(upbeat music) (logo shimmers) >> Good afternoon everyone, and welcome back to AWS re Invent 2022. We are live here from the show floor in Las Vegas, Nevada, we're theCUBE, my name is Savannah Peterson, joined by John Furrier, John, are you excited for the next segment? >> I love the innovation story, this next segment's going to be really interesting, an example of ecosystem innovation in action, it'll be great. >> Yeah, our next guests are actually award-winning, I am very excited about that, please welcome Alan and Becky from IBM. Thank you both so much for being here, how's the show going for ya? Becky you got a, just a platinum smile, I'm going to go to you first, how's the show so far? >> No, it's going great. There's lots of buzz, lots of excitement this year, of course, three times the number of people, but it's fantastic. >> Three times the number of people- >> (indistinct) for last year. >> That is so exciting, so what is that... Do you know what the total is then? >> I think it's over 55,000. >> Ooh, loving that. >> John: A lot. >> It's a lot, you can tell by the hallways- >> Becky: It's a lot. >> John: It's crowded, right. >> Yeah, you can tell by just the energy and the, honestly the heat in here right now is pretty good. Alan, how are you feeling on the show floor this year? >> Awesome, awesome, we're meeting a lot of partners, talking to a lot of clients. We're really kind of showing them what the new IBM, AWS relationship is all about, so, beautiful time to be here. >> Well Alan, why don't you tell us what that partnership is about, to start us off? >> Sure, sure. So the partnership started with the relationship in our consulting services, and Becky's going to talk more about that, right? And it grew, this year it grew into the IBM software realm where we signed an agreement with AWS around May timeframe this year. >> I love it, so, like you said, you're just getting started- >> Just getting started. >> This is the beginning of something magic. >> We're just scratching the surface with this right? >> Savannah: Yeah. >> But it represents a huge move for IBM to meet our clients where they are, right? Meet 'em where they are with IBM technology, enterprise technology they're used to, but with the look and feel and usage model that they're used to with AWS. >> Absolutely and so to build on that, you know, we're really excited to be an AWS Premier Consulting Partner. We've had this relationship for a little over five years with AWS, I'd say it's really gone up a notch over the last year or two as we've been working more and more closely, doubling down on our investments, doubling down on our certifications, we've got over 15,000 people certified now, almost 16,000 actually- >> Savannah: Wow. >> 14 competencies, 16 service deliveries and counting. We cover a mass of information and services from Data Analytics, IoT, AI, all the way to Modernization, SAP, Security Services, right. So it's pretty comprehensive relationship, but in addition to the fantastic clients that we both share, we're doing some really great things around joint industry solutions, which I'll talk about in a few minutes and some of those are being launched at the conference this year, so that's even better. But the most exciting thing to me right now is that we just found out that we won the Global Innovator Partner of the Year award, and a LATAM Partner of the Year award. >> Savannah: Wow. >> John: That's (indistinct) >> So, super excited for IBM Consulting to win this, we're honored and it's just a great, exciting part to the conference. >> The news coming out of this event, we know tomorrow's going to be the big keynote for the new Head of the ecosystem, Ruba. We're hearing that it's going to be all about the ecosystem, enabling value creation, enabling new kinds of solutions. We heard from the CEO of AWS, this nextGen environment's upon us, it's very solution-oriented- >> Becky: Absolutely. >> A lot of technology, it's not an either or, it's an and equation, this is a huge new shift, I won't say shift, a continuation for AWS, and you guys, we've been covering, so you got the and situation going on... Innovation solutions and innovation technology and customers can choose, build a foundation or have it out of the box. What's your reaction to that? Do you think it's going to go well for AWS and IBM? >> I think it fits well into our partnership, right? The the thing you mentioned that I gravitate to the most is the customer gets to choose and the thing that's been most amazing about the partnership, both of these companies are maniacally focused on the customer, right? And so we've seen that come about as we work on ways the customer to access our technology, consume the technology, right? We've sold software on-prem to customers before, right, now we're going to be selling SaaS on AWS because we had customers that were on AWS, we're making it so that they can more easily purchase it by being in the marketplace, making it so they can draw down their committed spin with AWS, their customers like that a lot- [John] Yeah. >> Right. We've even gone further to enable our distributor network and our resellers, 'cause a lot of our customers have those relationships, so they can buy through them. And recently we've enabled the customer to leverage their EDP, their committed spend with AWS against IBM's ELA and structure, right, so you kind of get a double commit value from a customer point of view, so the amazing part is just been all about the customers. >> Well, that's interesting, you got the technology relationship with AWS, you mentioned how they're engaging with the software consumption in marketplace, licensed deals, there's all kinds of new business model innovations on top of the consumption and building. Then you got the consulting piece, which is again, a big part of, Adam calls it "Business transformation," which is the result of digital transformation. So digital transformation is the process, the outcome is the business transformation, that's kind of where it all kind of connects. Becky, what's your thoughts on the Amazon consulting relationships? Obviously the awards are great but- >> They are, no- >> What's the next step? Where does it go from here? >> I think the best way for me to describe it is to give you some rapid flyer client examples, you know, real customer stories and I think that's where it really, rubber meets the road, right? So one of the most recent examples are IBM CEO Arvind Krishna, in his three key results actually mentioned one of our big clients with AWS which is the Department of Veterans Affairs in the US and is an AI solution that's helped automate claims processing. So the veterans are trying to get their benefits, they submit the claims, snail mail, phone calls, you know, some in person, some over email- >> Savannah: Oh, it gives me all the feels hearing you talk about this- >> It's a process that used to take 25 to 30 days depending on the complexity of the claims, we've gotten it down with AWS down to within 24 hours we can get the veterans what they need really quickly so, I mean, that's just huge. And it's an exciting story that includes data analytics, AI and automation, so that's just one example. You know, we've got examples around SAP where we've developed a next generation SAP for HANA Platform for Phillips Carbon Black hosted on AWS, right? For them, it created an integrated, scalable, digital business, that cut out a hundred percent the capital cost from on-prem solutions. We've got security solutions around architectures for telecommunications advisors and of course we have lots of examples of migration and modernization and moving workloads using Red Hat to do that. So there's a lot of great client examples, so to me, this is the heart of what we do, like you said, both companies are really focused on clients, Amazon's customer-obsessed, and doing what we can for our clients together is where we get the impact. >> Yeah, that's one of the things that, it sounds kind of cliche, "Oh we're going to work backwards from the customer," I know Amazon says that, they do, you guys are also very customer-focused but the customers are changing. So I'd love to get your reaction because we're now in that cloud 2.0, I call that 2.0 or you got the Amazon Classic, my word, and then Next Gen Cloud coming, the customers are different, they're transforming because IT's not a department anymore, it's in the DevOps pipeline. The developers are driving a lot of IT but security and on DataOps, it's the structural change happening at the customer, how do you guys see that at IBM? I know we cover a lot of Red Hat and Arvind talks to us all the time, meeting the customer where they are, where are they? Where are the customers? Can you share your perspective on where they are? >> It's an astute observation, right, the customer is changing. We have both of those sets of customers, right, we still have the traditional customer, our relationship with Central IT, right, and driving governance and all of those things. But the folks that are innovating many times they're in the line of business, they're discovering solutions, they're building new things. And so we need our offerings to be available to them. We need them to understand how to use them and be convenient for these guys and take them through that process. So that change in the customer is one that we are embracing by making our offerings easy to consume, easy to use, and easy to build into solutions and then easy to parlay into what central IT needs to do for governance, compliance, and these types of things, it's becoming our new bread and butter. >> And what's really cool is- >> Is that easy button- >> We've been talking about- >> It's the easy button. >> The easy button a lot on the show this week and if you just, you just described it it's exactly what people want, go on Becky. >> Sorry about that, I was going to say, the cool part is that we're co-creating these things with our clients. So we're using things like the Amazon Working Backward that you just mentioned.` We're using the IBM garage methodology to get innovative to do design working, design thinking workshops, and think about where is that end user?, Where is that stakeholder? Where are they, they thinking, feeling, doing, saying how do we make the easier? How do we get the easy button for them so that they can have the right solutions for their businesses. We work mostly with lines of business in my part of the organization, and they're hungry for that. >> You know, we had a quote on theCUBE yesterday, Savannah remember one of our guests said, you know, back in the, you know, 1990s or two 2000s, if you had four production apps, it was considered complex >> Savannah: Yeah. >> You know, now you got hundreds of workloads, thousands of workloads, so, you know, this end-to-end vision that we heard that's playing out is getting more complex, but the easy button is where these abstraction layers and technology could come in. So it's getting more complex because there's more stuff but it's getting easier because- >> Savannah: What is the magnitude? >> You can make it easier. This is a dynamic, share your thoughts on that. >> It's getting more complex because our clients need to move faster, right, they need to be more agile, right, so not only are there thousands of applications there are hundreds of thousands microservices that are composing those applications. So they need capabilities that help them not just build but govern that structure and put the right compliance over that structure. So this relationship- >> Savannah: Lines of governance, yeah- >> This relationship we built with AWS is in our key areas, it's a strategic move, not a small thing for us, it covers things like automation and integration where you need to build that way. It covers things like data and AI where you need to do the analytics, even things like sustainability where we're totally aligned with what AWS is talking about and trying to do, right, so it's really a good match made there. >> John: It really sounds awesome. >> Yeah, it's clear. I want to dig in a little bit, I love the term, and I saw it in my, it stuck out to me in the notes right away, getting ready for you all, "maniacal", maniacal about the customer, maniacal about the community, I think that's really clear when we're talking about 24 days to 24 hours, like the veteran example that you gave right there, which I genuinely felt in my heart. These are the types of collaborations that really impact people's lives, tell me about some of the other trends or maybe a couple other examples you might have because I think sometimes when our head's in the clouds, we talk a lot about the tech and the functionality, we forget it's touching every single person walking around us, probably in a different way right now than we may even be aware- >> I think one of the things that's been, and our clients have been asking us for, is to help coming into this new era, right, so we've come out of a pandemic where a lot of them had to do some really, really basic quick decisions. Okay, "Contact Center, everyone work from home now." Okay, how do we do that? Okay, so we cobbled something together, now we're back, so what do we do? How do we create digital transformation around that so that we are going forward in a really positive way that works for our clients or for our contact center reps who are maybe used to working from home now versus what our clients need, the response times they need, and AWS has all the technology that we're working with like Amazon Connect to be able to pull those things together with some of our software like Watson Assistant. So those types of solutions are coming together out of that need and now we're moving into the trend where economy's getting tougher, right? More cost cutting potentially is coming, right, better efficiencies, how do we leverage our solutions and help our clients and customers do that? So I think that's what the customer obsession's about, is making sure we really understand where their pain points are, and not just solve them but maybe get rid of 'em. >> John: Yeah, great one. >> Yeah. And not developing in a silo, I mean, it's a classic subway problem, you got to be communicating with your community if you want to continue to serve them. And IBM's been serving their community for a very long time, which is super impressive, do you think they're ready for the challenge? >> Let's do it. >> So we have a new thing on theCUBE. >> Becky: Oh boy. >> We didn't warn you about this, but here we go. Although you told, Alan, you've mentioned you're feeling very cool with the microphone on, so I feel like, I'm going to put you in the hot seat first on this one. Not that I don't think Becky's going to smash it, but I feel like you're channeling the power of the microphone. New challenges, treat it like a 32nd Instagram reel-style story, a hot take, your thought leadership, money clip, you know, this is your moment. What is the biggest takeaway, most important thing happening at the show this year? >> Most important thing happening at the show? Well, I'm glad you mentioned it that way, because earlier you said we may have to sing (presenters and guests all laughing) >> So this is much better than- >> That's actually part of the close. >> John: Hey, hey. >> Don't worry, don't worry, I haven't forgotten that, it's your Instagram reel, go. (Savannah laughs) >> Original audio happening here on theCUBE, courtesy of Alan and IBM, I am so here for it. >> So what my takeaway and what I would like for the audience to take away, out of this conversation especially, but even broadly, the IBM AWS relationship is really like a landmark type of relationship, right? It's one of the biggest that we've established on both sides, right- >> Savannah: It seems huge, okay you are too monolith in the world of companies, like, yeah- >> Becky: Totally. >> It's huge. And it represents a strategic change on both sides, right? With that customer- >> Savannah: Fundamentally- >> In the middle right? >> Savannah: Yeah. >> So we're seeing things like, you know, AWS is working with us to make sure we're building products the way that a AWS client likes to consume them, right, so that we have the right integration, so they get that right look and feel, but they still get the enterprise level capabilities they're used to from IBM, right? So the big takeaway I like for people to take, is this is a new IBM, it's a new AWS and IBM relationship, and so expect more of that goodness, more of those new things coming out of it. [John] Excellent, wow. >> That was great, well done, you nailed it. and you're going to finish with some acapella, right? (Alan laughs) >> You got a pitch pipe ready? (everyone laughs) >> All right Becky, what about you? Give us your hot take. >> Well, so for me, the biggest takeaway is just the way this relationship has grown so much, so, like you said, it's the new IBM it's the new AWS, we were here last year, we had some good things, this year we're back at the show with joint solutions, have been jointly funded and co-created by AWS and IBM. This is huge, this is a really big opportunity and a really big deal that these two companies have come together, identified joint customer needs and we're going after 'em together and we're putting 'em in the booth. >> Savannah: So cool. And there's things like smart edge for welding solutions that are out there. >> Savannah: Yes. >> You know, I talked about, and it's, you know you wouldn't think, "Okay, well what's that?" There's a lot to that, a lot of saving when you look at how you do welding and if you apply things like visual AI and auditory AI to make sure a weld is good. I mean, I think these are, these things are cool, I geek out on these things- >> John: Every vertical. >> I'm geeking out with you right now, just geeking- >> Yeah, yeah, yeah, so- >> Every vertical is infected. >> They are and it's so impactful to have AWS just in lockstep with us, doing these solutions, it's so different from, you know, you kind of create something that you think your customers like and then you put it out there. >> Yeah, versus this moment. >> Yeah, they're better together. >> It's strategic partnership- >> It's truly a strategic partnership. and we're really bringing that this year to reinvent and so I'm super excited about that. >> Congratulations. >> Wow, well, congratulations again on your awards, on your new partnership, I can't wait to hear, I mean, we're seven months in, eight months in to this this SaaS side of the partnership, can't wait to see what we're going to be talking about next year when we have you back on theCUBE. >> I know. >> and maybe again in between now and then. Alan, Becky, thank you both so much for being here, this was truly a joy and I'm sure you gave folks a taste of the new IBM, practicing what you preach. >> John: Great momentum. >> And I'm just, I'm so impressed with the two companies collaborating, for those of us OGs in tech, the big companies never collaborated before- >> Yeah. >> John: Yeah. Joint, co-created solutions. >> And you have friction between products and everything else. I mean's it's really, co-collaboration is, it's a big theme for us at all the shows we've been doing this year but it's just nice to see it in practice too, it's an entirely different thing, so well done. >> Well it's what gets me out of the bed in the morning. >> All right, congratulations. >> Very clearly, your energy is contagious and I love it and yeah, this has been great. Thank all of you at home or at work or on the International Space Station or wherever you might be tuning in from today for joining us, here in Las Vegas at AWS re Invent where we are live from the show floor, wall-to-wall coverage for three days with John Furrier. My name is Savannah Peterson, we're theCUBE, the source for high tech coverage. (cheerful upbeat music)

