>> From the Salesforce Tower in downtown San Francisco, it's theCUBE. Covering Accenture Tech Vision 2019. Brought to you by SiliconANGLE Media. >> Hey, welcome back, everybody. Jeff Frick here with theCUBE. We're in downtown San Francisco in the Salesforce Tower. Accenture's taken over five floors of the Salesforce Tower, and they're opening their brand new Innovation Hub. It's pretty cool, formal ribbon cutting earlier today. We're excited to be here. It's three floors of cool innovation, then a couple work floors, so if you get a chance come check it out. A lot co-creation, a lot of neat technology happening. But we're here to talk about something a little bit different, that's championship basketball. So we're excited to be joined by Jeremy Thum, he's the senior director of digital experience from the Golden State Warriors, Jeremy, great to see you. >> Great to see you, thank you. >> And he's accompanied by Greg Jensen managing director from Accenture. Welcome. >> Thank you, great to be here. >> So digital experience, you guys are getting ready to embark on a big new adventure, a big construction project just south of, I was going to say AT&T Park, Oracle Park now at the new Chase Center. >> Yeah. >> A lot of talk, really excitement, tell us about what is going on at the Chase Center. >> There's never a dull moment at the offices these days as the Golden State Warriors organization is going through a pretty big transition. A transformation from basketball team that leases a building 50 nights a year into an entertainment company that owns and operates a world-class facility. And so all eyes are pointing to this project. All thought is going onto the project, and it's a really exciting time in the organization. >> It's really an amazing story of how much impact leadership really has. I mean, you had a perennial doormat franchise, right, that hadn't been to the playoffs for a long time. And David Lee shows up as the first all-star in Lord knows how long, and they have completely transformed their franchise on the basketball side. And now you see the same kind of energy vision, vision, probably, is really the best word, and now moving from Oracle Arena, one of the most beloved basketball home courts into the new Chase Center. So I what if you can just share some insight on what it is like to work for these guys? You know, what is the passion? How do they drive it down through the whole organization? >> It's incredible. I say that on a daily basis there is an energy level and an excitement about taking this organization to the next level, and there is no rest. We know that sports is cyclical, and the performance on the court is going to be cyclical, but the business can operate in a way, and create an environment that a business can succeed and thrive. And that's part of the move into Chase Center is the organization is expanding. The business is expanding into different areas, that we've never been in before, so it's exciting. >> Right. So how long have you been working with the Warriors? >> About 18 months. >> 18 months? And why did they bring you in? What are you helping them with? >> So we are the Warriors' official technology innovation partner. And as Jeremy and the team were thinking through the fan experience, they where assembling a really great team of partners, and one of those partners is Accenture. And so the reason that I'm here is because I spent about 3 1/2 years working with other media companies on transformations, doing sort of similar fan experience design. And it's really my job to bring the best of Accenture to the Warriors and make sure that as they're innovating on the fan experience, that we're helping them and that we're there as great partners to support them along the way. >> So what are some of the things that win the new fan experience besides just being the loudest arena in the NBA? >> Well, I think the most exciting thing that I'm working on with Greg and the Accenture team is the mobile application of the future. We have a Warriors App that exists now that serves a very specific purpose. As we move into a new building in a new district that surrounds the building and have a variety of events, we need a new mobile experience, also, so we will be building this new mobile experience as an application built specifically for the local fan. Anyone that can, or should, or will be coming to the district to enjoy an event at Chase Center. And of course, as we have a global fan base, there will still be content and interesting things to bring in a global audience to the mobile app. But this is really designed for the local fan to say how can we help you if you have a ticket to an upcoming event, or if you don't have a ticket to an event but just kind of want to see what's happening on the district, how can we help that experience along the way? And all the different touchpoints that go along with a game or an event experience. >> Right. So how much of the mobile app is kind of a launching point into the other things that are happening at the Chase Center versus being kind of its self-contained experience in it of itself? >> I'd love for your opinion on this, too. >> Yeah, I think the thing that the Warriors have done really well is they've positioned technology as enabler of the overall end-to-end experience. And so think of the mobile app as sort of the gateway that ties a lot of that experience together. But certainly there are other exciting activations that will happen within the Chase Center throughout the district, and the Warriors know how to put on a great show, both on the court and off. And so it's really that blend of sort of that background technology that's orchestrating this in concert along with that front, in-your-face, exciting Warrior brand and anthem that is really going to get folks excited. >> Yeah, we talk an awful lot about how we don't want technology to be the story. We want it to live in the background and help enhance the fan experience rather than being the headline. >> Right, I was going to say I'm sure the purists are like, I want to come watch a basketball game. It's a beautiful game, this is why I'm paying a big ticket price because this is what I want to watch. I don't need all these distractions of all these other things. So when you think about the experience and integrating it, as you said, as an amplification of watching the basketball game versus a distraction or something that takes away from the core. How do you kind of balance those priorities? How do you kind of level set a new feature request or a new workflow request? Versus, you know, don't forget at the end of the day, it's still about the basketball game first. >> It is, and in addition to the basketball game, it's all about the 200 other events that will be there. Think of all the concerts and family shows that could be coming to a facility that San Francisco has never had before. So the mobile experience is supposed to get enhanced, and I think were spending a lot of time thinking through. The moment you think about coming to an event, is when that sort of experience begins, and the mobile app should be a conduit to help and not get in the way of the experience, which is that thing that's on the stage or on the court. >> Right. A really good friend of mine is Bill Schlough, he's the CIO of the Giants, right, and every year they go through some big huge technology play, whether it's a new jumbo tron or it's new wifi under the seats. It's this really cool, like you said, this delicate balance where you want to bring in the tech, and people are expected to have tech. They want their Instagram to work when they send a picture with the kids. But, again, it's got to be, I don't want to say secondary, but it is secondary or a little bit behind the scenes. >> And I think the Warriors have been really thoughtful around using the application to help coming to the district and Chase Center become an experience. And what I mean by that is, your ability to do wayfinding from your home to get to your seat. Your ability to book a car service if you choose to leave the district or after a game. The ability to just sort of make your life more simplistic around the game, so that getting to and getting from the event is much simpler and much more streamlined for the fan. But when your in that experience, sure, you can pull up the stats to see that Stephs hit 11 three pointers in a row and broken Clay's most recent record. Or you certainly can just enjoy the game for what it is. >> Right, right. All right, before I let you go, thanks for bringing the trophy, too, Jeremy. Very nice. What's one or two totally unique nuggets that you can share at the Chase Center that are completely new and maybe kind of fall below the radar that you think are pretty cool? >> Well, I don't know if I want to give too many secrets away, but I will say that I think the experience will be something that cannot miss. From the visuals and where it's placed, I think just the visuals when you see the aesthetics is going to blow everyone away. And I think, hopefully, if we do it right, the technology and the mobile experience will be an element to it, but won't be the leading story. >> All right. Well, thanks for stopping by. Congrats on all the rings. And I look forward to one more season, right? We have one more season to go? >> Here we go! >> All right, thanks a lot. >> Thank you. >> All right he's Greg, he's Jeremy, I'm Jeff, you're watching theCUBE. We're at the Accenture Innovation Hub in downtown San Francisco. Thanks for watching, we'll see you next time. (upbeat music)

>>Hi, we're back. We're watching, you're watching the cube coverage of Falcon 2022 live from the aria in Las Vegas, Dave Valante with Dave Nicholson and we, yes, folks, there are females in the cyber security industry. Amanda Adams is here. So the vice president of America Alliance at CrowdStrike. Thanks for coming on. >>Thank you so much for having me. >>We it's, it's fantastic to, to actually, as I was starting to wonder, but we >>Do have females in leadership. >>Wait, I'm just kidding. There are plenty of females here, but this cybersecurity industry in general, maybe if we have time, we can talk about that, but I wanna talk about the, the Alliance program, but before I do, yeah. You know, you, you got a nice career here at CrowdStrike, right? You've kind of seen the ascendancy, the rocket ship you've been on it for five years. Yep. So what's that been like? And if you had to put on the binoculars and look five years forward, what can you tell us in that 10 year span? Oh >>My goodness. What a journey it's been over the last five, six years. I've been with CrowdStrike almost six years and really starting with our first core group of partners and building out the alliances, seen obviously the transformation with our sales organization. And as we scaled, I think of our, of our technology. We started with, I think, two products at that time, we were focused on reinventing how our customers thought about NextGen AB but also endpoint detection response. From there, the evolution is really driving towards that cloud security platform, right? How our partners fit into that. And, and how we've evolved is it's not just resell. It's not just focusing on the margin and transactions. We really have focused on building the strategic relationships with our partners, but also our customers and fitting them in that better together story with that CrowdStrike platform. It's been the biggest shift. Yeah. >>And you've got that. The platform chops for that. It's just, I think you're up to 22 modules now. So you're not a point product. You guys make that, that, that point lot now in terms of the, the partners and the ecosystem, you know, it's, it's, it's good here. I mean, it's, this it's buzzing. I've said it's like service. I've said, number of times, it's like service. Now back in 2013, I was there now. They didn't have the down market, the SMB that you have that's right. And I think you you're gonna have an order. You got 20,000 customers. That's right. I predict CrowdStrike's gonna have 200,000. I, I'm not gonna predict when I need to think about that. But, but in thinking about the, the, the co your colleagues and the partners and the skill sets that have evolved, what's critical today. And, and, and what do you see as critical in the future? >>So from a skill set standpoint, if I'm a partner and engaging with CrowdStrike and our customers, if you think about, again, evolving away from just resell, we have eight routes to market. So while that may sound complicated, the way that I like to think about it is that we truly flex to our partners, go to market their business models of what works best for their organization, but also their customers. The way that they've changed, I think from a skillset standpoint is looking beyond just the technology from a platform, building a better together story with our tech Alliance partners or store, if thinking about the XDR Alliance, which we are focusing on, there's so much great value in bringing that to our customers from a skillset standpoint, beyond those services services, we've talked about every day. I know that this is gonna be a top topic for the week yesterday through our partner summit, George, our CEO, as well as Jim Cidel, that's really the opportunity as we expand in new modules. If you think about humo or log scale identity, and then cloud our partners play a critical role when it comes into the cloud migration deployment integration services, really, we're not gonna get bigger from a services organization. And that's where we need our partners to step in. >>Yeah. And, you know, we we've talked a lot about XDR yeah. Already in day one here. Yeah. With, with the X extending into other areas. That's right. I think that services be, would become even more critical at that point, you know, as you spread out into the, really the internet of things that's right. Especially all of the old things that are out there that maybe should be on the internet, but aren't yet. Yeah. But once they are security is important. So what are you doing in that arena from a services perspective to, to bolster that capability? Is it, is it, is it internally, or is it through partners generally? >>It's definitely, I think we look to our partners to extend beyond the core of what we do. We do endpoint really well, right? Our services is one of the best in the business. When you look at instant response, our proactive services, supporting our customers. If you think to XDR of integration, building out those connect air packs with our customers, building the alliances, we really do work with our partners to drive that successful outcome with our customers. But also too, I think about it with our tech alliances of building out the integration that takes a lot of effort and work. We have a great team internally, which will help guide those services to be, to be built. Right. You have to have support when you're building the integrations, which is great, but really from like a tech Alliance and store standpoint, looking to add use cases, add value to more store apps for our customers, that's where we're headed. Right. >>What about developers? Do you see that as a component of the ecosystem in the future? Yeah, >>Without a doubt. I mean, I think that as our partner program evolves right now working with our, our developers, I mean, there's different personas that we work with with our customer standpoint, but from a partner working with them to build our new codes, the integration that's gonna be pretty important. >>So we were, we sort of tongue in cheek at the beginning of this interview yeah. With women in tech. And it's a, it's a topic that, on the cube that we've been very passionate about since day one yep. On the cube. So how'd you get in to this business? H how did your, your career progress, how did you get to where you are? >>You know, I have been incredibly fortunate to have connections, and I think it's who, you know, and your network, not necessarily what, you know, to a certain extent, you have to be smart to make it long term. Right. You have to have integrity. Do what you're saying. You're gonna do. I first started at Cisco and I had a connection of, it was actually a parent of somebody I grew up with. And they're like, you would fit in very nicely to Cisco. And I started with their channel marketing team, learned a ton about the business, how to structure, how to support. And that was the first step into technology. If you would've asked me 20 years ago, what did I wanna do? I actually wanted to be a GM of an organization. And I was coming outta I come on, which is great, which I'm, it really is right up. >>If you knew me, you're like, that actually makes a lot of sense. But coming outta college, I had an opportunity. I was interviewing with the golden state warriors in California, and I was interviewing with Cisco and that I had two ops and I was living in San Jose at the time. The golden state warriors of course paid less. It was a better opportunity in sales, but it was obviously where I wanted to go from athletics. And I grew up in athletics, playing volleyball. Cisco paid me more, and it was in San Jose. And really the, the golden state warriors seemed that I was having that conversation. They said, one year community is gonna be awful. It's awful from San Jose to Oakland, but also too, like you have more money on the table. Go take that. And so I could have very much ended up in athletics, most likely in the back office, somewhere. Like I would love that. And then from there, I went from Cisco. I actually worked for a reseller for quite some time, looking at, or selling into Manhattan when I moved from California to Manhattan, went to tenable. And that was when I shifted really into channel management. I love relationships, getting snow people, building partnerships, seeing that long term, that's really where I thrive. And then from there came to CrowdStrike, which in itself has been an incredible journey. I bet. Yeah. >>Yeah. I think there's an important thread there to pull on. And that is, we, we put a lot of emphasis on stem, which people, some sometimes translate into one thing, writing code that's right. There are, but would you agree? There are many, many, many opportunities in tech that aren't just coding. >>Absolutely. >>And I think I, as a father of three daughters, it's, it's a message that I have shared with them. Yeah. They are not interested in the coding part of things, but still, they need to know that there are so many opportunities and, and it's always, sometimes it's happenstance in terms of finding the opportunity in your case, it was, you know, cosmic connection that's right. But, but that's, you know, that's something that we can foster is that idea that it's not just about the hardcore engineering and coding aspect, it's business >>That's right. So if, if there was one thing that I can walk away from today is I say that all the time, right? If you look at CrowdStrike in our mission, we really don't have a mission statement. We stop breaches every single day. When I come to work and I support our partners, I'm not super technical. I obviously know our technology and I, I enable and train our partners, but I'm not coding. Right. And I make an impact to our business, our partners, more importantly, our customers, every single day, we have folks that you can come from a marketing operations. There is legal, there's finance. I deal with folks all across the business that aren't super technical, but are making a huge impact. And I, I don't think that we talk about the opportunities outside of engineering with the broader groups. We talk about stem a lot, but within college, and I look to see like getting those early in career folks, either through an intern program could be sales, but too, if they don't like, like sales, then they shift into marketing or operations. It's a great way to get into the industry. >>Yeah. But I still think you gotta like tech to be in the tech business. Oh, you >>Do? Yeah. You do. I'm >>Not saying it's like deep down is like, not all of us, but a lot of us are kind of just, you know, well, at least you, >>At least you can't hate it. >>Right. Okay. But so women, 50% of the population, I think the stat is 17% in the technology. Yeah. Industry, maybe it's changed a little bit, but you know, 20% or, or less, why do you think that is? >>I, you know, I always go back to within technology, people hire from their network and people that they know, and usually your network are people that are very like-minded or similar to you. I have referred females into CrowdStrike. It's a priority of mine. I also have a circle that is also men, but also too, if you look at the folks that are hired into CrowdStrike, but also other technology companies, that's the first thing that I go to also too. I think it's a little bit intimidating. Right. I have a very strong personality and I'm very direct, but also too, like I can keep up with our industry when it comes to that stereotypes essentially. And some people maybe are introverted and they're not quite sure where they fit in. Right. Whether it's marketing operations, et cetera. So they, they're not sure of the opportunities or even aware of where to get started. You know what I mean? >>Yeah. I mean, I think there is a, a, a stereotype today, but I'm not sure why it's, is it unique to the, to the technology industry? No. Is it not? Right? It happens >>Thinking, I mean, there's so many industries where healthcare, >>Maybe not so much. Right. Because you know, >>You have nurses versus doctors. I feel like that is flipped. >>Yeah. That's true. Nurses versus doctors. Right. Well, I, I know a lot of women doctors though, but >>Yeah. That's kind of flipped. It's better. >>Yeah. Says >>Flipped over. Yeah. I think it's more women in medical school now, but than than men. But, >>And, and I do think in our industry, you know, when you look at companies like IBM, HPE, Cisco, Dell, and, and, and many others. Yeah. They are making a concerted effort for on round diversity. They typically have somebody who's in charge of diversity. They report, you know, maybe not directly to the CEO, but they certainly have a seat at the table. That's right. And you know, maybe you call it, oh, it's quotas. Maybe the, the old white guys feel, you know, a little slighted, whatever. It's like, nobody's crying for us. I mean, it's not like we got screwed. >>See, I know problema we can do this in Spanish. Oh, oh, >>Oh, you're not a old white guy. Sorry. We can do >>This in Spanish if you want. >>Okay. Here we go. So, no, but, but, but I, so I do think that, that the industry in general, I talked to John Chambers about this recently and he was like, look, we gotta do way better. And I don't disagree with that. But I think that, I think the industry is doing better, but I wonder if like a rocket ship company, like CrowdStrike who has so many other things going on, you know, maybe they gotta get you a certain size. I mean, you've reached escape velocity. You're doing obviously a lot of corporate, you know, good. Yeah. You know, and, and, and, and we just had earlier on we, you know, motor motor guides was very cool. Yeah. So maybe it's a maturity thing. Maybe these larger companies with you crowd size $40 billion market cap, but maybe the, the hundred plus billion dollar market cap companies. I don't know. I don't know. You guys got a bigger market cap than Dell. So >>I, I don't think it's necessarily related to market cap. I think it's the size of the organization of how many roles are open that we currently write. So we're at just over 6,000 employees. If you look at Cisco, how many thousands of employees they have there's >>Right. Maybe a hundred thousand employees. >>That's right. There's >>More opportunities. How many, what's a headcount of crowd strike >>Just over 6,000, >>6,000. So, okay. But >>If you think about the, the areas of opportunity for advancement, and we were talking about this earlier, when you look at early and career or entry level, it's actually quite, even right across the Americas of, we do have a great female population. And then as progression happens, that's where it, it tees off from a, a female in leadership. And we're doing, we're focusing on that, right? Under JC Herrera's leadership, as well as with George. One of the things that I always think is important though, is that you're mindful as, as the female within the organization and that you're out seeking somebody, who's not only a mentor, but is a direct champion for you when you're not in the room. Right. This is true of CrowdStrike. It's true of every organization. You're not gonna be aware of the opportunities as the roles are being created. And really, as the roles are being created, they probably have somebody in mind. Right. And so if you have somebody that's in that room says, you know what, Amanda Adams would be perfect for that. Let's go talk to her about it. You have to have somebody who's your champion. Yeah. >>There there's, there's, there's a saying that 80% of the most important moments in your life happen in your absence. Yeah. And that's exactly right. You know, when they're, when someone needs to be there to champion, you, >>Did that happen for you? >>Yes. I have a very strong champion. >>So I mean, I, my observation is if, if you are a woman in tech and you're in a senior leadership position, like you are, or you're a, you're a general manager or a P and L manager or a CEO, you have to be so incredibly talented because all things being equal, maybe it's changing somewhat in some of those companies I talked about, but for the last 30 years, all takes be equal. A, a, a woman is gonna lose out to a man who is as qualified. And, and I think that's maybe slowly changing. Maybe you agree with that, maybe you don't. And maybe that's, some people think that's unfair, but you know, think about people of color. Right. They, they, they, they grew up with less op opportunities for education. And this is just the statistics that's right. Right. So should society overcompensate for that? I personally think, yes, the, the answer is just, they should, there should still be some type of meritocracy that's right. You know, but society has a responsibility to, you know, rise up all ships. >>I think there's a couple ways that you can address that through Falcon funds, scholarship programs, absolutely. Looking at supporting folks that are coming outta school, our internship program, providing those opportunities, but then just being mindful right. Of whether or not you publish the stats or not. We do have somebody who's responsible for D I, within CrowdStrike. They are looking at that and at least taking that step to understand what can we do to support the advancement across minorities. But also women is really, really important. >>Did you not have a good educational opportunity when you were growing up where you're like you had to me? Yeah, no, seriously, >>No. Seriously. I went to pretty scary schools. Right. >>Okay. So you could have gone down a really bad path. >>I, a lot of people that I grew up with went down really, really bad paths. I think the inflection point at, at least for me what the inflection point was becoming aware of this entire universe. Yeah. I was, I was headed down a path where I wasn't aware that any of this existed, when I got out of college, they were advertising in the newspaper for Cisco sales engineers, $150,000 a year. We will train. I'm a smart guy. I had no idea what that meant. Right. I could have easily gone and gotten one of those jobs. It was seven or eight years before I intersected with the tech world again. And so, you know, kind of parallel with your experience with you had someone randomly, it's like, you'd be great at Cisco. Yeah. But if, if you're not around that, and so you take people in different communities who are just, this might as well be a different planet. Yes. Yeah. The idea of eating in a restaurant where someone is serving you, food is uncomfortable, right? The idea of checking into a hotel, the idea of flying somewhere on an airplane, we talk about imposter syndrome. That's right. There are deep seated discomfort levels that people have because they just, this is completely foreign, but >>You're saying you could have foreign, you could have gone down a path where selling drugs or jacking cars was, was, was lucrative. >>I had, I had, yeah. I mean, we're getting, we're getting like deep into societal things. I was, I was very lucky. My parents were very, very young, but they're still together to this day. I had loving parents. We were very, very poor. We were surrounded by really, really, really bad stuff. So. >>Okay. So, so, okay. So this, >>I, I don't, I don't compare my situation to others. >>White woman. That's I guess this is my point. Yeah. The dynamic is different than, than a kid who grew up in the inner city. Yes. Right. And, and, and they're both important to address, but yeah. I think you gotta address them in different ways. >>Yes. But if they're, but if they're both completely ignorant of this, >>They don't know it. So it's lack of >>A, they'll never be here. >>You >>Never be here. And it's such a huge, this is such a huge difference from the rest of the world and from the rest, from the rest of our economy. >>So what would you tell a young girl? My daughters, aren't interested in tech. They want to go into fashion or healthcare, whatever Dave's daughters maybe would be a young girl, preteen, maybe teen interested in, not sure which path, why tech, what would advice would you give? >>I think just understanding what you enjoy about life, right? Like which skills are you great at? What characteristics about roles and not really focusing on a specific product. Definitely not cybersecurity versus like the broader network. I mean, literally what do you enjoy doing? And then the roles of, you know, from the skillset that's needed, whether that be marketing, and then you can start to dive into, do I wanna support marketing for a corporate environment for retail, for technology like that will come and follow your passion, which I know is so easy to say, right? But if you're passionate about certain things, I love relationships. I think that holding myself from integrity standpoint, leading with integrity, but building strong relationships on trust, that's something I take really pride in and what I get enjoyment with. It's >>Obviously your superpower. >>It, >>It is. >>But >>Then it will go back to OST too, just being authentic in the process of building those relationships, being direct to the transparency of understanding, like again, knowing what you're good at and then where you can fit into an organization, awareness of technology opportunities, I think will all lend that to. But I also wouldn't worry, like when I was 17 year old, I, I thought I would be playing volleyball in college and then going to work for a professional sports team. You know, life works out very differently. Yeah. >>Right. And then, and for those of you out there, so I love that. Thank you for that great interview. Really appreciate letting us go far field for those of you might say, well, I don't know, man. I don't know what my passion is. I'll give you a line from my daughter, Alicia, you don't learn a lot for your kids. She said, well, if you don't know what your passion is, follow your curiosity. That's great. There you go. Amanda Adams. Thanks so much. It was great to have you on. Okay. Thank you. Keep it right there. We're back with George Kurtz. We're to the short break. Dave ante, Dave Nicholson. You watching the cube from Falcon 22 in Las Vegas.

>> Hey everyone, welcome to theCUBE's coverage of the AWS startup showcase. This is season two, episode three of our ongoing series featuring AWS and its big ecosystem of partners. This particular season is focused on MarTech, emerging cloud scale customer experiences. I'm your host, Lisa Martin, and I'm pleased to be joined by James Fang, the VP of product marketing at mparticle. James, welcome to the program. Great to have you on. >> Thanks for having me. >> Tell us a little bit about mparticle, what is it that you guys do? >> Sure, so we're mparticle, we were founded in 2013, and essentially we are a customer data platform. What we do is we help brands collect and organize their data. And their data could be coming from web apps, mobile apps, existing data sources like data warehouses, data lakes, et cetera. And we help them help them organize it in a way where they're able to activate that data, whether it's to analyze it further, to gather insights or to target them with relevant messaging, relevant offers. >> What were some of the gaps in the market back then as you mentioned 2013, or even now, that mparticle is really resolving so that customers can really maximize the value of their customer's data. >> Yeah. So the idea of data has actually been around for a while, and you may have heard the buzzword 360 degree view of the customer. The problem is no one has really been actually been able to, to achieve it. And it's actually, some of the leading analysts have called it a myth. Like it's a forever ending kind of cycle. But where we've kind of gone is, first of all customer expectations have really just inflated over the years, right? And part of that was accelerated due to COVID, and the transformation we saw in the last two years, right. Everyone used to, you know, have maybe a digital footprint, as complimentary perhaps to their physical footprint. Nowadays brands are thinking digital first, for obvious reasons. And the data landscape has gotten a lot more complex, right? Brands have multiple experiences, on different screens, right? And, but from the consumer perspective, they want a complete end to end experience, no matter how you're engaging with the brand. And in order to, for a brand to deliver that experience they have to know, how the customers interacted before in each of those channels, and be able to respond in as real time as possible, to those experiences. >> So I can start an interaction on my iPad, maybe carry it through or continue it on my laptop, go to my phone. And you're right, as a, as a consumer, I want the experience across all of those different media to be seamless, to be the same, to be relevant. You talk about the customer 360, as a marketer I know that term well. It's something that so many companies use, interesting that you point out that it's really been, largely until companies like mparticle, a myth. It's one of those things though, that everybody wants to achieve. Whether we're talking about healthcare organization, a retailer, to be able to know everything about a customer so that they can deliver what's increasingly demanded that personalized, relevant experience. How does mparticle fill some of the gaps that have been there in customer 360? And do you say, Hey, we actually deliver a customer 360. >> Yeah, absolutely. So, so the reason it's been a myth is for the most part, data has been- exists either in silos, or it's kind of locked behind this black box that the central data engineering team or sometimes traditionally referred to as IT, has control over, right? So brands are collecting all sorts of data. They have really smart people working on and analyzing it. You know, being able to run data science models, predictive models on it, but the, the marketers and the people who want to draw insights on it are asking how do I get it in, in my hands? So I can use that data for relevant targeting messaging. And that's exactly what mparticle does. We democratize access to that data, by making it accessible in the very tools that the actual business users are are working in. And we do that in real time, you don't have to wait for days to get access to data. And the marketers can even self-service, they're able to for example, build audiences or build computed insights, such as, you know, average order value of a customer within the tool themselves. The other main, the other main thing that mparticle does, is we ensure the quality of that data. We know that activation is only as as good, when you can trust that data, right? When there's no mismatching, you know, first name last names, identities that are duplicated. And so we put a lot of effort, not only in the identity resolution component of our product but also being able to ensure that the consistency of that data when it's being collected meets the standard that you need. >> So give us a, a picture, kind of a topology of a, of a customer data platform. And what are some of the key components that it contains, then I kind of want to get into some of the use cases. >> Yeah. So at, at a core, a lot of customer data platforms look similar. They're responsible first of all for the collection of data, right? And again, that could be from web mobile sources, as well as existing data sources, as well as third party apps, right? For example, you may have e-commerce data in a Shopify, right. Or you may have, you know, a computer model from a, from a warehouse. And then the next thing is to kind of organize it somehow, right? And the most common way to do that is to unify it, using identity resolution into this idea of customer profiles, right. So I can look up everything that Lisa or James has done, their whole historical record. And then the third thing is to be able to kind of be able to draw some insights from that, whether to be able to build an audience membership on top of that, build a predictive model, such as the churn risk model or lifetime value of that customer. And finally is being able to activate that data, so you'll be able to push that data again, to those relevant downstream systems where the business users are actually using that data to, to do their targeting, or to do more interesting things with it. >> So for example, if I go to the next Warrior's game, which I predict they're going to win, and I have like a mobile app of the stadium or the team, how, and I and I'm a season ticket holder, how can a customer data platform give me that personalized experience and help to, yeah, I'd love to kind of get it in that perspective. >> Yeah. So first of all, again, in this modern day and age consumers are engaging with brands from multiple devices, and their attention span, frankly, isn't that long. So I may start off my day, you know, downloading the official warriors app, right. And I may be, you know browsing from my mobile phone, but I could get distracted. I've got to go join a meeting at work, drop off my kids or whatever, right? But later in the day I had in my mind, I may be interested in purchasing tickets or buying that warriors Jersey. So I may return to the website, or even the physical store, right. If, if I happen to be in the area and what the customer data platform is doing in the background, is associating and connecting all those online and offline touchpoints, to that user profile. And then now, I have a mar- so let's say I'm a marker for the golden state warriors. And I see that, you know, this particular user has looked at my website even added to their cart, you know, warriors Jersey. I'm now able to say, Hey, here's a $5 promotional coupon. Also, here's a special, limited edition. We just won, you know, the, the Western conference finals. And you can pre-book, you know, the, you know the warriors championships Jersey, cross your fingers, and target that particular user with that promotion. And it's much more likely because we have that contextual data that that user's going to convert, than just blasting them on a Facebook or something like that. >> Right. Which all of us these days are getting less and less patient with, Is those, those broad blasts through social media and things like that. That was, I love that example. That was a great example. You talked about timing. One of the things I think that we've learned that's in very short supply, in the last couple of years is people's patience and tolerance. We now want things in nanoseconds. So, the ability to glean insights from data and act on it in real time is no longer really a nice to have that's really table stakes for any type of organization. Talk to us about how mparticle facilitates that real time data, from an insights perspective and from an activation standpoint. >> Yeah. You bring up a good point. And this is actually one of the core differentiators of mparticle compared to the other CDPs is that, our architecture from the ground up is built for real time. And the way we do that is, we use essentially a real time streaming architecture backend. Essentially all the data points that we collect and send to those downstream destinations, that happens in milliseconds, right? So the moment that that user, again, like clicks a button or adds something to their shopping cart, or even abandons that shopping cart, that downstream tool, whether it's a marketer, whether it's a business analyst looking at that data for intelligence, they get that data within milliseconds. And our audience computations also happens within seconds. So again, if you're, if you have a targeted list for a targeted campaign, those updates happen in real time. >> You gave an- you ran with the Warrior's example that I threw at you, which I love, absolutely. Talk to me. You must have though, a favorite cu- real world customer example of mparticle's that you think really articulates the value to organizations, whether it's to marketers operators and has some nice, tangible business outcomes. Share with me if you will, a favorite customer story. >> Yeah, definitely one of mine and probably one of the- our most well known's is we were actually behind the scenes of the Whopper jr campaign. So a couple of years ago, Burger King ran this really creative ad where the, effectively their goal was to get their mobile app out, as well as to train, you know, all of us back before COVID days, how to order on our mobile devices and to do things like curbside checkout. None of us really knew how to do that, right. And there was a challenge of course that, no one wants to download another app, right? And most apps get downloaded and get deleted right out away. So they ran this really creative promotion where, if you drove towards a McDonald's, they would actually fire off a text message saying, Hey, how about a Whopper for 99 cents instead? And you would, you would, you would receive a text message personalized just for you. And you'd be able to redeem that at any burger king location. So we were kind of the core infrastructure plumbing the geofencing location data, to partner of ours called radar, which handles you geofencing, and then send it back to a marketing orchestration vendor to be able to fire that targeted message. >> Very cool. I, I, now I'm hungry. You, but there's a fine line there between knowing that, okay, Lisa's driving towards McDonald's let's, you know, target her with an ad for a whopper, in privacy. How do you guys help organizations in any industry balance that? Cause we're seeing more and more privacy regulations popping up all over the world, trying to give consumers the ability to protect either the right to forget about me or don't use my data. >> Yeah. Great question. So the first way I want to respond to that is, mparticle's really at the core of helping brands build their own first party data foundation. And what we mean by that is traditionally, the way that brands have approached marketing is reliant very heavily on second and third party data, right? And most that second-third party data is from the large walled gardens, such as like a Facebook or a TikTok or a Snapchat, right? They're they're literally just saying, Hey find someone that is going to, you know fit our target profile. And that data is from people, all their activity on those apps. But with the first party data strategy, because the brand owns that data, we- we can guarantee that or the brands can guarantee to their customers it's ethically sourced, meaning it's from their consent. And we also help brands have governance policies. So for example, if the user has said, Hey you're allowed to collect my data, because obviously you want to run your business better, but I don't want any my information sold, right? That's something that California recently passed, with CPRA. Then brands can use mparticle data privacy controls to say, Hey, you can pass this data on to their warehouses and analytics platforms, but don't pass it to a platform like Facebook, which potentially could resell that data. >> Got it, Okay. So you really help put sort of the, the reigns on and allow those customers to make those decisions, which I know the mass community appreciates. I do want to talk about data quality. You talked about that a little bit, you know, and and data is the lifeblood of an organization, if it can really extract value from it and act on it. But how do you help organizations maintain the quality of data so that what they can do, is actually deliver what the end user customer, whether it's a somebody buying something on a, on a eCommerce site or or, a patient at a hospital, get what they need. >> Yeah. So on the data quality front, first of all I want to highlight kind of our strengths and differentiation in identity resolution. So we, we run a completely deterministic algorithm, but it's actually fully customizable by the customer depending on their needs. So for a lot of other customer data providers, platform providers out there, they do offer identity resolution, but it's almost like a black box. You don't know what happens. And they could be doing a lot of fuzzy matching, right. Which is, you know, probabilistic or predictive. And the problem with that is, let's say, you know, Lisa your email changed over the years and CDP platform may match you with someone that's completely not you. And now all of a sudden you're getting ads that completely don't fit you, or worse yet that brand is violating privacy laws, because your personal data is is being used to target another user, which which obviously should not, should not happen, right? So because we're giving our customers complete control, it's not a black box, it's transparent. And they have the ability to customize it, such as they can specify what identifiers matter more to them, whether they want to match on email address first. They might've drawn on a more high confidence identifier like a, a hash credit card number or even a customer ID. They have that choice. The second part about ensuring data quality is we act actually built in schema management. So as those events are being collected you could say that, for example, when when it's a add to cart event, I require the item color. I require the size. Let's say it's a fashion apparel. I require the size of it and the type of apparel, right? And if, if data comes in with missing fields, or perhaps with fields that don't match the expectation, let's say you're expecting small, medium, large and you get a Q, you know Q is meaningless data, right? We can then enforce that and flag that as a data quality violation and brands can complete correct that mistake to make sure again, all the data that's flowing through is, is of value to them. >> That's the most important part is, is to make sure that the data has value to the organization, and of course value to whoever it is on the other side, the, the end user side. Where should customers start, in terms of working with you guys, do you recommend customers buy an all in one marketing suite? The best, you know, build a tech stack of best of breed? What are some of those things that you recommend for folks who are going, all right, We, maybe we have a CDP it's been under delivering. We can't really deliver that customer 360, mparticle, help us out. >> Yeah, absolutely. Well, the best part about mparticle is you can kind of deploy it in phases, right. So if you're coming from a world where you've deployed a, all in one marketing suite, like a sales force in Adobe, but you're looking to maybe modernize pieces of a platform mparticle can absolutely help with that initial step. So let again, let's say all you want to do is modernize your event collection. Well, we can absolutely, as a first step, for example, you can instrument us. You can collect all your data from your web and mobile apps in real time, and we can pipe to your existing, you know Adobe campaign manager, Salesforce, marketing cloud. And later down the line, let's say, you say I want to, you know, modernize my analytics platform. I'm tired of using Adobe analytics. You can swap that out, right again with an mparticle place, a marketer can or essentially any business user can flip the switch. And within the mparticle interface, simply disconnect their existing tool and connect a new tool with a couple of button clicks and bam, the data's now flowing into the new tool. So it mparticle really, because we kind of sit in the middle of all these tools and we have over 300 productized prebuilt integrations allows you to move away from kind of a locked in, you know a strategy where you're committed to a vendor a hundred percent to more of a best of breed, agile strategy. >> And where can customers that are interested, go what's your good and market strategy? How does that involve AWS? Where can folks go and actually get and test out this technology? >> Yeah. So first of all, we are we are AWS, a preferred partner. and we have a couple of productized integrations with AWS. The most obvious one is for example, being able to just export data to AWS, whether it's Redshift or an S3 or a kinesis stream, but we also have productized integrations with AWS, personalized. For example, you can take events, feed em to personalize and personalize will come up with the next best kind of content recommendation or the next best offer available for the customer. And mparticle can ingest that data back and you can use that for personalized targeting. In fact, Amazon personalize is what amazon.com themselves use to populate the recommended for use section on their page. So brands could essentially do the same. They could have a recommended for you carousel using Amazon technology but using mparticle to move the data back and forth to, to populate that. And then on top of that very, very soon we'll be also launching a marketplace kind of entry. So if you are a AWS customer and you have credits left over or you just want to transact through AWS, then you'll have that option available as well. >> Coming soon to the AWS marketplace. James, thank you so much for joining me talking about mparticle, how you guys are really revolutionizing the customer data platform and allowing organizations and many industries to really extract value from customer data and use it wisely. We appreciate your insights and your time. >> Thank you very much, Lisa >> For James Fang, I'm Lisa Martin. You're watching theCube's coverage of the AWS startup showcase season three, season two episode three, leave it right here for more great coverage on theCube, the leader in live tech coverage.

