times, you'll be able to move people from a job that was kind of repetitive and dull and be able to augment their skills and perhaps allow them to do a job that they couldn't have done before. So I'm pretty confident just based on the impact that this is going to have from a productivity perspective, where this is going to go from a job perspective. There's a really cool McKinsey report and it talks about the impact of the steam engine on what that drove on productivity and that was a .3% increase in productivity year and year over 50 years. But the prediction around artificial intelligence is it'll produce a productivity increase of 1.4% for the next 50 years. So you're looking at something that people are predicting could be five times as impactful as the industrial revolution. That's pretty significant. >> Next machine age, this is a huge topic. We're out of time, but I would love for you, Dave, to come back to our Silicon Valley studio and maybe talk about this in more depth because it's a really important discussion. >> I'm always around, happy to do it. >> Thanks very much for coming on The Cube it's great to see you again. >> All right, thanks, guys. >> All right, keep it right there, everybody, we're back with our next guest right after this short break. Be right back.