>> From San Francisco, it's theCUBE, covering Conga Connect West 2018, brought to you by Conga. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're in downtown San Francisco at Salesforce Dreamforce, they're saying it's 170,000 people. Take public transit, do not bring your car, do not take Uber, grab a line, grab a BART, whatever you need. So we're excited to have a practitioner. We love to get customers on, we love to talk to people that are out here actually using all these tools, and our next guest, we're excited to have Becky Bastien. She's a senior force.com developer for BD, which is Becton Dicksinson-- >> Dickinson. >> Becky, welcome. >> Thank you. >> So, what type of products do you work on? >> So, I mean primarily we're a Salesforce.com platform, right? And we have a lot of add-ons with Conga, DocuSign, you name it, we're doing it. Apttus CLM, and we also use Oracle CPQ. Anything that connects to the Salesforce.com platform, you can imagine we probably use it. >> And you've been developing on Salesforce for a number of years, looking at your LinkedIn history, so you've got a lot of experience with the platform. Just a little bit of perspective, how this conference has changed, how Salesforce is a platform from just a pure play kind of Salesforce management system, which is what it started at CRM, to what kind of it is today? >> Yeah, I mean the conference has changed astronomically obviously over the years. What you said, it was 170 thousand, right? It's crazy. >> That's crazy. >> Logistically, it's a little tough to get around but it's so much fun and there's so much that you can learn here. It's just increased over the years. The content has gotten better, there's more focused areas, which I really like. I'm a developer at heart so I really focus on that. But as far as the platform itself, it's really grown. You can do anything with it. At BD, we even have done things that are completely custom, like our entire implementation team for one of our business units runs out of Salesforce.com as a project management application. We don't just use it for sales, right? >> Right. >> Or marketing, even. We use it across the board for implementation and now we're getting into the service aspect as well. >> Right, we're here at the Conga event and we talked before we turned the cameras on, you're using the Conga tool set in kind of a unique and slightly different way than some of the applications we've heard. I wonder if you could share some of the applications that you use and how you use them? >> Sure, so one of our primary uses of Conga is actually generating documents that are customer facing, that really educate our clients, our end clients and then also helps us with some of the data that we're gathering for our product development. But what we do is we go out to the client's site and we're actually sometimes in an operating room, or at a catheter injection or a blood draw, multiple things that we actually gather data on via another application called Fulcrum. We pull all that data back into Salesforce and then we use Conga to generate the documents that are customer facing. With that, it really empowers our business as well because they have full control over that Conga document, so they can make the changes that they need to, without involving IT, and we just kind of hook it all up in the back end for them. >> Right, right. It's really a new kind of world in terms of the opportunity to go gather data on your products, whether it's connected via an application or different things, as opposed to back in the old day, you made it, you shipped it, you sent it out through your distributor and you had no idea how end users are using it, how the doctors are using it in this case. >> Yeah. >> But now, you've got this opportunity to do more of a closed loop feedback, back into the product development. >> Yeah and it's not only a product development, but we're actually educating the hospitals on, are you using the product to what we actually manufactured it for? Are you using it for something entirely different? Are you using it the wrong way? It's actually an education tool back to our end customer and saying, "Hey, this is where you can improve "operating procedures," basically. >> Another hot topic that we hear about all the time, we go to all these conferences, is bots. You talked about, you guys are doing something interesting with bots, again, leveraging the Conga application probably not necessarily the way that's it's, I didn't see Bots on their product sheet. >> Yeah. >> Tell us a little bit about that application? >> Yeah, We have a bot where our sales reps can basically enter some information into an Excel spreadsheet. It's for a quick quote for a customer, and the bot will crawl that spreadsheet and feed it back into SAP. What we've found is that our sales reps are having a hard time getting the right customer number, getting the right contact information and things like that, where the Bot would fail if they didn't have the right information. What we've done with Conga is we generate that Excel spreadsheet from Salesforce.com so the sales rep is on an opportunity, and they generate the bot, they generate the spreadsheet, they fill out the rest of the information and then it gets sent along its way and it creates the order and SAP eventually. It's really cutting out some human error. >> Right, so does the Bot fill in the missing data? Or it just flags that you've got some incomplete stuff you have to fill in? >> Yeah so, we're passing it as much as we can for the rep. They're having to manually enter some things like what product, what quantity, and things like that, and then the bot crawls it and throws it into SAP. It's just an easier way for a rep when they're sitting out on-site with a client. They can actually put it in an Excel spreadsheet, which they love. >> Right. Of course we're trying to get 'em away from Excel spreadsheets anyway, but let's go ahead and automate some of it for them so it cuts out that error. >> It's a really interesting story because it's often a battle to get the sales people to work in Salesforce. >> Yeah. >> As opposed to report in Salesforce. >> Right. >> You're really kind of bridging that gap, letting 'em work in Excel, which isn't necessarily their preferred solution but if that's what they're doing and then integrating that back into the automated system. >> It's hard to change that behavior, for sure. >> Yes it is. >> But yeah, by giving them the bot, we're actually making them go into Salesforce. It gets them more comfortable with it and a way to drive user adoption. >> Right and I'm sure you can see a future where AI is going to enable more and more automation of all the little bits and pieces of that process going forward. >> Yeah, absolutely. I think, too, what we talked about with gathering all that data, that's one of the things with Einstein that we're really interested in, especially at Dreamforce this year, is learning more about Einstein and what we can do on the platform with all the data that we have gathered. >> Right, right. The other thing you mentioned before we turn on the cameras, it's again, kind of a new technology, is voice. Obviously with the proliferation of Alexa and Google Home and OK Siri, and all these things, voice is going to be an increasingly important way that people interact with applications. As you look forward, down the road, what are some of the opportunities you see there, where you can start to integrate more potential voice control into the applications? >> I think it kind of goes back to our sales reps, again. Where they're on on-site. If they can talk into their phone really quickly and say, "Update this opportunity amount." I mean, that's great. It gets them, again, into Salesforce, it's going to drive that user adoption. I saw a session on it earlier today and I thought it was pretty cool. I think they'll be excited about that. We're also implementing field service for Lightning. We have our actual texts that get dispatched out on-site, so I can really see them using that on the mobile experience as well. >> The dispatch is going out through Lightning and then the management of the service call is also happening inside of Lightning? >> Yeah, we're implementing Service Cloud right now. The next phase will be implementing field service for Lightning. We're now dispatching out of SAP, but we're looking to move it entirely to Salesforce. >> Wow. >> Yeah. >> Okay, if Marc Benioff came in and sat down, there was a guy that looked just like his brother here earlier, what would you ask him? What kind of magic wand you've been developing in this thing for a number of years, would you say, Marc, love it, love it, but could you just give me a little of this and and a little of that? >> I'd say, show me the road map and no safe harbor, tell me it's actually going to happen. No, I think mobile is where we're always really trying to figure out where Salesforce is going, and I think they've really improved. But I offline capability is something that has struggled with Salesforce. We have to rely on other apps that write back into Salesforce. >> Right. >> It'd be nice to eliminate those other offline applications and just use Salesforce.com for that offline power train. Because a lot of times we're at the hospital, and there's no wifi, there's no connection. >> Right, right. >> So we have to have that offline capability. >> Still kind of the soft underbelly of cloud-based things but 5G is coming, we were just at the AT&T show and we'll have 5G 10x the speed, 100x the speed. >> Bring it on, yeah. >> So good stuff. Alright, Becky, thanks for taking a few minutes. >> Absolutely. >> And keep coding away. >> Thank you. >> Alright. >> She's Becky, I'm Jeff, you're watching theCUBE. We're at the Conga Connect West at Salesforce Dreamforce at the Thirsty Bear, downtown San Francisco, come on by. (upbeat techno music)

(click) >> Hey, Lisa Martin on the ground with theCUBE at Google for the Sixth Annual CloudNOW Top Women in Cloud Awards Event, our second year covering this, very excited to be joined by tonight's emcee, Becky Wanta, the founder of RSW1C. Welcome to theCUBE. >> Thank you. >> It's great to have you here. So tell us a little bit about what you do and your background as a technology leader. >> So, I've been in technology for close to 40 years. I started out as a software. >> Sorry, I don't even, what? (laughing) >> Ha, ha, ha, it's a long time ago, yeah. So I started out as a developer back in the Department of Defense. So it wasn't rocket science in the early days when I began because it was back when computers took up whole rooms and I realized I had an affinity for that. So, I leveraged that, but then I got into, at that time, and I'm from northern California, if you remember right, the Department of Defense was drawing down. And so I decided I was going to leverage my experience in IT to get into either integrative financial services or healthcare, right. So I took over running all of tech for the Money Store at the time which you would have no idea who that is. And then that got acquired by Wells Fargo First Union, so I took over as their Global CTO for Wells Fargo. And what you'll see is, so let me just tell you about RSW1C because what it is is it's a technology consulting firm that's me. And the reason I have it is because tech changes so much that it's easy to stay current. And when I get brought into companies, and you'll look at me, so I've been the executive officer for tiny little companies like PepsiCo, Wells Fargo, Southwest Airlines. >> The small ones. >> Yeah, tiny, not really, MGM Resorts International, the largest worker's comp company in California, a company that, unborn midsize SMB in southern California that just wrapped up last year. And when I get brought into these companies, I get brought in to transform them. It's at a time in the maturation of these companies, these tiny little brands we've mentioned, where they're ready to jettison IT. So I take that very seriously because I know technology is that gateway to keep that competitive advantage. And the beauty is of that the companies I've mentioned, they're all number one in their markets. And when you're number one, there's only one direction to go, so they take that very seriously. >> How do you come in there and help an MGM Grand Resorts transform? >> So what happened in MGM's case and probably in the last five CIO positions that I've taken, they've met me as a consultant, again, from RSW1C. And then when I look into what needs to happen and I have the conversation, because everybody thinks they want to do digital transformation, and it's not an easy journey and if you don't have the executive sponsorship, don't even try it at home, right? And so, in MGM's case, they had been talking. MGM's the largest taxpayer in Nevada. People think about it as MGM Grand. It's 19 brands on The Strip. >> Is that right? >> It's Bellagio, MGM, so it's the largest taxpayer in Nevada. So it owns 44,860 rooms on The Strip. So if I just counted now, you have Circa Circa, Slots of Fun, Mirage, Bellagio, Monte Carlo, New York, New York, um, MGM Grand Las Vegas, MGM Grand Detroit. They're in the countries and so forth. So it's huge. And that includes Mandalay, ARIA, and all those, so it's huge, right? And so in MGM's case, they knew they wanted to do M life, so M life game changes their industry. And I put that in. This will be our nine year anniversary coming up on Valentine's Day. Thirty years they talked about it, and I put in with a great team And that was part of the transformation into a new way of running their business. >> Wow, we have a couple of minutes left. I'd love to get your perspective on being a female leader in tech. Who were your mentors back in the day? And who are your mentors now? >> So, I don't have any mentors. I never did. Because when I started in the industry, there wasn't a lot of women. And obviously, technology was fairly new which is why one of my passions is around helping the next generation be hugely successful. And one of the things that's important is in the space of tech, I like this mantra, this mantra that says, "How about brains "and beauty that gets you in the door? "How about having the confidence in yourself?" So I want to help a lot of the next generation be hugely successful. And that's what Jocelyn has built with CloudNow, her and Susan. And I'm a big proponent of this because I think it's a chance for us to give back and help the next generation of leaders in a non-traditional way be hugely successful in brands, in companies that are going to unleash their passion and show them how to do that. Because, the good news is that I'm a total bum, Lisa. I've never had a job. I love what I do, and I do it around the clock, so. >> Oh, if only more people could say that. That's so cool. But what we've seen with CloudNow, this is our second year covering it, I love talking to the winners and even the folks that are keynoting or helping to sponsor scholarships. There's so much opportunity. >> There really is. >> And it's so exciting when you can see someone whose life is changing as a result of finding a mentor or having enough conviction to say, "You know what? "I am interested in a STEM field. "I'm going to pursue that." >> Right. >> So, we thank you so much Becky for stopping by theCUBE. And your career is amazing. >> Thanks. >> And I'm sure you probably are mentors to countless, countless men and women out there. >> Absolutely. >> Well, thanks again for stopping by. >> Thank you, Lisa. >> Thank you for watching theCUBE. I'm Lisa Martin on the ground at Google with the CloudNow Sixth Annual Top Women in Cloud Awards Event. Stick around, we'll be right back.