(upbeat music) >> Despite its 70 to $80 billion total available market, computer storage is like a small town, everybody knows everybody else. We say in the storage world, there are a hundred people, and 99 seats. Infinidat is a company that was founded in 2011 by storage legend, Moshe Yanai. The company is known for building products with rock solid availability, simplicity, and a passion for white glove service, and client satisfaction. Company went through a leadership change recently, in early this year, appointed industry vet, Phil Bullinger, as CEO. It's making more moves, bringing on longtime storage sales exec, Richard Bradbury, to run EMEA, and APJ Go-To-Market. And just recently appointed marketing maven, Eric Hertzog to be CMO. Hertzog has worked at numerous companies, ranging from startups that were acquired, two stints at IBM, and is SVP of product marketing and management at Storage Powerhouse, EMC, among others. Hertzog has been named CMO of the year as an OnCon Icon, and top 100 influencer in big data, AI, and also hybrid cloud, along with yours truly, if I may say so. Joining me today, is the newly minted CMO of Infinidat, Mr.Eric Hertzog. Good to see you, Eric, thanks for coming on. >> Dave, thank you very much. You know, we love being on theCUBE, and I am of course sporting my Infinidat logo wear already, even though I've only been on the job for two weeks. >> Dude, no Hawaiian shirt, okay. That's a pretty buttoned up company. >> Well, next time, I'll have a Hawaiian shirt, don't worry. >> Okay, so give us the backstory, how did this all come about? you know Phil, my 99 seat joke, but, how did it come about? Tell us that story. >> So, I have known Phil since the late 90s, when he was a VP at LSA of Engineering, and he had... I was working at a company called Milax, which was acquired by IBM. And we were doing a product for HP, and he was providing the subsystem, and we were providing the fiber to fiber, and fiber to SCSI array controllers back in the day. So I met him then, we kept in touch for years. And then when I was a senior VP at EMC, he started originally as VP of engineering for the EMC Isilon team. And then he became the general manager. So, while I didn't work for him, I worked with him, A, at LSA, and then again at EMC. So I just happened to congratulate him about some award he won, and he said "Hey Herzog, "we should talk, I have a CMO opening". So literally happened over LinkedIn discussion, where I reached out to him, and congratulate him, he said "Hey, I need a CMO, let's talk". So, the whole thing took about three weeks in all honesty. And that included interviewing with other members of his exec staff. >> That's awesome, that's right, he was running the Isilon division for awhile at the EMC. >> Right. >> You guys were there, and of course, you talk about Milax, LSA, there was a period of time where, you guys were making subsystems for everybody. So, you sort of saw the whole landscape. So, you got some serious storage history and chops. So, I want to ask you what attracted you to Infinidat. I mean, obviously they're a leader in the magic quadrant. We know about InfiniBox, and the petabyte scale, and the low latency, what are the... When you look at the market, you obviously you see it, you talk to everybody. What were the trends that were driving your decision to join Infinidat? >> Well, a couple of things. First of all, as you know, and you guys have talked about it on theCUBE, most CIOs don't know anything about storage, other than they know a guy got to spend money on it. So the Infinidat message of optimizing applications, workloads, and use cases with 100% guaranteed availability, unmatched reliability, the set and forget ease of use, which obviously AIOps is driving that, and overall IT operations management was very attractive. And then on top of that, the reality is, when you do that consolidation, which Infinidat can do, because of the performance that it has, you can dramatically free up rack, stack, power, floor, and operational manpower by literally getting rid of, tons and tons of arrays. There's one customer that they have, you actually... I found out when I got here, they took out a hundred arrays from EMC Hitachi. And that company now has 20 InfiniBoxes, and InfiniBox SSAs running the exact same workloads that used to be, well over a hundred subsystems from the other players. So, that's got a performance angle, a CapEx and OPEX angle, and then even a clean energy angle because reducing Watson slots. So, lots of different advantages there. And then I think from just a pure marketing perspective, as someone has said, they're the best kept secret to the storage industry. And so you need to, if you will, amp up the message, get it out. They've expanded the portfolio with the InfiniBox SSA, the InfiniGuard product, which is really optimized, not only as the PBA for backup perspective, and it works with all the backup vendors, but also, has an incredible play on data and cyber resilience with their capability of local logical air gapping, remote logical air gapping, and creating a clean room, if you will, a vault, so that you can then recover their review for malware ransomware before you do a full recovery. So it's got the right solutions, just that most people didn't know who they were. So, between the relationship with Phil, and the real opportunity that this company could skyrocket. In fact, we have 35 job openings right now, right now. >> Wow, okay, so yeah, I think it was Duplessy called them the best kept secret, he's not the only one. And so that brings us to you, and your mission because it's true, it is the best kept secret. You're a leader in the Gartner magic quadrant, but I mean, if you're not a leader in a Gartner magic quadrant, you're kind of nobody in storage. And so, but you got chops and block storage. You talked about the consolidation story, and I've talked to many folks in Infinidat about that. Ken Steinhardt rest his soul, Dr. Rico, good business friend, about, you know... So, that play and how you handle the whole blast radius. And that's always a great discussion, and Infinidat has proven that it can operate at very very high performance, low latency, petabyte scale. So how do you get the word out? What's your mission? >> Well, so we're going to do a couple of things. We're going to be very, very tied to the channel as you know, EMC, Dell EMC, and these are articles that have been in CRN, and other channel publications is pulling back from the channel, letting go of channel managers, and there's been a lot of conflict. So, we're going to embrace the channel. We already do well over 90% of our business within general globally. So, we're doing that. In fact, I am meeting, personally, next week with five different CEOs of channel partners. Of which, only one of them is doing business with Infinidat now. So, we want to expand our channel, and leverage the channel, take advantage of these changes in the channel. We are going to be increasing our presence in the public relations area. The work we do with all the industry analysts, not just in North America, but in Europe as well, and Asia. We're going to amp up, of course, our social media effort, both of us, of course, having been named some of the best social media guys in the world the last couple of years. So, we're going to open that up. And then, obviously, increase our demand generation activities as well. So, we're going to make sure that we leverage what we do, and deliver that message to the world. Deliver it to the partner base, so the partners can take advantage, and make good margin and revenue, but delivering products that really meet the needs of the customers while saving them dramatically on CapEx and OPEX. So, the partner wins, and the end user wins. And that's the best scenario you can do when you're leveraging the channel to help you grow your business. >> So you're not only just the marketing guy, I mean, you know product, you ran product management at very senior levels. So, you could... You're like a walking spec sheet, John Farrier says you could just rattle it off. Already impressed that how much you know about Infinidat, but when you joined EMC, it was almost like, there was too many products, right? When you joined IBM, even though it had a big portfolio, it's like it didn't have enough relevant products. And you had to sort of deal with that. How do you feel about the product portfolio at Infinidat? >> Well, for us, it's right in the perfect niche. Enterprise class, AI based software defined storage technologies that happens run on a hybrid array, an all flash array, has a variant that's really tuned towards modern data protection, including data and cyber resilience. So, with those three elements of the portfolio, which by the way, all have a common architecture. So while there are three different solutions, all common architecture. So if you know how to use the InfiniBox, you can easily use an InfiniGuard. You got an InfiniGuard, you can easily use an InfiniBox SSA. So the capability of doing that, helps reduce operational manpower and hence, of course, OPEX. So the story is strong technically, the story has a strong business tie in. So part of the thing you have to do in marketing these days. Yeah, we both been around. So you could just talk about IOPS, and latency, and bandwidth. And if the people didn't... If the CIO didn't know what that meant, so what? But the world has changed on the expenditure of infrastructure. If you don't have seamless integration with hybrid cloud, virtual environments and containers, which Infinidat can do all that, then you're not relevant from a CIO perspective. And obviously with many workloads moving to the cloud, you've got to have this infrastructure that supports core edge and cloud, the virtualization layer, and of course, the container layer across a hybrid environment. And we can do that with all three of these solutions. Yet, with a common underlying software defined storage architecture. So it makes the technical story very powerful. Then you turn that into business benefit, CapEX, OPEX, the operational manpower, unmatched availability, which is obviously a big deal these days, unmatched performance, everybody wants their SAP workload or their Oracle or Mongo Cassandra to be, instantaneous from the app perspective. Excuse me. And we can do that. And that's the kind of thing that... My job is to translate that from that technical value into the business value, that can be appreciated by the CIO, by the CSO, by the VP of software development, who then says to VP of industry, that Infinidat stuff, we actually need that for our SAP workload, or wow, for our overall corporate cybersecurity strategy, the CSO says, the key element of the storage part of that overall corporate cybersecurity strategy are those Infinidat guys with their great cyber and data resilience. And that's the kind of thing that my job, and my team's job to work on to get the market to understand and appreciate that business value that the underlying technology delivers. >> So the other thing, the interesting thing about Infinidat. This was always a source of spirited discussions over the years with business friends from Infinidat was the company figured out a way, it was formed in 2011, and at the time the strategy perfectly reasonable to say, okay, let's build a better box. And the way they approached that from a cost standpoint was you were able to get the most out of spinning disk. Everybody else was moving to flash, of course, floyers work a big flash, all flash data center, etc, etc. But Infinidat with its memory cache and its architecture, and its algorithms was able to figure out how to magically get equivalent or better performance in an all flash array out of a system that had a lot of spinning disks, which is I think unique. I mean, I know it's unique, very rare anyway. And so that was kind of interesting, but at the time it made sense, to go after a big market with a better mouse trap. Now, if I were starting a company today, I might take a different approach, I might try to build, a storage cloud or something like that. Or if I had a huge install base that I was trying to protect, and maybe go into that. But so what's the strategy? You still got huge share gain potentials for on-prem is that the vector? You mentioned hybrid cloud, what's the cloud strategy? Maybe you could summarize your thoughts on that? >> Sure, so the cloud strategy, is first of all, seamless integration to hybrid cloud environments. For example, we support Outpost as an example. Second thing, you'd be surprised at the number of cloud providers that actually use us as their backend, either for their primary storage, or for their secondary storage. So, we've got some of the largest hyperscalers in the world. For example, one of the Telcos has 150 Infiniboxes, InfiniBox SSAS and InfiniGuards. 150 running one of the largest Telcos on the planet. And a huge percentage of that is their corporate cloud effort where they're going in and saying, don't use Amazon or Azure, why don't you use us the giant Telco? So we've got that angle. We've got a ton of mid-sized cloud providers all over the world that their backup is our servers, or their primary storage that they offer is built on top of Infiniboxes or InfiniBox SSA. So, the cloud strategy is one to arm the hyperscalers, both big, medium, and small with what they need to provide the right end user services with the right outside SLAs. And the second thing is to have that hybrid cloud integration capability. For example, when I talked about InfiniGuard, we can do air gapping locally to give almost instantaneous recovery, but at the same time, if there's an earthquake in California or a tornado in Kansas City, or a tsunami in Singapore, you've got to have that remote air gapping capability, which InfiniGuard can do. Which of course, is essentially that logical air gap remote is basically a cloud strategy. So, we can do all of that. That's why it has a cloud strategy play. And again we have a number of public references in the cloud, US signal and others, where they talk about why they use the InfiniBox, and our technologies to offer their storage cloud services based on our platform. >> Okay, so I got to ask you, so you've mentioned earthquakes, a lot of earthquakes in California, dangerous place to live, US headquarters is in Waltham, we're going to pry you out of the Golden State? >> Let's see, I was born at Stanford hospital where my parents met when they were going there. I've never lived anywhere, but here. And of course, remember when I was working for EMC, I flew out every week, and I sort of lived at that Milford Courtyard Marriott. So I'll be out a lot, but I will not be moving, I'm a Silicon Valley guy, just like that old book, the Silicon Valley Guy from the old days, that's me. >> Yeah, the hotels in Waltham are a little better, but... So, what's your priority? Last question. What's the priority first 100 days? Where's your focus? >> Number one priority is team assessment and integration of the team across the other teams. One of the things I noticed about Infinidat, which is a little unusual, is there sometimes are silos and having done seven other small companies and startups, in a startup or a small company, you usually don't see that silo-ness, So we have to break down those walls. And by the way, we've been incredibly successful, even with the silos, imagine if everybody realized that business is a team sport. And so, we're going to do that, and do heavy levels of integration. We've already started to do an incredible outreach program to the press and to partners. We won a couple awards recently, we're up for two more awards in Europe, the SDC Awards, and one of the channel publications is going to give us an award next week. So yeah, we're amping up that sort of thing that we can leverage and extend. Both in the short term, but also, of course, across a longer term strategy. So, those are the things we're going to do first, and yeah, we're going to be rolling into, of course, 2022. So we've got a lot of work we're doing, as I mentioned, I'm meeting, five partners, CEOs, and only one of them is doing business with us now. So we want to get those partners to kick off January with us presenting at their sales kickoff, going "We are going with Infinidat "as one of our strong storage providers". So, we're doing all that upfront work in the first 100 days, so we can kick off Q1 with a real bang. >> Love the channel story, and you're a good guy to do that. And you mentioned the silos, correct me if I'm wrong, but Infinidat does a lot of business in overseas. A lot of business in Europe, obviously the affinity to the engineering, a lot of the engineering work that's going on in Israel, but that's by its very nature, stovepipe. Most startups start in the US, big market NFL cities, and then sort of go overseas. It's almost like Infinidat sort of simultaneously grew it's overseas business, and it's US business. >> Well, and we've got customers everywhere. We've got them in South Africa, all over Europe, Middle East. We have six very large customers in India, and a number of large customers in Japan. So we have a sales team all over the world. As you mentioned, our white glove service includes not only our field systems engineers, but we have a professional services group. We've actually written custom software for several customers. In fact, I was on the forecast meeting earlier today, and one of the comments that was made for someone who's going to give us a PO. So, the sales guy was saying, part of the reason we're getting the PO is we did some professional services work last quarter, and the CIO called and said, I can't believe it. And what CIO calls up a storage company these days, but the CIO called him and said "I can't believe the work you did. We're going to buy some more stuff this quarter". So that white glove service, our technical account managers to go along with the field sales SEs and this professional service is pretty unusual in a small company to have that level of, as you mentioned yourself, white glove service, when the company is so small. And that's been a real hidden gem for this company, and will continue to be so. >> Well, Eric, congratulations on the appointment, the new role, excited to see what you do, and how you craft the story, the strategy. And we've been following Infinidat since, sort of day zero and I really wish you the best. >> Great, well, thank you very much. Always appreciate theCUBE. And trust me, Dave, next time I will have my famous Hawaiian shirt. >> Ah, I can't wait. All right, thanks to Eric, and thank you for watching everybody. This is Dave Vellante for theCUBE, and we'll see you next time. (bright upbeat music)

from around the globe it's thecube with coverage of kubecon and cloudnativecon north america 2020 virtual brought to you by red hat the cloud native computing foundation and ecosystem partners hey welcome back everybody jeff frick here with thecube coming to you from our palo alto studios with our ongoing coverage of kubecon cloud nativecon north america 2020 virtual it's virtual like everything else that we're doing in 2020 we're really excited by our next guest we're going to dive into a company that you probably know a little bit on the surface but probably don't know a lot of the stuff that's going on behind the surface so we're really excited to have our next guest he is jai chakrabarti he is the director of engineering for core infrastructure at spotify jai great to see you great to be here with you today so as a as a long-standing uh spotify fan and and customer and premium customer and family playing customer just so there's no question i'm a big fan the infrastructure to deliver what i want to hear basically any sound any song from the entire world it seems like i don't know what the actual uh percentage of every published song you guys have you know kind of at my fingertips searchable available now to listen to is an amazing accomplishment i can't imagine how big and significant and complicated the infrastructure you guys must be managing and and not only that but kind of the meteoric growth over the last several years so first off just talk a little bit about spotify scale how you guys think about it is there some things that you can share to help people really understand you know some of the some of the big iron that's behind giving me the songs i want to hear absolutely and thank you for the opportunity to let me talk about this so it's a as you say it's a pretty mammoth project to be able to deliver just about any song that's in the world or now any podcast that you might want to listen to to hundreds of millions of fans and also enable creators to be able to share their content with the consumers who are interested in consuming that content so some of the metrics that go behind us are we have thousands of microservices running in production we were one of the early adopters of microservices at scale and continued to build on that foundation with early entrants to dockerize services and now of course largely on kubernetes we also have thousands of data pipelines hundreds of uh websites as well as micro app features and we're doing about 20 000 deployments a day to give you kind of a scale of how fast things are changing and for us speed is a great virtue as we're testing out features doing ab tests and trying to roll out the next best thing for the audio network it's amazing and i'm and i'm curious in terms of execution on the business side i mean clearly you're in many many countries you know you're global are all the licensing agreements for the music different by country are you just like super micromanaging um you know kind of the the revenue streams and the licensing by geo or is is that just as complex as it feels like it might be or is there some some simplicity or some scale that you can bring to uh to bring a little bit of of clarification there yeah so that is an area of complexity as well um so you know licensing across the broad set of content that we have as well as the number of publishers and creators that we have to make sure that everything is well accounted for is also kind of a source of complexity in our organizational makeup and then and then the the piece that i don't think a lot of people know is you guys are huge consumers and contributors back to open source and clearly we're here at q con cloud native con you've talked already about kubernetes and containers but i wonder before we get into some of the specifics if you can talk about philosophically the role of open source and why you know you guys are such a big open source company versus kind of back in the old days when you would have a lot of proprietary technology that you would try to develop and keep in-house as part of the as part of the secret sauce yeah thank you for that question so philosophically we are big proponents of open source we believe in giving back to the community we believe that when we as a community come together to solve these problems at scale the end result is much better than if we were to try it alone if any one company were to try it alone so some of the projects that we've contributed or invested a lot of time in are envoy for example which we use to power our perimeter at spotify or kubernetes which we use for deployment purposes as many companies do but there are also a number of other open source projects that we're committing to so for example with cloud bigtable we have produced an auto scaler that's now fairly widely used to be able to manage costs better with cloud bigtable we've also invested in a open source time series database called heroic to manage millions of data points for a metrics platform and scales so those are just a few examples but philosophically we believe this isn't something that we want to do alone and we want to leverage and do this together with the community right another one that you didn't mention there but you've talked about i want to dig into is backstage and as you mentioned you have a lot of developer teams working on a lot of projects like i saw a statistic maybe in github of the number of of github projects you guys are working on it's a it's a lot so what is backstage all about give us the story there yeah so at spotify we have almost somewhere around 500 engineering teams and so you can think about backstage as kind of like a central nervous system to be able to help engineers interface across the wide landscape that is spotify's engineering ecosystems so if you're an engineer you can go into backstage and you can manage your services your data pipelines your micro features you can see what other teams are doing what the organizational structure is you can get recommendations and insights on your tech health so you can see where you might need to invest more time and get some recommendations on how to get back to the blessed stock so it's really a one-stop developer portal that engineers spend the bulk of their time in today we open sourced it uh earlier this year and we've been absolutely thrilled with the response we've gotten thus far a number of companies have already started using it and contributing back so we've seen you know a lot of contributions coming back to backstage which is of course one of the ideas to be able to get some of the great ideas uh on backstage so we're really excited about that and specifically within backstage something that my team has just released into the open is a product called cost insights so one of the problems that we were dealing with at spotify is how do we sustainably look at cloud costs but do it in a way that isn't like a compliance exercise isn't a focus on traditional top top down cost controls but really taps into developers innate desire to work on optimization because all of us who come from an engineering background know that optimization is fun at the same time premature optimization is the root of all evil as the saying goes and so what we've done within our cost insights product and backstage is really try to find a good balance between engineering love for optimization and letting people know what are the areas where cloud spend really matters so if making an investment here isn't going to move the needle for us we let people know that this isn't worth your time to worry about so let me unpack you touch on a couple things first off you talked about it gives you an assessment of your engineering health so does that mean that it's kind of uh compliance within a standard is that looking for i guess not quite red flags yet but yellow flags of things that that are known potential issues down the road is it you know tapping into maybe higher cost services or microservices versus less that maybe there's a less expensive way so so how do you define health and how do you you know keep track of people getting away from health and then you know steering them back to being more healthy yeah that's a great question so we have this concept at spotify called golden state which is a reflection of how far away are you from all of the blessed frameworks libraries that we recommend to engineers and the way we think about golden state is there ought to be clear value adds to going to a new service a new library version and so the way we try to express it is unless of course there's a kind of a direct security concern and there aren't really too many ways to get around that but we really tried to preserve engineering autonomy and say if you go to this new framework for example you're going to save this much time on average so the recommendations that you'll find there are going to be highly specific so for example if you adopt uh you know an auto scaler for bigtable you're going to save this much time and spend this much less that's in general how we phrase these things okay and then on the cost insights i mean clearly when a dev is working on a new feature or new uh you know experimenting maybe with a bunch of new features and you're you're setting up multiple a b testing this and that are they are they not really working worrying about cost at the front end of that or is really kind of the cost optimization and you mentioned you know don't optimize too early does that come kind of after the fact and after you've you know moved some new things into production they have potential and now we do maybe a second order kind of analysis of the appropriateness of that feature because i imagine if they're just if you're just trying to come up with new features and exploring and trying new things not really worrying about the you're not worrying about the cloud bill right you're just trying to get some feature functionality and make sure you don't have too many bugs and make sure you're going to get some good client value and some new customer experience yeah yeah no and and we agree with that perspective so we think about the world in terms of startup scale-ups and mature businesses at spotify so there are a lot of teams who are experimenting with new ideas that fall into the startup category and by and large they are not going to be worrying about costs that being said we as infrastructure teams have the notice on us to think about how do we provide shared services and frameworks that abstract away a lot of these questions around how do you properly manage your costs right so that that is on us as infrastructure teams but really our perspective is for startups to move as quickly as they can and really if that's an idea that's viable and you get to what we call the scale-up stage or you get to the mature business stage where it really is a core part of our business then that's where you know you might start to get some nudges or recommendations and cost insights so interesting so i'd love to you know your background you came from financial services and trading where clearly speed matters accuracy matters you know that that's i mean basically financial services is is a software game at this stage of the game and it's a speed game and i saw another interesting uh video getting ready for this i think it was with gustav soderstrom talking about the competitive advantage of the early days really being speed and speed to return a result and speed to start that stream and it just struck me very much like you know the early days of google which was that was their whole speed thing and they even told you how fast you got a return on your search when you're thinking about optimizing now with the huge suite of features and functionalities that you have how do you think about speed is it still speed number one how is kind of the priority changed and what are some of the design priorities that when things go from experiment to start to be into the scale realm and hopefully be successful in production that that need to be thought about and potentially rank ordered um in in the proper way yeah yeah that's it's a great question and so you know i'll just refer to daniel x quote around this which is we aim to fail faster than anyone else and so for us as a company and with our growth trajectory and investing in the areas that we are looking to invest into it's still absolutely critical that we move fast that we get the ideas of the startup phase out to be vetted and validated if we can go to the next phase to the scale-up phase so i see that just as important today if not more than when i first joined spotify uh you know over four years ago at this point and regarding financial services um there are certainly you know touch points in terms of the amount of data that we're processing and the scale of technology that it requires to process that kind of data but one of the things that i really love about spotify of course is that we get to move fast which is sometimes of course going to be a lot more difficult when you're talking about the financial service arena and various uh compliance bodies that are overseeing any changes that you might make yeah you guys are you guys were running a little bit ahead of the regs i think which is pretty typical uh in the music business napster was running a little bit ahead of the regs and you know then we saw the evolution with the itunes and then you know you guys really really nailing the streaming service really for the first time and and opening up this new con consumption bottle and i wonder if you could talk about you know kind of keeping the customer experience first and making sure that that's a positive thing i can't help but think of of the netflix experience where they spend so much time on people's interaction with the application to to get them to try new things a recommendation engine such an important piece of the of the puzzle and i think what you guys have really nailed is the discovery piece because it's one thing to be able to quickly access a favorite song and be able to listen to it but everyone loves discovery right and discovery is kind of an interesting and interesting process and you guys have taken a really scientific approach in terms of cataloging music and and different attributes of music and then using those to help drive the recommendation engine i wonder if you can share you know kind of your thoughts in terms of being you know kind of ultimately driven by the customer experience and their interaction with the application and these things called you know music or podcast which is such a such a a a very personal thing to interact with yeah so from the perspective of core infrastructure you know it's spotify our goal is to really enable the scale in which we are processing the amount of audio content that goes through our system and so podcast of course is a new category that wasn't there when i originally joined spotify but it's really to provide a platform so these experiments can be done seamlessly so we can have different ways of looking at discovery looking at user segmentation and being able to come up with new ways that are going to be compelling to our customers so that's very exciting and fulfilling for us to be able to provide that platform by which our sister teams can iterate very quickly knowing that they have the guard rails uh which you know in our on-premise days at times was a struggle and where we're in a very different place now yeah so last question before i let you go we're at cubecon cloudnativecon um and and it's just an interesting thing that i always think about when you're managing engineering teams that are heavily open source participants and you know it's such a big piece now of of a lot of engineers motivation to be active participants in open source and to and to show their work to others outside the company but at the same time they have to get company work done so i just wonder if you could share your perspective of how do you manage open source contributions how do you keep them you know working on company projects but also make sure you allocate time and priorities to open source contributions because that is a really important piece of the motivation for a lot of engineers it's not just working for the company and getting paid at the india at the end of every two weeks yeah it's a key motivation as you say and it's key to our recruiting strategy and also how we think about retaining engineers and spotify so there are different mechanisms that we use and there's a lot of focus that's modified on coming up with development plans for engineers that actually make sense um so you know i would say that all the way from the oft quoted 20 time is something that you might hear at spotify where you have engineers who are working on open source 20 of the time or you might see a variety of customized customized options depending on who the engineer is where they want to grow and really i think the key here is providing the right support structures so even if you have the time are you getting the mentorship are you getting the right kind of support system so you know how to connect with the community and so you have other like-minded people who are bouncing ideas and you don't feel like you're doing it yourself so that's something that i feel really excited about that we've grown those support structures over the last few years eyes have also been very intentional about giving engineers time to work on open source and you give them as much as 20 i'd never heard that before yeah in some cases some i mean if that is what where an engineer really wants to focus and grow there are a number of folks at spotify who are spending up to 20 of their time on open source wow that's amazing that that is a uh that's a it's just it's such a great commitment for the company to the engineer if that's their priority and then everyone's going to benefit from it both the engineer the company as well as the community so really a forward-looking you know point of view to take that long-term view versus the you know maybe we should only give them 10 we're losing 10 of their time working on a project so that is super super progressive and i'm sure you must be seeing great roi on it or you wouldn't continue to be such huge proponents of open source and such huge contributors back so that's that's a great story yeah terrific i mean you know we we want those contributions to be in line with where we're growing as a company and we see a lot of opportunities uh where that is happening so like envoy or kubernetes um just to name a couple of examples where folks have devoted time in those areas well thanks for uh thanks for sharing some of the the story behind the scenes you know again household name what what a tremendous success story and and and uh you know i'm a movie customer so i'm definitely a customer though no no doubt about it so uh thank you for your contributions congrats to the team and uh and really loved the story of how you guys are contributing back and and doing a lot more than just making great music available to us all and a great channel for uh for creators to get their stuff out there so thanks again thanks so much for your time i really appreciate it all right he's jai i'm jeff you're watching the cube's continuing coverage of kubecon cloud nativecon north america 2020 thanks for watching we'll see you next [Music] time you