(bright music) (crowd talking indistinctly in the background) >> Hey guys, welcome back to Detroit, Michigan. theCUBE is live at KubeCon + CloudNativeCon 2022. You might notice something really unique here. Lisa Martin with our newest co-host of theCUBE, Savannah Peterson! Savannah, it's great to see you. >> It's so good to be here with you (laughs). >> I know, I know. We have a great segment coming up. I always love talking couple things, cars, one, two, with companies that have been around for a hundred plus years and how they've actually transformed. >> Oh yeah. >> Ford is here. You have a great story about how you, about Ford. >> Ford brought me to Detroit the first time. I was here at the North American International Auto Show. Some of you may be familiar, and the fine folks from Ford brought me out to commentate just like this, as they were announcing the Ford Bronco. >> Satish: Oh wow. >> Which I am still lusting after. >> You don't have one yet? >> For the record. No, I don't. My next car's got to be an EV. Although, ironically, there's a Ford EV right behind us here on set today. >> I know, I know. >> Which we were both just contemplating before we went live. >> It's really shiny. >> We're going to have to go check it out. >> I have to check it out. Yep, we'll do that. Yeah. Well, please welcome our two guests from Ford, Satish Puranam, is here, The Technical Leader at Cloud and Rebecca Risk, Principal Architect, developer relations. We are so excited to have you guys on the program. >> Clearly. >> Thanks for joining us. (all laugh) >> Thank you for having us. >> I love you're Ford enthusiasts! Yeah, that's awesome. >> I drive a Ford. >> Oh, awesome! Thank you. >> I can only say that's one car company here. >> That's great. >> Yes, yes. >> Great! Thank you a lot. >> Thank you for your business! >> Absolutely. (all laugh) >> So, Satish, talk to us a little bit about- I mean I think of Cloud as a car company but it seems like it's a technology company that makes cars. >> Yes. Talk to us about Ford as a Cloud first, technology driven company, and then we're going to talk about what you're doing with Red Hat and Boston University. >> Yeah, I'm like everything that all these cars that you're seeing, beautiful right behind us it's all built on, around, and with technology, right? So there's so much code goes into these cars these days, it's probably, it's mind boggling to think that probably your iPhones might be having less code as opposed to these cars. Everything from control systems, everything is code. We don't do any more clay models. Everything is done digital, 3D, virtual reality and all that stuff. So all that takes code, all of that takes technology. And we have been in that journey for the last- since 2016 when we started our first mobile app and all that stuff. And of late we have been like, heavily invested in Google. Moving a lot of these experiences, data acquisition systems AI/ML modeling for like all the autonomous cars. It's all technology and like from the day it is conceived, to the day it is marketed, to the day when you show up for a servicing, and hopefully soon how you can buy and you know, provide feedback to us, is all technology that drives all of this stuff. So it's amazing for us to see everything that we go and immerse ourselves in the technology. There is a real life thing that we can see what we all do for it, right? So- >> Yes, we're only sorry that our audience can't actually see the car, >> Yep. >> but we'll get some B-roll for you later on. Rebecca, talk a little bit about your role. Here we are at KubeCon, Savannah and I and John were talking when we went live this morning, that this is huge. That the show floor is massive, a lot bigger than last year. The collaboration and the spirit of the community is not only alive and well, as we heard in the keynote this morning, it's thriving. >> Yeah. >> Talk about developer relations at Ford and what you are helping to drive in your role. >> Yeah, so my team is all about helping developers work faster with different platforms that my team curates and produces, so that our developers don't have to deal with all of the details of setting up their environments to actually code. And we have really great people, kind of the top software developers in the company, are part of my team to produce those products that other people can use, and accelerate their development. And we have a great relationship with the developers in the company and outside with the different vendor relationships that we have, to make sure that we're always producing the next platform with the next tech stack that our developers will want to continue to use to produce the really great products that we are all about making at Ford. >> Let's dig in there a little bit because I'm curious and I suspect you both had something to do with it. How did you approach your Cloud Native transformation and how do you evaluate new technologies for the team? >> It's sometimes- many a times I would say it's like dogfooding and like experimentation. >> Yeah. Isn't anything in innovation a lot of- >> Yeah, a lot of experimentation. We started our, as I said, the Cloud Native journey back in 2016 with Cloud Foundry and things, technologies around that. Soon realized, that there was like a lot of buzz around that time. Twelve-Factor was a thing, Stateless was a thing. And then all those Stateful needs to drive the Stateless. So where do we do that thing? And the next logical iteration was Kubernetes was bursting upon the scene at that time. So we started doing a lot of experimentation. >> Like the Kool-Aid man, burst on the Kubernetes scene- >> Exactly right. >> Through the wall. >> So, the question is like, why can't we do? I think we were like crazy enough to say that Kubernetes people are talking about our serverless or Twelve-Factor on Kubernetes. We are crazy enough to do Stateful on Kubernetes and we've been doing it successfully for five years. So it's a lot about experimentation. I think good chunk of experiments that we do do not yield the results that we get, but many a times, some of them are like Gangbusters. Like, other aspects that we've been doing of late is like partnering with Becky and rest of the organization, right? Because they are the people who are like closest to the developers. We are somewhat behind the scenes doing some things but it is Becky and the rest of the architecture teams who are actually front and center with the customers, right? So it is the collaborative effort that we've been working through past few years that has been really really been useful and coming around and helping us to make some of these products really beautiful. >> Yeah, well you make a lot of beautiful products. I think we've all, I think we've all seen them. Something that I think is really interesting and part of why I was so excited for this interview, and kind of nudged John out, was because you've been- Ford has been investing in technology in a committed way for decades and I don't think most people are aware of that. When I originally came out to Dearborn, I learned that you've had a head of VR who happens to be a female. For what it's worth, Elizabeth, who's been running VR for you for two and a half decades, for 25 years. >> Satish: Yep. >> That is an impressive commitment. What is that like from a culture perspective inside of Ford? What is the attitude around innovation and technology? >> So I've been a long time Ford employee. I just celebrated my 29th year. >> Oh, wow! >> Congratulations! >> Wow, congrats! That's a huge deal. >> Yeah, it's a huge deal. I'm so proud of my career and all that Ford has brought to me and it's just a testament. I have many colleagues like me who've been there for their whole career or have done other things and come to Ford and then spent another 20 years with us because we foster the culture that makes you want to stay. We have development programs to allow you to upscale and change your role and learn new things and play with the new technologies that people are interested in doing and really make an impact to our community of developers at Ford or the company itself and the results that we're delivering. So to have that, you know, culture for so many years that people really love to work. They love to work with the people that they're working with. They love to stay engaged and they love the fact that you can have many different careers within the same umbrella, which we call the "blue oval". And that's really why I've been there for so long. I think I probably had 13 very unique and different jobs along the way. It's as if I left, and you know shopped around my skills elsewhere. But I didn't ever have to leave the company. It's been fabulous. >> The cultural change and adoption of- embracing modern technology- Cloud Native automotive software is impressive because a lot of historied companies, you guys have been there a long time, have challenges with that because it's really hard to get an entire moving, you'll call it the blue oval, to change and adapt- >> Savannah: I love that. >> and be willing to experiment. So that that is impressive. Talk about, you go by Becky, so I'll call you Becky, >> Rebecca/Becky: Yeah. >> The developer culture in terms of the developers really being the center of the nucleus of influencing the direction in which the company's going. I imagine that they probably are fairly influential. >> Yeah, so I had a very- one of the unique positions I held was a culture change for our department, Information Technology in 2016. >> Satish: Yeah. >> As the teacher was involved with moving us to the cloud, I was responsible- >> You are the transformation team! This is beautiful. I love this. We've got the right people on the show. >> Yeah, we do. >> I was responsible for changing the culture to orient our employees to pay attention to what do we want to create for tomorrow? What are the kind of skills we need to trust each other to move quickly. And that was completely unique. >> Satish: Yeah. >> Like I had men in the trenches delivering software before that, and then plucked out because they wanted someone, you know who had authentic experience with our development team to be that voice. And it was such a great investment that Ford continues to do is invest in our culture transformation. Because with each step forward that we do, we have to refine what our priorities are. And you do that through culture transformation and culture management. And that's been, I think really, the key to our successful pivots that we've made over the last six years that we've been able to continue to refine and hone where we really want to go through that culture movement. >> Absolutely. I think if I could add another- >> Please. >> spotlight to it is like the biggest thing about Ford has been among various startup-like culture, right? So the idea is that we encourage people to think outside the box, right? >> Savannah: Or outside the oval? >> Right! (laughs) >> Lisa: Outside the oval, yes! >> Absolutely! Right. >> So the question is like, you can experiment with various things, new technologies and you will get all the leadership support to go along with it. I think that is very important too and like we can be in the trenches and talk about all of these nice little things but who the heck would've thought that, you know Kubernetes was announced in 2015, in late 2016, we have early dev Kubernetes clusters already running. 2017, we are live with workloads on Kubernetes! >> Savannah: Early adopters over here. >> Yeah. >> Yeah. >> I'm like all of this thing doesn't happen without lot of foresight and support from the leadership, but it's also the grassroot efforts that is encouraged all along to be on the front end of all of these things and try different things. Some of them may not work >> Savannah: Right. >> But that's okay. But how do we know we are doing something, if you're not failing? We have to fail in order to do something, right? >> Lisa: I always say- >> So I think that's been a great thing that is encouraged very often and otherwise I would not be doing, I've done a whole bunch of stuff at Ford. Without that kind of ability to support and have an appetite for, some of those things would not have been here at all. >> I always say failure is not a bad F-word. >> Satish: Yep. >> Savannah: I love that. >> But what you're talking about there is kind of like driving this hot wheel of experimentation. You have to have the right culture and the mindset- >> Satish: Absolutely. >> to do that. Try fail, move on, learn, iterate, go. >> Satish: Correct. >> You guys have a great partnership with Red Hat and Boston University. You're speaking about that later today. >> Satish: Yes. >> Unpack that for us. What, from a technical perspective, what are you doing and what's it resulting in? >> Yeah, I think the biggest thing is Becky was talking about as during this transformation journey, is lot has changed in very small amount of time. So we traditionally been like, "Hey, here's a spreadsheet of things I need you to deliver for me" to "Here is a catalog of things, you can get it today and be successful with it". That is frightening to several of our developers. The goal, one of the things that we've been working with Q By Example, Red Hat and all the thing, is that how can we lower the bar for the developers, right? Kubernetes is great. It's also a wall of YAML. >> It's extremely complex, number one complaint. >> The question is how can I zero on? I'm like, if we go back think like when we talk about in cars with human-machine interfaces, which parts do I need to know? Here's the steering wheel, here's the gas pedal, or here's the brake. As long as you know these two, three different things you should be fairly be okay to drive those things, right? So the idea of some of the things with enablementing we are trying to do is like reduce that barrier, right? Reduce- lower the bar so that more people can participate in it. >> One of the ways that you did that was Q By Example, right, QBE? >> Satish: Yes, Yes. >> Can you tell us a little bit more about that as you finish this answer? >> Yeah, I think the biggest thing with Q By Example is like Q By Example gives you the small bite-sized things about Kubernetes, right? >> Savannah: Great place to start. >> But what we wanted to do is that we wanted to reinforce that learning by turning into a real world living example app. We took part info, we said, Hey, what does it look like? How do I make sure that it is highly available? How do I make sure that it is secure? Here is an example YAML of it that you can literally verbatim copy and paste into your editor and click run and then you will get an instant gratification feedback loop >> I was going to say, yeah, they feel like you're learning too! >> Yes. Right. So the idea would be is like, and then instead of giving you just a boring prose text to read, we actually drop links to relevant blog posts saying that, hey you can just go there. And that has been inspirational in terms of like and reinforcing the learning. So that has been where we started working with the Boston University, Red Hat and the community around all of that stuff. >> Talk a little bit about, Becky, about some of the business outcomes. You mentioned things like upskilling the workforce which is really nice to hear that there's such a big focus on it. But I imagine too, there's more participation in the community, but also from an end customer perspective. Obviously, everything Ford's doing is to serve the end customers >> Becky: Right. How does this help the end customer have that experience that they really, these days, demand with patience being something that, I think, is gone because of the pandemic? >> Right? Right. So one of the things that my team does is we create the platforms that help Accelerate developers be successful and it helps educate them more quickly on appropriate use of the platforms and helps them by adopting the platforms to be more secure which inherently lead to the better results for our end customers because their data is secure because the products that they have are well created and they're tested thoroughly. So we catch all those things earlier in the cycle by using these platforms that we help curate and produce. And that's really important because, like you had mentioned, this steep learning curve associated with Kubernetes, right? >> Savannah: Yeah. >> So my team is able to kind of help with that abstraction so that we solve kind of the higher complex problems for them so that developers can move faster and then we focus our education on what's important for them. We use things like Q By Example, as a source instead of creating that content ourselves, right? We are able to point them to that. So it's great that there's that community and we're definitely involved with that. But that's so important to help our developers be successful in moving as quickly as they want and not having 20,000 people solve the same problems. >> Satish: (chuckles) Yeah. >> Each individually- >> Savannah: you don't need to! >> and sometimes differently. >> Savannah: We're stronger together, you know? >> Exactly. >> The water level rises together and Ford is definitely a company that illustrates that by example. >> Yeah, I'm like, we can't make a better round wheel right? >> Yeah! So, we have to build upon what we have already been built ahead of us. And I think a lot of it is also about how can we give back and participate in the community, right? So I think that is paramount for us as like, here we are in Detroit so we're trying to recruit and show people that you know, everything that we do is not just old car and sheet metal >> Savannah: Combustion. >> and everything and right? There's a lot of tech goes and sometimes it is really, really cool to do that. And biggest thing for us is like how can we involve our community of developers sooner, earlier, faster without actually encumbering them and saying that, hey here is a book, go master it. We'll talk two months later. So I think that has been another journey. I think that has been a biggest uphill challenge for us is that how can we actually democratize all of these things for everybody. >> Yeah. Well no one better to try than you I would suspect. >> We can only try and hope everything turns out well, right? >> You know, as long as there's room for the bumpers on the lane for if you fail. >> Exactly. >> It sounds like you're driving the program in the right direction. Closing question for you, what's next? Is electric the future? Is Kubernetes the future? What's Ford all in on right now, looking forward? (crowd murmuring in the background) >> Data is the king, right? >> Savannah: Oh, okay, yes! >> Data is a new currency. We use that for several things to improve the cars improve the quality of autonomous driving Is Level 5 driving here? Maybe will be here soon, we'll see. But we are all working towards it, right? So machine learning, AI feedback. How do you actually post sale experience for example? So all of these are all areas that we are working to. We are, may not be getting like Kubernetes in a car but we are putting Kubernetes in plants. Like you order a Marquis or you order a Bronco, you see that here. Here's where in the assembly line your car is. It's taking pictures. It's actually taking pictures on Kubernetes platform. >> That's pretty cool. >> And it is tweeting for you on the Twitter and the social media platform. So there's a lot of that. So it is real and we are doing it. We need more help. A lot of the community efforts that we are seeing and a lot of the innovation that is happening on the floor here, it's phenomenal. The question is how we can incorporate those things into our workflows. >> Yeah, well you have the right audience for that here. You also have the right attitude, >> Exactly. >> the right appetite, and the right foundation. Becky, last question for you. Top three takeaways from your talk today. If you're talking to the developer community you want to inspire: Come work for us! What would you say? >> If you're ready to invest in yourself and upskill and be part of something that is pretty remarkable, come work for us! We have many, many different technical career paths that you can follow. We invest in our employees. When you master something, it's time for you to move on. We have career growth for you. It's been a wonderful gift to me and my family and I encourage everyone to check us out careers.ford.com or stop by our booth if you're happen to be here in person. >> Satish: Absolutely! >> We have our curated job openings that are specific for this community, available. >> Satish: Absolutely. >> Love it. Perfect close. Nailed pitch there. I'm sure you're all going to check out their job page. (all laugh) >> Exactly! And what you talked about, the developer experience, the customer experience are inextricably linked and you guys are really focused on that. Congratulations on all the work that you've done. We got to go get a selfie with that car girl. >> Yes, we do. >> Absolutely. >> We got to show them, we got to show the audience what it looks like on the inside too. We'll do a little IG video. (Lisa laughs) >> Absolutely. >> We will show you that for our guests and my cohost, Savannah Peterson. Lisa Martin here live in Detroit with theCUBE at KubeCon and CloudNativeCon 2022. The one and only John Furrier, who you know gets FOMO, is going to be back with me next. So stick around. (all laugh) (bright music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data driven insights from theCUBE and ETR, This is "Breaking Analysis with Dave Vellante". >> Black Hat 22 was held in Las Vegas last week, the same time as theCUBE Supercloud event. Unlike AWS re:Inforce where words are carefully chosen to put a positive spin on security, Black Hat exposes all the warts of cyber and openly discusses its hard truths. It's a conference that's attended by technical experts who proudly share some of the vulnerabilities they've discovered, and, of course, by numerous vendors marketing their products and services. Hello, and welcome to this week's Wikibon CUBE Insights powered by ETR. In this "Breaking Analysis", we summarize what we learned from discussions with several people who attended Black Hat and our analysis from reviewing dozens of keynotes, articles, sessions, and data from a recent Black Hat Attendees Survey conducted by Black Hat and Informa, and we'll end with the discussion of what it all means for the challenges around securing the supercloud. Now, I personally did not attend, but as I said at the top, we reviewed a lot of content from the event which is renowned for its hundreds of sessions, breakouts, and strong technical content that is, as they say, unvarnished. Chris Krebs, the former director of Us cybersecurity and infrastructure security agency, CISA, he gave the keynote, and he spoke about the increasing complexity of tech stacks and the ripple effects that that has on organizational risk. Risk was a big theme at the event. Where re:Inforce tends to emphasize, again, the positive state of cybersecurity, it could be said that Black Hat, as the name implies, focuses on the other end of the spectrum. Risk, as a major theme of the event at the show, got a lot of attention. Now, there was a lot of talk, as always, about the expanded threat service, you hear that at any event that's focused on cybersecurity, and tons of emphasis on supply chain risk as a relatively new threat that's come to the CISO's minds. Now, there was also plenty of discussion about hybrid work and how remote work has dramatically increased business risk. According to data from in Intel 471's Mark Arena, the previously mentioned Black Hat Attendee Survey showed that compromise credentials posed the number one source of risk followed by infrastructure vulnerabilities and supply chain risks, so a couple of surveys here that we're citing, and we'll come back to that in a moment. At an MIT cybersecurity conference earlier last decade, theCUBE had a hypothetical conversation with former Boston Globe war correspondent, Charles Sennott, about the future of war and the role of cyber. We had similar discussions with Dr. Robert Gates on theCUBE at a ServiceNow event in 2016. At Black Hat, these discussions went well beyond the theoretical with actual data from the war in Ukraine. It's clear that modern wars are and will be supported by cyber, but the takeaways are that they will be highly situational, targeted, and unpredictable because in combat scenarios, anything can happen. People aren't necessarily at their keyboards. Now, the role of AI was certainly discussed as it is at every conference, and particularly cyber conferences. You know, it was somewhat dissed as over hyped, not surprisingly, but while AI is not a panacea to cyber exposure, automation and machine intelligence can definitely augment, what appear to be and have been stressed out, security teams can do this by recommending actions and taking other helpful types of data and presenting it in a curated form that can streamline the job of the SecOps team. Now, most cyber defenses are still going to be based on tried and true monitoring and telemetry data and log analysis and curating known signatures and analyzing consolidated data, but increasingly, AI will help with the unknowns, i.e. zero-day threats and threat actor behaviors after infiltration. Now, finally, while much lip service was given to collaboration and public-private partnerships, especially after Stuxsnet was revealed early last decade, the real truth is that threat intelligence in the private sector is still evolving. In particular, the industry, mid decade, really tried to commercially exploit proprietary intelligence and, you know, do private things like private reporting and monetize that, but attitudes toward collaboration are trending in a positive direction was one of the sort of outcomes that we heard at Black Hat. Public-private partnerships are being both mandated by government, and there seems to be a willingness to work together to fight an increasingly capable adversary. These things are definitely on the rise. Now, without this type of collaboration, securing the supercloud is going to become much more challenging and confined to narrow solutions. and we're going to talk about that little later in the segment. Okay, let's look at some of the attendees survey data from Black Hat. Just under 200 really serious security pros took the survey, so not enough to slice and dice by hair color, eye color, height, weight, and favorite movie genre, but enough to extract high level takeaways. You know, these strongly agree or disagree survey responses can sometimes give vanilla outputs, but let's look for the ones where very few respondents strongly agree or disagree with a statement or those that overwhelmingly strongly agree or somewhat agree. So it's clear from this that the respondents believe the following, one, your credentials are out there and available to criminals. Very few people thought that that was, you know, unavoidable. Second, remote work is here to stay, and third, nobody was willing to really jinx their firms and say that they strongly disagree that they'll have to respond to a major cybersecurity incident within the next 12 months. Now, as we've reported extensively, COVID has permanently changed the cybersecurity landscape and the CISO's priorities and playbook. Check out this data that queries respondents on the pandemic's impact on cybersecurity, new requirements to secure remote workers, more cloud, more threats from remote systems and remote users, and a shift away from perimeter defenses that are no longer as effective, e.g. firewall appliances. Note, however, the fifth response that's down there highlighted in green. It shows a meaningful drop in the percentage of remote workers that are disregarding corporate security policy, still too many, but 10 percentage points down from 2021 survey. Now, as we've said many times, bad user behavior will trump good security technology virtually every time. Consistent with the commentary from Mark Arena's Intel 471 threat report, fishing for credentials is the number one concern cited in the Black Hat Attendees Survey. This is a people and process problem more than a technology issue. Yes, using multifactor authentication, changing passwords, you know, using unique passwords, using password managers, et cetera, they're all great things, but if it's too hard for users to implement these things, they won't do it, they'll remain exposed, and their organizations will remain exposed. Number two in the graphic, sophisticated attacks that could expose vulnerabilities in the security infrastructure, again, consistent with the Intel 471 data, and three, supply chain risks, again, consistent with Mark Arena's commentary. Ask most CISOs their number one problem, and they'll tell you, "It's a lack of talent." That'll be on the top of their list. So it's no surprise that 63% of survey respondents believe they don't have the security staff necessary to defend against cyber threats. This speaks to the rise of managed security service providers that we've talked about previously on "Breaking Analysis". We've seen estimates that less than 50% of organizations in the US have a SOC, and we see those firms as ripe for MSSP support as well as larger firms augmenting staff with managed service providers. Now, after re:Invent, we put forth this conceptual model that discussed how the cloud was becoming the first line of defense for CISOs, and DevOps was being asked to do more, things like securing the runtime, the containers, the platform, et cetera, and audit was kind of that last line of defense. So a couple things we picked up from Black Hat which are consistent with this shift and some that are somewhat new, first, is getting visibility across the expanded threat surface was a big theme at Black Hat. This makes it even harder to identify risk, of course, this being the expanded threat surface. It's one thing to know that there's a vulnerability somewhere. It's another thing to determine the severity of the risk, but understanding how easy or difficult it is to exploit that vulnerability and how to prioritize action around that. Vulnerability is increasingly complex for CISOs as the security landscape gets complexified. So what's happening is the SOC, if there even is one at the organization, is becoming federated. No longer can there be one ivory tower that's the magic god room of data and threat detection and analysis. Rather, the SOC is becoming distributed following the data, and as we just mentioned, the SOC is being augmented by the cloud provider and the managed service providers, the MSSPs. So there's a lot of critical security data that is decentralized and this will necessitate a new cyber data model where data can be synchronized and shared across a federation of SOCs, if you will, or mini SOCs or SOC capabilities that live in and/or embedded in an organization's ecosystem. Now, to this point about cloud being the first line of defense, let's turn to a story from ETR that came out of our colleague Eric Bradley's insight in a one-on-one he did with a senior IR person at a manufacturing firm. In a piece that ETR published called "Saved by Zscaler", check out this comment. Quote, "As the last layer, we are filtering all the outgoing internet traffic through Zscaler. And when an attacker is already on your network, and they're trying to communicate with the outside to exchange encryption keys, Zscaler is already blocking the traffic. It happened to us. It happened and we were saved by Zscaler." So that's pretty cool. So not only is the cloud the first line of defense, as we sort of depicted in that previous graphic, here's an example where it's also the last line of defense. Now, let's end on what this all means to securing the supercloud. At our Supercloud 22 event last week in our Palo Alto CUBE Studios, we had a session on this topic on supercloud, securing the supercloud. Security, in our view, is going to be one of the most important and difficult challenges for the idea of supercloud to become real. We reviewed in last week's "Breaking Analysis" a detailed discussion with Snowflake co-founder and president of products, Benoit Dageville, how his company approaches security in their data cloud, what we call a superdata cloud. Snowflake doesn't use the term supercloud. They use the term datacloud, but what if you don't have the focus, the engineering depth, and the bank roll that Snowflake has? Does that mean superclouds will only be developed by those companies with deep pockets and enormous resources? Well, that's certainly possible, but on the securing the supercloud panel, we had three technical experts, Gee Rittenhouse of Skyhigh Security, Piyush Sharrma who's the founder of Accurics who sold to Tenable, and Tony Kueh, who's the former Head of Product at VMware. Now, John Furrier asked each of them, "What is missing? What's it going to take to secure the supercloud? What has to happen?" Here's what they said. Play the clip. >> This is the final question. We have one minute left. I wish we had more time. This is a great panel. We'll bring you guys back for sure after the event. What one thing needs to happen to unify or get through the other side of this fragmentation and then the challenges for supercloud? Because remember, the enterprise equation is solve complexity with more complexity. Well, that's not what the market wants. They want simplicity. They want SaaS. They want ease of use. They want infrastructure risk code. What has to happen? What do you think, each of you? >> So I can start, and extending to the previous conversation, I think we need a consortium. We need a framework that defines that if you really want to operate on supercloud, these are the 10 things that you must follow. It doesn't matter whether you take AWS, Slash, or TCP or you have all, and you will have the on-prem also, which means that it has to follow a pattern, and that pattern is what is required for supercloud, in my opinion. Otherwise, security is going everywhere. They're like they have to fix everything, find everything, and so on and so forth. It's not going to be possible. So they need a framework. They need a consortium, and this consortium needs to be, I think, needs to led