>> Announcer: From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCUBE conversation. >> Hey, welcome back everybody Jeff Frick here with the cube. This is a special week it's Grace Hopper week, and Grace Hopper is the best name in tech conferences. The celebration of women in computing, and we've been going there for years we're not there this year, but one of the themes that comes up over and over at Grace Hopper is women and girls need to see women in positions that they can envision themselves being in someday. That is a really important piece of the whole diversity conversation is can I see people that I can role model after and I just want to bring up something from a couple years back from 2016 when we were there, we were there with Mimi Valdez, Christina Deoja and Dr. Jeanette Epps, Dr. Jeanette Epps is the astronaut on the right. They were there talking about "The Hidden Figures" movie. If you remember it came out 2016, it was about Katherine Johnson and all the black women working at NASA. They got no credit for doing all the math that basically keep all the astronauts safe and they made a terrific movie about it. And Janet is going up on the very first Blue Origin Space Mission Next year. This was announced a couple of months ago, so again, phenomenal leadership, black lady astronaut, going to go into space and really provide a face for a lot of young girls that want to get into that and its clearly a great STEM opportunity. So we're excited to have four terrific women today that well also are the leaders that the younger women can look up to and follow their career. So we're excited to have them so we're just going to go around. We got four terrific guests, our first one is Annabel Chang, She is the Head of State Policy and Government Regulations at Waymo. Annabel great to see you, where are you coming in from today? >> from San Francisco >> Jeff: Awesome. Next up is Inamarie Johnson. She is the Chief People and Diversity Officer for Zendesk Inamarie, great to see you. Where are you calling in from today? >> Great to be here. I am calling in from Palos Verdes the state >> Jeff: awesome >> in Southern California. >> Jeff: Some of the benefits of a virtual sometimes we can, we couldn't do that without the power of the internet. And next up is Jennifer Cabalquinto she is the Chief Financial Officer of the Golden State Warriors. Jennifer, great to see you Where are you coming in from today? >> Well, I wish I was coming in from the Chase Center in San Francisco but I'm actually calling in from Santa Cruz California today. >> Jeff: Right, It's good to see you and you can surf a lot better down there. So that's probably not all bad. And finally to round out our panelists, Kate Hogan, she is the COO of North America for Accenture. Kate, great to see you as well. Where are you coming in from today? >> Well, it's good to see you too. I am coming in from the office actually in San Jose. >> Jeff: From the office in San Jose. All right, So let's get into it . You guys are all very senior, you've been doing this for a long time. We're in a kind of a crazy period of time in terms of diversity with all the kind of social unrest that's happening. So let's talk about some of your first your journeys and I want to start with you Annabel. You're a lawyer you got into lawyering. You did lawyering with Diane Feinstein, kind of some politics, and also the city of San Francisco. And then you made this move over to tech. Talk about that decision and what went into that decision and how did you get into tech? 'cause we know part of the problem with diversity is a pipeline problem. You came over from the law side of the house. >> Yes, and to be honest politics and the law are pretty homogenous. So when I made the move to tech, it was still a lot of the same, but what I knew is that I could be an attorney anywhere from Omaha Nebraska to Miami Florida. But what I couldn't do was work for a disruptive company, potentially a unicorn. And I seized that opportunity and (indistinct) Lyft early on before Ride Hailing and Ride Sharing was even a thing. So it was an exciting opportunity. And I joined right at the exact moment that made myself really meaningful in the organization. And I'm hoping that I'm doing the same thing right now at Waymo. >> Great, Inamarie you've come from one of my favorite stories I like to talk about from the old school Clorox great product management. I always like to joke that Silicon Valley needs a pipeline back to Cincinnati and Proctor and Gamble to get good product managers out here. You were in the classic, right? You were there, you were at Honeywell Plantronics, and then you jumped over to tech. Tell us a little bit about that move. Cause I'm sure selling Clorox is a lot different than selling the terrific service that you guys provide at Zendesk. I'm always happy when I see Zendesk in my customer service return email, I know I'm going to get taken care of. >> Oh wow, that's great. We love customers like you., so thank you for that. My journey is you're right from a fortune 50 sort of more portfolio type company into tech. And I think one of the reasons is because when tech is starting out and that's what Zendesk was a few five years back or so very much an early stage growth company, two things are top of mind, one, how do we become more global? And how do we make sure that we can go up market and attract enterprise grade customers? And so my experience having only been in those types of companies was very interesting for a startup. And what was interesting for me is I got to live in a world where there were great growth targets and numbers, things I had never seen. And the agility, the speed, the head plus heart really resonated with my background. So super glad to be in tech, but you're right. It's a little different than a consumer products. >> Right, and then Jennifer, you're in a completely different world, right? So you worked for the Golden State Warriors, which everybody knows is an NBA team, but I don't know that everyone knows really how progressive the Warriors are beyond just basketball in terms of the new Chase Center, all the different events that you guys put on it. And really the leadership there has decided we really want to be an entertainment company of which the Golden State Warrior basketball team has a very, very important piece, you've come from the entertainment industry. So that's probably how they found you, but you're in the financial role. You've always been in the financial role, not traditionally thought about as a lot of women in terms of a proportion of total people in that. So tell us a little bit about your experience being in finance, in entertainment, and then making this kind of hop over to, I guess Uber entertainment. I don't know even how you would classify the warriors. >> Sports entertainment, live entertainment. Yeah, it's interesting when the Warriors opportunity came up, I naturally said well no, I don't have any sports background. And it's something that we women tend to do, right? We self edit and we want to check every box before we think that we're qualified. And the reality is my background is in entertainment and the Warriors were looking to build their own venue, which has been a very large construction project. I was the CFO at Universal Studios Hollywood. And what do we do there? We build large attractions, which are just large construction projects and we're in the entertainment business. And so that sort of B to C was a natural sort of transition for me going from where I was with Universal Studios over to the Warriors. I think a finance career is such a great career for women. And I think we're finding more and more women entering it. It is one that you sort of understand your hills and valleys, you know when you're going to be busy and so you can kind of schedule around that. I think it's really... it provides that you have a seat at the table. And so I think it's a career choice that I think is becoming more and more available to women certainly more now than it was when I first started. >> Yeah, It's interesting cause I think a lot of people think of women naturally in human resources roles. My wife was a head of human resources back in the day, or a lot of marketing, but not necessarily on the finance side. And then Kate go over to you. You're one of the rare birds you've been at Accenture  for over 20 years. So you must like airplanes and travel to stay there that long. But doing a little homework for this, I saw a really interesting piece of you talking about your boss challenging you to ask for more work, to ask for a new opportunity. And I thought that was really insightful that you, you picked up on that like Oh, I guess it's incumbent on me to ask for more, not necessarily wait for that to be given to me, it sounds like a really seminal moment in your career. >> It was important but before I tell you that story, because it was an important moment of my career and probably something that a lot of the women here on the panel here can relate to as well. You mentioned airplanes and it made me think of my dad. My father was in the air force and I remember him telling stories when I was little about his career change from the air force into a career in telecommunications. So technology for me growing up Jeff was, it was kind of part of the dinner table. I mean it was just a conversation that was constantly ongoing in our house. And I also, as a young girl, I loved playing video games. We had a Tandy computer down in the basement and I remember spending too many hours playing video games down there. And so for me my history and my really at a young age, my experience and curiosity around tech was there. And so maybe that's, what's fueling my inspiration to stay at Accenture for as long as I have. And you're right It's been two decades, which feels tremendous, but I've had the chance to work across a bunch of different industries, but you're right. I mean, during that time and I relate with what Jennifer said in terms of self editing, right? Women do this and I'm no exception, I did this. And I do remember I'm a mentor and a sponsor of mine who called me up when I'm kind of I was at a pivotal moment in my career and he said you know Kate, I've been waiting for you to call me and tell me you want this job. And I never even thought about it. I mean I just never thought that I'd be a candidate for the job and let alone somebody waiting for me to kind of make the phone call. I haven't made that mistake again, (laughing) but I like to believe I learned from it, but it was an important lesson. >> It's such a great lesson and women are often accused of being a little bit too passive and not necessarily looking out for in salary negotiations or looking for that promotion or kind of stepping up to take the crappy job because that's another thing we hear over and over from successful people is that some point in their career, they took that job that nobody else wanted. They took that challenge that really enabled them to take a different path and really a different Ascension. And I'm just curious if there's any stories on that or in terms of a leader or a mentor, whether it was in the career, somebody that you either knew or didn't know that was someone that you got kind of strength from kind of climbing through your own, kind of career progression. Will go to you first Annabel. >> I actually would love to talk about the salary negotiations piece because I have a group of friends about that we've been to meeting together once a month for the last six years now. And one of the things that we committed to being very transparent with each other about was salary negotiations and signing bonuses and all of the hard topics that you kind of don't want to talk about as a manager and the women that I'm in this group with span all types of different industries. And I've learned so much from them, from my different job transitions about understanding the signing bonus, understanding equity, which is totally foreign to me coming from law and politics. And that was one of the most impactful tools that I've ever had was a group of people that I could be open with talking about salary negotiations and talking about how to really manage equity. Those are totally foreign to me up until this group of women really connected me to these topics and gave me some of that expertise. So that is something I strongly encourage is that if you haven't openly talked about salary negotiations before you should begin to do so. >> It begs the question, how was the sensitivity between the person that was making a lot of money and the person that wasn't? And how did you kind of work through that as a group for the greater good of everyone? >> Yeah, I think what's really eye opening is that for example, We had friends who were friends who were on tech, we had friends who were actually the entrepreneurs starting their own businesses or law firm, associates, law firm partners, people in PR, so we understood that there was going to be differences within industry and frankly in scale, but it was understanding even the tools, whether I think the most interesting one would be signing bonus, right? Because up until a few years ago, recruiters could ask you what you made and how do you avoid that question? How do you anchor yourself to a lower salary range or avoid that happening? I didn't know this, I didn't know how to do that. And a couple of women that had been in more senior negotiations shared ways to make sure that I was pinning myself to a higher salary range that I wanted to be in. >> That's great. That's a great story and really important to like say pin. it's a lot of logistical details, right? You just need to learn the techniques like any other skill. Inamarie, I wonder if you've got a story to share here. >> Sure. I just want to say, I love the example that you just gave because it's something I'm super passionate about, which is transparency and trust. Then I think that we're building that every day into all of our people processes. So sure, talk about sign on bonuses, talk about pay parody because that is the landscape. But a quick story for me, I would say is all about stepping into uncertainty. And when I coach younger professionals of course women, I often talk about, don't be afraid to step into the role where all of the answers are not vetted down because at the end of the day, you can influence what those answers are. I still remember when Honeywell asked me to leave the comfort of California and to come to the East coast to New Jersey and bring my family. And I was doing well in my career. I didn't feel like I needed to do that, but I was willing after some coaching to step into that uncertainty. And it was one of the best pivotal moment in my career. I didn't always know who I was going to work with. I didn't know the challenges and scope I would take on, but those were some of the biggest learning experiences and opportunities and it made me a better executive. So that's always my coaching, like go where the answers aren't quite vetted down because you can influence that as a leader. >> That's great, I mean, Beth Comstock former vice chair at GE, one of her keynotes I saw had a great line, get comfortable with being uncomfortable. And I think that its a really good kind of message, especially in the time we're living in with accelerated change. But I'm curious, Inamarie was the person that got you to take that commitment. Would you consider that a sponsor, a mentor, was it a boss? Was it maybe somebody not at work, your spouse or a friend that said go for it. What kind of pushed you over the edge to take that? >> It's a great question. It was actually the boss I was going to work for. He was the CHRO, and he said something that was so important to me that I've often said it to others. And he said trust me, he's like I know you don't have all the answers, I know we don't have this role all figured out, I know you're going to move your family, but if you trust me, there is a ton of learning on the other side of this. And sometimes that's the best thing a boss can do is say we will go on this journey together. I will help you figure it out. So it was a boss, but I think it was that trust and that willingness for him to stand and go alongside of me that made me pick up my family and be willing to move across the country. And we stayed five years and really, I am not the same executive because of that experience. >> Right, that's a great story, Jennifer, I want to go to you, you work for two owners that are so progressive and I remember when Joe Lacob came on the floor a few years back and was booed aggressively coming into a franchise that hadn't seen success in a very long time, making really aggressive moves in terms of personnel, both at the coaches and the players level, the GM level. But he had a vision and he stuck to it. And the net net was tremendous success. I wonder if you can share any of the stories, for you coming into that organization and being able to feel kind of that level of potential success and really kind of the vision and also really a focus on execution to make the vision real cause vision without execution doesn't really mean much. If you could share some stories of working for somebody like Joe Lacob, who's so visionary but also executes so very, very effectively. >> Yeah, Joe is, well I have the honor of working for Joe, for Rick Welts to who's our president. Who's living legend with the NBA with Peter Guber. Our leadership at the Warriors are truly visionary and they set audacious targets. And I would say from a story the most recent is, right now what we're living through today. And I will say Joe will not accept that we are not having games with fans. I agree he is so committed to trying to solve for this and he has really put the organization sort of on his back cause we're all like well, what do we do? And he has just refused to settle and is looking down every path as to how do we ensure the safety of our fans, the safety of our players, but how do we get back to live entertainment? And this is like a daily mantra and now the entire organization is so focused on this and it is because of his vision. And I think you need leaders like that who can set audacious goals, who can think beyond what's happening today and really energize the entire organization. And that's really what he's done. And when I talked to my peers and other teams in there they're talking about trying to close out their season or do these things. And they're like well, we're talking about, how do we open the building? And we're going to have fans, we're going to do this. And they look at me and they're like, what are you talking about? And I said, well we are so fortunate. We have leadership that just is not going to settle. Like they are just always looking to get out of whatever it is that's happening and fix it. So Joe is so committed His background, he's an epidemiologist major I think. Can you imagine how unique a background that is and how timely. And so his knowledge of just around the pandemic and how the virus is spread. And I mean it's phenomenal to watch him work and leverage sort of his business acumen, his science acumen and really think through how do we solve this. Its amazing. >> The other thing thing that you had said before is that you basically intentionally told people that they need to rethink their jobs, right? You didn't necessarily want to give them permission to get you told them we need to rethink their jobs. And it's a really interesting approach when the main business is just not happening, right? There's just no people coming through the door and paying for tickets and buying beers and hotdogs. It's a really interesting talk. And I'm curious, kind of what was the reception from the people like hey, you're the boss, you just figure it out or were they like hey, this is terrific that he pressed me to come up with some good ideas. >> Yeah, I think when all of this happened, we were resolved to make sure that our workforce is safe and that they had the tools that they needed to get through their day. But then we really challenged them with re imagining what the next normal is. Because when we come out of this, we want to be ahead of everybody else. And that comes again from the vision that Joe set, that we're going to use this time to make ourselves better internally because we have the time. I mean, we had been racing towards opening Chase Center and not having time to pause. Now let's use this time to really rethink how we're doing business. What can we do better? And I think it's really reinvigorated teams to really think and innovate in their own areas because you can innovate anything, right?. We're innovating how you pay payables, we're all innovating, we're rethinking the fan experience and queuing and lines and all of these things because now we have the time that it's really something that top down we want to come out of this stronger. >> Right, that's great. Kate I'll go to you, Julie Sweet, I'm a big fan of Julie Sweet. we went to the same school so go go Claremont. But she's been super aggressive lately on a lot of these things, there was a get to... I think it's called Getting to 50 50 by 25 initiative, a formal initiative with very specific goals and objectives. And then there was a recent thing in terms of doing some stuff in New York with retraining. And then as you said, military being close to your heart, a real specific military recruiting process, that's formal and in place. And when you see that type of leadership and formal programs put in place not just words, really encouraging, really inspirational, and that's how you actually get stuff done as you get even the consulting businesses, if you can't measure it, you can't improve it. >> Yeah Jeff, you're exactly right. And as Jennifer was talking, Julie is exactly who I was thinking about in my mind as well, because I think it takes strong leadership and courage to set bold bold goals, right? And you talked about a few of those bold goals and Julie has certainly been at the forefront of that. One of the goals we set in 2018 actually was as you said to achieve essentially a gender balance workforce. So 50% men, 50% women by 2025, I mean, that's ambitious for any company, but for us at the time we were 400,000 people. They were 500, 6,000 globally. So when you set a goal like that, it's a bold goal and it's a bold vision. And we have over 40% today, We're well on our path to get to 50%, I think by 2025. And I was really proud to share that goal in front of a group of 200 clients the day that it came out, it's a proud moment. And I think it takes leaders like Julie and many others by the way that are also setting bold goals, not just in my company to turn the dial here on gender equality in the workforce, but it's not just about gender equality. You mentioned something I think it's probably at as, or more important right now. And that's the fact that at least our leadership has taken a Stand, a pretty bold stand against social injustice and racism, >> Right which is... >> And so through that we've made some very transparent goals in North America in terms of the recruitment and retention of our black African American, Hispanic American, Latinex communities. We've set a goal to increase those populations in our workforce by 60% by 2025. And we're requiring mandatory training for all of our people to be able to identify and speak up against racism. Again, it takes courage and it takes a voice. And I think it takes setting bold goals to make a change and these are changes we're committed to. >> Right, that's terrific. I mean, we started the conversation with Grace Hopper, they put out an index for companies that don't have their own kind of internal measure to do surveys again so you can get kind of longitudinal studies over time and see how you're improving Inamarie, I want to go to you on the social justice thing. I mean, you've talked a lot about values and culture. It's a huge part of what you say. And I think that the quote that you use, if I can steal it is " no culture eats strategy for breakfast" and with the social injustice. I mean, you came out with special values just about what Zendesk is doing on social injustice. And I thought I was actually looking up just your regular core mission and value statement. And this is what came up on my Google search. So I wanted to A, you published this in a blog in June, taking a really proactive stand. And I think you mentioned something before that, but then you're kind of stuck in this role as a mind reader. I wonder if you can share a little bit of your thoughts of taking a proactive stand and what Zendesk is doing both you personally, as well as a company in supporting this. And then what did you say as a binder Cause I think these are difficult kind of uncharted waters on one hand, on the other hand, a lot of people say, hello, this has been going on forever. You guys are just now seeing cellphone footage of madness. >> Yeah Wow, there's a lot in there. Let me go to the mind reader comments, cause people are probably like, what is that about? My point was last December, November timing. I've been the Chief People Officer for about two years And I decided that it really was time with support from my CEO that Zendesk have a Chief Diversity Officer sitting in at the top of the company, really putting a face to a lot of the efforts we were doing. And so the mind reader part comes in little did I know how important that stance would become, in the may June Timing? So I joked that, it almost felt like I could have been a mind reader, but as to what have we done, a couple of things I would call out that I think are really aligned with who we are as a company because our culture is highly threaded with the concept of empathy it's been there from our beginning. We have always tried to be a company that walks in the shoes of our customers. So in may with the death of George Floyd and the world kind of snapping and all of the racial injustice, what we said is we wanted to not stay silent. And so most of my postings and points of view were that as a company, we would take a stand both internally and externally and we would also partner with other companies and organizations that are doing the big work. And I think that is the humble part of it, we can't do it all at Zendesk, we can't write all the wrongs, but we can be in partnership and service with other organizations. So we used funding and we supported those organizations and partnerships. The other thing that I would say we did that was super important along that empathy is that we posted space for our employees to come together and talk about the hurt and the pain and the experiences that were going on during those times and we called those empathy circles. And what I loved is initially, it was through our mosaic community, which is what we call our Brown and black and persons of color employee resource group. But it grew into something bigger. We ended up doing five of these empathy circles around the globe and as leadership, what we were there to do is to listen and stand as an ally and support. And the stories were life changing. And the stories really talked about a number of injustice and racism aspects that are happening around the world. And so we are committed to that journey, we will continue to support our employees, we will continue to partner and we're doing a number of the things that have been mentioned. But those empathy circles, I think were definitely a turning point for us as an organization. >> That's great, and people need it right? They need a place to talk and they also need a place to listen if it's not their experience and to be empathetic, if you just have no data or no knowledge of something, you need to be educated So that is phenomenal. I want to go to you Jennifer. Cause obviously the NBA has been very, very progressive on this topic both as a league, and then of course the Warriors. We were joking before. I mean, I don't think Steph Curry has ever had a verbal misstep in the history of his time in the NBA, the guy so eloquent and so well-spoken, but I wonder if you can share kind of inside the inner circle in terms of the conversations, that the NBA enabled right. For everything from the jerseys and going out on marches and then also from the team level, how did that kind of come down and what's of the perception inside the building? >> Sure, obviously I'm so proud to be part of a league that is as progressive and has given voice and loud, all the teams, all the athletes to express how they feel, The Warriors have always been committed to creating a diverse and equitable workplace and being part of a diverse and equitable community. I mean that's something that we've always said, but I think the situation really allowed us, over the summer to come up with a real formal response, aligning ourselves with the Black Lives Matter movement in a really meaningful way, but also in a way that allows us to iterate because as you say, it's evolving and we're learning. So we created or discussed four pillars that we wanted to work around. And that was really around wallet, heart, beat, and then tongue or voice. And Wallet is really around putting our money where our mouth is, right? And supporting organizations and groups that aligned with the values that we were trying to move forward. Heart is around engaging our employees and our fan base really, right? And so during this time we actually launched our employee resource groups for the first time and really excited and energized about what that's doing for our workforce. This is about promoting real action, civic engagement, advocacy work in the community and what we've always been really focused in a community, but this really hones it around areas that we can all rally around, right? So registration and we're really focused on supporting the election day results in terms of like having our facilities open to all the electorate. So we're going to have our San Francisco arena be a ballot drop off, our Oakland facilities is a polling site, Santa Cruz site is also a polling location, So really promoting sort of that civic engagement and causing people to really take action. heart is all around being inclusive and developing that culture that we think is really reflective of the community. And voice is really amplifying and celebrating one, the ideas, the (indistinct) want to put forth in the community, but really understanding everybody's culture and really just providing and using the platform really to provide a basis in which as our players, like Steph Curry and the rest want to share their own experiences. we have a platform that can't be matched by any pedigree, right? I mean, it's the Warriors. So I think really getting focused and rallying around these pillars, and then we can iterate and continue to grow as we define the things that we want to get involved in. >> That's terrific. So I have like pages and pages and pages of notes and could probably do this for hours and hours, but unfortunately we don't have that much time we have to wrap. So what I want to do is give you each of you the last word again as we know from this problem, right? It's not necessarily a pipeline problem, it's really a retention problem. We hear that all the time from Girls in Code and Girls in Tech. So what I'd like you to do just to wrap is just a couple of two or three sentences to a 25 year old, a young woman sitting across from you having coffee socially distanced about what you would tell her early in the career, not in college but kind of early on, what would the be the two or three sentences that you would share with that person across the table and Annabel, we'll start with you. >> Yeah, I will have to make a pitch for transportation. So in transportation only 15% of the workforce is made up of women. And so my advice would be that there are these fields, there are these opportunities where you can make a massive impact on the future of how people move or how they consume things or how they interact with the world around them. And my hope is that being at Waymo, with our self driving car technology, that we are going to change the world. And I am one of the initial people in this group to help make that happen. And one thing that I would add is women spend almost an hour a day, shuttling their kids around, and we will give you back that time one day with our self driving cars so that I'm a mom. And I know that that is going to be incredibly powerful on our daily lives. >> Jeff: That's great. Kate, I think I might know what you're already going to say, but well maybe you have something else you wanted to say too. >> I don't know, It'll be interesting. Like if I was sitting across the table from a 25 year old right now I would say a couple of things first I'd say look intentionally for a company that has an inclusive culture. Intentionally seek out the company that has an inclusive culture, because we know that companies that have inclusive cultures retain women in tech longer. And the companies that can build inclusive cultures will retain women in tech, double, double the amount that they are today in the next 10 years. That means we could put another 1.4 million women in tech and keep them in tech by 2030. So I'd really encourage them to look for that. I'd encouraged them to look for companies that have support network and reinforcements for their success, and to obviously find a Waymo car so that they can not have to worry where kids are on for an hour when you're parenting in a few years. >> Jeff: I love the intentional, it's such a great word. Inamarie, >> I'd like to imagine that I'm sitting across from a 25 year old woman of color. And what I would say is be authentically you and know that you belong in the organization that you are seeking and you were there because you have a unique perspective and a voice that needs to be heard. And don't try to be anything that you're not, be who you are and bring that voice and that perspective, because the company will be a better company, the management team will be a better management team, the workforce will be a better workforce when you belong, thrive and share that voice. >> I love that, I love that. That's why you're the Chief People Officer and not Human Resources Officer, cause people are not resources like steel and cars and this and that. All right, Jennifer, will go to you for the wrap. >> Oh my gosh, I can't follow that. But yes, I would say advocate for yourself and know your value. I think really understanding what you're worth and being willing to fight for that is critical. And I think it's something that women need to do more. >> Awesome, well again, I wish we could go all day, but I will let you get back to your very, very busy day jobs. Thank you for participating and sharing your insight. I think it's super helpful. And there and as we said at the beginning, there's no better example for young girls and young women than to see people like you in leadership roles and to hear your voices. So thank you for sharing. >> Thank you. >> All right. >> Thank you. >> Okay thank you. >> Thank you >> All right, so that was our diversity panel. I hope you enjoyed it, I sure did. I'm looking forward to chapter two. We'll get it scheduled as soon as we can. Thanks for watching. We'll see you next time. (upbeat music)

>> Announcer: From the Cosmopolitan Hotel in Las Vegas, Nevada, it's theCUBE. Covering Coupa Inspire 2019. Brought to you by Coupa. >> Welcome to theCUBE. Lisa Martin on the ground at Coupa Inspire '19 from the Vegas. I'm very pleased to welcome not Bono, not Sting, it's Chandar, the CMO of Coupa. Chandar, welcome to theCUBE. >> Lisa, thank you, it's great to be here today. >> This is a really cool event. Procurement is sexy. >> It is sexy. >> It can be so incredibly transformative to any organization. I loved how the last two days, what you guys have done is a great job of articulating Coupa's value in procurement, invoicing, payments, expense, through the voices of your customers and I think there's no better brand value that you can get. >> Sure, absolutely. >> Tell us a little bit about your role as the CMO of Coupa and marketing in a fast-growing company with a product that people might go, "I haven't heard of that, what is that again?" >> Yeah, it's a good question. I think if I look at it, my role is at Coupa, especially, for Coupa, what's interesting about it, as you said, is that every company makes money, every company spends money. So, invariably, Coupa can be used across a set of different companies. One from the Golden State Warriors to Procter & Gamble to the Lukemia & Lymphoma Society. Across the board. And then, from our perspective, holistically, we're looking at business, but managed from different aspects of spend. You said procurement was in expenses. So, my role is to build a marketing engine to get the flywheel effect of first you drive awareness. All marketing starts with awareness and you said people haven't heard of it. And so, to first to drive awareness in a very thoughtful way to the right contextual community we want to go after. And, two, drive acquisition, we'll drive close synergies between sales and marketing to ultimately drive pipeline and win rates and ultimately deals. And then, very importantly in today's world, is to drive the advocacy and get your most passionate customers to evangelize about the brand, so that you create the flywheel effect of awareness, acquisition, and advocacy. And, that's really what my role today is. >> And, I love how I read an article where you call that the stairway to marketing heaven. So, I thought, I wonder if you're a guitar guy, but you're right. It's how to drive awareness, but in a meaningful, thoughtful way. Especially today, with all all the technology, we wake up with it, right? Our phone is our alarm clock. We are bombarded by ads. If we're on Instagram, following our favorite celebrities or whatnot and it's scary when they have the right context, but it has to be thoughtful. We need to know our audience. So, you describe this stairway to marketing heaven, as you just mentioned, it's awareness, it's acquisition, which is key. But, I feel like a lot of companies don't forget the advocacy part, but they don't invest enough in it because that's the best salesperson for your technology, is the people that are using it successfully, right? >> Totally. Yeah, so, in fact, there was a study about a couple of years which looked at how balanced the boat is in terms of spending in presale versus post-sale. And, it's interesting that 87% of B2B marketing spend was presale. In other words, only 13% of people were investing in retention marketing, adoption mastery, customer marketing, and this is what advocacy marketing. And, in today's world, that doesn't work because you got to balance the boat because, to your point, you're getting in a peer-bond world where your existing customers are your best sellers. And, prospects who have all the buying power today are looking to your existing customers to guide them in their purchasing decisions. So, as an organization, if you balance the boat, then you're going to get the flywheel effect going for you in terms of driving the right advocacy across all channels. Just not your own channel if you earn channels to ultimately drive that acquisition going. >> Do you think that's actually more valuable? 'Cause it's one thing to have on your .com site, your social media sites, all these great things about your technologies, etc., coming from customers or from product experts, from influencers. Talk about the value. As technology advances so much and we are influenced by so many other channels, the value of the earned channel and that peer-to-peer relationship. >> Yeah, I think, as I say, that every mom says her baby is good-looking. But, in software, not every baby is really good-looking. Which means, if you take that analogy and extend it, if you're coming to your own channel, invariably, you're going to see some great customer videos about your product, you're going to see some great endorsements and testimonials, you're going to see some great quotes about your product. The reality, there's no bad news about your product on your own website, on your own channel. But, the reality is there are some, some people who might have different opinions. If you go to Glassdoor, no company gets a five on Glassdoor. And, if you take the same thing and extend it to earned channels for advocacy, folks like G2 Crowd, TrustRadius, and B2B, for example, are becoming more relevant today than before because two things. One is 85% of our customers' journey is self-directed. >> Lisa: That much? >> That much and Forrester has anywhere from 60 to 80, but reality is whether you're buying a car or you're buying Coupa. Today, a customer is discovering more journeys. And, in that process, they are looking to more of these earned channels as validation of which ones to go after than just your own channels. So, that's why we got to balance the boat and distribute our advocacy spend dollars across both your own channels and your earned channels. And, that's really important for you and the flywheel will pay off for you over time from that perspective. >> It will and that seems like a lot of the things that Suzy Irwin was talking about to the audience earlier. That's common sense. Why is it that you see these marketing budgets that are so heavily weighted towards just getting awareness, getting customers acquired, and then not thinking about retention marketing account based marketing. >> I'll tell you why. I think any smart CMO will conceptually agree with you. Nobody's going to say, of course, this is not important for me to get advocacy. The challenge comes in in terms of how that marketing department is measured. What gets measured gets funding at the end of the day. >> Lisa: That's a good point. >> And, reality is a lot of these B2B companies are still measuring marketing based on, what's the pipeline you're driving and what's at the top of the funnel metrics that you're driving? In reality, that's a little bit of a skewed thing because then if that's what you're being measured at the board level, at the executive level, then guess what? All your funding is going to go towards that. But, really, the true measurement of marketing, one, is about, yes, you have to get pipeline. You have to influence win rates at the bottom of the funnel and that's where product marketing comes in. But, as importantly, you have to look at the number of brand advocates you create and lifetime value of a customer. >> Yes, CLV, yes. >> And, that's really, really, customer lifetime value is so important because in a SaaS business, ultimately, the Mufasa metric, I'm a Lion King fan. The Mufasa metric is really lifetime value because if a customer stays longer with you, pays you more, and is shouting from the rooftop, then, invariably, that SaaS business is doing well. And, that's why you have to balance the boat in terms of post-advocacies, post-acquisition spend into advocacy, as much as you've done in pre-acquisition. >> When you came into Coupa a couple of years ago, have you been able to shift those budgets because you're able to demonstrate the value that that advocacy piece generates with the flywheel? >> Absolutely and I have a very progressive-thinking CEO who's partners with me on this too. So, we've been absolutely able to do that. In fact, what we're trying to do at the end of the day and most software companies, the real goal should be creating a tribe. In technology, you have to create a tribe to be a titan. And, it's just not about the capability, it's about the community. And, that's really what we're trying to do at Coupa is to create the tribal community feeling. So, if the community is bigger than the brand, it is about the community itself and learning, sharing, and growing with each other and being successful. And, we're just fostering that. So, from that perspective, if you look at this conference and the investment we're making here, some of the programs we're doing in terms of advocacy, what we call spend sellers, etc., is all about that community tribal feeling and go establish that. To use some inspiration from our consumer brands, if you really think about it, people don't buy what they want. People buy what they want to be. So, let me give you what I mean by that. What I want could be a bike. It could be any motorbike, but what I want to be could be part of a very special community and that's why Harley Davidson is successful. What I want could be any stationary bike today, but what I want to be is part of some cool community like Peloton. That's why Peloton is successful. So, similarly for us, what I want could be some spend management software, but what I want to be is part of this community, this cool club, and that's the feeling we're trying to create in the post-acquisition cycle. >> I love that you said that because you talked about that this morning and I loved how you had the word community on the slide and then broke that out into communication unity. And, one of the senses that I got yesterday when-- >> Chandar: Rob was talking about it. >> Yeah, when Rob kicked off everything is this is a very collaborative community. We think about that in terms in terms even like a developer community or something like that. But, Coupa is now managing $1.2 trillion of spend through the platform that every other business that's using Coupa gets to benefit from. It's customer-centric, it's supplier-centric, but it's about applying the right technologies, AI, machine learning, to all this data, so everybody benefits. >> That's right and one of the interesting aspects of community building is one aspect of community building is that Marc Benioff had a great, evangelistic marketing was a way of community building. He would come in and really evangelize and this is where we're going and you all need to come with us. When I was at Marketo, it was interesting. Community building was through more educational marketing and doing it through this, I'm going to educate you through though leadership. Another good way of community building is through product intelligence, which is community intelligence. So, collectively, the sum of all parts are smarter than the parts themselves. And, Rob has a great line, which says, "None of us is as smart as all of us." And, the fundamental community intelligence offering is based on this first principle. So, example, if I'm the community of Coupa customers, the next customer is smarter than the previous customer because the collective intelligence grew, which means I can then go benchmark it myself. I gave an example this morning of USO, the company that provides services to the United States troops. And, when Rick Quaintance at USO benchmarked himself using community intelligence, versus the rest of the community, he realizes that his invoice cycle times are seven times lower. So, that kind of intelligence is extremely beneficial and invaluable to companies. So, that's the value of the community, is providing the collective intelligence. Waze is a great consumer example. Those of us who use Waze for traffic know that it's all community driven and each one of us is smarter because we're collectively using it. It's the same concept in applying that to B2B software. >> So, as we see, you mentioned the over 80% of the buying decision is self-directed whether we're buying a car or Coupa software. Did Coupa foresee that in the last decade to see we're going to have to go to a more community-driven collaboration because the consumer of any thing, any product or service, is going to be so empowered 'cause that's a part of the Coupa foundation. >> It is. >> Lisa: Which, we don't see a lot in companies that are 10 plus years old. >> Yeah, and credit to Rob for his vision for this. It's because I think early part of the company, he wrote into the contracts that the company can benefit. Collectively, every company can benefit by being part of this community. And, the fact is data's aggregated, abstracted, there's no information that is sensitive, etc. But, the fact is we all can collectively benefit through it. That was a great vision of Rob and early people and that's benefited us because the benefit is really over scale and time. Now, your $1.2 trillion, it is really statistically significant in each different industry to get that intelligence. And, that is one of the other reasons we launched our business spend index. It's called spendindex.com. Where we can use the billions of dollars spent in the community to provide a leading indicator of economic growth based on current business spend sentiment. You think of ADP as this payroll, it's called ADP payroll thing that comes out and the gross domestic product report comes out. Those tend to be rear-view mirror lagging indicators. But, as we're using community-based intelligence to provide a windshield, a leading indicator of where the economy is going. So, there's so many different use cases. Benefiting based on spend you're doing as well as where the economy is going and all this is based on the intelligence. >> It's so powerful because, to your point, you're not looking behind. >> Chandar: It's the windshield. >> Exactly, able to be looking forward. So, with all the announcements and the great things that have come out with the AWS expansion, what you guys are doing with Coupa Pay. I was shocked to learn the percentages of businesses that are still writing paper checks. Or, the fact that a lot of companies have 10 plus banks that they're working with. There's still so much manual processes. You must just be, the future is so bright, you got to wear shades with Coupa. But, what excites you about what you guys have announced the last coupe of days and the feedback that you're hearing from your tribe? >> I think there's two kinds of things. One is continue to set the innovation agenda for the industry. And, really, you have to look at every customer on their unique journey of maturity and maturation, so we have a very thoughtful, what we call, maturity index, The business spend management index. Whereas, you are seeing some of these customers, for example, you mentioned, may be in the first stage of this maturity, where, for them, it's just getting automation and going from paper to paperless could be the first step. But, some other customers might say, "I've gotten there, "but I want to get the next level of sophistication "to orchestrate these business spend processes." So, what's exciting for us in the feedback is we're creating product capability across this maturation journey for our customers to make them successful at each of those places. And, Coupa Pay is one example of that. Whereas, some of the other pieces we talked about, we announced about some of the community offerings that we did also is on that. So, that's one exciting piece. The other exciting piece that customers tell us at this conference is, "Foster platforms for us "to engage with each other, learn from each other, "share from each other, and grow with each other." So, even stuff that Rob talked about, which is sourced together. This concept of customers coming together to drive a sourcing process and, again, the collective intelligence in the community, that, we're getting very, very positive feedback from that perspective. And, ultimately, Rob has a really good saying that, "It is not about customer satisfaction. "It is about customer success." That's a delineation there. A customer could be very satisfied with you, but they may not be necessarily successful. And, we say, it's not about satisfaction. It's about success. And, by creating this innovation cycle and then having a post-implementation process that's getting true value, that's truly how we drive customer success. >> And, something that I've heard over and over as I've talked to a number of your customers yesterday and today is how much they're feeling Coupa is listening. Their feedback is being incorporated. They're actually influencing the development of the technology and that was loud and clear the last two days. >> Yeah, I think there is, Rob talked about the number of features that are being influenced by the community and we have these-- >> 300 plus in the last 12 months. >> Yes, 300 plus in the last 12 months. And, there's this concept of two ears, one mouth. And, listen, learn, and innovate and that's the philosophy here. But, it's a right mix of listening to customers, learning from them, and getting the right input from them for driving innovation, as well as having strategic vision on where this market is going and having the right mix of those to provide the capability to customers. >> Wow, you're on a rocket ship. Chandar, it was great to have you on theCUBE. You'll have to come back. >> Yes, Lisa, absolutely, I'll come back and it was a pleasure being here. Awesome. >> Awesome, thank you so much. For Chandar, I'm Lisa Martin and you're watching theCUBE from Coupa Inspire '19. Thanks for watching. (techno music)