by the cloud providers because they're the ones who have these foundational infrastructure elements, and the security vendor should contribute on providing more severe detections or severe findings. So that's, in my opinion, should be the model. >> Great, well, thank you, Gee. >> Yeah, I would think it's more along the lines of a business model. We've seen in cloud that the scale matters, and once you're big, you get bigger. We haven't seen that coalesce around either a vendor, a business model, or whatnot to bring all of this and connect it all together yet. So that value proposition in the industry, I think, is missing, but there's elements of it already available. >> I think there needs to be a mindset. If you look, again, history repeating itself. The internet sort of came together around set of IETF, RSC standards. Everybody embraced and extended it, right? But still, there was, at least, a baseline, and I think at that time, the largest and most innovative vendors understood that they couldn't do it by themselves, right? And so I think what we need is a mindset where these big guys, like Google, let's take an example. They're not going to win at all, but they can have a substantial share. So how do they collaborate with the ecosystem around a set of standards so that they can bring their differentiation and then embrace everybody together. >> Okay, so Gee's point about a business model is, you know, business model being missing, it's broadly true, but perhaps Snowflake serves as a business model where they've just gone out and and done it, setting or trying to set a de facto standard by which data can be shared and monetized. They're certainly setting that standard and mandating that standard within the Snowflake ecosystem with its proprietary framework. You know, perhaps that is one answer, but Tony lays out a scenario where there's a collaboration mindset around a set of standards with an ecosystem. You know, intriguing is this idea of a consortium or a framework that Piyush was talking about, and that speaks to the collaboration or lack thereof that we spoke of earlier, and his and Tony's proposal that the cloud providers should lead with the security vendor ecosystem playing a supporting role is pretty compelling, but can you see AWS and Azure and Google in a kumbaya moment getting together to make that happen? It seems unlikely, but maybe a better partnership between the US government and big tech could be a starting point. Okay, that's it for today. I want to thank the many people who attended Black Hat, reported on it, wrote about it, gave talks, did videos, and some that spoke to me that had attended the event, Becky Bracken, who is the EIC at Dark Reading. They do a phenomenal job and the entire team at Dark Reading, the news desk there, Mark Arena, whom I mentioned, Garrett O'Hara, Nash Borges, Kelly Jackson, sorry, Kelly Jackson Higgins, Roya Gordon, Robert Lipovsky, Chris Krebs, and many others, thanks for the great, great commentary and the content that you put out there, and thanks to Alex Myerson, who's on production, and Alex manages the podcasts for us. Ken Schiffman is also in our Marlborough studio as well, outside of Boston. Kristen Martin and Cheryl Knight, they help get the word out on social media and in our newsletters, and Rob Hoff is our Editor-in-Chief at SiliconANGLE and does some great editing and helps with the titles of "Breaking Analysis" quite often. Remember these episodes, they're all available as podcasts, wherever you listen, just search for "Breaking Analysis Podcasts". I publish each on wikibon.com and siliconangle.com, and you could email me, get in touch with me at david.vellante@siliconangle.com or you can DM me @dvellante or comment on my LinkedIn posts, and please do check out etr.ai for the best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, and we'll see you next time on "Breaking Analysis". (upbeat music)

>>Live from Las Vegas. It's the cube covering UI path forward Americas 2019 brought to you by UI path. >>Welcome back to UI path forward three. This is UI pass. Third North American conference. We're here at the Bellagio hotel. You are watching the cube, the leader in live tech coverage. We go out to the events, we extract the signal from the noise, we pick the brains of experts. Kevin crone is here. He's a financial services intelligent automation leader at PWC. Kevin, thanks for coming on the cube Bexar Avenue. You're very welcome. So financial services has always been kind of a leading indicator of technology adoption. I presume that automation is, is no difference, but you know, you're in the New York area, you're belly to belly with the financial services companies, the big whales, what's going on in Fs these days? Sure. >>So as we look across the financial services industry, they were one of the leaders with automation more because the overarching business environment really forced them. As we looked at, um, the regulatory burden that a lot of our banking clients we're under over the past decade kind of post crash that really, um, has kind of forced two things. One, it's limited the amount of um, discretionary spend that they have to spend on really big technology transformation projects. It's also forced a lot of margin pressure and having to think about, uh, differently how they could run their business at a much lower and more effective price points. And so that's, um, driven automation to the top. And we've seen tools like U I path and kind of the broader RPA ecosystem becoming kind of, you know, the right technology at the right time of being able to, um, really kind of embrace that, that, that, that rightsizing agenda and financial services sector. >>Yeah. And furniture at the macro level, they're a little bit out of favor right now you've had this, what we thought was this rising interest rate environment and that's reversed. And so that's not necessarily good for them. So they got to look for other ways to sort of drive the bottom line. So maybe you could talk a little bit about, you know, gen generally where you're seeing automation, um, back office, front office. Think about the maturity curve. What are the leaders doing? What, >>what's the sort of best practice right now for intelligent automation RPA? Sure. So as we looked at intelligent automation right now, I think one of the interesting things, vital services was an early adopter. So a lot of, a lot of the big banks and asset managers and insurance companies really start investing in this, this class of technology four, five, six, seven years ago. And so we're actually seeing the, the early returns from, from those, which is informing how this, you know, this topic goes to other industries. But I think as we look at those returns, we see a couple of major challenges. Um, there's challenges with getting the scaling technology, there's challenges with, so that's interesting. Okay. So the, the ladder changing, the nature of work is, as you're saying, largely automating existing mundane processes, kind of paving the cow path as I sometimes say. >>However, if, if it's a, if it's not the most efficient processy to begin read process to begin with, they need to sort of re look at that and that may be falls into the, to the, to the former category of enterprise life. And so where people investing in boat or they are they just hitting the low hanging fruit where we're seeing an investment in both. And then PWC is used that a while fucks your mission program should have both channels and each channel should be informing the other. So if citizens are coming up with ideas of things that they can automate themselves, that's great, but those should also be contributed into the kind of broader ecosystem. And there may be, um, what's called grander ways to, to, to solve that problem, both from a technology perspective and from a process reengineering perspective. Is there a, is there an automation ex-officio is there a chief who's sort of looking at all this stuff or is it more organic? >>It's, you know, one of the, I think interesting things we've seen and learned from our clients over the past couple of years is the con, you know, we thought there'd be an emergence of a chief automation officer or something like that. But really the automation agenda's owned in so many different places within our clients. And it's not consistent client decline in some cases. It's really a CIO own topic. A lot of cases it's more of a chief operating officer, chief digital officer, chief transformation officer. We're also seeing a push at the chief HR officer level because this is really, you know, there's a, there's a big question straight in terms of thinking about kind of skills and how you equip your workforce with the right digital skills for the future, which is now putting HR at the table for this, which is the place where I think traditionally with big technology transformations, they've never really sat. >>So, in thinking about, um, ROI, you know, you've laid out this sort of bifurcated, you know, paths to vectors the hard sort of end-to-end problems and then the sort of low hanging fruit changing the way to work. I would presume the second one gives you the quick hit, you know, faster break even, but probably lower net present value. Um, and, and so maybe you could talk a little bit about the ROI equation and how people are looking at that. Yeah. It's interesting cause I think yeah, to your point, I think an enterprise led initiative, you're going to want to define a business case and say this is why we're doing it and what we're looking to achieve going down to SIS and let channel, that's a harder thing to do because you don't want to stifle innovation. The organization, one of our views is that the people that sit closest to the business process are the ones that should be coming up the right ideas, if they're given the right upscaling and the right tools at their disposal. >>Um, but you know, it's bottoms up exercise. And so again, going back to the concept of having a kind of an ecosystem with both an enterprise channel and a citizen channel is important because you're at the enterprise level, you're going to need to understand what type of benefits are actually being created at the, you know, at the micro level and figure out two things. One, are there things that, you know, do, have we built enough that we can start to release capacity from organization? Um, or is there something else that if I put in, will allow us to really think about transforming our business? So it's a, it's a lover. It's not that the end solution, right? When I tell people about you that don't know what RPA is, I say it's a lot of back office stuff and it is. Um, but we heard today that from one of the keynotes that, you know, we gotta move from the back office to the, to the front office. >>How much is that happening in financial services and how much of a sort of a holistic end to end strategy are you seeing? I'm sure you guys are promoting that are fans of that because you're going to get a much bigger business impact. It's transformational. But where are we at in the maturity of that? Yeah, it's interesting, right? So we, you know, staying on this theme of the enterprise and citizen light innovation levers, you know, the enterprise. Um, and you know, innovation levers tend to be focused more in the back office, high transaction volume type processes. I think when we look at the citizen led channel and a lot of the ideas that have been coming out in our cotton with our clients are starting to embrace this. They tend to be more front office oriented processes. There's lots of things, especially client servicing or that are tasks that are done are somewhat mundane. >>And um, you know, it's the business case and LOC isn't necessarily back capacity. It's about client experience and customer service. So, you know, you can take the, um, you know, the, the, the wealth advisor that has to log into five different systems to answer a simple client question. That's a, you know, that's a process that being able to actually have an automated way to generate that same thing at their fingertips, um, you know, could be really powerful. And so there's a big push there. I think the interesting part on the, um, going back to your bet, your business case question from before is that, um, you know, the, the business case for a lot of those types of automations, um, it's not just a factor of um, you know, have we built enough that we think that there's benefit, it's also about adoption. So if I build a robot to automate that wealth advisor process that I just noted, if 50 wealth advisors can adopt that rather than one wealth advisor, it's going to be a much greater business case. And that's a much, that's a different way of thinking about business case in the RPA sense. Because most people tend to think, here's a process, this process, I have five people that run this on a day to day basis. Um, and here's, here's my business case. In this case it's, I built something really innovative. If I can get a a hundred people to use this because it's, it takes 10 minutes out of their day, there's real, there's, there's real time there, but it is causing a lot of our clients to think differently. >>So you talk about three things as challenges scaled the business case, which you just talked about and change management. Is that part of the, and they're interrelated? Is that part of the challenge with scale? It is far as the channel. >>I mean just building on the last point around adoption, you know, that what we're doing, what we're talking about here with RPA, I think people that live in the RPA space day to day, this does this almost become second nature. And like, yeah, the technology is not that complicated. This is very basic, but you start going out to the entire organization and especially outside of technology. Um, it's, it's new. And so the change management's really important. Um, and it's important we, we view from two lenses. One is really thinking about how do you, um, upskill your workforce at a minimum so they know what technology is actually out there. It doesn't necessarily mean you're gonna make everyone a bot builder in your organization. But knowing what RPA is and knowing that, Hey, I have some tools to go help solve a given business problem is really important. But, uh, you know, the, the uh, the second point that we think is really important in here is the ability to, um, really think, sorry, really think about the, um, you know, what the longterm impact of kind of, um, you know, the overall organizational model and how that actually adopts to using automation over time. >>And that ties into change management, which is the other thing and people don't like change. Um, the other thing we heard this morning, um, Craig LeClaire Forrester analyst talked about how a lot of robots are idle sitting around ill, you know, then though at the orchestrator. And so I was, I was thinking, well, we're seeing sass models emerge, you know, UI path announced their cloud product and I would expect you're going to see new pricing models as well, kind of usage base pricing, which is kind of generally not how things are priced today. But is that something that customers are pushing for >>or definitely. I mean I think there's, um, there's two, two things we hear from customers in this space. I think as RPA, as a product is developed and you know, I think there was a push, uh, with most, with all the vendors towards kind of what's priced for bot. But the concept of a bot is a somewhat ambiguous concept to a lot of our clients. And what our clients really want is to price and value, right? And understand, um, if I'm building bots that are, you know, covering this part of the organization, I'm appropriately paying for this, um, rather than worry about how much workload did I put onto one bod versus another. I think with, uh, with the mass adoption of cloud and the fact that the RP ecosystems quickly moving from an on prem solution to a cloud based solution, I think a lot of this is just gonna happen naturally. Um, over time. I think the other, I think the other really important part in there is not to just make this a technology question about the kind of the pricing. It's also a question on value delivered and realize the benefits case and can you actually tie what those realized benefits are to what the actual price that's actually going to pay for the software is >>all right. You ready for some curve balls? Sure. Okay. So you're, you know, thought leader you worked for one of the largest consultancies on the planet global scale. You guys do some really great work disruption. We talk about digital transformation, automation obviously plays in there, blockchain, AI, RPA, et cetera. Do you, do you think that banks will lose control of payment systems? >>I'm not sure. I would say the pro, the biggest problems that banks are facing, um, with regards to that isn't necessarily whether they control the payment system or not. I actually think it's how effective they can run the system internally. I mean, I'm a, I'm an automation guy, right? And my goal is to make clients run as efficiently and as effectively as possible. And I look at a lot of the legacy debt that sits within a lot of our clients infrastructure. I think that's the biggest problem to tackle. I think if they don't tackle that and are not successful topics like RPA and automation, it, it's going to create the forces of nature that allow some of the broader disruption to happen. So it's, you know, to me, at least in my mind, it's one of these things that you, you have your agenda in what'd you can control. These are the things that you actually shouldn't be focusing on. So you're set up to compete with some of the big disruptors in the future. >>Yeah, interesting. I mean that's one industry, there's a disruption all around us, but that's one industry along with healthcare and defense that it hasn't been highly disrupted yet because it's very high risk. Not only that they're, you know, they've got very strong relationship with the government. So this, and they're big and they're well funded, but, but it seems like that disruption scenario is coming to financial services. When you talk to people in the industry, they certainly see it, but there's also a lot of complacency. It's like, Hey, we're a big, big Fs. We're doing really well. Um, dots on that. >>Um, you know, there is, you know, when we looked across and I'll just say kind of technology investment in the banking sector, big banks and asset managers, insurance companies are some of the biggest spenders on technology out there. And in your view, look at a lot of the commentary that comes out of analyst calls. There's pretty consistent, um, push a to talk about, um, you know, Becky organization as a technology company or some form of that. And there's also a big push to talk about how much money they're spending. That's great. But we've also, yeah, I think when you, you kind of look under the covers, there's been a lot of historical challenges with um, with implementing big technology projects and things. There's a lot of legacy debt that's been built over the past 25 years and complexity really thinking about this from a front to back perspective. >>Like from the point, you know, taking a, the trading side of a bank, looking at the point of trade entry through post-trade processing through finance processing through kind of every step in the life cycle. It's still run from a technology perspective, probably not as efficient as possible. And I think especially when you get outside the front office area and some of the training areas and look at that. So there's a ton of opportunity for improvement and, and you know, kind of building on the last theme, I think to the extent that technologies like RPA and automation are embraced, it helps think about that problem a little bit differently and gives us a chance to tackle some of these big meaty legacy problems that had been around for a while. If we're successful at this and we can force the ROI to be proved, we can force the change management exercise to happen. I think it sets our clients up for, again, for success to avoid some of these disruptive factors. >>Yeah. So huge opportunity then for a UI path than some of its competitors, you know, penetration wise, adoption wise, what inning are we in? >>Uh, adding to we're, we're in early days. I mean, I think we've seen a ton of interest. It's under the excitement from our clients. But you know, our surveys of, of, of the financial services industry, um, most clients will acknowledge their past the pilot and proof of concept phase and there may be even past the first 10 bought phase, but they're not at scale. Right. And I think until three things happen, I think until we can prove that the technology is being used, um, you know, from an organizational coverage across a much wider swath than it is today. I think when we can prove that there's actually a real demonstrable benefit happening from a, from an organizational operating model perspective, and to the extent that the workforce is actually embracing this and I'm posing it, I think we'll, you know, >>be in a much better position to say, Hey, we're working now getting to ending five or six and, and this, this picture's becoming more complete. But it's still early. A lot of opportunities. Kevin, thanks very much to come into the Q was great to have you. Thank you for having me. Hi, and thank you for watching. We're right back with our next guest right after this short break. You're watching the cube live from UI path forward 2019 at the Bellagio right back.

produced from the cube studios this is strong by science in-depth conversations about science based training sports performance and all things health and wellness here's your host max smart [Music] [Applause] [Music] all right thank you guys tune in today I have the one and only Dean of big data the man the myth the legend bill Schwarz oh also my dad is the CTO of Hitachi van Tara and IOC in analytics he has a very interesting background because he is the well he's known as the Dean of big data but also the king of the court and all things basketball related when it comes to our household and unlike most people in the data world and I want to say most as an umbrella term but a some big bill has an illustrious sports career playing at Coe College the Harvard of the Midwest my alma mater as well but I think having that background of not just being computer science but where you have multiple disciplines involved when it comes to your jazz career you had basketball career you have obviously the career Iran now all that plays a huge role in being able to interpret and take multiple domains and put it into one so thank you for being here dad yeah thanks max that's a great introduction I rep reciate that no it's it's wonderful to have you and for our listeners who are not aware bill is referring him is Bill like my dad but I call my dad the whole time is gonna drive me crazy bill has a mind that thinks not like most so he he sees things he thinks about it not just in terms of the single I guess trajectory that could be taken but the multiple domains that can go so both vertically and horizontally and when we talk about data data is something so commonly brought up in sports so commonly drop in performance and athletic development big data is probably one of the biggest guess catchphrases or hot words or sayings that people have nowadays but doesn't always have a lot of meaning to it because a lot of times we get the word big data and then we don't have action out of big data and bill specialty is not just big data but it's giving action out of big data with that going forward I think a lot of this talk to be talking about how to utilize Big Data how do you guys data in general how to organize it how to put yourself in a situation to get actionable insights and so just to start it off Becky talked a little bit on your background some of the things you've done and how you develop the insights that you have thanks max I have kind of a very nos a deep background but I've been doing data analytics a long time and I was very fortunate one of those you know Forrest Gump moments in life where in the late 1980s I was involved in a project at Procter & Gamble I ran the project where we brought in Walmart's point of sales data for the first time into a what we would now call a data warehouse and for many of this became the launching point of the data warehouse bi marketplace and we can trace the effect the origins of many of the BI players to that project at Procter & Gamble in 87 and 88 and I spent a big chunk of my life just a big believer in business intelligence and data warehousing and trying to amass data together and trying to use that data to report on what's going on and writing insights and I did that for 20 25 years of my life until as you probably remember max I was recruited out Business Objects where I was the vice president of analytic applications I was recruited out of there by Yahoo and Yahoo had a very interesting problem which is they needed to build analytics for their advertisers to help those advertisers to optimize or spend across the Yahoo ad network and what I learned there in fact what I unlearned there was that everything that I had learned about bi and data warehouse and how you constructed data warehouses how you were so schema centric how everything was evolved around tabular data at Yahoo there was an entirely different approach the of my first introduction to Hadoop and the concept of a data Lake that was my first real introduction into data science and how to do predictive analytics and prescriptive analytics and in fact it was it was such a huge change for me that I was I was asked to come back to the TD WI data world Institute right was teaching for many years and I was asked to do a keynote after being at Yahoo for a year or so to share sort of what were the observations what did I learn and I remember I stood up there in front of about 600 people and I started my presentation by saying everything I've taught you the past 20 years is wrong and it was well I didn't get invited back for 10 years so that probably tells you something but it was really about unlearning a lot about what I had learned before and probably max one of the things that was most one of the aha moments for me was bi was very focused on understanding the questions that people were trying to ask an answer davus science is about us to understand the decisions they're trying to take action on questions by their very nature our informative but decisions are actionable and so what we did at Yahoo in order to really drive the help our advertisers optimize your spend across the Yahoo ad network is we focus on identifying the decisions the media planners and buyers and the campaign managers had to make around running a campaign know what what how much money to allocate to what sides how much how many conversions do I want how many impressions do I want so all the decisions we built predictive analytics around so that we can deliver prescriptive actions to these two classes of stakeholders the media planners and buyers and the campaign managers who had no aspirations about being analysts they're trying to be the best digital marketing executives or you know or people they could possibly be they didn't want to be analysts so and that sort of leads me to where I am today and my my teaching my books my blogs everything I do is very much around how do we take data and analytics and help organizations become more effective so everything I've done since then the books I've written the teaching I do with University of San Francisco and next week at the National University of Ireland and Galway and all the clients I work with is really how do we take data and analytics and help organizations become more effective at driving the decisions that optimize their business and their operational models it's really about decisions and how do we leverage data and analytics to drive those decisions so what would how would you define the difference between a question that someone's trying to answer versus a decision but they're trying to be better informed on so here's what I'd put it I call it the Sam test I am and that is it strategic is it actionable is it material and so you can ask questions that are provocative but you might not fast questions that are strategic to the problems you're trying to solve you may not be able to ask questions that are actionable in a sense you know what to do and you don't necessarily ask questions that are material in the sense that the value of that question is greater than the cost of answering that question right and so if I think about the Sam test when I apply it to data science and decisions when I start mining the data so I know what decisions are most important I'm going through a process to identify to validate the value and prioritize those decisions right I understand what decisions are most important now when I start to dig through the data all this structured unstructured data across a number different data sources I'm looking for I'm trying to codify patterns and relationships buried in that data and I'm applying the Sam test is that against those insights is it strategic to the problem I'm trying to solve can I actually act on it and is it material in the sense that it's it's it's more valuable to act than it is to create the action around it so that's the to me that big difference is by their very nature decisions are actually trying to make a decision I'm going to take an action questions by their nature are informative interesting they could be very provocative you know questions have an important role but ultimately questions do not necessarily lead to actions so if I'm a a sport coach I'm writing a professional basketball team some of the decisions I'm trying to make are I'm deciding on what program best develops my players what metrics will help me decide who the best prospect is is that the right way of looking at it yeah so we did an exercise at at USF too to have the students go through an exercise - what question what decisions does Steve Kerr need to make over the next two games he's playing right and we go through an exercise of the identifying especially in game decisions exercise routes oh no how often are you gonna play somebody no how long are they gonna play what are the right combinations what are the kind of offensive plays that you're gonna try to run so there's a know a bunch of decisions that Steve Kerr is coach of the Warriors for example needs to make in the game to not only try to win the game but to also minimize wear and tear on his players and by the way that's a really good point to think about the decisions good decisions are always a conflict of other ideas right win the game while minimizing wear and tear on my players right there's there are there are all the important decisions in life have two three or four different variables that may not be exactly the same which is by this is where data science comes in the data science is going to look across those three or four very other metrics against what you're going to measure success and try to figure out what's the right balance of those given the situation I'm in so if going back to the decision about about playing time well think about all the data you might want to look at in order to optimize that so when's the next game how far are they in this in this in the season where do they currently sit ranking wise how many minutes per game has player X been playing looking over the past few years what's there you know what's their maximum point so there's there's a there's not a lot of decisions that people are trying to make and by the way the beauty of the decisions is the decisions really haven't changed in years right what's changed is not the decisions it's the answers and the answers have changed because we have this great bound of data available to us in game performance health data you know all DNA data all kinds of other data and then we have all these great advanced analytic techniques now neural networks and unstructured supervised machine learning on right all this great technology now that can help us to uncover those relationships and patterns that are buried in the data that we can use to help individualize those decisions one last point there the point there to me at the end when when people talk about Big Data they get fixated on the big part the volume part it's not the volume of big data that I'm going to monetize it's the granularity and what I mean by that is I now have the ability to build very detailed profiles going back to our basketball example I can build a very detailed performance profile on every one of my players so for every one of the players on the Warriors team I can build a very detailed profile it the details out you know what's their optimal playing time you know how much time should they spend before a break on the feet on the on the on the court right what are the right combinations of players in order to generate the most offense or the best defense I can build these very detailed individual profiles and then I can start mission together to find the right combination so when we talk about big it's not the volume it's interesting it's the granularity gotcha and what's interesting from my world is so when you're dealing with marketing and business a lot of that when you're developing whether it be a company that you're trying to find more out about your customers or your startup trying to learn about what product you should develop there's tons of unknowns and a lot of big data from my understanding it can help you better understand some patterns within customers how to market you know in your book you talk about oh we need to increase sales at Chipotle because we understand X Y & Z our current around us now in the sports science world we have our friend called science and science has helped us early identify certain metrics that are very important and correlated to different physiological outcomes so it almost gives us a shortcut because in the big data world especially when you're dealing with the data that you guys are dealing with and trying to understand customer decisions each customer is individual and you're trying to compile all together