>> No, that makes total sense. You've got me thinking a little bit. You see some of this right now going on general fitness and these thirty six minute classes will fit thirty six is awesome there. Big group No. One, their trainers. And they do a really good job of it. But the onset of maybe not such, um, high intensity aspects that you're doing. But you're promoting motor patterns, right? So it's not like, Okay, let's train for thirty six minutes. Generally was trained for forty five minutes. Let's train for an hour. But let's have a specific program that we're picking on to develop an athlete and push him in direction. So I mean by that is, I kind of see this in this is my attempt to digest cores. Mind not break it down and bring her with me. I thought you'd like to roost e a seven day period. And then you said in this period, I want to accomplish, you know, thiss five sets off total or five sets of ten reps and back squat and then your micro dose in mind like you, you slice it up, and so all of a sudden it doesn't become a five by ten because fifty total wrapped trying to get you won't take that ten reps here and twenty wraps here and maybe five reps here, and you put it in different ways. So if you look at it holistically, it's this very on the certainly first. See, it looks almost just organized, but looks like a lot happening at once. When you take us back, you look at a full truck, the full pies there, and so people they come and see me one of your workout So they see on Instagram that, oh, it's just Korea Doing, you know, appears to be basic patterns that kind of seem random. But really, you said, Okay, this is my goal. This is what I want from these guys and you're taking a step back. You applied it in a very strategic way. So it's not just people say, Oh, it's a fitness class. No, First off, Micro does seem just That's if I like, you know, a thirty minute workout. It's a thirty minute directed work out with the candle quantifiable goal over Baghdad, a period of time. Is that a fair assessment? I dove into the brain of Cory. No, my deal >> looked like this. Lookit. Let's look at another population. We look at prisoners when they go to the yard. How much time do they have a day? All right, >> You know what, >> Right. That's what I'm saying. Like, it's not a lot like they're locked up in a cell for the whole day. So when they go to the yard, they go ham on whatever's available, it ain't like they got this nice little hole like, Okay, we're going to do from squads. And they were gonna go to bench and they were going to Arlo, and we're going to do no. They pick something that is available and they go ham on it for an hour, and they're on really terrible food and really terrible environments, but tend to get really strong. Okay, well, that makes sense. So and you know what? They do it again the next day and the next day and the next day. So I'm not saying we're trained like prisoners, But what I'm saying is there's a reason why if I was to tell any elite level lifter, OK? All you can do today for thirty minutes is squad. What do you think's gonna happen? They're going to go heavy often. And they're going to be able to be fresh the next day to do the same thing. I mean, no one leaves a power lifting meet the next day saying, Oh, time to go train again. No, their body is trashed, right? Because of all the intensity that they didn't through multiple movements. Same idea, right? All I'm doing is isolating it. So, for instance, I'm looking for a specific response. If I want to train relative string, I want to find a movement that they can move a lot of way, obviously not through a high speed. And that's the movement we're going to do. If I want a absolute velocity, for instance, Woodchuck and Tendo terms, I want them to be very elastic. Reactive owned him to move very, very fast. Then I'm gonna pick a movement, say, like a barbell squad job. Maybe it's a credible swing. Maybe it's throws and then they're going to go ham on that. But if you just take that one isolated lift, I don't care. If you do tend doubles at it, you're not going to be that sword, especially if you've been doing this for over a year. First start the preseason. We gotta look at stress holistically. The biggest stress they have is basketball. So the last thing I'm going to do is beat them down. And here I'm just going to make sure that we'Ll stay on the cart. So you look at our total volume. It looks something like four sets of four. But by the time we're at the end of the season January, February, March, we're hitting our P R's and reason why we're hit Rp. Ours is because we've made this huge reservoir of stress that they're able tto handle. So now practises cut in half. So I have more reserves in the weight room. So that force that's afore we were hitting for those compound movements in preseason. Well, now they look like ten sets of doubles or twelve sets of singles because they have that reservoir. So now we're expressing in a controlled environment faster weights have your weights at the time of year that we're looking for those adaptations so that now we're quote unquote stronger and faster. We're trying to win the championship, not tryingto win it and the summer, which you generally see like thereby sent PR is before they go home and summer. Well, that's great. And then they go into their maintenance program for the season, which last six months. Can you maintain anything for longer than six? No, you can't, like, maybe your oil, but you've not wantto patients, you know? I'm saying so. You know, that's that's where it really came down to is I'm trying to find the best means to produce performance, >> so I'm on times Lower standard. Yeah. Please do not mind around it. So I get it correct. Nowhere earthly it's looking at How do we given work out at that? Fits? The current state needed the athlete, so Okay, there begin the year, right? Their capacity only so localize outside stressors to fit in the workout around the other twenty three hours. Right? And then you're applying a stressor that's heavy enough, but not too light. And you do it. I'm not not overly fatigued them, but at least stimulate them. So you working guide rails? Not a written in stone. A type of thing, >> right? Yeah. So yeah. Yeah. How Basically how I how I keep the best part of the best way to put it is what I've done this year that I haven't done in the past is abuse Tendo Units, I'm just That's my way of just monitoring. How about speed? Okay, Cool, because load is one thing. But once again, how do you move that load now? We're not We're not dicing up like, Oh, it's point seven. You're supposed to hit point five like up. You know, add thirty kilos or vice versa, right? Like you're not exact. But if you're within a range, it gives me a whole lot of details, all right? And then you're basically all we do from that point is record the wait, not the speed. I just keep them in a certain zone. Stay within this. You, for instance, our strength speed or a relative strength and strength. Speed movements can't go anything more than triples our speed, strength and are absolute velocity. You can't go anything over five reps. If you hit quote unquote those triples or those fives, then the next time you come in, guess what we get to upload if you're not above that was going to stick with the same load. And if you prove it within your early work sex, then we'LL have a little bit alert. But that's our way of day to day, keeping them on the road, if you will. >> No, that makes sense. Do I couldn't agree more. I see it carrying over so well. Universally way you looked at the origins of strength training and we're like Oh, came from Russia and even your ever pashanski for those people aren't nerds like myself. Russian sports science even started like appeared ization. It's kind of a made up thing, right? So one hundred percent made up haven't made up and it kind of came from the four years cycle of Russia itself. America takes that andan. What happens is you get the the non athlete world's intelligent public world. Everything is monetized, right? So it's like, Okay, we know that training really heavy every days and probably a good. So we're going to make these things called, you know, in small little workouts that might last twenty five minutes are our six minutes, you know, have a shrink it as Lois and possibly can. But no, let's make it not necessarily difficult, but challenging. Um and we make money office. We labeled something different and you see different fitness fads come off when I come and go. But a lot of because I got the capitalistic market monetization. People try to make money off of things. But that really does him from, like the athletic side. If you're thinking about Hey, I'm Cory. I'm dealing with Alex. I don't know how they're going to walk into my door today. I don't know if they're going to be high lower, you know, just normal. How can I then give myself the opportunity to provide environment where they can work successfully and and what you do, which is really cool, And I find it really inspiring kind of cheesy word. But you give a lot of ownership to all your athletes when it comes to selection of exercises and movements. And I find that to be something that we don't say. We as in the general world of anything sports, science and fitness don't always like to do. Um, and you say Okay, you know, credit. I'm wrong, Corey to I don't want take worth mountains, him incorrectly. Just so you know, here's a pattern and maybe select one of these three exercises that you feel like gets you ready. And what's so great about that? It removes the constraints of this exercise is the best. You know, this is the golden exercise and really, I mean you and I know it, but we want to feel good. We would always have a bench press when I came in town, but absolutely, it's like, Okay, let's let's really understand that it's not really a difference between Aback Squad versus upfront squad versus may be something of a trap, our poll, especially if you're using it to get the athlete ready. So talk. If you could talk a little bit about how you decide some of that and what led you down that path and giving those athletes that kind of ownership and understanding of you know, I want to do this versus I have to >> do this right? I mean, to me, autonomy is everything, because what you generally see and it's to me, it's almost criminal is everyone gets the piece of paper. They fill it out with me you get, then you do the same thing, right? You get that piece of paper the next day, fill it out. Get that piece of paper. Next thing, fill it out. And then four years later you go. Well, I'm leaving now. Where's my piece of paper For the rest of my life. Oh, so you didn't really learn how to train, did you? You didn't really learn what worked for you. You didn't really In the really issue is like I deal with crazy, different levers. I mean, I got guys that are five eight all the way to seven foot. So you can't tell me there's a golden exercise that it doesn't exist in my world. >> I >> like knowing you're on. I would love to have everybody do the exact same thing. They love doing it. And they all do it very, very well so that I can have my little lab and I can have my control and I can show. Hey, guys, look how much better we got this year because of my implementation. Bax Wass What? What does that say? That says that I care more about what I'm doing more than what's best for that athlete and what they're doing if you really the real reason why I got to this autonomy stage is when I realized what I do is such a small percentage of their overall success and the reason why I say that I'm not necessarily saying I agree with hit or disagree with Hit, but you could have a hit program. You could have an Olympic based program. You could have your holistic based program, whatever you want to say, and I see the hit program Win a national championship and I'm like, what happened? Like I don't agree with that program, but they won well, it's all about it's all about the dude's. So if I can give quote unquote my dudes the best training environment that works for them. So what I mean by that is Look, here's a squad. You hate doing back squats because the bar on your back, it's jerking the hell out of your shoulders because you don't like to be an external rotation will. Then maybe I'm just going to hate. How about this Bar safety squad bar that feel better? Cool court. My knees are super tender away. It's basketball. Everybody's needs at some point this season, every a super tender last thing I'm going to do is put them in an environment. Teo, flame up those tendons so that they can't perform at a higher level on the basketball court. So what are we going to do? Well, let's Hinch, how about we just do some already? L stay. How about we do some kettle bell swings? Maybe some tribe are dead. Lift. It doesn't necessarily have to be this golden exercise that everybody fits in. And I think really what it stands from is that strength coaches got approved to their sport coaches that we'll look at, our numbers go up and they have to have a control to do that. And the exact opposite. It's a sport. Coaches coming down saying one of our guys bench. Well, if our sport coaches cares so much about bench press, well, then what do you think I got to do? Well, I gotta bench my guys so we could get those numbers so I could look like, you know, I'm validated my job. Well, how about we take something that's oh, universally accepted. So how about a counter movement? Jump out force plate. Now, I'm not saying everybody has forced plates, but you could just use jump height. Friend sits. Who cares how you got there? As long as you are trending right, that's all that matters. Why should we be fixated to a certain methodology or a certain pattern or not? Pattern but exercise. Just give them a pattern, let him choose. And to be honest with you, if it feels right, it's going to fly, right? If it feels good to do attract bar squat, opposed to doing a front squat well, they're probably gonna put more load and they put more load that I'm going to get the stress response adaptation. If I don't like the front squat because it's choking me the hell out. Well, then I'm probably not going to put his much load on it. Now, I have a negative connotation now have all these internal stress is going on, and then I'm gonna have a weird as look atyou, saying I don't like what we're doing in here. So now you think the quote unquote Byeon is going to be there. So now we're not getting any stresses that are going to give me that positive adaptation I'm looking for. So at the end of the day, if I can give them the education tto, learn how to do these movements and how to choose for themselves, well, then now it's not just what they did here for four years. I just gave them skills for the rest of their life. And if they're good enough to play pros now, they can take that and they can articulate it to the next coaching stuff so they could do a better >> job. No, that's that's awesome, man like this. A lot of things I want. I head into their I'LL keep it all Diamond all nine hundred promised. But I couldn't agree more and one of things that you say, you know, let's have a king P I They said jump high, for example, a point of reference. Then let's not care what we d'Oh, to the extent I mean not care. But let's not constrain ourselves of what we dio in order to improve that k p I. So the way I think about it, it's kind of like you ever use waze before that? Yes, that we got right. It knows to things and knows where you are. It knows where you were. If you're driving, it knows where you're going. Road. And then as okay, all I care about getting to point B So it will take you on detours left and right. Little Granny is driving slow in front of you for the pothole. If whatever is going to find the best way to get there, it doesn't care how it gets there, right, Right. And so work that it's say, OK, let's get the sevens environment where we can learn. And we know we need to get to be for me. And I'm not gonna say to go in a straight line because you might go through building and crashing hit pedestrians. We're gonna find a way to get to be. We're going to find a way that makes sense for the athlete and yourself. So my teaching them, you know, let's have you like and learn to do some of these movements then don't know taking a left at this next stop light to get to point B will be quicker than you saying go straight because they're the one in the driver's seat, right? And if that educational environment where you start to look at this a really complex system, her planting a really simple abie model and apply it to something as complex as the human body so that we can learn. And the example I give. It's like, you know, the ways part like, that's the more complex and assumptions we make more room for aeri half All right, we'Ll screw this. We assume that the sumo gets here. Well, if we assume in order to get to A to B, we got a one a two a three a four, a five. But any point on the line that, you know, assumption breaks, we don't get to be all right, you guys, you stuck at a whatever and doing. You know, we have to follow this waterfall method. It's very much a living method where things come in, things come out, things make you change. But you know what? You want to go? I >> mean, it's we work in team sports. Like the only objective we are the only objective that matters is wins and losses, period. Right? So if I wasn't a stopwatch sport, maybe my mind would change a little bit, right? Maybe I got okay. We need to drift towards this because literally it's did you get faster? Did you not get faster? Right? Swimming whatever you're doing, maybe these are the things we need to do more often to make that happen. But I'm dealing with incompetent. I mean great human beings, but just physically incompetent. There's still learning about their bodies were still growing into their bodies. I think it's the most arrogance thing that a strength coach could do is to say, Here's a program that's gonna get you better for six weeks. What? What is that? Even here's a block that's going to get youto point me. How do you know Like, till you know Saddamist like, can you honestly tell me that following this six week plan is doing that? Hey, they got sport practice. They got exams, they got pick up your tell me none of those factors could potentially there off your little plan or that your little plan can go up. They're KP eyes, if you will, or their Their goal is just a play basketball. So that to me, that's where as this thing, it's like the most arrogant thing in our field and it just drives me up the wall. But the other day, like I got a sport coach who has all the faith in the world of me gives me the keys to the castle. He just tells me, Do what you think is best. I I report the numbers that he doesn't even know he needs. That's what's awesome about he's like Chord. I just trust you like these were things that I want to see my guys do. We want a quote unquote play fast. Well, okay, here's some standards that we can set And these Airways that we know we got quote unquote faster. Now, from the technical tactical aspect, that's where you guys come in and you guys got it. Apply what you think is best to make that happen, right? But I gave you the physical requirements. I told you exactly what you need to get done and how we got there. Now you guys apply the technical tactical aspect. And then there we go. Now we have a happy marriage is long as I can supply valuable information. It doesn't matter what the information ISS, and that's where everybody gets stuck on these controlled environment numbers like like looking, swatting inventions like Who cares? Like Who cares about written load? Load gets you to here right after that, it's all about It's all about speed. It's all about rhythm coordination, your vestibular system that there's so many things that go into making. You better not just, uh, put three fifteen on the back squat suite. No, >> that's you know. Yes, yes, I agree. I'm not going to deviate too far. My ma, you know how I work or my mind races and I don't go in straight lines. I apologized immediately. Good. I was thinking about your friend mentioned earlier. It was everything that this lately, too. People who've been the private sector's I work in personal training, and I worked in exercise clinic for two and a half years. Iowa State, where don't older adults randall off cool testing on them. But ultimately they showed up because they enjoy it. And one things that I think we I don't mean We have everybody some people forget is that it needs to be enjoyable back. And when you're in a private sector and you're literally your food is the ability for something to come back to you. Hey, it's really different and you start. You said Okay, you know what exercise and movement do you like, and then you manipulate How do I make that exercise the most effective exercise for that person? And that's what you kind of mentioned with the educational process for your athletes. You're taking this approach. Where? How did you get them to win? Firstly, they gotta want to be here, but they don't want to be who I try hard. And secondly, no Adam, take ownership of these movements. I really like that concept because it's really melting in the world of Hey, you're here. You have to get better. But everyone knows when you want to get better. Vs have to get better, right? The be out a little different and unusual marks Lefton excited to move. I just keep thinking about that from like the private side. That's really where, like the general public, and you could deal with great Alan to deal with a lot of athletes who really want to be there. But unfortunately, majority the world doesn't want to work out like they're they're not interested, and I hate to make an assumption, but it's hard not to think that it's either them not knowing or them intimidated that have to do something in there, right? Right. I'm like that mindset a beam to apply. Okay, let's have an ownership model that drives it, because if you talk to people, her successful personal trainers, they have a way to make sure people come back. Oh, for should join a box in a way that a strength coach you're no environment might not even have to be exposed to just because it's the nature of >> well, for me, like the off season. I mean, when I get a freshman, that's a great thing about basketball. But I get a freshman. I mean, maybe they picked up some weights like a B. There's still just such a greenhorn in the weight room. They don't know what's good and what's bad, right? So, essentially the off season is a little bit of dictatorship like Sorry, I'm to tell you what to do because you don't know shit, right? But the goal is to earn that autonomy as well. So, you know, my guys that are kind of like slaps like for the whole offseason. Well, their leashes a lot tighter like Nah, bro, you're going to do this because I know you need to do this. You have earned the right to have that a top. So I want to make sure that that's, like pretty clear, too, because if you just give autonomy all day and there's going to run over you. But the one aspect that I think that is so important with our autonomy is it's my biggest performance enhancer, and I actually had dated Approve it. Like if I just look at my C M J members from our force plates once again. Yes, there are some maybe eight sets of doubles or six sets of triples or whatever, right? But once again, that is Tendo based, like to a certain agree with most of our movement. So you know, it could be a triple. It could be a double. It could be a single. It depends on where they fall in on along those lines, but essentially the flexibility of the sets and wraps, the unbelievable latitude of the movement pattern that they're doing. But yet counter movement jumps in February. They are p r ng, not season. P R's. I'm talking life top ers Guys that have been here for three years are hidden from nineteen point one to twenty six point four. I can't say names the twenty six point four in February. So what does that say? It says that my biggest performance enhancer is the kids saying I want to do that. Cool. That's what we're going to do. >> No, I love it that zik perfect. If you want to be there, you're intense. Going to be high. You're going to try harder. You're going toe actually care about what you d'oh and that mindset really house dr an aspect of performance that otherwise we can't because all internal right korea we really started wrapping up towards the end you buy a couple questions for you before you go yourself thank you i appreciate it it's always good to have you next way clich a weekly cycle korea >> will make a >> record you know fire i slowly thanks for having you guys we wanted to come with because you're a scientist I mean, if you had to share a bitter fight and this is to anybody and this isn't their coach, Jenny, where nobody is looking to enhance their fitness, their performance, um, their overall well being You that with activity, right? How is what would you advise someone to get into and regards Tio training our house to someone Initiate That's on top of the micro dose in a kind of giving that much of credit here, obviously some e How does someone injured? I heard it put that way and I'll get straight to the point that one look into into exercise probably should do some form of micro dose in to see if you even like it everyone to overdose. How do they start that process if they're not athletes per se how they decide where they began? >> Well, essentially is what do you want to end up like, What's the what's the point beyond ways, right? Do you just want to look aesthetically better? How aesthetically do you want to look? Do you wanna look like a big body voter? Do you want to look like a swimmer? What do you want to look like? And I think that the vein than fan ity. And I mean, that's what drives my basketball players there in tank tops here around. Of course, they want nice arms. Right? So there's certain things that you gotta know. Like, I want to look like this. Now, some of the performance guys, Maybe I wantto sprint faster or jump higher. Like that's a whole another aspect. But we're talking about general population number one. What do you wanna look like? Okay, so if I'm three hundred pounds and I want to lose some body fat for my own general health and I want to, you know, be more presentable, if you will. And smaller clothing. Well, then maybe just walking ten minutes every day, and then you start adding layers to it, So Okay, You know what I mean? Killing these walks. How about we go Stairmaster? Okay, that's a little tougher. Okay, how about we introduce maybe some med ball exercises because that's not necessarily too complex to do that. I can do it through different ranges. It's easy to manipulate. Okay, Now, let's take a dumb bill or kettle bill. Then we work our way to a bar bill and now. Oh, man, what do you know? I just dropped one hundred pounds and in them. Oh, before all of that eating. But like, we're just talking about the physical aspects, but as far as that, where do you want to be? Okay, I want to look like Brad Pitt. OK, for one, get plastic surgery. But if you want to look cool air at Brad Pitt and Fight Club Okay, well, these are the things that I need to do. So let's reverse into near the process, okay? He cut his little jack, so that means he's got muscular strength. OK, cool. So that means weights are going to get involved at some point we'll he got really lean for this too. So my general fitness sucks. Maybe I just need to start with walking. Maybe a jump rope, maybe just medicine Ball toss is something that's super easy. The number one. What's going to make me more consistent? What consistency is goingto win? It's not. They'll work out you do that's going to make you go from a counter movement jumped a nineteen point one to twenty six point for It's the consistency that got you there. All right. That was a two year process for that kid. Just to get to that point, right? If you try to hijack the system, if you try to go, I want to get from point A to point Z like that. Well, you're going to run into multiple things. One possibly injury and two. What's the real reason why you're Russian? The real reason why you Russians, Because I don't want to be there in first place. Now you've just ruined the whole concept. Now you've just ruined the journey. To me, that is much more important. Like when I used to be a fake body motor, if you will, that when I try to get ready for shows. I don't remember the show at all. The only thing I remembered was those nights where I was damn hungry those mornings where I had to get up, do my quote unquote fasted cardio meal prep backs without remember only big. How I was on stage for forty five seconds like that was twelve weeks for forty five seconds. Right? So that's where you gotta understand like it's the beauty or what is it that Jake whole line of the beauty is in the is in the cash. Basically what? The thing that you want to fall in love with the most is the adversity that they were going to fall in love with the most is the stressful points. That's what's going to create the beauty, if you will remember that Jake Colon. But essentially, that Google >> search really quick pressure that the Brad Pitt Fight Club I >> mean, that dude was solid, Man, that was a solid right. May like Brad Pitt. He was a pretty boy until fight club. And I was like, Yo, that is some white trash. I would not mess with him. He can go. >> Uh, great. I love it. Lastly, Yeah. Course lesson. Where do we find you? On social media and other venues? Assault media were coming here more than beauty and wonder himself. >> Yeah. So Instagram is probably what you can find me on the most slash strength as C h L E s strength. You could find me there pretty active on it. You want to see so naked cats? So to sphinx, with my beautiful wife and ah, multiple podcast. I'm on a lot of different podcast that you just Google. I, too, are goingto iTunes type in my name. You'LL find many other platforms where I go into a lot more depth about how we train on And then, of course, speaking engagements. I do multiple speaking, engage with the nationally and internationally. And so there's opportunities to meet me in person there. >> There's beauty in the struggle. >> There is beauty in the struggle. This beauty >> I got my end. >> Yes, there is beauty in the struggle. That's when they >> get here in Britain, right? Right there. Where >> you Brooks. But there's beauty in the struggle >> A lasting well, Korea appreciate you have coming on here. I mean, I hope something useful. I >> was one hundred percent. My pleasure, Max. I love working with you, man. >> Now you do. And anybody curious about Corey? I mean, I really encourage checking out his social media. Yeah, I know. It's a lot of crazy stuff on Instagram that is really thought provoking. Put it that way and I can't believe it. Oh, my goodness. I can't let you escape Korea quite yet. >> Well, what you got? >> Uh, whole off the exit. Give me five minutes on it. I was going to ask his social media is going to ask. Yeah, way rehab itself. Yeah, to spring loaded monster man who means you want to share a little bit on this because I know you have been doing this yourself. Yeah, this is it in chorus singer based Achilles program. I love some of the actors. I love thee, not the unloaded foot contact under your hand motion who was seen Alice into this isn't the course in a chair, and he's for lack of better words. Words. MacInnis foot on the floor like a pogo stick and doing extremely extremely unloaded movements early on that site, too early on but in the rehab process itself to introduce low level plyometrics, He's doing band assisted jumps. He's doing isometrics. He's doing heavy squads. He's doing some bar bell curls. All things important for the curies. >> Sure are. Absolutely yeah beyond you. My understandings of the lower leg complex is off the charts because of my injury. So for the viewer's eye, tor macula or a ruptured my Achilles tendon with a full rupture but right at the insertion, which is the very atypical tear because I've been dealing teno sis for over a year before I tore it. So they had it cut me up top to bring me down low, if you will. So usually Achilles ruptures that all they do is bring it together and then tie it. There are. So it through the mind was at the very bottom. So essentially, they had to cut me up top toh length and me and then, uh, suitors through. So is very atypical, which sucks only that that part sucks. Spike. Um, it's not that I am Well, maybe a little bit arrogant, but I honestly want to take full control of my physical therapy because I think that intuitively I understand the process not just of rehab, but of how to increase performance. So all I did was watered down as much of that is possible and truly started as soon as I got to the pain free. And so, yeah, with all the unloaded stuff, it just made sense to me like that's something you just don't see in physical therapy to It's kind of blows. My mind is what's the first thing to go like when you get older? What happens? Will you lose your ability to do very forceful things or to lose power or the ability to generate power. So that's the first thing that came in my mind when I rupture. Or when a Torme Achilles was okay. I need to go back and not be old because essentially, I'm staying still. So if I'm staying still, it's like use it or lose it protocol. So from that perspective, I told myself, I need to move fast at some point. So I started with all my available limbs at the time, just moving fast. Then I progress toe when my suitors seal or excuse me with my I want my wound healed. I got into the pool, so that's the most is about is unloaded. You should get, and all it did was just frail. My leg and there a cz muchas I could through different planes and of course, he has fold up. But of course, it's going to like your adding a stress. And so I just did it Mohr or Mohr. And so I just Kim. Training fast, even though, is the most unloaded way you can do it. And then, like Max was talking about, I got to a seated position and I just started doing be most unloaded pogo jumps you've ever seen or ankle pops or whatever you want to call it. So then I transition to standing on it isometrics, then putting more force into the forefoot isometrics. And then I started using the bands I mean super heavy bands and then just started like Pogo's and then start lighting the bands I went to arm went the body weight. To me, it's like super common sense, but I don't know, maybe the physical world. It doesn't really look at it that way. They look at it and isolation opposed to global. So to me, I knew if I could quickly get back to global patterns that I will be able to promote healing faster. And so, like Chase talked about, his last one ought to be a far protocols. Luckily, I had him as a resource to help me with my healing process, but right now, on that four and a half months, almost five months, and I'm doing some pretty cool things if just to give you a point of reference. Dez Bryant, wide receiver. He tore his a week after mine, and essentially, you guys Essentially, he's What's a similar athletes level athlete? You know, very someone. Uh, actually, he's going to be up until eight to nine months. John Wall tour has a few months after mine. He's going to be an entire year for his process. Boog, Golden State warriors took him a whole year to get back on my goal. If I can get it back and lesson seven months, that means I did something, right? >> No, I love it. Well, that's tough stuff. Get to see if you check out his instagram page. So me, please, dear, do yourself a service. Go check out the man. He's a good dude, Tio. So sometimes no kid. Don't >> you know you're right there, e >> I don't want call corps on a bad day. >> You >> know, it's all good now. I really appreciate it, man. Thanks for being on here. And, uh, again we follow sometime in near future. I feel I'm expecting that shirt. By the way, where is my core bighead T shirt? >> You know, I want to find one of my earlier body building picks, and I'm gonna put it on a T shirts and, Tio, >> I love it. How I rocked the hell out of it. Man, >> you're beard in a most >> and be right here. Yes, right behind. Maybe my postal records slash proposing bronze and gold. You're welcome. You're welcome. An absolutely huge in that >> purple banana hammock to >> Wouldn't ask for another way. What? The full real deal. Korean stage. Ready, you know. Awesome. Well armed man up that thing. You guys, Listen, I appreciate it. Great South Korea on. If we're curious about finding more, check him out on instagram and look for Teo. No doing more. These in near future. >> Awesome. Thanks, Max.