to find patterns no one's doing science on that right it's not like a lab work where someone is understanding muscle protein synthesis and the amount of nutrients you need to recover from it so in my position I have all these pillars that maybe exist already where I can begin my search there's still a bunch of unknowns with that kind of environment do you take a different approach or do you still go with the I guess large encompassing and collect everything you can and siphon after maybe I'm totally wrong I'll let you take it away no that's it's a it's a good question and what's interesting about that max is that the human body is governed by a series of laws we'll say in each me see ology and the things you've talked about physics they have laws humans as buyers you know shoppers travelers we have propensity x' we don't have laws right I have a propensity that I'm gonna try to fly United because I get easier upgrades but I might fly you know Southwest because of schedule or convenience right I have propensity x' I don't have laws so you have laws that work to your advantage what's interesting about laws that they start going into the world of IOT and this concept called digital twins they're governed by laws of physics I have a compressor or a chiller or an engine and it's got a bunch of components in it that have been engineered together and I can actually apply the laws I can actually run simulations against my digital twins to understand exactly when is something likely to break what's the remaining useful life in that product what's the severity of the the maintenance I need to do on that so the human body unlike the human psyche is governed by laws human behaviors are really hard right and we move the las vegas is built on the fact that human behaviors are so flawed but body mate but bat body physics like the physics that run these devices you can actually build models and one simulation to figure out exactly how you know what's the wear and tear and what's the extensibility of what you can operate in gotcha yeah so that's when from our world you start looking at subsystems and you say okay this is your muscular system this is your autonomic nervous system this is your central nervous system these are ways that we can begin to measure it and then we can wrote a blog on this that's a stress response model where you understand these systems and their inferences for the most part and then you apply a stress and you see how the body responds and even you determine okay well if I know the body I can only respond in a certain number of ways it's either compensatory it's gonna be you know returning to baseline and by the mal adaptation but there's only so many ways when you look at a cell at the individual level that that cell can actually respond and it's the aggregation of all these cellular responses that end up and manifest in a change in a subsystem and that subsystem can be measured inferential II through certain technology that we have but I also think at the same time we make a huge leap and that leap is the word inference right we're making an assumption and sometimes those assumptions are very dangerous and they lead to because that assumptions unknown and we're wrong on it then we kind of sway and missed a little bit on our whole projection so I like the idea of looking at patterns and look at the probabilistic nature of it and I'm actually kind of recently change my view a little bit from my room first I talked about this I was much more hardwired and laws but I think it's a law but maybe a law with some level of variation or standard deviation and it we have guardrails instead so that's kind of how I think about it personally is that something that you say that's on the right track for that or how would you approach it yeah actually there's a lot of similarities max so your description of the human body made up of subsystems when we talk to organizations about things like smart cities or smart malls or smart hospitals a smart city is comprised of a it's made up of a series of subsystems right I've got subsystems regarding water and wastewater traffic safety you know local development things like this look there's a bunch of subsystems that make a city work and each of those subsystems is comprised of a series of decisions or clusters of decisions with equal use cases around what you're trying to optimize so if I'm trying to improve traffic flow if one of my subsystems is practically flow there are a bunch of use cases there about where do I do maintenance where do I expand the roads you know where do I put HOV lanes right so and so you start taking apart the smart city into the subsystems and then know the subsystems are comprised of use cases that puts you into really good position now here's something we did recently with a client who is trying to think about building the theme park of the future and how do we make certain that we really have a holistic view of the use cases that I need to go after it's really easy to identify the use cases within your own four walls but digital transformation in particular happens outside the four walls of an organization and so what we what we're doing is a process where we're building journey maps for all their key stakeholders so you've got a journey map for a customer you have a journey map for operations you have a journey map for partners and such so you you build these journey maps and you start thinking about for example I'm a theme park and at some point in time my guest / customer is going to have a pity they want to go do something you want to go on vacation at that point in time that theme park is competing against not only all the other theme parks but it's competing against major league baseball who's got things it's competing against you know going to the beach in Sanibel Island just hanging around right there they're competing at that point and if they only start engaging the customer when the customers actually contacted them they must a huge part of the market they made you miss a huge chance to influence that person's agenda and so one of the things that think about I don't know how this applies to your space max but as we started thinking about smart entities we use design thinking and customer journey match there's a way to make certain that we're not fooling ourselves by only looking within the four walls of our organization that we're knocking those walls down making them very forest and we're looking at what happens before somebody engages it with us and even afterwards so again going back to the theme park example once they leave the theme park they're probably posting on social media what kind of fun they had or fun they didn't have they're probably making plans for next year they're talking to friends and other things so there's there's a bunch of stuff we're gonna call it afterglow that happens after event that you want to make certain that you're in part of influencing that so again I don't know how when you combined the data science of use cases and decisions with design thinking of journey Maps what that might mean to do that your business but for us in thinking about smart cities it's opened up all kinds of possibilities and most importantly for our customers it's opened up all kinds of new areas where they can create new sources of value so anyone listening to this need to understand that when the word client or customer is used it can be substituted for athlete and what I think is really important is that when we hear you talk about your the the amount of infrastructure you do for an idea when you approach a situation is something that sports science for in my opinion especially across multiple domains it's truly lacking what happens is we get a piece of technology and someone says go do science while you're taking the approach of let's actually think out what we're doing beforehand let's determine our key performance indicators let's understand maybe the journey that this piece of technology is going to take with the athlete or how the athletes going to interact with this piece of technology throughout their four years if you're in the private sector right that afterglow effect might be something that you refer to as a client retention and their ability to come back over and over and spread your own word for you if you're in the sector with student athletes maybe it's those athletes talking highly about your program to help with recruiting and understanding that developing athletes is going to help you know make that college more enticing to go to or that program or that organization but what really stood out was the fact that you have this infrastructure built beforehand and the example I give I spoke with a good number of organizations and teams about data utilization is that if if you're to all of a sudden be dropped in the middle of the woods and someone says go build a cabin now how was it a giant forest I could use as much wood as I want I could just keep chopping down trees until I had something that had with a shelter of some sort right even I could probably do that well if someone said you know what you have three trees to cut down to make a cabin you could become very efficient and you're going to think about each chop in each piece of wood and how it's going to be used and your interaction with that wood and conjunction with that woods interaction with yourself and so when we start looking at athlete development and we're looking at client retention or we're looking at general health and wellness it's not just oh this is a great idea right we want to make the world's greatest theme park and we want to make the world's greatest training facility but what infrastructure and steps you need to take and you said stakeholders so what individuals am i working with am I talking with the physical therapist am i talking with the athletic trainer am I talking with the skill coach how does the skill coach want the data presented to them maybe that's different than how the athletic trainer is going to have a day to present it to them maybe the sport coach doesn't want to see the data unless something a red flag comes up so now you have all these different entities just like how you're talking about developing this customer journey throughout the theme park and making sure that they have a you know an experience that's memorable and causes an afterglow and really gives that experience meaning how can we now take data and apply it in the same way so we get the most value like you said on the granular aspect of data and really turn that into something valuable max you said something really important and one of the things that let me share one of many horror stories that that that comes up in my daily life which is somebody walking up to me and saying hey I got a client here's their data you know go do some science on it like well well what the heck right so when we created this thing called the hypothesis development canvas our sales teams hate it or do the time our data science teams love it because we do all this pre work we just say we make sure we understand the problem we're going after the decision they're trying to make the KPI is it's what you're going to measure success in progress what are they the operational and financial business benefits what are the data sources we want to consider here's something by the way that's it's important that maybe I wish Boeing would have thought more about which is what are the costs of false positives and false negatives right do you really understand where your risks points are and the reason why false positive and false negatives are really important in data science because data size is making predictions and by virtue of making predictions we are never 100% certain that's right or not predictions hath me built on I'm good enough well when is good enough good enough and a lot of that determination as to when is good enough good enough is really around the cost of false positives and false negatives think about a professional athlete like the false the you know the ramifications of overtraining professional athlete like a Kevin Durant or Steph Curry and they're out for the playoffs as huge financial implications them personally and for the organization so you really need to make sure you understand exactly what's the cost of being wrong and so this hypothesis development canvas is we do a lot of this work before we ever put science to the data that yeah it's it's something that's lacking across not just sports science but many fields and what I mean by that is especially you referred to the hypothesis canvas it's a piece of paper that provides a common language right it's you can sit it out before and for listeners who aren't aware a hypothesis canvas is something bill has worked and developed with his team and it's about 13 different squares and boxes and you can manipulate it based on your own profession and what you're diving into but essentially it goes through the infrastructure that you need to have setup in order for this hypothesis or idea or decision to actually be worth a damn and what I mean by that is that so many times and I hate this but I'm gonna go in a little bit of a rant and I apologize that people think oh I get an idea and they think Thomas Edison all son just had an idea and he made a light bulb Thomas Edison's famous for saying you know I did you know make a light bulb I learned was a 9000 ways to not make a light bulb and what I mean by that is he set an environment that allowed for failure and allowed for learning but what happens often people think oh I have an idea they think the idea comes not just you know in a flash because it always doesn't it might come from some research but they also believe that it comes with legs and it comes with the infrastructure supported around it that's kind of the same way that I see a lot of the data aspect going in regards to our field is that we did an idea we immediately implement and we hope it works as opposed to set up a learning environment that allows you to go okay here's what I think might happen here's my hypothesis here's I'm going to apply it and now if I fail because I have the infrastructure pre mapped out I can look at my infrastructure and say you know what that support beam or that individual box itself was the weak link and we made a mistake here but we can go back and fix it

live from Las Vegas it's the cube covering service now knowledge 2018 brought to you by service now welcome back to the cubes live coverage of service now knowledge 18 we are here in Las Vegas Nevada I'm your host Rebecca Knight along with my co-host Dave allanté we are joined by John Donahoe who is the president and CEO of ServiceNow thanks so much for coming on the cube it's great to be here Rebecca so I want to talk with you a little bit about what you said on the main stage this morning you said this is your first year your anniversary of joining ServiceNow you said when you got here you could barely spell IT but when you reflect back on this year what has been sort of the biggest surprise challenges and surprises about about leading this company well I would say a couple things one I've sort of fallen in love with our customers and the challenges and opportunities they have and what I spoke about this morning this digital transformation thing even a year ago is a bit of a buzzword it's a reality for CEOs for companies and therefore for CIOs and then the second thing that is as I talked about it something very exciting is the role of the CIO the role of IT is transforming before our very eyes out of necessity because technology is here to stay technology's driving strategic change at every company can call it a digital transformation called a tech transformation and CEOs need the most technically savvy leader in the c-suite to help with that and that's often the CIO and so I think that's an enormous ly exciting opportunity for the people that are our traditional customer base and then the last thing I just I'm thrilled about is how many companies are saying that ServiceNow is a strategic platform of choice going forward far beyond just IT and so that's something to roll build upon I was struck yesterday in the Financial Analysts session you shared with us your meeting with the board yeah and you said to them look if you want to clean this thing up flip it whatever that don't hire me I'm here to build a sustainable company during company I think is what you said and the attributes of an enduring companies that are Purpose Driven they both innovate and execute they invest in talent and they have a will to win they got a fight in them a lot of good sports analogies there yeah so okay so you've set that framework where do you see this thing going in the next near term mid term and long term well we've said I think it's really important to set the aspiration of what it is you're shooting toward I've been surprised how many customers have responded well to the statement that we aspire to create a built to last company it starts with the purpose I defined our purpose and that purpose is a long term investment and our employees are already deeply resonating with the purpose and then comes the hard work the hard work of how you bring the purpose to life and our purpose and our product and the work we do with our customers all fit together you talked about automation and in many executives that we talked to kind of run away from that we don't want to talk about automation because it implies we're gonna replace humans you said hey we're at the center of automation we have to take that issue head-on what's the conversation like with the executives and customers that you talk to well the first thing is I have to think yet to look at the data which is what I've spent time doing and two things jump out one if you look at where automation is really gonna have the biggest impact it's not in any given job it's actually the third of all of our jobs that are repetitive administrative redundant right that's so we need to automate the low value-added parts of all of our jobs and then that will free our time up to be due to leverage our more creative capabilities to add more value and so if you look at it both at a micro and macro standpoint where automation is going to impact jobs it's not a given category it's more of a horizontal cut of all jobs and then secondly looking at aggregate job creation I've done a fair amount of work with James mineka the McKinsey Institute is to blow up a suit who's got to think the best objective macro study about job creation and there going to be some jobs they'll be fewer of and other jobs they'll be more of and how do we migrate the skills migration so that people have the skills for the jobs of the future one of which by the ways things like being a ServiceNow administrator you do not have to be a computer science major or an engineer to be a ServiceNow administrator you have to like technology you have to embrace technology but you can do it as a mere mortal and so we're looking at ways of how do we help retrain people to have the skills to create one of the jobs that we're creating through ServiceNow administrators John you talk to a lot of people I think five or six hundred customers know and they'll have since I met you a year ago it ServiceNow headquarters we obviously talked to a lot of people on the cube and no question every CEO the ax talked it was trying to get digital right yep they understand it but there's somewhat of a dissonance and I wonder if you sense it in and I wonder if you could talk about how ServiceNow can help wear this the c-suite gets it and they're driving for that but when you go below the line there's a lot of sometimes complacency not in our industry not in my lifetime I'll be retired by then do you hear a lot of that and how can ServiceNow help increase the urgency well I'd say I take a couple things Dave one is the c-suite gets it by not every c-suites role-modeling what's necessary without the cross-functional leadership the partnership of ITN HR and the business units then what happens by tama goes to three levels down people have functional identities and so people role model are behaving the way they see their leadership team role modeling and so if that if that c suite is embracing technology and understanding technology demands cross-functional engagement to deliver great customer experiences and employee experiences then it makes it a lot easier two three steps down the second thing I think c-suite people need to do is be able to say we take if off the table we said I talked about top-down goals most people are scared of a top-down goal the problem is if there's a not a top-down goal then people can debate if we need to make this change and how but if the CEO the c-suite says we are going to improve the employee experience and I'm setting this goal then it's when you go a level two levels down it's not if no no they said if now our job is how and so I think leadership has to do its role and I think I think the c-suite and leadership's learning how you lead and a technology enabled environment so leadership is the key and and the CEO is really leading a little suite I think the whole the whole C suite set of leaders and partnering and reaching out to one another so we I mean as you said on the main stage in many ways the technology is the easy part but what you're talking about is the hard stuff because this is the real change management and and it's human lead so what are you hearing what are you seeing and do you have any ideas for best practices I mean as you said that the the C suite needs to embrace it yes and then push that down but how do you do it what are some what are some of the things you've seen that work well here's some of the things that we're trying to do to contribute toward that because obviously we're a software platform but one is to do what I did this morning which is be more articulate about what best practice looks like what is best in class so that anyone in any organization can can go to their boss and say oh this is best practice this is best-in-class we need to emulate this and here are the returns we can get if we emulate it so one is just hold out the successes successful examples and illustrate what's required that's why I kept saying over and over this morning employee experience is not just an HR issue employee experience is not just an IT issue you need a powerful team of CIO C HR o other functional leaders and then the second thing I think is getting people on i.t to see themselves a little bit differently we have a CIO track going on upstairs with a hundred top CIOs and the whole day is around driving culture change and CIO is leader and I think good leaders they don't just allow a label to be attached to them they invest in themselves they build their skills they build change management skills communication skills and I think whether it's a CIO or IT if they're going to have the kind of transformative impact they can across the company they need to build their technical expertise along with other skill sets you heard Andrew Wilson talk about that and they need to learn to speak business and not just IT John I want to push on something that I'm discerning from you guys and get your reaction so obviously cloud you guys are born in the cloud cloud is a tailwind for you we've seen this Asif occation of business but we seem to be entering a new era moving from a cloud of remote services to one of us fabric Ubiquiti is fabric of digital services so my question is around innovation you talked about that as one of the key attributes of an enduring company what's the innovation equation going forward yeah it's not Moore's law anymore it's not cloud mobile social Big Data at least it doesn't feel that way anymore is it machine intelligence combined with cloud what do you see I think it gets down actually to what I talked about this morning user experience I think machine learning I think AI is going to be a commodity functionality we're gonna get it from AWS or Azure or Google the cloud infrastructure providers whether it's natural language processing whether it's the kind of machine learning capabilities that's that's gonna be sort of available widely then it's our job as a software platform to build that into our platform so we built machine learning capability into our platform we built chat bot functionality into our platform we built leading-edge mobile capability into our platform and again I'll call that I don't know it's the easy part but that's our job in this equation the hard job then is how you apply that to real-world use cases whether you're applying using real-world datasets specific customer data sets and real-world workflows and use cases so let me give you a small example we bought a machine learning company a year ago called DX continuum great machine learning team great machine learning technology we rebuilt it inside the ServiceNow platform okay and I don't believe a AI is a horizontal platform is I don't you know we didn't call it a name it after a a dead scientist that's out what we're gonna do and I'm not casting judgment on it but it's not a solution looking for a problem we built machine learning into our platform and then so we want to be the first user we want to use it on a specific challenge so the case we used it on our own inbound customer support we have about 800 customer support agents that serve our customers about 11 percent of their time is spent on something we call incident categorization and incident routing sounds kind of grunty terms but when summer calls with a problem we have to be able to identify what that problem is and then route it to the right person to fix the problem so 11% of our peoples time was doing that that's not a fun task so we turned on machine learning and within two weeks the machine was categorizing the issue and routing it more accurately than a human can so now what happens is our customers problems are getting solve faster and the 11% of those resources those customer support resources who are engineers in our case are focused on solving customer problems not doing what felt like an administrative task to them and so I think the actual application of machine learning the actual application in many of these these technologies it's the application that's going to matter not the invention so a lot of what you said makes it makes sense to me because you're saying that your customers are gonna be buying essentially that machine learning capability in relative and applying it in very narrow use cases to solve their business problems rather than trying to build it right and you do see some companies trying to maybe get over out over their skis and over-rotate to try to build some of that stuff that's gonna come from the technology suppliers what yours if we're doing our job the infrastructure providers the software platforms like us we're doing our job we're making it easy another small example will be mobile I talked this morning about companies everywhere need to build mobile experiences and so there one do I need to build a mobile design team a mobile coding team if you're up if you're a bank or utility or an oil and gas company or a retailer or well platforms like ours make building mobile experiences really easy for them so we're trying to build that mobile capability that design capability that Design Thinking the mobile capability into the platform so they can just get out-of-the-box functionality and they don't have to have their own mobile designers they don't have their own mobile engineers they can just be saying how do I want to use mobile inside my company and then there they're taking our mobile platform if you will and and creating mobile applications and mobile experiences that are relevant for them so your brand identity is now making work work better for people yes when you are doing your blue sky thinking about the pain points that employees feel and that job candidates feel because that's their another important part of of companies trying to keep their people happy yes what what are what do you see I mean as you said the next three to five years are going to be this the revolution is going to be in the workplace yes what do you see as sort of the biggest challenges that you want to help solve well let me just take a simple use case that that comes to mind as you mention that let's take from the time you start being recruited for a company through that let's say you get hired and get started so the recruiting process you're sending a resume and you don't know if I got in didn't get in if anyone someone may or may not contact you you may get an interview you got to find out where you're going if you're going did you get called back maybe you get an offer letter it comes you get it all set all kind of I would call an unstructured workflow let's say you get hired then the onboarding process onboarding is a classic unstructured workflow you got to go to this security to get your badge you got to go to facilities to get your desk you got to go to it2 get your laptop or mobile phone you got to get to another part of IT to get your email credentials put on you've got to enter your information into the payroll system you got to reenter your same information and pick a health care provider you got a range of the same information and and and get a in the tini system you got to do all this compliance training painting an accurate ownerís picture this is your first impression of the company you're joining now there is no reason they took my mobile phone away from me so I'm twitching there's no reason why there shouldn't be an app that says a recruit says I want to interview if the company they download the app they submit their resume based on the app we give a response in the app they say oh might my resume was accepted and I they want me to do an interview and they want me to be in Santa Clara next once at 8:00 and here's who I'm going to be meeting with and here's their background in the app then they do the interview let's say they get invited back who they're interviewing with we're inside the app okay let's say then they get an offer well then the app has more permission in the offer comes through the app you can print it or you can read it then onboarding starts onboarding can be a seamless experience it still can connect but you enter your data in once it pre fills all those systems and then in one mobile experience you're picking what's your laptop what's your healthcare system what's the bank you want your payroll in teeny to go into and all the complexity is hidden underneath it that's what we have in the consumer world our lives at home when you buy something on eBay all the complexities hidden when you pay with PayPal all the complexities hidden there's no reason why all the complexity can't be hidden in the recruiting and onboarding process and and so the technology's there to do it but it's managing all the workflows managing all the processes underneath so you can pull that together into a seamless experience and that's the kind of experience it's funny I have four grown kids my daughter she started working I won't say where but a major technology company and she's like dad what's up with this onboarding process why isn't it in a mobile app and the Millennials will start demanding this and so I I just think there's so much opportunity to make our lives at work feel more like our lives at home and you just described the capability that allow you to reach your aspirations of the next great enterprise software company when we think of great enterprise software companies we think of Oracle and si P you're nothing like Oracle and si P in my opinion and then of course you think of Salesforce different you know you're not a an SMB how should we be thinking about the next great enterprise software company so this I think this is a really important question Dave and I'd look at it through the eyes that what I heard from the 500 customers and here's what I heard they're embracing digital transformation they're embracing cloud they're embracing cloud at the infrastructure level figuring out their data center strategy and how much they embrace public cloud and then at the software platform level they're saying we want to have four to six strategic platforms and often it's the born in the cloud platforms often its sales force and workday and service now and maybe office 365 or Google for email or communications maybe if they have a supply chain ASAP and they're saying I want those platforms to work well together so no one platform should be claiming they can do everything each of us needs to figure out what's our role and how do we work with one another and our role ServiceNow I'm proud to say is one of those strategic platforms as I said earlier people see our capabilities as being connective tissues helping to pull those platforms together you know in the onboarding example we pull all the data sets and platforms together by the way we don't slap our brand on top because actually employees want to see their own brands they want to see their own company's brand they don't want to know what the enterprise software brand underneath it is they just wanna have a great experience and so I I don't view it I think the winning enterprise software I see a chance for Salesforce and workday and ServiceNow and Microsoft to all be winners and delivering this future for companies where you are the platform of platforms though correct but that's not and I'm being very careful the way I say it I'm not saying we're the top dog sure I'm saying what we're good at is cross-functional workflow actually it's probably the grunt 'ya stuff all those things and you're the best at it and we're the best at you are and our brand we're not we're not forcing our brand everywhere that we're doing it in service to our customers and so I just want to always be listening to what our customers want that's gonna be our North Star they're gonna guide us it always has been I know you know Fred Letty started that from the beginning and that's what we're gonna continue to do well John it's always a pleasure having you on the cube so thanks so much for coming on our show thank you very much Becky thank you Dave great to be happy John I'm Rebecca night for Dave Allante we will have more from ServiceNow knowledge 18 in just a little bit [Music]