>> Live from Las Vegas it's theCUBE, covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> Hey welcome back everyone, we're here live in Las Vegas, for AWS re:Invent 2018. Our sixth year covering, I'm John Furrier with Dave Vellante. Dave, it's been a wild ride, a lot going on, changing formations over the years, cloud is kickin' butt. >> Innovation, growth. >> Partnership with VMware's paying dividends. The ecosystem's evolving, startups are having opportunities. C-Chains is here. Tom Gillis, Senior Vice President and General Manager Networking and Security Business Unit at VMware is our next guest. Great to have you Tom, thanks for comin' on. >> Thanks gentlemen for havin' me. Yeah, it's good to be here. >> I'm glad you're on, because one of the things I'm always excited about is networking. If Stu Miniman were here, he'd be all over this conversation as well. It's hard, it's been part of the holy trinity of infrastructure, network, compute, storage, is never going away, but it's changing. There's new abstraction layers, there's new opportunities, you're now living and breathing and working on with VMWare, and they just, ways to make networking better. How's it going, what's the update, what's going on in networking, this Outpost deal is really interesting. You bring in worlds together, in a consistency-- >> You hit the nail on the head, right. We're bringing the worlds together. And I think, one of the things we're seeing, is that, in the enterprise, enterprise IT is looking at an increasingly heterogeneous data center environment. In in the next 12 months, you're going to have data center, where one rack is running EC2, and your data center, one rack is running vSphere, in your data center, another workload is running on Amazon, another one is running out of the Edge, so tying this all together creates some challenges, and this is a problem I think VMWare is uniquely suited to solve, networking is the fabric that connects all these disparate islands, and lets them talk to each other, lets them talk to each other in an orderly way, right? So, networking is about connectivity. It's also about policy enforcement, those are the two things we focus on with the intersects team at VMWare. >> And I'll say, as the landscape changes around how cloud impacts it, no perimeter, but networking still has to move packets from A to B, storage goes from now to then, so things are moving around. So networking is constant, straightforward and consistent, you got to move packets around. >> Yes, this is an important thing that I think people get confused on, is, when they understand, they look at the numbers that we're posting in networking, it's all software networking, right? We don't move packets from A to B. We do the policy administration. So, something has to move the packets from A to B. Cisco's switches, Arista's switches, there's a lot of really good networking hardware out there that's not going to go away any time soon. But I always say, use the right tool for the right job, so, a product like Cisco ACI is a fabric manager for a switch. And NSX is a policy layer, right. It's a software networking layer, and something we learned from the public cloud is that, you can automate network deployment using this software networking approach. How many networking people does it take to deploy a workload on AWS? >> Zero. >> Zero! You push a button and it goes. So we're giving you that same capability on-prem, within a stack, so it's automation that allows you to automatically spin up and deploy a network, and a policy to go with that network that makes sense. >> How does that impact the largest networking vendor on the planet, Cisco? How does that scenario, and how do you guys work together? Is it conflicting, is it together? >> As you pointed out, the electrons have to move from A to B and Cisco is really, really good at doing that, actually moving electrons, doing it cost effectively, efficiently, at scale, hard problem to do. So we work very closely with Cisco to make sure that, NSX and, you know, Cisco's products, are interoperable, that they work together, they solve different problems. The problem that we solve with NSX is the policy piece of it, web server can talk to app server, can talk to database. That's a very simple policy, but when you try to express that in IP addresses, that could be 5,000 firewall rules, and in NSX that's one rule, it's English language. So it's that simplicity of software networking, allows us to enforce policy, in a increasingly heterogeneous environment. >> Okay, so let's talk about Outpost a little bit. You're got two versions, if you will. You've got VMWare Cloud on AWS Outpost, and then your piece, which is the cloud foundation for EC2 on Outpost, so that's low-latency, it's consistent networking, talk about that piece of it, drill down, and some of the challenges that you had to solve. >> So, as you pointed out, we think Outpost is an industry-defining announcement, because it's really blurring the line between private and public cloud. And VMWare and Amazon have partnered very deeply to continue to make this just feel like one thing. And the piece of the puzzle that we bring to the table is infrastructure, so policy management, that connectivity, the web server talks to app server, who gets to talk to who, security policies, data management and protection policies, these are things that customers expect from us. It's very easy for us to deliver that in a VMWare, vSphere environment. I think you talked to my colleague Mark Lohmeyer, about VMC that's going to run on Outpost, that's a VMWare environment running on Amazon hardware. We also are introducing services that are going to provide VMWare capability in a native EC2 environment running on Outpost, that's what we call VMWare Cloud Foundation, or VCF for short. >> That's a particular instance of Outpost, there's also the Amazon version, how do you guys doing under the covers? Explain how it works from a VMWare standpoint on the premised piece? Talk about under the covers. >> As you pointed out, the trick is to get all these disparate hybrid, you know, clouds, these different kind of islands the capacity to talk to each other. And so we've worked very closely with Amazon team to take NSX networking, embed it into Outpost so it can talk seamlessly to enterprise networks of all shapes and sizes. That's a deep, important part of the relationship. And in addition to that, we're putting the VCF capability into EC2 to extend consistent policy enforcement, either in a vSphere environment, private thing that you're managing, the hybrid thing that maybe VMWare is managing, or that Amazon's managing, in any scenario we're going to give you one set of policy, one set of enforcement across all of this with VMWare Cloud Foundation, as well as the VMC on AWS. >> The software engineering and engineering in general for the data center, where there's hardware, software, the generations of developers have all had the same kind of language, just changes tone. Put a wrapper around it! Container, VMs, but now all the same principles. You want to make something smarter and better like an old mission critical work load, you put a wrapper around it, you kind of put software around it, and you can still run that and have new modern ways to add value to it, connector, whether it's a Micro service or an API, is a trend, the heterogeneous environment you just described, EC2 rack over here, isn't this kind of like a container for the data center? In a way? >> My view on this, and I think Amazon is really pioneering this front, the data center is becoming an appliance. When you think about it, like, every enterprise is buildin their own data center with their own pieces parts, that's nuts! It'd be like, every company building their own furniture. Yeah, you could do it, but like, really? Wouldn't you just rather buy this desk from a furniture maker? And so, Amazon has built an incredibly efficient, incredibly powerful, call it an appliance, this hardware infrastructure, that works, and it works at scale, and it's easy to use, and you can get it in two days, it ships with Amazon Prime, that is super compelling. And I think a huge amount of customers are going to look for that simplicity, that easy of use, what's necessary, you pointed this out, is an abstraction, software abstractions, that's what VMWare does. We create software abstractions to simplify the administration of all the bits and bytes, all the electrons that are flowing from A to B. We make that stuff easier to manage, with virtualization technology, that is an abstraction. >> Operational-wise, I think it is the very key point too. How do you get it to run? (chuckles) Operating the networks, operating the data center, operating systems that feed developers value and giving developers a programmable infrastructure, that's the vision of a software-defined data center. >> So, you talkin about, data centers as an appliance, I always thought Larry Ellison had it right. You develop all these appliances, like the iPhone, for enterprise, the problem was just Oracle, very narrow set of use-cases. I feel like, in a way, that I felt when the Warriors got K.D. Right? That's what Outpost to me, is like, it's almost like an unfair advantage-- >> Game over! >> It changing the game, here, so I, look, VMWare is a software company, you love anybody who will run your software on their hardware. >> But Even Duran is a great analogy. >> But you got to think, that the guys who been playing in this, you know, on-prem cloud market, are going to say, "Whoa, what do we do now? How do we respond," how do you think that affects some of your other partners? >> I think the magic of what Amazon is doing, is it's simplicity from A to Z, meaning, I have a work load, I need to deploy it, I push a button, two days later, this rack of hardware shows up at my data center, you plug it in, it talks to the cloud, it hooks itself, like, that's awesome, right? >> Patches itself, I don't have to worry about it. >> The thing they got to remember, is that data center is a means to an end, not an end in itself, right? What is a data center supposed to, it's powering software that powers the business, and companies are spending too much time building the machinery to power the software to power the business, and they want to focus on the software that's powering the business. >> Software is the world. >> Too much head count, involved in-- >> It's just a lot of work, a lot of energy, a lot of bandwidth, a lot of attention, a lot of arguing, a lot of debate. >> Move that head count into high-value activities. >> Exactly. >> That is really, I think, the key point. And again, it became its own cottage industry, for the wrong reason! >> Yeah, I feel like, working with Amazon, we can simplify how you build, deploy a data center. There's an unsung hero in this equation, that is Intel. Intel is just making these processors faster, stronger, and so, we see less and less need for highly-specialized general, specialized servers, we can go with a more generalized compute infrastructure that can cover a wider array of workloads, including networking. We're using Intel processors, and we're running 40 gigs of enterprise-grade networking-- >> I got to say Tom, that's a great to point out Intel, I was reading the news on my phone, just in between breaks here, the news articles, "Oh, Intel's new competition with ARM," what they don't understand is, this is a massively expanding addressable market. So it's not a winner-take-all, Intel doesn't have to get every deal. 'Cause there's specialism at the silicon-level now, to power these software abstractions. >> To your point too, a decade ago Paul Muret said, "We're going to run any workload, "any application, anywhere in the world, on VMWare," and a lot of people laughed. And said, "You're not going to move some of the SAP stuff, or Oracle stuff," it all went, I mean, except for very, very few. And that's to your point, it's a general purpose system now, that can pretty much do any mainstream commercial app. >> So with the power of an abstraction layer, now we can optimize, and I think we're still learning the details of what exactly Amazon's done to optimize, but we all know, it's powerful, right? And now, you can get that in Outpost. >> They've got some street cred! >> Yes, they've got some street cred, yes. >> Tom, great insight, thanks for coming on theCube. >> Gentlemen, thank you for having me, this is good-- >> Great stuff, Senior Vice President, Senior Executive at VMWare, breaking down the relationship with Amazon, it's like the Golden State Warriors getting Kevin Duran, they run the table, if they had Lebron, that'd be like, best analogy. We'll be back with more live coverage here at theCube cover of AWS Reinvented after this short break. Stay with us. (punchy electronic music)

(upbeat music) >> Hello everyone. I'm John Furrier here in Palo Alto at our CUBE headquarters. We're here with John Del Santo, Senior Managing Director at Accenture for a Cube Conversation. John, welcome to theCUBE. Good to see you. >> Thanks, John. Great to be here. >> So we just talked before we came on camera about Accenture and all the stuff you guys are doing. You guys are in the cloud heavily. We've been following, you guys have probably one of the most comprehensive analytics teams out there. And global SI market and just, the world's changing. So it's pretty fun. I'm looking forward to this conversation. So I got to ask you first, before we get started. I want to jump in with a ton of questions. What is your role at Accenture? You're in the Bay Area. Take a minute to explain what you do for Accenture and what's your territory. >> I've got the best job at Accenture. So, Accenture's got close to half a million people right now and my job is, I'm responsible for our business on the West Coast, across all of our industries, et cetera. I've been here 32 years, so I've seen a lot of things happen in the Bay Area. And I now have the responsibility of making sure that we're doing great work for our clients. And we're doing great work in the community. And then we're providing great opportunities to the thousands of people that work for us here in the Bay Area and across the West Coast. So it's a lot of fun. >> Obviously, West Coast is booming. And for tech it's been a hotbed. And obviously the industry's across the board now is global. I got to ask you because, you know, you've been around multiple waves of innovation. And Accenture's been, had their hands in enabling a lot of value creation for clients. You guys have a great reputation. There's a lot of smart people. But the waves are always kind of different in their own way, but sometimes it's the same. What's different about the way we're living now? Because you can almost look back and see the major inflection points. Obviously the PC revolution, client server, interoperability, networking stacks went standard. Then you saw the Internet come. Now you've got Web 2.0. And now you got the whole global, you got things like cryptocurrency and blockchain. You have multiple clouds. You have a whole new game-changing dynamic going on with IT infrastructure combined with opensource at a whole 'nother level. So how is this wave different? Is it like the, how would you compare? >> Well, I think all the technologies that have waved through my career, at least, have been real enablers for the business model that the companies had at the time, and that they evolved. What we see now is epic disruption, right? So, the waves now are, we have digital native companies that are just disrupting the heck out of the industry or the company that we're trying to help. And so it's now about pulling all of those technologies together, and really figuring out a new business model for a client. Figuring out a new distribution channel, a new product that's maybe natively digital. And so it's very, very different, I feel, then it was five, 10, 15, 20 years ago, through some of the other waves. >> Talk about the things going on in the Bay Area before we get more in the global themes, because I think the Bay Area is always kind of a leading indicator. I call it a bellwether. Some cool things happened. You've got things like the Golden State Warriors got a stadium that's being built. I'm watching the World Series with the Red Sox, and you see Amazon stat cast, you're seeing overlays, you're seeing rosserial. All these things are changing the work and play. The Bay Area's got a lot of leading indicators. What are some of the projects that you've been involved in? What's happening now that you think is worth noting, that's exciting, that piques your interest? >> Yeah, I mean, we work across every industry, and we do a ton of work in tech, but I actually find some of the more interesting projects are the ones we're doing for healthcare companies in the Bay Area, some of the utilities in the Bay Area, some of the big resource companies, some of the financial services institutions, 'cause, like I said before, all of those industries have disruption coming or have been disrupted, and so we're doing some work right now around patient services in healthcare and in pharma that is really interesting. It's meant to change the experience that a patient has, that you and I have when we interact with our healthcare providers or, you know, the whole industry. And so those kinds of projects are real interesting cause a lot of these industries are old and sort of have a big legacy estate and model that they need to transform from. So they need to move fast, and we kind of describe it as a wise pivot. They sort of need to move, but they need to make sure they're moving at the right time. They can't hurt their existing business, but they got to pivot to the next business model, and that's happening in lots of places. And you're right, I think it is happening a lot in the Bay Area and the West Coast as sort of a bellwether. >> I want to get your thoughts on some of the moments that are going on in tech. You mentioned prior, before we came on camera, you worked for Apple in the old days. Tim Cook was just recently tweeting yesterday, and that tweet's going around, privacy. He was at this big GDPR conference. The role of regulatory now is changing some of the West Coast dynamics. Used to be kind of fast and loose West Coast, innovate, and then it gets operationalized globally with tech, tech trends. What's the tech enablers now that you see that are involved that actually have to deal with regulatory, and is regulatory an opportunity? You're mentioning utilities, finance, those are two areas you can jump out and say okay, we see something there. Privacy is another one. So you have a perfect storm with tech and regulatory frameworks. How has that impacted your job in the West Coast? >> Well, I mean, GDBR, we live with everyday. And clearly we're doing a ton of work in Europe. And I think that's one of the advantages Accenture has of being a big global company, and being able to take lessons learned from other parts of the world that are likely to come to the United States, et cetera, so, but I think the combination of tech and regulatory are going to be merging together here pretty quickly, especially when you talk about AI and data privacy, and that sort of thing. But it's definitely been an evolution. Great to hear Tim's point of view on what Apple thinks. And it's been really fun in my life to see Apple in the 80s when I worked there. They were a client of mine in the 80s. I worked with NEXT Computing in the 90s. And then obviously they're a big partner of ours now, so it's been a really interesting evolution. >> What are some of the growth accomplishments you guys have in the Bay Area? Obviously there's been growth here for you guys. Obviously, we've been seeing it. >> Well, I think the amount of tech-driven disruption, or digital transformation, we call it, is growing like crazy. So, you know, 20 years ago we were doing a lot of eCommerce work. We kind of shied away from doing Y2K work and a lot of our competitors saw that as a big opportunity. We didn't think it was a lot of value for our clients, fixing the old systems. And so we pivoted to eCommerce in a very aggressive way. And I would say now that's evolved even further, where more than close to 2/3 of our business here on the West Coast is what we call the new, which is clouds, security, digital analytics. And I really think it gets down to, we were talking a little bit earlier, about the data. And so we have more data scientists than we've ever had. We're probably hiring one or two every day out here on the West Coast. And it's about the data. Data is driving our consulting business. It's driving our technology business. It's driving what we're doing with AI, obviously, and things like that, so. The transformation's been pretty tremendous. >> So take a minute to explain the difference (mumbles), data, you mentioned a lot of things, you got data in there, you got cloud, and you mentioned earlier you got kind of cloud first companies, got born in the cloud, born in AI, AI first, data first, these new companies that are essentially disrupting incumbents, also your clients, that are kind of born before the cloud. And they got to transform. Is digital transformation one of those things or both of those things? How does digital transformation translate to the clients that you guys work with? >> Well, every client has a unique set of needs depending on where they came from. We do a lot of work with the digital natives. We do a lot of work with the unicorns out here on the West Coast. And their needs are different. You know, they need to learn how to scale globally. They need help in the back office. They need help sort of maturing their business model. We do a lot of work with legacy financial services companies, healthcare companies, that sort of thing. They need to figure out how to sort of, you know, pivot to digital products or digital interactions with their customers. We have a very large business now in Accenture Interactive around helping to find customer experiences for clients. And we think our mission is sort of help our clients really redefine that relationship with their customer, their supplier, their supply chain, and the experience is a key part of that. Given expectations means a lot. >> We have a lot of CUBE Conversations around IT transformation as well. And I had a CIO, big time firm, we won't say the name cause it'll out em, but he said, "We've been outsourcing IT for so many years, but now we got to build the core competency internally because now it's a competitive advantage." And they have to ramp up pretty quickly. Cloud helps them there, and they need partners that can help them move the needle on the top line. That this is not just cost control and operational scale or whether it's horizontally scalable scale-out or whatnot. Top line revenue. This is where the bread and butter of the companies are. >> Right. >> So how are you guys engaging with the clients? Give some examples of how you're helping them with the digital transition to drive their business, how do you engage them? Do you do the standard sales calls engagements? You bring them to a technology center? As the world starts to change, how do you guys help those clients meet those top lines? >> Well, a perfect client for us, you know, we're really good at helping clients cut costs and get really efficient and be good with their peers on cost structure. We love a client where they want us to help em with that and they want to pivot the savings to the new part. The way, one of the things that triggered a thought when you mentioned that was we like to bring our clients into our innovation hubs, so we've had labs here on the West Coast for a long time. We now have 10 innovation hubs in the U.S. We have a very large one in San Francisco now, and so we'll bring a client into our innovation hub and really roll up our sleeves with the client and over a week or two weeks or three period of time, we really brainstorm on envisioning their future for their company, build a minimal viable product if we have to out of our rapid prototyping capability and really envision what the target and state of their business could be, of their product could be or their customer interaction and we'll model it. Rather than sort of do a study, do another study, do a PowerPoint presentation, it's let's roll up our sleeves and figure out how to really pivot your business to the new and then take it from there. >> And they come to your location Absolutely. >> For an extended period of time? >> Yeah, so we'll have, any given day we'll have at least two different clients in our location doing either a couple a day workshop, a multi-week workshop, and it's co-creation. It's us collaborating with our client to figure out a solution. A good example is we had one of our large clients from the West Coast in there recently and we were trying to figure out how to use drone technology to drive analytics in, you know, over a geography to provide better data for them to minimize risk. And we've got a number of co-creation projects now going on with them to figure out how do we take that into a solution that not only helps their business but maybe it is a commercially available system. >> Yeah, our Wikibon research team brings us all the time with IOT and security you're starting to see companies leverage their existing assets, which is physical as well as digital and then figure out a model that makes them work together because these new use cases are springing up. So what if some of those use cases that you guys see happening, because you mentioned drones, cause that's an IOT device, right, essentially. There's all these new scenarios that are emerging and the speed is critical. It's not like, you can't do a study. There's no time to do a study. There's no time to do these things. You got to get some feet on the ground. You got to have product in market, you got to iterate. This is devops culture. >> Right. >> What is an example? >> So we did a project for a big ag company and not actually a West Coast based company but they came to our labs to look at it. And basically what we did was, we covered an area that's basically the size of Delaware in terms of drone video and we were able to drive analytics from that and ten times faster figure out for them where the forest was weak and where it wasn't. where they ought to worry about vegetation, where they might have disease issues or other risks that were facing them. And those analytics we were able to drive a lot faster and so rather than manually going around this huge square mile set of geography, they were able to sort of do it through technology a lot faster. >> Yeah, just a side note. I was talking to Paul Daugherty and interviewed him. We were celebrating, covering the celebration, your 30th anniversary of your labs. And one of the interviews I did was a wacky idea which made total sense, was during like a car accident or scene where there's been a car accident, they send drones in first and they map out the forensics- >> Sure. >> First. And you think, okay, who would have thought of that? I mean, these are new things that are happening that are changing the game on the road because they'll open up faster. They get the data that they need. They don't have to spend all that physical time laying things out. This is not just a one-off, this is like in every industry. Is there an industry that's hotter than another for you guys? (mumbles) oil and gas, utilities, financial services is kind of the big ones. What are some of the hot areas that you guys see the most activity on, on this kind of new way of taking existing industries and transforming them? >> I don't know if I could pinpoint an industry, I really don't. I mean, because I see what we're trying to do with anti-money laundering and banking is really moving the ball forward. What we're doing with patient services and pharma in health care is pretty aggressive. Even some of the things that we're doing for some of the states and governments around citizen services to make sure that ... Cause all of us have expectations now on how we want to interact with government and our expectations are not being met in just about every department, right? So we're doing a lot of work with states around how to provide a better experience to citizens. So I don't know if I could pinpoint an actual industry. One of the fun ones that we just, that we're involved with our here in our patch is one of the big gaming companies in Vegas. We are doing a lot of video analytics and technology and again, it's something like 20 times faster being able to detect fraud, being able to figure out what's going on on a gaming table and how to provide rewards quicker to their customers, keep em at the table faster or longer- >> He's got to nice stack of chips. Oh, he's going down. (laughs) Give him a comp through, he's feeling down. Look at his facial expression. I can (mumbles) imagine, I mean, this is the thing. I would agree. I think this every vertical we see is being disrupted. Just mentioned public sectors. Interesting. We were riffing at an Amazon event one time around who decides with the self-driving cars? These towns and cities don't have the budget or the bandwidth to figure out and reimagine the public services that they have, they're offering the citizens. The consumerization of IT hits the public sector. >> For sure. >> And they need help. So again every industry is going on. Okay, well I want to step back and get some time in for analytics because you guys have been investing as a company heavily in analytics in the past 10 years. Past, I think, seven years, you guys have been really, really ramping up the investment on data science, analytics. Give us an update on that. How is that going? How's that changed? And what's the update today? >> Yeah, and it's a good point. I mean, and again, you mentioned those labs being here for 30 years. A lot of our data scientists and big machine learning and big data folks frankly started at the labs here years and years ago and so, we've now got one of the largest analytics capabilities, I think, of any services company globally. We called it applied intelligence. It's a combination of our analytics capability and artificial intelligence, and we basically have an analytics capability that's built into all the different services that we provide. So we think it's, everything's about analytics just about. I mean, clearly you can't do a consulting project unless you've really got a unique analytical point of view and unique data around assessing a client's problem. You really can't really do a project or implement a system without a heavy data influence. So we are adding, frankly, I think every day I'm approving more analytics head count into our team on the West Coast in lots of different practices. And so it disbands industries, it spans all the platform sets, that sort of thing, but we're the largest of most of the big data players. >> I think one of the consistent trends with AI, which is now being the word artificial intelligence, AI, is kind of encapsulated the whole big data world because big data's now AI is the implementation of it. You're seeing everything from fraud. You mentioned anti-money laundering, know your customer, these kind of dynamics. But you get the whole dark web phenomenon going out there with fraud. All kinds of underground economies going on. So AI is a real value driver across all industries around one, understanding what's happening, >> Sure. >> And then how to figure out how to applications development could be smarter. >> Right. >> This is kind of relatively new concept for these scale out applications, which is what businesses do. So how is that going? Any color commentary on the impact of AI specifically around how companies are operationally changing and re-imagining their businesses? >> Well, I think it's very early days for most of our clients, most big companies. I think, we've done some recent surveys that say something like 78% of our clients believe that AI's really, really important and they're not at all prepared to deal with or apply it to their business. So I think it's relatively early days. There's a huge fight for skills, so we're building our team and that sort of thing. We're also classic Accenture. We grow skills pretty well too through both on-the-job training and real training. And so I think we're seeing sort of baby steps with AI. There's a lot of great vended solutions out there that we're able to apply to business problems as well. But I think we're in relatively early days. >> It's almost as if, you know, the old black-box garbage in, garbage out. You have good data, >> Exactly. >> and you got to understand data differently, and I think what I'm seeing is a lot of data architects going on, figuring out how do we take the role of data and put it in a position to be successful. It's kind of like, cause then you use AI and you go, that's great, but what about, oh, we missed this data set. >> Right. >> You'll have fully exposed data sets, so this is all new dynamics. >> So you have to iterate through it and you'll have to (mumble) solutions that'll start and restart. >> All right, so final question for you. Talk about this technology hubs again. So you have the labs, get that. So how many hubs do you have, technology hubs? >> Well, in the U.S., there's 10. But I would say in the West Coast it's really San Francisco and Seattle right now, with San Francisco being our flagship and frankly it's a flagship in the U.S. We've had the 30 year presence of our labs here on the West Coast and we've had design studios on the West Coast. We've had our what we call liquid studios, which is a big rapid prototyping sort of capability. We've had our research, et cetera. We've pulled all of those locations, so our lab started in Palo Alto, went to San Jose and is now in San Francisco. We've pulled all those locations together into what we're calling the innovation hub for the West Coast and it's a five-story marquee building in San Francisco and it's where we bring our clients and we expect to have literally, I think last year we had 200 and something client workshops and co-creation sessions there. This year we think the number's going to go to 400 and so it's really becoming a fabric of all our practices. >> How important is the co-creation, because you have a physical presence here and it's the flagship for the innovation hub and it's an accumulation of a lot of work you guys have done across multiple things you've done. Labs, liquid labs, all that stuff coming together. How important is the co-creation part as a mechanism for fostering collaboration with your clients? Co-creation's certainly hot. Your thoughts on co-creation. >> Great question, and I would tell you Accenture's kind of gone through waves as technology's gone through waves and so we were always an enabler for a client's projects and we did a lot of project work. I think we're in a wave now where we're going to be the innovation partner. We continue to sort of be named the innovation partner or the digital partner for certain clients. And we're going to do that through co-creating with them, and it's not just at their site, et cetera. It's going to be co-creation in our labs where we're taking advantage of the hundreds of data scientists and computer researchers and technical architects that we have in our labs to create something that's new and fresh and purpose-built for their particular business model. So we think co-creation is a huge part of the formula for us being successful with our clients over the next 10 years. And so that's why we've put this infrastructure in place, expect it to expand and to be sold out and that sort of thing. But it's a good way for us to build capability and really, really viable solutions for our clients going forward. >> So it's not just a sales development initiative. It's an operationalized engagement and delivery mechanism for you guys. >> Exactly, exactly. It's not, I mean it has, it self markets but it's not about marketing. It's about, we'll have tours and we'll have a little tourism through our center and so clients'll say, Wait, look at that maker lab. Look what you're doing with that client. I want one of those, right? I need to do that in my business, even though I'm in a different industry. So it's not really a marketing tool per se, it's a way for us to interact and engage with our clients. >> Well, it's a showcase in the sense of where you can showcase what you have and if clients see value, they can go to the next step. It's an accelerated path to outcomes re-imagining businesses. Okay, final question. What have you learned from all this? Because now you guys have a state of the art engagement model, delivery model, around cloud, all these things coming together, perfect storm for what you guys do. As you guys look back and see what you've built and where it's going to go, what are the key learnings that you guys came out of the West Coast team around pulling it all together over the years? What's the key learnings? >> Well, I think that our clientele is just thirsty for innovation and innovation now. It's now about sort of let's envision the future and we'll get to it some other day. It's what can we do right now and what journey, what glide path are we on to change our business? So the pace is just radically different than it used to be. And so it's about changing, rapidly changing, putting real innovation on it, and collaborating with clients in a pace that we've never seen before. I mean, I've been here 32 years and I've just never the pace of change. >> That's great, John. So (mumbles), really appreciate it. We'll get a quick plug in. What's coming up for you guys? What's going on in the West Coast? What's happening? >> Well, we're in event season right now, so we just finished all the ... We're wrapping up Oracle Open World. We just won five awards at Oracle Open World. We just did an acquisition on the West Coast to beef up our Oracle capabilities. We've got ReInvent and we have all kinds of events coming up but it's a, it's been a pretty busy season. >> So cloud and data have certainly helped rise the tide for your business. >> 100%. I mean, cloud is taking Accenture from kind of in the back of the office and put us into the front office over the last 10 years. >> Well, certainly it's awesome, (mumbles), leveling the playing field, allowing companies to scale out very rapidly, bringing a devops culture, new kinds of modern application developments, real value being created, super exciting time. Thanks for coming in and sharing your time. John Del Santo here in theCube for Cube Conversation, senior managing director at Accenture. I'm John Furrier here in theCube studios for Cube Conversation. Thanks for watching. (upbeat music)

>> Live from San Francisco, it's theCUBE, covering DockerCon 18, brought to you by Docker and its ecosystem partners. >> Welcome to theCUBE. We are live in San Francisco at DockerCon 2018. I am Lisa Martin with my co-host for the day, John Troyer. John, it is not only a stunning day in San Francisco, beautiful blue skies, this is a packed event. Their fifth DockerCon event and they've got between 5,000 and 6,000 people. We just came from the general session keynote, and it was standing room only as far as the eyes could see. >> Yeah, looks like a good crowd here, a lot of energy. Docker keynotes, always super interesting, they always do a lot of demos, they bring up a lot of employees. It's not just like a parade of middle-aged executives, always is super dynamic, a lot of demos. Really liked the keynote this morning. >> I did too. The energy you mentioned was great. It kicked off with... who's the name of that gentleman that is one of the rally guys for... >> Franco Finn. >> Franco Finn, who has worked for the Warriors, the 2018 Golden State Warriors, NBA Champs. So that was a great way to kick it off, but also Steve Singh had great energy, their CEO, we're gonna have him on shortly today. Scott Johnston, and as you talked about their employees and also customers. They have some really great numbers. They've got, I think, about 120 sessions this year at DockerCon. Nine big enterprise customers talking about how they are approaching containerization with DockerCon. One of them was McKesson, which is a 183 year old company with a lot of staff that gave a really compelling keynote or a, yeah, a keynote this morning about how they are moving and modernizing their data center with Docker. >> A really nice story, a really an emphasis on trust, an emphasis on developer usability, and I liked one of the points was, once we got the developers using it it became easier, and I think using the whole platform. Lisa, I think they hit a lot of familiar things for Docker: so, developer experience, really big for Docker. That's they way they started, that's what they're still counting on. When Steve Singh got up, he talked about community, their very first thing. Over half the people here, first time at DockerCon and over half of the folks are just using containers in the late last year. That means this whole journey is just starting. There's a lot of white space in the container world. So developer experience, a big announcement, preview announcement for Docker Desktop, being able to create apps off of templates and things like that but very developer-focused shows as opposed to some of the more IT-focused. There's a broad mix here but definitely a lot of developers here at the show. >> A lot of developers, as you said, but also, you're right, it is a mix. It's IT professionals, it's enterprise architects, and it's executives and that's one of the... one of the targeted audiences that, I think, both Steve Singh and Scott Johnston talked about, so it'll be great to explore. As the CEO and the Chief Product Officer respectfully, what are they hearing from enterprise customers who have a lot of challenges with legacy applications that are very difficult to manage and I also read some stats, they had some stats in the press release this morning, but 80% of enterprise IT budgets are spent keeping the lights on for enterprise apps which leaves about 20% for innovation and of course, as we know, organizations that can aggressively innovate are the ones that win. So I'm not only looking forward to hearing with Docker Desktop, what they're doing to make it easy, easier, for developers to get in there and play around on both on Mac and Windows but also the executive conversation. What are they hearing from the executives and where is containerization, you know, from the c-sweep to the board room. >> Yeah, modernizing enterprise apps also has been a Docker theme for the last few years. Microsoft, the big guest up on stage, they've been a multi-year partnership with Microsoft and Docker, putting Docker with Windows together. The big announcement today, pre-technology preview of Kubernetes and Windows Server and the big demo was, they took a very old .net application and, you know, put it up on Kubernetes on Windows with just a couple of clicks. So again, I think that message to the executives is, "You're very safe in Docker's hands "We've got the developer experience covered, "we've got the partnerships." And then going big on Windows, I think choice was another theme that I heard ... >> Yes, it was. Steve talked a lot about choice. >> Um, to the execs here as well, both GUI and CLI, right? A lot of the cloud is very CLI-focused, very Linux-focused. Docker says "We're in on Windows, we support Windows "just as well as Linux so don't hate on the GUI. "You can use a GUI or you can use a CLI." No religion actually too, in terms of Linux versus Windows but Kubernetes, I thought, was a very big. Got mentioned a lot in the keynote this morning, Lisa. >> It did and you talked about choice. One of the things that Steve Singh mentioned from an executive's perspective is, three things that Docker is aiming to deliver. That sounds to me, as a marketer, like competitive differentiation. Talked about choice so that organizations can run apps wherever it makes sense for them, managing applications on any infrastructure, and, as you said earlier, about a few clips, managing their container infrastructures across multiple clouds in just a few clicks. They also talked about being, they also talked a number of times, not just in the press release but also this morning in the keynote, about no vendor lock-in. John, we hear that a lot, it sounds like a marketing term. What are you expecting to hear? What does that mean for Docker? >> I'm not so sure that lock-in is always important for every enterprise, in that any choice you make, it has a certain element of lock-in but it's an active argument or debate online that I see a lot. "Are you locked in when you go to a certain cloud? "Are you locked in when you choose a certain provider," whether it's open-sourced or not. Certainly a lot of Docker is open source. A lot of your choices are protected and they are really trying to say "We're going to be a platform that's going to "service a lot of different abilities to deploy." The big announcement that finished off the keynote was Docker Enterprise Edition can now manage Kubernetes. Not only Kubernetes in the cloud. Kubernetes on Prim, Kubernetes in the cloud managed by Docker, but can actually work with the native Kubernetes cluster managers of the clouds, of the three major clouds: Google GKE, Azure AKS, and AWS EKS. I think I got all those names right. But that's big because a lot of folks say "run anywhere" but they mean "run within our environment anywhere" and what Docker has done in Tech Preview is to connect its platform with the native platforms, orchestration platforms, of the three different clouds so that you can run on Prim, manage via Docker, or you can connect into the cloud's own cluster orchestration. And if they can deliver on that, the devil is in the details, but if they can deliver on that, that's actually a very nice feature to avoid that sort of lock-in. >> And that also goes to, John, one of the major things which is agility and one of the things that they've talked about is, containers today are portable but one of the challenges is that management of containers has not been portable. I think they said that 85% approximately of enterprise I.T. organizations that they has surveyed are running a multi-cloud strategy so they've gotta be able to really deliver this single pane of glass management so they talked about federated application or federated management of containerized applications. I think that's kind of what you're referring to in terms of getting away from the silos and enabling organizations to have that portability and especially as multi-national organizations need to have different access, different security, policies may be maintained across multiple locations. >> Indeed, right. These are global organizations that are betting on container technology. They do need access to be running apps, either parts of apps or services on different clouds. You might be running a Google cloud in Europe, you might be running an AWS here or vice versa. You might have some on-Prim stuff. We've seen a lot of that. I think another theme that we'll hit on, Lisa, along with that multi-cloud portfolio aspect, is the time to value. It's been a theme of this conference season. This last month or two, you and I have both been at a lot of different conference centers and I think time to value, being able to spin up apps within weeks or months that actually work and have value versus the old way, which was years and I think the theme for 2018 is that it's real. People are actually doing it and we'll talk to a couple of customers, I hope, today. >> And that's essential because enterprises, while there's still trepidation with moving into the container journey, they don't really have a choice to be able to aggressively innovate to be able to be leaders and compete with these cloud-native organizations. They don't have the luxury of time to rip and replace old enterprise applications and put them on a container or a micro-service's space archicture, they've got to be able to leverage something like containers to maximize time to value to deliver differentiating services. >> Absolutely. I'm very interested in being here today and we'll see what the day brings us. >> I think we're gonna have a lot of fun today, John. I think they kicked off things with great energy. I loved how, you know, they always do demos, right, on main stage during general sessions, and we were at SAP last week and of course, one of the demos didn't work. That's just the nature of trying to do things live. I liked how they were very cheeky with the praying to the demo Gods with the fortune cookies. I thought that was really good but the demos were simple. They were very clearly presented and I'm excited with you to dig in to what are they doing. Also what is setting them apart and how are they enabling enterprise organizations like MetLife, like McKesson, PayPal, Splunk to be able to transform to compete. >> Absolutely. One last thing about the conference, Lisa, is I do want to call out. It's a very humane conference. Not only do they have kind of a cheeky sense of humor here at Docker, but there's child care onsite, and there's spouse-tivities, there are activities for if you bring your spouse or family to the conference. They're trying to do a lot of things to make the conference experience good and successful and friendly and humane for people here at the show which I really appreciate. >> I like that, humane conference. You're right. We don't always see that. Well, John and I are going to be here all day talking with Docker executives, customers, partners and we're excited to have you with us. Lisa Martin for John Troyer. You're watching theCUBE at DockerCon 2018. We'll be right back with our first guest. (techno music)

(upbeat music) >> Announcer: From the VMware campus in Palo Alto, CA Its theCUBE covering Women Transforming Technology. (music beats) >> I'm Lisa Martin with theCUBE and we are on the ground in Palo Alto at VMware for the third annual Women Transforming Technology event. Excited to be talking with Stephanie Joe, next Vice President of Operations in the Networking and Security business here at VMware. Hi Stephanie. >> Hi, thanks for having me. >> Lisa: Thanks for joining me today >> Lisa: Absolutely, our pleasure >> So, you've been in tech for a long time at VMware, for about five years. >> Stephanie: Yes >> Tell me a little bit about your journey in tech. Was it, did you want to get into software and technology many years ago? >> Stephanie: So being actually a native of the Silicone Valley and being raised in this in California, my father worked for a high tech company for 30 plus years. And so, for me it was natural to go into technology. I'm very much of a finance person and numbers person, so it gave me the opportunity to take my desire for math and my desire for finance and be close to products and be close to innovation. So, I would say yes, from early on it was no question that I would be working in technology. Its a great place to be in the Silicone Valley for that. >> Lisa: It is. It really is. >> yeah yeah >> So you were in finance for a long time >> Stephanie: Yes >> then moved into operations. >> Stephanie: Yes, a couple years ago. >> How did you get that courage to go, you know what I've been doing this for a long time >> Stephanie: Yeah >> and you mentioned your dad, you know, working in it for 30 years. >> Stephanie: Yes >> I think parent's generation was you get a job and you do the same thing for 30 or 40 years >> Stephanie: In the same company >> Yes. How did you get that courage internally to go you know what I want to try something different. >> Yeah, so being in finance, I had the opportunity to work in many different groups within the finance organization and as I worked in finance, I got the opportunity to take a look at what was important to me and what was interesting to me and although I love my numbers piece, I also was very much interested in process and operations and holding people accountable. And, I got to a point, honestly, where I was in finance and I tried many different pieces of finance, and I got to a point where okay, what am I going to do next? Um, and there's also something that's been important to me is constantly re reinvigorating myself, and rebranding myself, not rebranding but continuing my brand. And as part of that, operations was just the next natural piece and I had thought about making that dive many different times in my finance career, but there was always either that risk of oh its a little scary, or there was something else I still wanted to do within finance. And an opportunity came along a couple of years ago, and specifically in the networking security space. And VMware, it is one of the highest priorities within the company and because of the technology, and because of the opportunity, I said you know, now is the right time to go do this. Now is the right time to take that leap, take that chance. And, at the same time, I also knew I had the backing of supporters and mentors to help me be successful in that move. Um, I knew it wasn't going to be a slam dunk. I've always told people you almost have to do that next thing that you know you're going to be able to contribute, yet at the same time, its a little scary And, you have to have the confidence and the planning around that confidence to go for it. Um and take that risk. And its been worthwhile. It has been a nice change. Its given me new energy and I think I know I am contributing to the company. >> And it must feel good. >> Stephanie: Yes >> You talked about, touched on a number of points we have heard today at the Women Transforming Technology event where we, you know things were kicked off this morning, ahh with Laylah Ali who talked about having, finding that courage, and that confidence. Um, but also needing to be mentioned being around an organization, whether its an organization or just a group who support whatever change that you are thinking of making, >> Yeah >> And I do think some change that's scary is good >> Yeah >> Ah, but I think that is one of the hallmarks of women transforming technology >> Stephanie: Yes >> is this consortium of industry, nonprofits, academia coming together to to confront head on the issues, the diversity issues that we're facing. >> Not just as women in technologies, >> Stephanie: Right a lot of different gaps >> Right But, also providing that support and enabling women and men >> Stephanie: Right >> to have mentors to learn from because it isn't just >> Stephanie: Yes >> challenging to get women in tech, its very challenging to retain women in technology who leave at very high rates >> yes >> for other careers. >> Correct Correct >> So how did you at being at, you said, Cisco for quite a long time and now >> correct VMware five years, >> Did you have women in leadership positions that you looked up to that were mentors to you? >> I think, so its interesting when you dive into your career at the very beginning, long time ago, you don't necessarily think about okay who are my mentors or who do I look up to? Or is there women specifically who can support me? I think for me its become just natural and I've had the opportunity where I've had a combination of both leaders, men and women, that have been mentors to me and supporters and as I moved forward in my career, I've discovered what was important was having, even a diverse set of mentors, men and women, but a circle of women around me too, that were living the challenges I was living. And I also don't think I realized some of the diversity challenges I was living until I got to a certain point and I looked back and went wow and I listened and part of WT2 allows you to listen to some of the other challenges that other people are having and you realize, I'm not alone and that person is experiencing the same thing that I'm experiencing. and I've now turned into a position of, where I am like, how can I help you? How can I help that you live through the same things that um, I've lived through. How can I help you and how can I help you contribute? This is a forum that allows us to come together and create new mentors, to get away from the everyday busyness and be selfish for a day and think about myself and how can I improve on things. Um, but really to connect and share our stories. >> You mentioned >> Stephanie: So I am thankful for that >> the word accountability earlier too and I think one of the things that's great about women transforming technology, women who code, we also, we cover a lot of women events, women and data science. Its at the VMware level, VMware is a huge organization very successful for many years, >> Stephanie: Yes >> But, they the this long-standing partnership Stanford and now the Clayman Institute, and now the new Innovation Lab, from an accountability perspective you are starting to see it. I shouldn't say starting, but you're seeing it in a big way >> Yes >> That's a big investment >> Stephanie: Yeah big investment by a big corporation >> Yes >> With 20 plus thousand people and of course Stanford University. >> Stephanie: right To look at what are these big barriers, um, that are effecting, that effect everybody >> Stephanie: That effect everybody. >> And how can they start to identify them and start to eradicate them and having companies participate and step up to be accountable to that is huge. >> Its huge. And I think, you know, its a journey, right. And I think we all started a couple of years ago just looking at the facts and looking at the data, and not pushing but I think presenting the facts of this is what our own diversity metrics look like. Not just men versus women, but, you know, different different you know, diversity factors in addition to okay, as a result of these facts, then what should we do as far as the next step. And I think over the past couple of years, there has been a natural progression around we're going to start looking at this and we're going to start asking questions, and we're going to start holding people accountable to doing what they said they were going to do from a people perspective, Diversity being one of them. So its been nice seeing that evolvement. Exciting to me is the partnership between VMware and Stanford because I think it takes it to the next level of its not just the data, its not just the facts, its not just we know its important, its what are the underlying behaviors underneath it, what are the underlying actions that we now can take, not just for VMware, not just for Stanford, but for the whole entire community, right? And that's what its all about. Its about coming together as a multiple different companies coming together as a great institution like Stanford coming together saying how can we make a difference in the community that we live in and make a difference from a technology perspective, so >> Yeah >> Its exciting to me and I think it will be interesting to be a part of the journey, but also see where we are a year from now, two years from now. >> Right, so you've, you sound like you have sort of found you voice with ah, wanting to be inspire inspirational >> Stephanie: yeah to other women, whatever stage of their career. >> Stephanie: Yeah >> It just seems like something that sort of occurred to you. Hey, I've been through this. I'm not the only one. A lot of people go through this. Um, what was that kind of ah hah moment when you said I have an opportunity here to give back. >> Stephanie: Yeah, I think its interesting cause I look back and I'm like there wasn't, well maybe their were a couple of moments, where I am like wait wait that comment just made, that was because I was a woman not because of what I was contributing. And, either it was like, okay, that was an interesting comment and how do I handle it. But it really wasn't, I think, until I was up in the higher ranks, right, and I starting saying okay, I've done a lot, we've been very results oriented, how do I start giving back? And how do I start mentoring others? And it started out as mentoring others that were maybe new college grads or maybe just new people to the company. And as I started mentoring to others, then I started realizing too that some of the women that I was mentoring, wait, their living through the same things that I lived through. And there was a big time where I thought oh it was just Stephanie. Right, oh, its just unique to me. Nobody else was dealing with this or it I also went through a period of like I wasn't any different than anybody else, right. And then as I started going through this, I realized no there's others that are living the same path that I lived. Um, and I think that I can help them grow and contribute to their own growth. And by the way, me, at the same time, me learn from them, um which is what its all about. >> Lisa: Very symbiotic >> Yeah >> It takes events like this, like WT squared, to identify hey, there is a lot of commonality and challenges that we all face regardless of gender or sexual orientation or what not. The more you are aware of some of these challenges, the more we can identify how how do we hold acc organizations or what not accountable. It takes that courage though to come together and be the one to raise your hand thinking you might have a dumb question when of course there really are no dumb questions (laugher) And finding that support, I mean, the strength in numbers, right, that's what the Golden State >> Warriors, Golden State Warriors >> Exactly. >> It is the team I love (laugher) >> Um, but its really true and its a very pervasive feeling when you come to an event like this, you walk in, and you feel that there's this inclusion >> Stephanie: Yeah >> Lisa: Across >> Stephanie: You feel the power of the people in the audience, but you also feel the affirmation from the panels or you know, Laylah Ali who is speaking today and her struggles and her journey, um, and just saying I can identify with that, right. I'm not alone, but also how do we together come together and have a voice, right? How do we hold others accountable? And doing it in a way that is fair. I think that's what all of us are ask for. Its not, I have never asked for special treatment because I am a woman or because I am an Asian, but because its fair, right, and I'm treated fair, and I'm treated the way that my peers are treated. Um, and I think that's what we all want. >> Yeah >> Yeah >> You mentioned Laylah Ali, her keynote this morning was it was great. >> Phenomenal I think its so, you you can tell, even if I hadn't seen her speak, you know Laylah Ali is a very strong woman >> Stephanie: Yes >> Physically, mentally, but it was really refreshing for her to say hey there's moments where I got to recheck, what's my purpose here, what am I doing. >> Stephanie: My inside warrior >> Yes, and I love that she said you know we got to find that inner warrior. She's in there >> Yeah >> Sometimes she's quiet, um, maybe has some tape across her mouth, but seeing a naturally innately strong female saying sometimes I don't feel that way, I think that is a very important message to get out, to all of those people, regardless of gender or orientation who don't have this sort of natural confidence that a Laylah Ali has. That's normal. >> Yeah yeah. And for me hearing somebody else say, a couple of things she said having that interior warrior, inside warrior, who, okay give yourself a day to feel bad. Give yourself a day to deal with it. And then its time to go back for the fight. Its time to go focus on what's important to you and bring out that passion and go. And, how many times have all of us felt that? Um, many a times. Um, the other part that, for me, that really hit home for me was confidence. And its funny, cause some people will say Oh,Steph you have very high confidence and I am like no I don't. And she said something to confidence is in planning and being prepared. >> Lisa: Yes >> And as I think about that, that is something that is very true. It resonated very close to me and I think about as I talk to women and they I say you are going to go into this meeting, think about how you are going to prepare for that meeting. Because then it allows you to immediately say yep, this is what we should do. Yep, this is my idea. To be able to have that voice. So I would say for me, those were probably the two pieces, right, confidence and preparation, or being prepared to have confidence and the inside warrior where it just really hit home for me. >> The preparation thing I thought was really cool too because we talk a lot about imposter syndrome. >> Stephanie: Yeah >> And its a real issue that a lot of people face, >> Stephanie: Very true >> Whatever stage of career they are at or industry, but she's right in that if you're prepared for whatever it is that you are doing, that confidence will come. But preparation is really key. >> Stephanie: Yeah I chuckle a little bit because when you say the imposter piece, I will admit I think there was a time in my career where I acted a certain way, and I was in meetings as a certain way, or I went down a path because that's the path you should go down, right. Um, but it wasn't true to myself and so I think the part around being prepared, being confident as a result of being prepared, really allows you to be true to yourself and allows you to bring out the passion. That's important. Um, and that applies to everybody, not just us. >> It does. So in your, kind of wrapping things up here, what are some of the cultural um shifts that you've seen being in tech industry for 20 years and some of the things you are looking forward to in the next year at VMware? >> Stephanie: Yeah, so I will say, cultural shifts, just from the standpoint of awareness, right. I think that is a very important piece of people being respectful and aware of the environment that we're in and people having the conversations. I don't think we would even be having these conversations 10 years ago. and there is multiple different reasons for that. Whether it be results of showing with inclusion and with diversity, you have better business results. Um, or whether it be people speaking up and saying hey, we have a right to have a voice. We have a right to be treated in a certain way. And so, from a culture standpoint, that voice and that awareness has then lead to being able to have the conversations of how people should be treated, how they should be respected, and how we um, should even have the discussion with each other. Right? Looking forward, I look forward to the fact of being able to have a stronger voice. And when I say a stronger voice, I don't mean hey, let's go for the fight and let's make sure we've go the right numbers. But it really is the voice in the room. Um, I think we still have the discussion around the numbers. We haven't necessarily had the discussion of how do we make sure that the people in the room, that is a diverse set of people, that their voices come out, so we get a diverse set of of suggestions and ideas to come to the best outcome. >> Stephanie, thank you so much for stopping by theCUBE, >> Stephanie: Thank you for having me. >> And sharing your backstory and your history. And um, its really nice to hear from other mentors who recognize and are proud to be in that position. So, thank you. >> Its a pleasure. Thank you >> We want to thank you for watching theCUBE. Lisa Martin, on the ground at VMware for the third annual Women Transforming Technology. Thanks for watching. (closing music beats)

>> Welcome back everybody, Jeff Frick here with theCUBE. It's International Women's Day 2018. There's a ton of events happening all over the world. Check the social media stream, you'll be amazed. But we're excited to be here, downtown San Francisco, at the Accenture event. It's called Getting to Equal, 400 people, it's a packed house here at the Hotel Nikko, and we're really excited to have the authors of some really important research here as our next guests. This is Julie Sweet, the CEO of North America for Accenture. Good to see you, Julie. >> Great, thanks for having me today. >> And Ellyn Shook, the Chief Leadership and HR Officer at Accenture. Great to see you. >> Thank you, Jeff. >> All right. So Ellen, I want to start with you just cause I noticed your title, and I wrote it down, I've never seen, we do hundreds of events, thousands of interviews, I've never seen Chief Leadership and HR. Where did that title come from, and why is "Leadership" ahead of "HR"? That's a pretty significant statement. >> It is, it is, and Accenture's a talent-led business, and part of being a talent-led business is growing our people to grow our business, so leadership and leadership development is essential to our business. It's a core competency of ours, and that's why my title is Chief Leadership & Human Resources Officer. >> And Leadership before HR, meaning you really need people to get out in front. >> Yes. >> It's not about compliance, >> Yes, leaders at all levels. >> and this and that, leaders of all levels. >> Correct, correct. >> Okay, so let's talk about the research. >> Sure. >> It says, "When she rises, we all rise." I think it's pretty common, and everybody knows hopefully by this point, that diversity of opinion, diversity of teams, leads to better business outcomes. So what specifically is this piece of research, and give us a little background. >> Sure, the research, I think, is groundbreaking because never have I seen a piece of research that looks at the cultural aspects of an organization and really helps to articulate very transparently, what are the biggest accelerators in a culture for equality? And that's what the research is about. >> And you've identified, and is this an ongoing research, is this the first time it's been published, is it kind of an annual thing? >> Every year we publish a piece of research about gender equality, and this year we put a different lens on it to really look at equality for all. >> So you've identified 40 kind of key areas, but of those 40, really 14 are the big hitters. Is that accurate? >> That's correct. >> So what are some of those 14? >> Well, I would put them, we've put them in three categories. The first is bold leadership, so think about companies like Accenture who set targets and have CEOs who are very clear about their priorities. The second is comprehensive action, so think about policies and practices that are really effective. And then finally third, which I think is often under focused on, which is an empowering environment. What does it feel like to be at work every day? Do they ask you to dress a certain way? Is there flexible time for all? And it's the combination of these 14 factors that really makes a difference about creating a culture of equality where men and women advance. And what was really impressive is we saw that, in companies with these factors, women were five times more likely to advance to director or senior manager, and men were two times more likely. And so it really is about, when she rises, all rise, and that is probably one of the most exciting things about the research. >> It's really interesting, we just had Lisa on from The Modist, and you know, I would never have thought of clothing and dress as such a significant factor, but you've got that identified in that third bucket that you mentioned. And in fact, it's the number one attribute. So what are some of the other surprises that kind of came out of the research? >> Well, I think one of the surprises was that companies that, as part of comprehensive action, that implemented maternity leave only, it actually had a negative effect on women's advancement. But where companies implemented parental leave, so it was for men and women, it eliminated that negative bias. And it really goes to the importance that these policies, and actions, and the focus need to be about women and men. And when you start putting women too much in a category, like flex time is a mommy track, as opposed to flex time being something that men and women commonly do, it really changes how it feels to, does it feel inclusive every day at work? >> Right. >> Yeah, so companies really need to, I think what the research showed very strongly is that companies need to look at programs, policies, practices, and an environment that levels the playing field rather than isolating any particular gender or other form of diversity. >> But it's interesting, kind of law of unintended consequences, I think that panel that you were on earlier, one of the gentlemen said, since the not me, there's been reports of, >> Me too. >> for me too, excuse me, a lot of hashtags today. That there's been people doing, men scared of mentoring maybe that they weren't before. I don't know how true that is, but no it is kind of interesting to think, are there some kind of counter balances, as you said, if there's just maternity and not parental leave that need to be thought about? That probably people aren't thinking it through that far. >> Well and I think, one of the things as we saw in the research is that it's not about also one action, and so the way that companies really create a culture of equality is it's a combination of these factors. And you said something when we first started that I think is really important, and that was, you said, well it's really commonly known that diversity is important. And I think that people do need to understand that, we are optimistic about where we are today because, as a company, we're constantly in the c-suite. We serve in the U.S., 3/4 of the fortune 500, and as much as we're talking as a leader in digital disruption and artificial intelligence, the conversation quickly turns to people, to talent, to diversity, and so there's a real business lens that's on this, and that's the context in which we're operating. >> Right, and we can go to Grace Hooper, we do a ton of women's events as well as large conventions. And most people, I think, hopefully have figured it out, that it's not just about doing the right thing, it's about actually having better business outcomes. You get better outcomes with diversity of opinions, diversity of teams, you think about things that you just wouldn't think about. You don't have that same experience, everybody has a bias from where they come from, so you want to get some other people and have different points of view, different lenses to look at things. So it is really important. But why do you think things feel like they're changing now? What's important about, March 8th, 2018, versus say a year ago when you started doing some of this research? Is it the tipping point that it feels like, or? >> I think there's a couple of factors that are coming together right now. First of all, we're living in the digital age, and the digital age is all about innovation and innovation fast. And as you just said, you cannot innovate without diversity. Diversity is a form of, you're able to tap into creativity, and it's a source of competitive advantages for organizations in this age. But also what's happening in culture around the world, the me too movement as well as other things that are occurring for women around the world, and it's a moment in time where a movement can really start to happen. And I think, companies who look at culture as an accelerator of change are going to be the winners. >> Right, so what impacted bold leadership? We had from the Golden State Warriors on earlier and I think there's, what's great about sports teams is we all get to see them do their business. And we get to see the scoresheet at the end of the day, we don't necessarily get to see that in other companies. But really a fantastic example of new leadership coming in, made bold sweeping changes, probably a little bit of luck, which most success stories have, but you know significant top-down culture change. So how do you see cultures changing with bold leadership and old-line companies? Can the old guard flip? Do they need to bring in new blood? How are people executing bold leadership? >> Well first of all, I do think that it's not about old-line, it's not about young, it's really about leadership. And so it is very dependent on who is the CEO and what kind of a board we have, and so, we don't, both of us don't subscribe to the idea that you have to be born digital to be have a great culture >> To be digital. >> Yeah to be digital. And I would say that, one of the key things we saw in the study was around transparency of goals. And we talk a lot at Accenture about transparency creates trust. And so when you think about, how do you change a culture? Bold leadership is in part to find in the research by the willingness to set public goals, and to be transparent and that creates the trust. The trust of your employees, and the trust of the people you want to attract. And what I often will say that is, when we put out our statistics in the U.S, we're the first professional services firm, it wasn't that we had phenomenal statistics, but the fact that we were willing to put them out created trust that we were trying to change. And it helped people want to be a part of that change. >> Right. I mean you know that, you guys are in this business, if you can't measure it, you can't improve it. It's interesting, the Anita Borg organization puts out a self-assessment, we do their show, and Grace Hopper, to have companies. Again, not necessarily that they're going to score high but at least they recognize the problem, they're trying to measure it, they're trying to set a base line and make moves. We've heard that from Brian at Intel, Intel's making moves. And you guys have made a very definitive statement, write a line in the sand, at 2025, you're going to hit 50%. I believe that's the goal. >> Correct. And not only do we say that we're going to do it but we're doing something about it. And a lot of companies will say they want to achieve gender equality, but it's actually the actions that you take every single day. And then, of course, reporting on your progress, whether it's what you wanted to see or not, just the full transparency around the scorecard is important. >> Yeah, it's so critically important cause again, if you can't measure it, you can't change it. So great event here, as you look forward into 2018, I still can't believe we're a quarter of the way in to the year, it shocks me. (laughs) What are some of the priorities for 2018, if we sit down here again a year from now, where will you have moved on that measure, what are some of the things that are your top priorities around this initiative this year? >> Well I know for me, we certainly are trying to make sure that we continue to make progress, but I also think there's a growing conversation about the intersectionality of diversity, and so, it's women in color, it's race and the workforce, and so. We're a global company, but certainly in the U.S, which is part of the business I lead, we are not only focusing on gender, but the intersectionality of diversity and on race. >> Yeah and I think just broadening the conversation from gender diversity to true equality for all is really the big push for us here at Accenture now. And I think it's essential that no part of our organization or no individual gets left behind. And that's what we're really focused on. >> Well that's great, and so I want to thank you for having us, and wish you well in 2018, and really a fantastic event and super, super initiative. >> Come back in 2019 and we'll show you our progress. >> Alright. >> Exactly. >> She's Julie, she's Ellyn, and I'm Jeff, you're watching theCUBE from International Women's Day at the Accenture event in downtown San Francisco. Thanks for watching.

>> Hey welcome back everybody. Jeff Frick here with the Cube. We're at the Hotel Nikko in downtown San Francisco, International Women's Day. Accenture's putting on a big event today. It's called Getting to Equal, about 400 executives. Packed house in the little conference area. So we're excited to sit down with some of the leadership team and talk about some interesting research that Accenture's come out with. And also just talk to some terrific guests and we're excited by our first guest. She's Jennifer Cabalquinto. She's the CFO of the Golden State Warriors. Jennifer, great to see you. >> Thank you. >> I'm joined by Mike Sutcliff. He's a group chief executive for Accenture Digital. Great to see you Mike. >> Great to be hear. >> Alright, so let's just jump in to it. We're a little short on time and got a packed schedule. But I want to jump in, Jennifer with you, in culture. >> Yeah. >> Talk about the culture at the Golden State Warriors. I think it's such a phenomenal example that we can all see. We can't see in lot's of other companies, but with a professional sports franchise, we can see what a top down culture change when the change of management happened. When, when >> Sure >> Joe and Peter came in and how they've been able to change the culture, but then also drive that through all the way down to the greatest operations. >> Yeah, no we've really been fortunate. Our ownership group has been so supportive. And they really want us to succeed and they gave us all the resources to do it. And they've really brought that sort of Silicon Valley leadership style and fast fail and really make us push to be innovative and to grow. I love, you know, they brought on Bob Myers as our general manager for the basketball operation side. And he always says that he recruits for character first. And then tall 'cause you can't teach tall, but character is really something that I think, we as part of the whole organization really focuses on is that, you know, it's that are we all willing to be a team and have that sort of drive together. >> Right. >> And Joe and Peter embody that from the top down and I think it really permeates. And it's really our desire to be innovative and to drive this business, both on the basketball side and on the business side. >> And what's interesting, I mean they're good guys, but they're not doing it to be good guys, they're doing it to win. I mean, it's a competitive business >> Sure. >> that we can all watch the winners and losers. It's a business decision for better business. >> That's exactly right and you know, they really do want to win. They're competitive and every single person I think in the organization is competitive. But I think they want to win in the right way. And I think you can see it in the way that we approach both the basketball side and the business side really wanting to, you know, I think do, I think the community the best that we can. I mean, we really want to reflect our community, as well as our business partners and really succeed together >> Right. So Mike, you're out on the field. You talk to a lot of customers. I mean, do people get it? Do people get that diversity of opinions, points of views, teams, isn't just to do the right thing? It's actually to drive better business outcomes? >> I think they do. I mean one of the reasons we were attracted to work with the Warriors is they were looking not just to change their game, but to change the community that they were involved in. We see lot's of clients with the same aspiration. They're trying to figure out how to improve the way the world works and lives. And so if you want improve the way the world works and lives, you got to have diversity of thought. People with different educational backgrounds, cultural backgrounds, different experiences who can look at those really tough problems and say there's a better way. >> Right. >> And that's where we think diversity brings powers. That diversity of experience allowing you to come up with new solutions. >> So Jennifer, just from a woman's perspective being in obviously a very male dominated world. Of course, a lot of the tech companies around here are as well, how are you attracted to this industry? You know, kind of, what was your experience going in knowing that you were going to be in the minority in terms of the executives around the table? >> Right. >> And how did you overcome? >> You know, I am one of five children. I have four brothers, two older, two younger. And raised in Brooklyn. I'd like to think that I've been competing with boys my entire life. And I think my environment sort of gave me a tough skin. So I don't look at it in that lens. I didn't approach the job thinking I'm the only woman, or I'm one of a handful of women. I really approached the job saying I can make a difference in this organization and to help drive and bring a new perspective to the sports industry. It was my first sports job I was out of entertainment space and not really the sports entertainment world. And I really thought that I could bring a different perspective. And I think, you know, the ownership saw the same thing. And that's why I came aboard. And I think not filtering anything that I do with the lens of I'm a woman. >> Right. >> I think really makes a difference in terms of how I approach the role and then how other people, you know, sort of receive that. >> Right. So that said, for the gals that weren't raised in Brooklyn with four brothers. Fighting for food at the table probably since you were a little kid. You know, what advice would you give them? I mean, is it just, there's some really great advice coming out of the panel in terms of just focus on data, focus on results, you know, raise your hand. What advice would you give to, you know, say young women, say a junior in college, a senior in college, first years out, who want to get started, and are attracted to a traditionally male dominated space? >> Sure, I think one, don't self edit. Like know you can succeed in that space. Just because it's male dominated doesn't mean that it needs to always be that way. I also think you have to be great at what you do. I mean it's performance first, I think in any industry. And so, when you can actually have the confidence in your abilities, I think it starts to show through and then people, you know, I think respond to that. So I think perform really, really well. Be deliberate about what you want. Ask for what you want. Set your rules. You know, I think all of that is really important. Find your voice. >> Alright, well we could go on and on, and I want to continue this later at the San Antonio game this evening, but we'll make that work out, but we got to drop. So I'll leave it there. Jennifer, Mike, thanks for >> See you there. >> taking a few minutes. >> Great to see you today. >> Alright, I'm Jeff Frick, we're at the Accenture International Women's Day celebration in downtown San Francisco. Thanks for watching. (upbeat music)

>> There's a movement that's sweeping across businesses everywhere here in this country and around the world. And it's all about data. Today businesses are being inundated with data. To the tune of over two and a half million gigabytes that'll be generated in the next 60 seconds alone. What do you do with all that data? To extract insights you typically turn to a data scientist. But not necessarily anymore. At least not exclusively. Today the ability to extract value from data is becoming a shared mission. A team effort that spans the organization extending far more widely than ever before. Today, data science is being democratized. >> Data Sciences for All: It's a Whole New Game. >> Welcome everyone, I'm Katie Linendoll. I'm a technology expert writer and I love reporting on all things tech. My fascination with tech started very young. I began coding when I was 12. Received my networking certs by 18 and a degree in IT and new media from Rochester Institute of Technology. So as you can tell, technology has always been a sure passion of mine. Having grown up in the digital age, I love having a career that keeps me at the forefront of science and technology innovations. I spend equal time in the field being hands on as I do on my laptop conducting in depth research. Whether I'm diving underwater with NASA astronauts, witnessing the new ways which mobile technology can help rebuild the Philippine's economy in the wake of super typhoons, or sharing a first look at the newest iPhones on The Today Show, yesterday, I'm always on the hunt for the latest and greatest tech stories. And that's what brought me here. I'll be your host for the next hour and as we explore the new phenomenon that is taking businesses around the world by storm. And data science continues to become democratized and extends beyond the domain of the data scientist. And why there's also a mandate for all of us to become data literate. Now that data science for all drives our AI culture. And we're going to be able to take to the streets and go behind the scenes as we uncover the factors that are fueling this phenomenon and giving rise to a movement that is reshaping how businesses leverage data. And putting organizations on the road to AI. So coming up, I'll be doing interviews with data scientists. We'll see real world demos and take a look at how IBM is changing the game with an open data science platform. We'll also be joined by legendary statistician Nate Silver, founder and editor-in-chief of FiveThirtyEight. Who will shed light on how a data driven mindset is changing everything from business to our culture. We also have a few people who are joining us in our studio, so thank you guys for joining us. Come on, I can do better than that, right? Live studio audience, the fun stuff. And for all of you during the program, I want to remind you to join that conversation on social media using the hashtag DSforAll, it's data science for all. Share your thoughts on what data science and AI means to you and your business. And, let's dive into a whole new game of data science. Now I'd like to welcome my co-host General Manager IBM Analytics, Rob Thomas. >> Hello, Katie. >> Come on guys. >> Yeah, seriously. >> No one's allowed to be quiet during this show, okay? >> Right. >> Or, I'll start calling people out. So Rob, thank you so much. I think you know this conversation, we're calling it a data explosion happening right now. And it's nothing new. And when you and I chatted about it. You've been talking about this for years. You have to ask, is this old news at this point? >> Yeah, I mean, well first of all, the data explosion is not coming, it's here. And everybody's in the middle of it right now. What is different is the economics have changed. And the scale and complexity of the data that organizations are having to deal with has changed. And to this day, 80% of the data in the world still sits behind corporate firewalls. So, that's becoming a problem. It's becoming unmanageable. IT struggles to manage it. The business can't get everything they need. Consumers can't consume it when they want. So we have a challenge here. >> It's challenging in the world of unmanageable. Crazy complexity. If I'm sitting here as an IT manager of my business, I'm probably thinking to myself, this is incredibly frustrating. How in the world am I going to get control of all this data? And probably not just me thinking it. Many individuals here as well. >> Yeah, indeed. Everybody's thinking about how am I going to put data to work in my organization in a way I haven't done before. Look, you've got to have the right expertise, the right tools. The other thing that's happening in the market right now is clients are dealing with multi cloud environments. So data behind the firewall in private cloud, multiple public clouds. And they have to find a way. How am I going to pull meaning out of this data? And that brings us to data science and AI. That's how you get there. >> I understand the data science part but I think we're all starting to hear more about AI. And it's incredible that this buzz word is happening. How do businesses adopt to this AI growth and boom and trend that's happening in this world right now? >> Well, let me define it this way. Data science is a discipline. And machine learning is one technique. And then AI puts both machine learning into practice and applies it to the business. So this is really about how getting your business where it needs to go. And to get to an AI future, you have to lay a data foundation today. I love the phrase, "there's no AI without IA." That means you're not going to get to AI unless you have the right information architecture to start with. >> Can you elaborate though in terms of how businesses can really adopt AI and get started. >> Look, I think there's four things you have to do if you're serious about AI. One is you need a strategy for data acquisition. Two is you need a modern data architecture. Three is you need pervasive automation. And four is you got to expand job roles in the organization. >> Data acquisition. First pillar in this you just discussed. Can we start there and explain why it's so critical in this process? >> Yeah, so let's think about how data acquisition has evolved through the years. 15 years ago, data acquisition was about how do I get data in and out of my ERP system? And that was pretty much solved. Then the mobile revolution happens. And suddenly you've got structured and non-structured data. More than you've ever dealt with. And now you get to where we are today. You're talking terabytes, petabytes of data. >> [Katie] Yottabytes, I heard that word the other day. >> I heard that too. >> Didn't even know what it meant. >> You know how many zeros that is? >> I thought we were in Star Wars. >> Yeah, I think it's a lot of zeroes. >> Yodabytes, it's new. >> So, it's becoming more and more complex in terms of how you acquire data. So that's the new data landscape that every client is dealing with. And if you don't have a strategy for how you acquire that and manage it, you're not going to get to that AI future. >> So a natural segue, if you are one of these businesses, how do you build for the data landscape? >> Yeah, so the question I always hear from customers is we need to evolve our data architecture to be ready for AI. And the way I think about that is it's really about moving from static data repositories to more of a fluid data layer. >> And we continue with the architecture. New data architecture is an interesting buzz word to hear. But it's also one of the four pillars. So if you could dive in there. >> Yeah, I mean it's a new twist on what I would call some core data science concepts. For example, you have to leverage tools with a modern, centralized data warehouse. But your data warehouse can't be stagnant to just what's right there. So you need a way to federate data across different environments. You need to be able to bring your analytics to the data because it's most efficient that way. And ultimately, it's about building an optimized data platform that is designed for data science and AI. Which means it has to be a lot more flexible than what clients have had in the past. >> All right. So we've laid out what you need for driving automation. But where does the machine learning kick in? >> Machine learning is what gives you the ability to automate tasks. And I think about machine learning. It's about predicting and automating. And this will really change the roles of data professionals and IT professionals. For example, a data scientist cannot possibly know every algorithm or every model that they could use. So we can automate the process of algorithm selection. Another example is things like automated data matching. Or metadata creation. Some of these things may not be exciting but they're hugely practical. And so when you think about the real use cases that are driving return on investment today, it's things like that. It's automating the mundane tasks. >> Let's go ahead and come back to something that you mentioned earlier because it's fascinating to be talking about this AI journey, but also significant is the new job roles. And what are those other participants in the analytics pipeline? >> Yeah I think we're just at the start of this idea of new job roles. We have data scientists. We have data engineers. Now you see machine learning engineers. Application developers. What's really happening is that data scientists are no longer allowed to work in their own silo. And so the new job roles is about how does everybody have data first in their mind? And then they're using tools to automate data science, to automate building machine learning into applications. So roles are going to change dramatically in organizations. >> I think that's confusing though because we have several organizations who saying is that highly specialized roles, just for data science? Or is it applicable to everybody across the board? >> Yeah, and that's the big question, right? Cause everybody's thinking how will this apply? Do I want this to be just a small set of people in the organization that will do this? But, our view is data science has to for everybody. It's about bring data science to everybody as a shared mission across the organization. Everybody in the company has to be data literate. And participate in this journey. >> So overall, group effort, has to be a common goal, and we all need to be data literate across the board. >> Absolutely. >> Done deal. But at the end of the day, it's kind of not an easy task. >> It's not. It's not easy but it's maybe not as big of a shift as you would think. Because you have to put data in the hands of people that can do something with it. So, it's very basic. Give access to data. Data's often locked up in a lot of organizations today. Give people the right tools. Embrace the idea of choice or diversity in terms of those tools. That gets you started on this path. >> It's interesting to hear you say essentially you need to train everyone though across the board when it comes to data literacy. And I think people that are coming into the work force don't necessarily have a background or a degree in data science. So how do you manage? >> Yeah, so in many cases that's true. I will tell you some universities are doing amazing work here. One example, University of California Berkeley. They offer a course for all majors. So no matter what you're majoring in, you have a course on foundations of data science. How do you bring data science to every role? So it's starting to happen. We at IBM provide data science courses through CognitiveClass.ai. It's for everybody. It's free. And look, if you want to get your hands on code and just dive right in, you go to datascience.ibm.com. The key point is this though. It's more about attitude than it is aptitude. I think anybody can figure this out. But it's about the attitude to say we're putting data first and we're going to figure out how to make this real in our organization. >> I also have to give a shout out to my alma mater because I have heard that there is an offering in MS in data analytics. And they are always on the forefront of new technologies and new majors and on trend. And I've heard that the placement behind those jobs, people graduating with the MS is high. >> I'm sure it's very high. >> So go Tigers. All right, tangential. Let me get back to something else you touched on earlier because you mentioned that a number of customers ask you how in the world do I get started with AI? It's an overwhelming question. Where do you even begin? What do you tell them? >> Yeah, well things are moving really fast. But the good thing is most organizations I see, they're already on the path, even if they don't know it. They might have a BI practice in place. They've got data warehouses. They've got data lakes. Let me give you an example. AMC Networks. They produce a lot of the shows that I'm sure you watch Katie. >> [Katie] Yes, Breaking Bad, Walking Dead, any fans? >> [Rob] Yeah, we've got a few. >> [Katie] Well you taught me something I didn't even know. Because it's amazing how we have all these different industries, but yet media in itself is impacted too. And this is a good example. >> Absolutely. So, AMC Networks, think about it. They've got ads to place. They want to track viewer behavior. What do people like? What do they dislike? So they have to optimize every aspect of their business from marketing campaigns to promotions to scheduling to ads. And their goal was transform data into business insights and really take the burden off of their IT team that was heavily burdened by obviously a huge increase in data. So their VP of BI took the approach of using machine learning to process large volumes of data. They used a platform that was designed for AI and data processing. It's the IBM analytics system where it's a data warehouse, data science tools are built in. It has in memory data processing. And just like that, they were ready for AI. And they're already seeing that impact in their business. >> Do you think a movement of that nature kind of presses other media conglomerates and organizations to say we need to be doing this too? >> I think it's inevitable that everybody, you're either going to be playing, you're either going to be leading, or you'll be playing catch up. And so, as we talk to clients we think about how do you start down this path now, even if you have to iterate over time? Because otherwise you're going to wake up and you're going to be behind. >> One thing worth noting is we've talked about analytics to the data. It's analytics first to the data, not the other way around. >> Right. So, look. We as a practice, we say you want to bring data to where the data sits. Because it's a lot more efficient that way. It gets you better outcomes in terms of how you train models and it's more efficient. And we think that leads to better outcomes. Other organization will say, "Hey move the data around." And everything becomes a big data movement exercise. But once an organization has started down this path, they're starting to get predictions, they want to do it where it's really easy. And that means analytics applied right where the data sits. >> And worth talking about the role of the data scientist in all of this. It's been called the hot job of the decade. And a Harvard Business Review even dubbed it the sexiest job of the 21st century. >> Yes. >> I want to see this on the cover of Vogue. Like I want to see the first data scientist. Female preferred, on the cover of Vogue. That would be amazing. >> Perhaps you can. >> People agree. So what changes for them? Is this challenging in terms of we talk data science for all. Where do all the data science, is it data science for everyone? And how does it change everything? >> Well, I think of it this way. AI gives software super powers. It really does. It changes the nature of software. And at the center of that is data scientists. So, a data scientist has a set of powers that they've never had before in any organization. And that's why it's a hot profession. Now, on one hand, this has been around for a while. We've had actuaries. We've had statisticians that have really transformed industries. But there are a few things that are new now. We have new tools. New languages. Broader recognition of this need. And while it's important to recognize this critical skill set, you can't just limit it to a few people. This is about scaling it across the organization. And truly making it accessible to all. >> So then do we need more data scientists? Or is this something you train like you said, across the board? >> Well, I think you want to do a little bit of both. We want more. But, we can also train more and make the ones we have more productive. The way I think about it is there's kind of two markets here. And we call it clickers and coders. >> [Katie] I like that. That's good. >> So, let's talk about what that means. So clickers are basically somebody that wants to use tools. Create models visually. It's drag and drop. Something that's very intuitive. Those are the clickers. Nothing wrong with that. It's been valuable for years. There's a new crop of data scientists. They want to code. They want to build with the latest open source tools. They want to write in Python or R. These are the coders. And both approaches are viable. Both approaches are critical. Organizations have to have a way to meet the needs of both of those types. And there's not a lot of things available today that do that. >> Well let's keep going on that. Because I hear you talking about the data scientists role and how it's critical to success, but with the new tools, data science and analytics skills can extend beyond the domain of just the data scientist. >> That's right. So look, we're unifying coders and clickers into a single platform, which we call IBM Data Science Experience. And as the demand for data science expertise grows, so does the need for these kind of tools. To bring them into the same environment. And my view is if you have the right platform, it enables the organization to collaborate. And suddenly you've changed the nature of data science from an individual sport to a team sport. >> So as somebody that, my background is in IT, the question is really is this an additional piece of what IT needs to do in 2017 and beyond? Or is it just another line item to the budget? >> So I'm afraid that some people might view it that way. As just another line item. But, I would challenge that and say data science is going to reinvent IT. It's going to change the nature of IT. And every organization needs to think about what are the skills that are critical? How do we engage a broader team to do this? Because once they get there, this is the chance to reinvent how they're performing IT. >> [Katie] Challenging or not? >> Look it's all a big challenge. Think about everything IT organizations have been through. Some of them were late to things like mobile, but then they caught up. Some were late to cloud, but then they caught up. I would just urge people, don't be late to data science. Use this as your chance to reinvent IT. Start with this notion of clickers and coders. This is a seminal moment. Much like mobile and cloud was. So don't be late. >> And I think it's critical because it could be so costly to wait. And Rob and I were even chatting earlier how data analytics is just moving into all different kinds of industries. And I can tell you even personally being effected by how important the analysis is in working in pediatric cancer for the last seven years. I personally implement virtual reality headsets to pediatric cancer hospitals across the country. And it's great. And it's working phenomenally. And the kids are amazed. And the staff is amazed. But the phase two of this project is putting in little metrics in the hardware that gather the breathing, the heart rate to show that we have data. Proof that we can hand over to the hospitals to continue making this program a success. So just in-- >> That's a great example. >> An interesting example. >> Saving lives? >> Yes. >> That's also applying a lot of what we talked about. >> Exciting stuff in the world of data science. >> Yes. Look, I just add this is an existential moment for every organization. Because what you do in this area is probably going to define how competitive you are going forward. And think about if you don't do something. What if one of your competitors goes and creates an application that's more engaging with clients? So my recommendation is start small. Experiment. Learn. Iterate on projects. Define the business outcomes. Then scale up. It's very doable. But you've got to take the first step. >> First step always critical. And now we're going to get to the fun hands on part of our story. Because in just a moment we're going to take a closer look at what data science can deliver. And where organizations are trying to get to. All right. Thank you Rob and now we've been joined by Siva Anne who is going to help us navigate this demo. First, welcome Siva. Give him a big round of applause. Yeah. All right, Rob break down what we're going to be looking at. You take over this demo. >> All right. So this is going to be pretty interesting. So Siva is going to take us through. So he's going to play the role of a financial adviser. Who wants to help better serve clients through recommendations. And I'm going to really illustrate three things. One is how do you federate data from multiple data sources? Inside the firewall, outside the firewall. How do you apply machine learning to predict and to automate? And then how do you move analytics closer to your data? So, what you're seeing here is a custom application for an investment firm. So, Siva, our financial adviser, welcome. So you can see at the top, we've got market data. We pulled that from an external source. And then we've got Siva's calendar in the middle. He's got clients on the right side. So page down, what else do you see down there Siva? >> [Siva] I can see the recent market news. And in here I can see that JP Morgan is calling for a US dollar rebound in the second half of the year. And, I have upcoming meeting with Leo Rakes. I can get-- >> [Rob] So let's go in there. Why don't you click on Leo Rakes. So, you're sitting at your desk, you're deciding how you're going to spend the day. You know you have a meeting with Leo. So you click on it. You immediately see, all right, so what do we know about him? We've got data governance implemented. So we know his age, we know his degree. We can see he's not that aggressive of a trader. Only six trades in the last few years. But then where it gets interesting is you go to the bottom. You start to see predicted industry affinity. Where did that come from? How do we have that? >> [Siva] So these green lines and red arrows here indicate the trending affinity of Leo Rakes for particular industry stocks. What we've done here is we've built machine learning models using customer's demographic data, his stock portfolios, and browsing behavior to build a model which can predict his affinity for a particular industry. >> [Rob] Interesting. So, I like to think of this, we call it celebrity experiences. So how do you treat every customer like they're a celebrity? So to some extent, we're reading his mind. Because without asking him, we know that he's going to have an affinity for auto stocks. So we go down. Now we look at his portfolio. You can see okay, he's got some different holdings. He's got Amazon, Google, Apple, and then he's got RACE, which is the ticker for Ferrari. You can see that's done incredibly well. And so, as a financial adviser, you look at this and you say, all right, we know he loves auto stocks. Ferrari's done very well. Let's create a hedge. Like what kind of security would interest him as a hedge against his position for Ferrari? Could we go figure that out? >> [Siva] Yes. Given I know that he's gotten an affinity for auto stocks, and I also see that Ferrari has got some terminus gains, I want to lock in these gains by hedging. And I want to do that by picking a auto stock which has got negative correlation with Ferrari. >> [Rob] So this is where we get to the idea of in database analytics. Cause you start clicking that and immediately we're getting instant answers of what's happening. So what did we find here? We're going to compare Ferrari and Honda. >> [Siva] I'm going to compare Ferrari with Honda. And what I see here instantly is that Honda has got a negative correlation with Ferrari, which makes it a perfect mix for his stock portfolio. Given he has an affinity for auto stocks and it correlates negatively with Ferrari. >> [Rob] These are very powerful tools at the hand of a financial adviser. You think about it. As a financial adviser, you wouldn't think about federating data, machine learning, pretty powerful. >> [Siva] Yes. So what we have seen here is that using the common SQL engine, we've been able to federate queries across multiple data sources. Db2 Warehouse in the cloud, IBM's Integrated Analytic System, and Hortonworks powered Hadoop platform for the new speeds. We've been able to use machine learning to derive innovative insights about his stock affinities. And drive the machine learning into the appliance. Closer to where the data resides to deliver high performance analytics. >> [Rob] At scale? >> [Siva] We're able to run millions of these correlations across stocks, currency, other factors. And even score hundreds of customers for their affinities on a daily basis. >> That's great. Siva, thank you for playing the role of financial adviser. So I just want to recap briefly. Cause this really powerful technology that's really simple. So we federated, we aggregated multiple data sources from all over the web and internal systems. And public cloud systems. Machine learning models were built that predicted Leo's affinity for a certain industry. In this case, automotive. And then you see when you deploy analytics next to your data, even a financial adviser, just with the click of a button is getting instant answers so they can go be more productive in their next meeting. This whole idea of celebrity experiences for your customer, that's available for everybody, if you take advantage of these types of capabilities. Katie, I'll hand it back to you. >> Good stuff. Thank you Rob. Thank you Siva. Powerful demonstration on what we've been talking about all afternoon. And thank you again to Siva for helping us navigate. Should be give him one more round of applause? We're going to be back in just a moment to look at how we operationalize all of this data. But in first, here's a message from me. If you're a part of a line of business, your main fear is disruption. You know data is the new goal that can create huge amounts of value. So does your competition. And they may be beating you to it. You're convinced there are new business models and revenue sources hidden in all the data. You just need to figure out how to leverage it. But with the scarcity of data scientists, you really can't rely solely on them. You may need more people throughout the organization that have the ability to extract value from data. And as a data science leader or data scientist, you have a lot of the same concerns. You spend way too much time looking for, prepping, and interpreting data and waiting for models to train. You know you need to operationalize the work you do to provide business value faster. What you want is an easier way to do data prep. And rapidly build models that can be easily deployed, monitored and automatically updated. So whether you're a data scientist, data science leader, or in a line of business, what's the solution? What'll it take to transform the way you work? That's what we're going to explore next. All right, now it's time to delve deeper into the nuts and bolts. The nitty gritty of operationalizing data science and creating a data driven culture. How do you actually do that? Well that's what these experts are here to share with us. I'm joined by Nir Kaldero, who's head of data science at Galvanize, which is an education and training organization. Tricia Wang, who is co-founder of Sudden Compass, a consultancy that helps companies understand people with data. And last, but certainly not least, Michael Li, founder and CEO of Data Incubator, which is a data science train company. All right guys. Shall we get right to it? >> All right. >> So data explosion happening right now. And we are seeing it across the board. I just shared an example of how it's impacting my philanthropic work in pediatric cancer. But you guys each have so many unique roles in your business life. How are you seeing it just blow up in your fields? Nir, your thing? >> Yeah, for example like in Galvanize we train many Fortune 500 companies. And just by looking at the demand of companies that wants us to help them go through this digital transformation is mind-blowing. Data point by itself. >> Okay. Well what we're seeing what's going on is that data science like as a theme, is that it's actually for everyone now. But what's happening is that it's actually meeting non technical people. But what we're seeing is that when non technical people are implementing these tools or coming at these tools without a base line of data literacy, they're often times using it in ways that distance themselves from the customer. Because they're implementing data science tools without a clear purpose, without a clear problem. And so what we do at Sudden Compass is that we work with companies to help them embrace and understand the complexity of their customers. Because often times they are misusing data science to try and flatten their understanding of the customer. As if you can just do more traditional marketing. Where you're putting people into boxes. And I think the whole ROI of data is that you can now understand people's relationships at a much more complex level at a greater scale before. But we have to do this with basic data literacy. And this has to involve technical and non technical people. >> Well you can have all the data in the world, and I think it speaks to, if you're not doing the proper movement with it, forget it. It means nothing at the same time. >> No absolutely. I mean, I think that when you look at the huge explosion in data, that comes with it a huge explosion in data experts. Right, we call them data scientists, data analysts. And sometimes they're people who are very, very talented, like the people here. But sometimes you have people who are maybe re-branding themselves, right? Trying to move up their title one notch to try to attract that higher salary. And I think that that's one of the things that customers are coming to us for, right? They're saying, hey look, there are a lot of people that call themselves data scientists, but we can't really distinguish. So, we have sort of run a fellowship where you help companies hire from a really talented group of folks, who are also truly data scientists and who know all those kind of really important data science tools. And we also help companies internally. Fortune 500 companies who are looking to grow that data science practice that they have. And we help clients like McKinsey, BCG, Bain, train up their customers, also their clients, also their workers to be more data talented. And to build up that data science capabilities. >> And Nir, this is something you work with a lot. A lot of Fortune 500 companies. And when we were speaking earlier, you were saying many of these companies can be in a panic. >> Yeah. >> Explain that. >> Yeah, so you know, not all Fortune 500 companies are fully data driven. And we know that the winners in this fourth industrial revolution, which I like to call the machine intelligence revolution, will be companies who navigate and transform their organization to unlock the power of data science and machine learning. And the companies that are not like that. Or not utilize data science and predictive power well, will pretty much get shredded. So they are in a panic. >> Tricia, companies have to deal with data behind the firewall and in the new multi cloud world. How do organizations start to become driven right to the core? >> I think the most urgent question to become data driven that companies should be asking is how do I bring the complex reality that our customers are experiencing on the ground in to a corporate office? Into the data models. So that question is critical because that's how you actually prevent any big data disasters. And that's how you leverage big data. Because when your data models are really far from your human models, that's when you're going to do things that are really far off from how, it's going to not feel right. That's when Tesco had their terrible big data disaster that they're still recovering from. And so that's why I think it's really important to understand that when you implement big data, you have to further embrace thick data. The qualitative, the emotional stuff, that is difficult to quantify. But then comes the difficult art and science that I think is the next level of data science. Which is that getting non technical and technical people together to ask how do we find those unknown nuggets of insights that are difficult to quantify? Then, how do we do the next step of figuring out how do you mathematically scale those insights into a data model? So that actually is reflective of human understanding? And then we can start making decisions at scale. But you have to have that first. >> That's absolutely right. And I think that when we think about what it means to be a data scientist, right? I always think about it in these sort of three pillars. You have the math side. You have to have that kind of stats, hardcore machine learning background. You have the programming side. You don't work with small amounts of data. You work with large amounts of data. You've got to be able to type the code to make those computers run. But then the last part is that human element. You have to understand the domain expertise. You have to understand what it is that I'm actually analyzing. What's the business proposition? And how are the clients, how are the users actually interacting with the system? That human element that you were talking about. And I think having somebody who understands all of those and not just in isolation, but is able to marry that understanding across those different topics, that's what makes a data scientist. >> But I find that we don't have people with those skill sets. And right now the way I see teams being set up inside companies is that they're creating these isolated data unicorns. These data scientists that have graduated from your programs, which are great. But, they don't involve the people who are the domain experts. They don't involve the designers, the consumer insight people, the people, the salespeople. The people who spend time with the customers day in and day out. Somehow they're left out of the room. They're consulted, but they're not a stakeholder. >> Can I actually >> Yeah, yeah please. >> Can I actually give a quick example? So for example, we at Galvanize train the executives and the managers. And then the technical people, the data scientists and the analysts. But in order to actually see all of the RY behind the data, you also have to have a creative fluid conversation between non technical and technical people. And this is a major trend now. And there's a major gap. And we need to increase awareness and kind of like create a new, kind of like environment where technical people also talks seamlessly with non technical ones. >> [Tricia] We call-- >> That's one of the things that we see a lot. Is one of the trends in-- >> A major trend. >> data science training is it's not just for the data science technical experts. It's not just for one type of person. So a lot of the training we do is sort of data engineers. People who are more on the software engineering side learning more about the stats of math. And then people who are sort of traditionally on the stat side learning more about the engineering. And then managers and people who are data analysts learning about both. >> Michael, I think you said something that was of interest too because I think we can look at IBM Watson as an example. And working in healthcare. The human component. Because often times we talk about machine learning and AI, and data and you get worried that you still need that human component. Especially in the world of healthcare. And I think that's a very strong point when it comes to the data analysis side. Is there any particular example you can speak to of that? >> So I think that there was this really excellent paper a while ago talking about all the neuro net stuff and trained on textual data. So looking at sort of different corpuses. And they found that these models were highly, highly sexist. They would read these corpuses and it's not because neuro nets themselves are sexist. It's because they're reading the things that we write. And it turns out that we write kind of sexist things. And they would sort of find all these patterns in there that were sort of latent, that had a lot of sort of things that maybe we would cringe at if we sort of saw. And I think that's one of the really important aspects of the human element, right? It's being able to come in and sort of say like, okay, I know what the biases of the system are, I know what the biases of the tools are. I need to figure out how to use that to make the tools, make the world a better place. And like another area where this comes up all the time is lending, right? So the federal government has said, and we have a lot of clients in the financial services space, so they're constantly under these kind of rules that they can't make discriminatory lending practices based on a whole set of protected categories. Race, sex, gender, things like that. But, it's very easy when you train a model on credit scores to pick that up. And then to have a model that's inadvertently sexist or racist. And that's where you need the human element to come back in and say okay, look, you're using the classic example would be zip code, you're using zip code as a variable. But when you look at it, zip codes actually highly correlated with race. And you can't do that. So you may inadvertently by sort of following the math and being a little naive about the problem, inadvertently introduce something really horrible into a model and that's where you need a human element to sort of step in and say, okay hold on. Slow things down. This isn't the right way to go. >> And the people who have -- >> I feel like, I can feel her ready to respond. >> Yes, I'm ready. >> She's like let me have at it. >> And the people here it is. And the people who are really great at providing that human intelligence are social scientists. We are trained to look for bias and to understand bias in data. Whether it's quantitative or qualitative. And I really think that we're going to have less of these kind of problems if we had more integrated teams. If it was a mandate from leadership to say no data science team should be without a social scientist, ethnographer, or qualitative researcher of some kind, to be able to help see these biases. >> The talent piece is actually the most crucial-- >> Yeah. >> one here. If you look about how to enable machine intelligence in organization there are the pillars that I have in my head which is the culture, the talent and the technology infrastructure. And I believe and I saw in working very closely with the Fortune 100 and 200 companies that the talent piece is actually the most important crucial hard to get. >> [Tricia] I totally agree. >> It's absolutely true. Yeah, no I mean I think that's sort of like how we came up with our business model. Companies were basically saying hey, I can't hire data scientists. And so we have a fellowship where we get 2,000 applicants each quarter. We take the top 2% and then we sort of train them up. And we work with hiring companies who then want to hire from that population. And so we're sort of helping them solve that problem. And the other half of it is really around training. Cause with a lot of industries, especially if you're sort of in a more regulated industry, there's a lot of nuances to what you're doing. And the fastest way to develop that data science or AI talent may not necessarily be to hire folks who are coming out of a PhD program. It may be to take folks internally who have a lot of that domain knowledge that you have and get them trained up on those data science techniques. So we've had large insurance companies come to us and say hey look, we hire three or four folks from you a quarter. That doesn't move the needle for us. What we really need is take the thousand actuaries and statisticians that we have and get all of them trained up to become a data scientist and become data literate in this new open source world. >> [Katie] Go ahead. >> All right, ladies first. >> Go ahead. >> Are you sure? >> No please, fight first. >> Go ahead. >> Go ahead Nir. >> So this is actually a trend that we have been seeing in the past year or so that companies kind of like start to look how to upscale and look for talent within the organization. So they can actually move them to become more literate and navigate 'em from analyst to data scientist. And from data scientist to machine learner. So this is actually a trend that is happening already for a year or so. >> Yeah, but I also find that after they've gone through that training in getting people skilled up in data science, the next problem that I get is executives coming to say we've invested in all of this. We're still not moving the needle. We've already invested in the right tools. We've gotten the right skills. We have enough scale of people who have these skills. Why are we not moving the needle? And what I explain to them is look, you're still making decisions in the same way. And you're still not involving enough of the non technical people. Especially from marketing, which is now, the CMO's are much more responsible for driving growth in their companies now. But often times it's so hard to change the old way of marketing, which is still like very segmentation. You know, demographic variable based, and we're trying to move people to say no, you have to understand the complexity of customers and not put them in boxes. >> And I think underlying a lot of this discussion is this question of culture, right? >> Yes. >> Absolutely. >> How do you build a data driven culture? And I think that that culture question, one of the ways that comes up quite often in especially in large, Fortune 500 enterprises, is that they are very, they're not very comfortable with sort of example, open source architecture. Open source tools. And there is some sort of residual bias that that's somehow dangerous. So security vulnerability. And I think that that's part of the cultural challenge that they often have in terms of how do I build a more data driven organization? Well a lot of the talent really wants to use these kind of tools. And I mean, just to give you an example, we are partnering with one of the major cloud providers to sort of help make open source tools more user friendly on their platform. So trying to help them attract the best technologists to use their platform because they want and they understand the value of having that kind of open source technology work seamlessly on their platforms. So I think that just sort of goes to show you how important open source is in this movement. And how much large companies and Fortune 500 companies and a lot of the ones we work with have to embrace that. >> Yeah, and I'm seeing it in our work. Even when we're working with Fortune 500 companies, is that they've already gone through the first phase of data science work. Where I explain it was all about the tools and getting the right tools and architecture in place. And then companies started moving into getting the right skill set in place. Getting the right talent. And what you're talking about with culture is really where I think we're talking about the third phase of data science, which is looking at communication of these technical frameworks so that we can get non technical people really comfortable in the same room with data scientists. That is going to be the phase, that's really where I see the pain point. And that's why at Sudden Compass, we're really dedicated to working with each other to figure out how do we solve this problem now? >> And I think that communication between the technical stakeholders and management and leadership. That's a very critical piece of this. You can't have a successful data science organization without that. >> Absolutely. >> And I think that actually some of the most popular trainings we've had recently are from managers and executives who are looking to say, how do I become more data savvy? How do I figure out what is this data science thing and how do I communicate with my data scientists? >> You guys made this way too easy. I was just going to get some popcorn and watch it play out. >> Nir, last 30 seconds. I want to leave you with an opportunity to, anything you want to add to this conversation? >> I think one thing to conclude is to say that companies that are not data driven is about time to hit refresh and figure how they transition the organization to become data driven. To become agile and nimble so they can actually see what opportunities from this important industrial revolution. Otherwise, unfortunately they will have hard time to survive. >> [Katie] All agreed? >> [Tricia] Absolutely, you're right. >> Michael, Trish, Nir, thank you so much. Fascinating discussion. And thank you guys again for joining us. We will be right back with another great demo. Right after this. >> Thank you Katie. >> Once again, thank you for an excellent discussion. Weren't they great guys? And thank you for everyone who's tuning in on the live webcast. As you can hear, we have an amazing studio audience here. And we're going to keep things moving. I'm now joined by Daniel Hernandez and Siva Anne. And we're going to turn our attention to how you can deliver on what they're talking about using data science experience to do data science faster. >> Thank you Katie. Siva and I are going to spend the next 10 minutes showing you how you can deliver on what they were saying using the IBM Data Science Experience to do data science faster. We'll demonstrate through new features we introduced this week how teams can work together more effectively across the entire analytics life cycle. How you can take advantage of any and all data no matter where it is and what it is. How you could use your favorite tools from open source. And finally how you could build models anywhere and employ them close to where your data is. Remember the financial adviser app Rob showed you? To build an app like that, we needed a team of data scientists, developers, data engineers, and IT staff to collaborate. We do this in the Data Science Experience through a concept we call projects. When I create a new project, I can now use the new Github integration feature. We're doing for data science what we've been doing for developers for years. Distributed teams can work together on analytics projects. And take advantage of Github's version management and change management features. This is a huge deal. Let's explore the project we created for the financial adviser app. As you can see, our data engineer Joane, our developer Rob, and others are collaborating this project. Joane got things started by bringing together the trusted data sources we need to build the app. Taking a closer look at the data, we see that our customer and profile data is stored on our recently announced IBM Integrated Analytics System, which runs safely behind our firewall. We also needed macro economic data, which she was able to find in the Federal Reserve. And she stored it in our Db2 Warehouse on Cloud. And finally, she selected stock news data from NASDAQ.com and landed that in a Hadoop cluster, which happens to be powered by Hortonworks. We added a new feature to the Data Science Experience so that when it's installed with Hortonworks, it automatically uses a need of security and governance controls within the cluster so your data is always secure and safe. Now we want to show you the news data we stored in the Hortonworks cluster. This is the mean administrative console. It's powered by an open source project called Ambari. And here's the news data. It's in parquet files stored in HDFS, which happens to be a distributive file system. To get the data from NASDAQ into our cluster, we used IBM's BigIntegrate and BigQuality to create automatic data pipelines that acquire, cleanse, and ingest that news data. Once the data's available, we use IBM's Big SQL to query that data using SQL statements that are much like the ones we would use for any relation of data, including the data that we have in the Integrated Analytics System and Db2 Warehouse on Cloud. This and the federation capabilities that Big SQL offers dramatically simplifies data acquisition. Now we want to show you how we support a brand new tool that we're excited about. Since we launched last summer, the Data Science Experience has supported Jupyter and R for data analysis and visualization. In this week's update, we deeply integrated another great open source project called Apache Zeppelin. It's known for having great visualization support, advanced collaboration features, and is growing in popularity amongst the data science community. This is an example of Apache Zeppelin and the notebook we created through it to explore some of our data. Notice how wonderful and easy the data visualizations are. Now we want to walk you through the Jupyter notebook we created to explore our customer preference for stocks. We use notebooks to understand and explore data. To identify the features that have some predictive power. Ultimately, we're trying to assess what ultimately is driving customer stock preference. Here we did the analysis to identify the attributes of customers that are likely to purchase auto stocks. We used this understanding to build our machine learning model. For building machine learning models, we've always had tools integrated into the Data Science Experience. But sometimes you need to use tools you already invested in. Like our very own SPSS as well as SAS. Through new import feature, you can easily import those models created with those tools. This helps you avoid vendor lock-in, and simplify the development, training, deployment, and management of all your models. To build the models we used in app, we could have coded, but we prefer a visual experience. We used our customer profile data in the Integrated Analytic System. Used the Auto Data Preparation to cleanse our data. Choose the binary classification algorithms. Let the Data Science Experience evaluate between logistic regression and gradient boosted tree. It's doing the heavy work for us. As you can see here, the Data Science Experience generated performance metrics that show us that the gradient boosted tree is the best performing algorithm for the data we gave it. Once we save this model, it's automatically deployed and available for developers to use. Any application developer can take this endpoint and consume it like they would any other API inside of the apps they built. We've made training and creating machine learning models super simple. But what about the operations? A lot of companies are struggling to ensure their model performance remains high over time. In our financial adviser app, we know that customer data changes constantly, so we need to always monitor model performance and ensure that our models are retrained as is necessary. This is a dashboard that shows the performance of our models and lets our teams monitor and retrain those models so that they're always performing to our standards. So far we've been showing you the Data Science Experience available behind the firewall that we're using to build and train models. Through a new publish feature, you can build models and deploy them anywhere. In another environment, private, public, or anywhere else with just a few clicks. So here we're publishing our model to the Watson machine learning service. It happens to be in the IBM cloud. And also deeply integrated with our Data Science Experience. After publishing and switching to the Watson machine learning service, you can see that our stock affinity and model that we just published is there and ready for use. So this is incredibly important. I just want to say it again. The Data Science Experience allows you to train models behind your own firewall, take advantage of your proprietary and sensitive data, and then deploy those models wherever you want with ease. So summarize what we just showed you. First, IBM's Data Science Experience supports all teams. You saw how our data engineer populated our project with trusted data sets. Our data scientists developed, trained, and tested a machine learning model. Our developers used APIs to integrate machine learning into their apps. And how IT can use our Integrated Model Management dashboard to monitor and manage model performance. Second, we support all data. On premises, in the cloud, structured, unstructured, inside of your firewall, and outside of it. We help you bring analytics and governance to where your data is. Third, we support all tools. The data science tools that you depend on are readily available and deeply integrated. This includes capabilities from great partners like Hortonworks. And powerful tools like our very own IBM SPSS. And fourth, and finally, we support all deployments. You can build your models anywhere, and deploy them right next to where your data is. Whether that's in the public cloud, private cloud, or even on the world's most reliable transaction platform, IBM z. So see for yourself. Go to the Data Science Experience website, take us for a spin. And if you happen to be ready right now, our recently created Data Science Elite Team can help you get started and run experiments alongside you with no charge. Thank you very much. >> Thank you very much Daniel. It seems like a great time to get started. And thanks to Siva for taking us through it. Rob and I will be back in just a moment to add some perspective right after this. All right, once again joined by Rob Thomas. And Rob obviously we got a lot of information here. >> Yes, we've covered a lot of ground. >> This is intense. You got to break it down for me cause I think we zoom out and see the big picture. What better data science can deliver to a business? Why is this so important? I mean we've heard it through and through. >> Yeah, well, I heard it a couple times. But it starts with businesses have to embrace a data driven culture. And it is a change. And we need to make data accessible with the right tools in a collaborative culture because we've got diverse skill sets in every organization. But data driven companies succeed when data science tools are in the hands of everyone. And I think that's a new thought. I think most companies think just get your data scientist some tools, you'll be fine. This is about tools in the hands of everyone. I think the panel did a great job of describing about how we get to data science for all. Building a data culture, making it a part of your everyday operations, and the highlights of what Daniel just showed us, that's some pretty cool features for how organizations can get to this, which is you can see IBM's Data Science Experience, how that supports all teams. You saw data analysts, data scientists, application developer, IT staff, all working together. Second, you saw how we support all tools. And your choice of tools. So the most popular data science libraries integrated into one platform. And we saw some new capabilities that help companies avoid lock-in, where you can import existing models created from specialist tools like SPSS or others. And then deploy them and manage them inside of Data Science Experience. That's pretty interesting. And lastly, you see we continue to build on this best of open tools. Partnering with companies like H2O, Hortonworks, and others. Third, you can see how you use all data no matter where it lives. That's a key challenge every organization's going to face. Private, public, federating all data sources. We announced new integration with the Hortonworks data platform where we deploy machine learning models where your data resides. That's been a key theme. Analytics where the data is. And lastly, supporting all types of deployments. Deploy them in your Hadoop cluster. Deploy them in your Integrated Analytic System. Or deploy them in z, just to name a few. A lot of different options here. But look, don't believe anything I say. Go try it for yourself. Data Science Experience, anybody can use it. Go to datascience.ibm.com and look, if you want to start right now, we just created a team that we call Data Science Elite. These are the best data scientists in the world that will come sit down with you and co-create solutions, models, and prove out a proof of concept. >> Good stuff. Thank you Rob. So you might be asking what does an organization look like that embraces data science for all? And how could it transform your role? I'm going to head back to the office and check it out. Let's start with the perspective of the line of business. What's changed? Well, now you're starting to explore new business models. You've uncovered opportunities for new revenue sources and all that hidden data. And being disrupted is no longer keeping you up at night. As a data science leader, you're beginning to collaborate with a line of business to better understand and translate the objectives into the models that are being built. Your data scientists are also starting to collaborate with the less technical team members and analysts who are working closest to the business problem. And as a data scientist, you stop feeling like you're falling behind. Open source tools are keeping you current. You're also starting to operationalize the work that you do. And you get to do more of what you love. Explore data, build models, put your models into production, and create business impact. All in all, it's not a bad scenario. Thanks. All right. We are back and coming up next, oh this is a special time right now. Cause we got a great guest speaker. New York Magazine called him the spreadsheet psychic and number crunching prodigy who went from correctly forecasting baseball games to correctly forecasting presidential elections. He even invented a proprietary algorithm called PECOTA for predicting future performance by baseball players and teams. And his New York Times bestselling book, The Signal and the Noise was named by Amazon.com as the number one best non-fiction book of 2012. He's currently the Editor in Chief of the award winning website, FiveThirtyEight and appears on ESPN as an on air commentator. Big round of applause. My pleasure to welcome Nate Silver. >> Thank you. We met backstage. >> Yes. >> It feels weird to re-shake your hand, but you know, for the audience. >> I had to give the intense firm grip. >> Definitely. >> The ninja grip. So you and I have crossed paths kind of digitally in the past, which it really interesting, is I started my career at ESPN. And I started as a production assistant, then later back on air for sports technology. And I go to you to talk about sports because-- >> Yeah. >> Wow, has ESPN upped their game in terms of understanding the importance of data and analytics. And what it brings. Not just to MLB, but across the board. >> No, it's really infused into the way they present the broadcast. You'll have win probability on the bottom line. And they'll incorporate FiveThirtyEight metrics into how they cover college football for example. So, ESPN ... Sports is maybe the perfect, if you're a data scientist, like the perfect kind of test case. And the reason being that sports consists of problems that have rules. And have structure. And when problems have rules and structure, then it's a lot easier to work with. So it's a great way to kind of improve your skills as a data scientist. Of course, there are also important real world problems that are more open ended, and those present different types of challenges. But it's such a natural fit. The teams. Think about the teams playing the World Series tonight. The Dodgers and the Astros are both like very data driven, especially Houston. Golden State Warriors, the NBA Champions, extremely data driven. New England Patriots, relative to an NFL team, it's shifted a little bit, the NFL bar is lower. But the Patriots are certainly very analytical in how they make decisions. So, you can't talk about sports without talking about analytics. >> And I was going to save the baseball question for later. Cause we are moments away from game seven. >> Yeah. >> Is everyone else watching game seven? It's been an incredible series. Probably one of the best of all time. >> Yeah, I mean-- >> You have a prediction here? >> You can mention that too. So I don't have a prediction. FiveThirtyEight has the Dodgers with a 60% chance of winning. >> [Katie] LA Fans. >> So you have two teams that are about equal. But the Dodgers pitching staff is in better shape at the moment. The end of a seven game series. And they're at home. >> But the statistics behind the two teams is pretty incredible. >> Yeah. It's like the first World Series in I think 56 years or something where you have two 100 win teams facing one another. There have been a lot of parity in baseball for a lot of years. Not that many offensive overall juggernauts. But this year, and last year with the Cubs and the Indians too really. But this year, you have really spectacular teams in the World Series. It kind of is a showcase of modern baseball. Lots of home runs. Lots of strikeouts. >> [Katie] Lots of extra innings. >> Lots of extra innings. Good defense. Lots of pitching changes. So if you love the modern baseball game, it's been about the best example that you've had. If you like a little bit more contact, and fewer strikeouts, maybe not so much. But it's been a spectacular and very exciting World Series. It's amazing to talk. MLB is huge with analysis. I mean, hands down. But across the board, if you can provide a few examples. Because there's so many teams in front offices putting such an, just a heavy intensity on the analysis side. And where the teams are going. And if you could provide any specific examples of teams that have really blown your mind. Especially over the last year or two. Because every year it gets more exciting if you will. I mean, so a big thing in baseball is defensive shifts. So if you watch tonight, you'll probably see a couple of plays where if you're used to watching baseball, a guy makes really solid contact. And there's a fielder there that you don't think should be there. But that's really very data driven where you analyze where's this guy hit the ball. That part's not so hard. But also there's game theory involved. Because you have to adjust for the fact that he knows where you're positioning the defenders. He's trying therefore to make adjustments to his own swing and so that's been a major innovation in how baseball is played. You know, how bullpens are used too. Where teams have realized that actually having a guy, across all sports pretty much, realizing the importance of rest. And of fatigue. And that you can be the best pitcher in the world, but guess what? After four or five innings, you're probably not as good as a guy who has a fresh arm necessarily. So I mean, it really is like, these are not subtle things anymore. It's not just oh, on base percentage is valuable. It really effects kind of every strategic decision in baseball. The NBA, if you watch an NBA game tonight, see how many three point shots are taken. That's in part because of data. And teams realizing hey, three points is worth more than two, once you're more than about five feet from the basket, the shooting percentage gets really flat. And so it's revolutionary, right? Like teams that will shoot almost half their shots from the three point range nowadays. Larry Bird, who wound up being one of the greatest three point shooters of all time, took only eight three pointers his first year in the NBA. It's quite noticeable if you watch baseball or basketball in particular. >> Not to focus too much on sports. One final question. In terms of Major League Soccer, and now in NFL, we're having the analysis and having wearables where it can now showcase if they wanted to on screen, heart rate and breathing and how much exertion. How much data is too much data? And when does it ruin the sport? >> So, I don't think, I mean, again, it goes sport by sport a little bit. I think in basketball you actually have a more exciting game. I think the game is more open now. You have more three pointers. You have guys getting higher assist totals. But you know, I don't know. I'm not one of those people who thinks look, if you love baseball or basketball, and you go in to work for the Astros, the Yankees or the Knicks, they probably need some help, right? You really have to be passionate about that sport. Because it's all based on what questions am I asking? As I'm a fan or I guess an employee of the team. Or a player watching the game. And there isn't really any substitute I don't think for the insight and intuition that a curious human has to kind of ask the right questions. So we can talk at great length about what tools do you then apply when you have those questions, but that still comes from people. I don't think machine learning could help with what questions do I want to ask of the data. It might help you get the answers. >> If you have a mid-fielder in a soccer game though, not exerting, only 80%, and you're seeing that on a screen as a fan, and you're saying could that person get fired at the end of the day? One day, with the data? >> So we found that actually some in soccer in particular, some of the better players are actually more still. So Leo Messi, maybe the best player in the world, doesn't move as much as other soccer players do. And the reason being that A) he kind of knows how to position himself in the first place. B) he realizes that you make a run, and you're out of position. That's quite fatiguing. And particularly soccer, like basketball, is a sport where it's incredibly fatiguing. And so, sometimes the guys who conserve their energy, that kind of old school mentality, you have to hustle at every moment. That is not helpful to the team if you're hustling on an irrelevant play. And therefore, on a critical play, can't get back on defense, for example. >> Sports, but also data is moving exponentially as we're just speaking about today. Tech, healthcare, every different industry. Is there any particular that's a favorite of yours to cover? And I imagine they're all different as well. >> I mean, I do like sports. We cover a lot of politics too. Which is different. I mean in politics I think people aren't intuitively as data driven as they might be in sports for example. It's impressive to follow the breakthroughs in artificial intelligence. It started out just as kind of playing games and playing chess and poker and Go and things like that. But you really have seen a lot of breakthroughs in the last couple of years. But yeah, it's kind of infused into everything really. >> You're known for your work in politics though. Especially presidential campaigns. >> Yeah. >> This year, in particular. Was it insanely challenging? What was the most notable thing that came out of any of your predictions? >> I mean, in some ways, looking at the polling was the easiest lens to look at it. So I think there's kind of a myth that last year's result was a big shock and it wasn't really. If you did the modeling in the right way, then you realized that number one, polls have a margin of error. And so when a candidate has a three point lead, that's not particularly safe. Number two, the outcome between different states is correlated. Meaning that it's not that much of a surprise that Clinton lost Wisconsin and Michigan and Pennsylvania and Ohio. You know I'm from Michigan. Have friends from all those states. Kind of the same types of people in those states. Those outcomes are all correlated. So what people thought was a big upset for the polls I think was an example of how data science done carefully and correctly where you understand probabilities, understand correlations. Our model gave Trump a 30% chance of winning. Others models gave him a 1% chance. And so that was interesting in that it showed that number one, that modeling strategies and skill do matter quite a lot. When you have someone saying 30% versus 1%. I mean, that's a very very big spread. And number two, that these aren't like solved problems necessarily. Although again, the problem with elections is that you only have one election every four years. So I can be very confident that I have a better model. Even one year of data doesn't really prove very much. Even five or 10 years doesn't really prove very much. And so, being aware of the limitations to some extent intrinsically in elections when you only get one kind of new training example every four years, there's not really any way around that. There are ways to be more robust to sparce data environments. But if you're identifying different types of business problems to solve, figuring out what's a solvable problem where I can add value with data science is a really key part of what you're doing. >> You're such a leader in this space. In data and analysis. It would be interesting to kind of peek back the curtain, understand how you operate but also how large is your team? How you're putting together information. How quickly you're putting it out. Cause I think in this right now world where everybody wants things instantly-- >> Yeah. >> There's also, you want to be first too in the world of journalism. But you don't want to be inaccurate because that's your credibility. >> We talked about this before, right? I think on average, speed is a little bit overrated in journalism. >> [Katie] I think it's a big problem in journalism. >> Yeah. >> Especially in the tech world. You have to be first. You have to be first. And it's just pumping out, pumping out. And there's got to be more time spent on stories if I can speak subjectively. >> Yeah, for sure. But at the same time, we are reacting to the news. And so we have people that come in, we hire most of our people actually from journalism. >> [Katie] How many people do you have on your team? >> About 35. But, if you get someone who comes in from an academic track for example, they might be surprised at how fast journalism is. That even though we might be slower than the average website, the fact that there's a tragic event in New York, are there things we have to say about that? A candidate drops out of the presidential race, are things we have to say about that. In periods ranging from minutes to days as opposed to kind of weeks to months to years in the academic world. The corporate world moves faster. What is a little different about journalism is that you are expected to have more precision where people notice when you make a mistake. In corporations, you have maybe less transparency. If you make 10 investments and seven of them turn out well, then you'll get a lot of profit from that, right? In journalism, it's a little different. If you make kind of seven predictions or say seven things, and seven of them are very accurate and three of them aren't, you'll still get criticized a lot for the three. Just because that's kind of the way that journalism is. And so the kind of combination of needing, not having that much tolerance for mistakes, but also needing to be fast. That is tricky. And I criticize other journalists sometimes including for not being data driven enough, but the best excuse any journalist has, this is happening really fast and it's my job to kind of figure out in real time what's going on and provide useful information to the readers. And that's really difficult. Especially in a world where literally, I'll probably get off the stage and check my phone and who knows what President Trump will have tweeted or what things will have happened. But it really is a kind of 24/7. >> Well because it's 24/7 with FiveThirtyEight, one of the most well known sites for data, are you feeling micromanagey on your people? Because you do have to hit this balance. You can't have something come out four or five days later. >> Yeah, I'm not -- >> Are you overseeing everything? >> I'm not by nature a micromanager. And so you try to hire well. You try and let people make mistakes. And the flip side of this is that if a news organization that never had any mistakes, never had any corrections, that's raw, right? You have to have some tolerance for error because you are trying to decide things in real time. And figure things out. I think transparency's a big part of that. Say here's what we think, and here's why we think it. If we have a model to say it's not just the final number, here's a lot of detail about how that's calculated. In some case we release the code and the raw data. Sometimes we don't because there's a proprietary advantage. But quite often we're saying we want you to trust us and it's so important that you trust us, here's the model. Go play around with it yourself. Here's the data. And that's also I think an important value. >> That speaks to open source. And your perspective on that in general. >> Yeah, I mean, look, I'm a big fan of open source. I worry that I think sometimes the trends are a little bit away from open source. But by the way, one thing that happens when you share your data or you share your thinking at least in lieu of the data, and you can definitely do both is that readers will catch embarrassing mistakes that you made. By the way, even having open sourceness within your team, I mean we have editors and copy editors who often save you from really embarrassing mistakes. And by the way, it's not necessarily people who have a training in data science. I would guess that of our 35 people, maybe only five to 10 have a kind of formal background in what you would call data science. >> [Katie] I think that speaks to the theme here. >> Yeah. >> [Katie] That everybody's kind of got to be data literate. >> But yeah, it is like you have a good intuition. You have a good BS detector basically. And you have a good intuition for hey, this looks a little bit out of line to me. And sometimes that can be based on domain knowledge, right? We have one of our copy editors, she's a big college football fan. And we had an algorithm we released that tries to predict what the human being selection committee will do, and she was like, why is LSU rated so high? Cause I know that LSU sucks this year. And we looked at it, and she was right. There was a bug where it had forgotten to account for their last game where they lost to Troy or something and so -- >> That also speaks to the human element as well. >> It does. In general as a rule, if you're designing a kind of regression based model, it's different in machine learning where you have more, when you kind of build in the tolerance for error. But if you're trying to do something more precise, then so much of it is just debugging. It's saying that looks wrong to me. And I'm going to investigate that. And sometimes it's not wrong. Sometimes your model actually has an insight that you didn't have yourself. But fairly often, it is. And I think kind of what you learn is like, hey if there's something that bothers me, I want to go investigate that now and debug that now. Because the last thing you want is where all of a sudden, the answer you're putting out there in the world hinges on a mistake that you made. Cause you never know if you have so to speak, 1,000 lines of code and they all perform something differently. You never know when you get in a weird edge case where this one decision you made winds up being the difference between your having a good forecast and a bad one. In a defensible position and a indefensible one. So we definitely are quite diligent and careful. But it's also kind of knowing like, hey, where is an approximation good enough and where do I need more precision? Cause you could also drive yourself crazy in the other direction where you know, it doesn't matter if the answer is 91.2 versus 90. And so you can kind of go 91.2, three, four and it's like kind of A) false precision and B) not a good use of your time. So that's where I do still spend a lot of time is thinking about which problems are "solvable" or approachable with data and which ones aren't. And when they're not by the way, you're still allowed to report on them. We are a news organization so we do traditional reporting as well. And then kind of figuring out when do you need precision versus when is being pointed in the right direction good enough? >> I would love to get inside your brain and see how you operate on just like an everyday walking to Walgreens movement. It's like oh, if I cross the street in .2-- >> It's not, I mean-- >> Is it like maddening in there? >> No, not really. I mean, I'm like-- >> This is an honest question. >> If I'm looking for airfares, I'm a little more careful. But no, part of it's like you don't want to waste time on unimportant decisions, right? I will sometimes, if I can't decide what to eat at a restaurant, I'll flip a coin. If the chicken and the pasta both sound really good-- >> That's not high tech Nate. We want better. >> But that's the point, right? It's like both the chicken and the pasta are going to be really darn good, right? So I'm not going to waste my time trying to figure it out. I'm just going to have an arbitrary way to decide. >> Serious and business, how organizations in the last three to five years have just evolved with this data boom. How are you seeing it as from a consultant point of view? Do you think it's an exciting time? Do you think it's a you must act now time? >> I mean, we do know that you definitely see a lot of talent among the younger generation now. That so FiveThirtyEight has been at ESPN for four years now. And man, the quality of the interns we get has improved so much in four years. The quality of the kind of young hires that we make straight out of college has improved so much in four years. So you definitely do see a younger generation for which this is just part of their bloodstream and part of their DNA. And also, particular fields that we're interested in. So we're interested in people who have both a data and a journalism background. We're interested in people who have a visualization and a coding background. A lot of what we do is very much interactive graphics and so forth. And so we do see those skill sets coming into play a lot more. And so the kind of shortage of talent that had I think frankly been a problem for a long time, I'm optimistic based on the young people in our office, it's a little anecdotal but you can tell that there are so many more programs that are kind of teaching students the right set of skills that maybe weren't taught as much a few years ago. >> But when you're seeing these big organizations, ESPN as perfect example, moving more towards data and analytics than ever before. >> Yeah. >> You would say that's obviously true. >> Oh for sure. >> If you're not moving that direction, you're going to fall behind quickly. >> Yeah and the thing is, if you read my book or I guess people have a copy of the book. In some ways it's saying hey, there are lot of ways to screw up when you're using data. And we've built bad models. We've had models that were bad and got good results. Good models that got bad results and everything else. But the point is that the reason to be out in front of the problem is so you give yourself more runway to make errors and mistakes. And to learn kind of what works and what doesn't and which people to put on the problem. I sometimes do worry that a company says oh we need data. And everyone kind of agrees on that now. We need data science. Then they have some big test case. And they have a failure. And they maybe have a failure because they didn't know really how to use it well enough. But learning from that and iterating on that. And so by the time that you're on the third generation of kind of a problem that you're trying to solve, and you're watching everyone else make the mistake that you made five years ago, I mean, that's really powerful. But that doesn't mean that getting invested in it now, getting invested both in technology and the human capital side is important. >> Final question for you as we run out of time. 2018 beyond, what is your biggest project in terms of data gathering that you're working on? >> There's a midterm election coming up. That's a big thing for us. We're also doing a lot of work with NBA data. So for four years now, the NBA has been collecting player tracking data. So they have 3D cameras in every arena. So they can actually kind of quantify for example how fast a fast break is, for example. Or literally where a player is and where the ball is. For every NBA game now for the past four or five years. And there hasn't really been an overall metric of player value that's taken advantage of that. The teams do it. But in the NBA, the teams are a little bit ahead of journalists and analysts. So we're trying to have a really truly next generation stat. It's a lot of data. Sometimes I now more oversee things than I once did myself. And so you're parsing through many, many, many lines of code. But yeah, so we hope to have that out at some point in the next few months. >> Anything you've personally been passionate about that you've wanted to work on and kind of solve? >> I mean, the NBA thing, I am a pretty big basketball fan. >> You can do better than that. Come on, I want something real personal that you're like I got to crunch the numbers. >> You know, we tried to figure out where the best burrito in America was a few years ago. >> I'm going to end it there. >> Okay. >> Nate, thank you so much for joining us. It's been an absolute pleasure. Thank you. >> Cool, thank you. >> I thought we were going to chat World Series, you know. Burritos, important. I want to thank everybody here in our audience. Let's give him a big round of applause. >> [Nate] Thank you everyone. >> Perfect way to end the day. And for a replay of today's program, just head on over to ibm.com/dsforall. I'm Katie Linendoll. And this has been Data Science for All: It's a Whole New Game. Test one, two. One, two, three. Hi guys, I just want to quickly let you know as you're exiting. A few heads up. Downstairs right now there's going to be a meet and greet with Nate. And we're going to be doing that with clients and customers who are interested. So I would recommend before the game starts, and you lose Nate, head on downstairs. And also the gallery is open until eight p.m. with demos and activations. And tomorrow, make sure to come back too. Because we have exciting stuff. I'll be joining you as your host. And we're kicking off at nine a.m. So bye everybody, thank you so much. >> [Announcer] Ladies and gentlemen, thank you for attending this evening's webcast. If you are not attending all cloud and cognitive summit tomorrow, we ask that you recycle your name badge at the registration desk. Thank you. Also, please note there are two exits on the back of the room on either side of the room. Have a good evening. Ladies and gentlemen, the meet and greet will be on stage. Thank you.