>>Okay. We're back at the area in Las Vegas, Falcon 22. You're watching the cube. My name is Dave Valante. Michael cent is here. He's the chief technology officer at CrowdStrike. Michael. Good to see you. Thanks. Thanks >>For >>Having me. Yeah. So this is your first time I think, on the cube. It is, and, and it's really a pleasure. I've been following you, watching you very closely. You're, you know, quite prominent and, and, you know, very articulate. I loved your keynote talking about what is XDR. I think you guys are gonna do really well in that space, cuz you've got clarity of vision and execution. Talk about some of the announcements that you made this week, particularly interested in, in insight. XDR what's that all about? >>Yeah. So I've been talking about XDR for a while and trying to help push the right narrative. There's a lot of marketing in the industry with XDR. So we've been talking a lot about what it, what it means that the benefit that it provides from a technology perspective, what you need in the architecture. So we firmly believe it's a philosophy and we build all of our technology to work together, but it's bringing in third parties. And that was really a lot of the, the announcements. My keynote was to show everybody the work that we've been doing to bring in data from Zscaler and Proofpoint. And we talked about bringing in data from a whole range of different vendors, firewall vendors, and we've been doing XDR use cases for a long time. So a big part of our strategy is to make security easy. And we've been doing a lot of XDR use cases with our Falcon insight module. So the announcement that I made was to relaunch Falcon insight as insight XDR and it means all of our close to 20,000 customers have access to the product. >>So that gets bundled right in it's like SAS automatically part of the portfolio >>Log off on Friday, come back on Monday and you're good to go. >>And then, and you, you just, you just called out Zscaler and Proofpoint you, I think you also mentioned Palo Alto network, Cisco for net as well. You're pulling in telemetry from, yeah, >>We've got a, we got a long map of, of people that we're integrating with. We talked about Cisco, we talked about for drop and for net, we announced that we're gonna be pulling in telemetry from, from Palo and a range of other vendors, Microsoft and others. And that's what XDR is about. It's about first party and third party integration and making all of the telemetry work together. >>I was talking to George about this yesterday is I think there's a lot of confusion. Sometimes when you have the dogma of cloud native, you know, snowflake, same thing, no, we're not doing OnPrem. This is hybrid. People think that that you're excluding on-prem data, but you're not, you can ingest on-prem data, right? >>We absolutely are not excluding on-prem. We will support and, and secure every workload, whether it's on-prem or in the cloud, whether it's connected to the internet or offline, a lot of the, the indicators of attack and the, and the detection techniques that we have are on the sensor itself. So you don't have to be connected anywhere for that capability to work. You get the benefit when you connect to the cloud of the additional visibility, the additional protection, but the core capabilities on the sensor that we have >>Given that you guys started 11 years ago, plus two days now, and you had that dogma cloud cloud, first cloud cloud, only Nate cloud native. Was there ever a point where you're like, you know, boy, we might be missing some of the market, you know? And, and you, you, you held true to your principles. Two part question. Did you ever question that and by focusing all your resources on cloud, what, what has that given you? >>It's there's been a Eliza focus on having a, a native cloud platform. It's easy to say cloud native. And if you look at a lot of the vendors in the industry today, if you are a, a customer and you ask them, Hey, can you gimme an on-premise product? I'm not gonna buy your product. They've got an on premise product. The problem is when you have two different versions, you end up having compromise. You have to manage two code bases, impact to your engineering team. Their features are different customers. Ultimately are the ones that miss out because if I have the on-prem version or if the cloud version, I may not get the same capability for us, it's been very clear. It's been a laser focus to be a cloud and cloud only from day one. >>You've renamed humo. I gotta stop using humo. I guess it's not called log scale, Falcon, complete log scale. You're bringing together security and observability. Although you're not doing the full spectrum of observability, you're just sort of focusing on, you know, part of it. Can you explain that? >>Yeah. So first of all, we did rebrand and bring the homeo brand closer to a crowd strike by renaming it Falcon log scale. And just to be clear, it's not just the rebranding of the name. We've been spending a lot of time. We made that acquisition in March of, of last year, and we've been doing a lot of work on the technology. We built out long, the Falcon long term retention. We built a whole bunch of capability into the product. So now was the right time to rebrand it as Falcon log scale. And at the same time, we also announced Falcon complete log scale. And it's part of the complete franchise. And that's where customers can get the value and the benefit of log scale, but they don't have to set it up. They don't have to manage it. They leave that to us. >>So you get pretty much involved in, in the, the M and a activity. You talked on stage yesterday about reify and, and what's going on there. You guys got, obviously gotta, still do that. You, but you made investments this week. You announced investments in salt security, the API specialist, and, and also Vanta compliance automation. What's the thinking behind that, you know, explain actually the fund that you guys are sprinkling around as a strategic investor and why those companies. Yeah. >>So there's two, two parts that, that I'm involved in on that part of my team. One is the M and a team. And one is the Falcon fund side of the business. Obviously two very different things. The, the M and a part of CrowdStrike, we're always looking to see for every technology space that we want to get into, you know, what is the best option build by a partner? Sometimes it's built sometimes it's a, it's a hybrid approach of build and partner. Other times we go down the path of M and a, and I was super excited about reify, great company, great technology. And as you said, we made announcements to we're investing as part of the fund into, into van and salt. We, we, we are very blessed. We're very fortunate to have achieved a lot of success in a short period of time. And we think we've got an opportunity to help fledgling companies to help them guide through the process of setting up the company, helping them with engineering principles and guidelines, helping them with the go to market perspective. So the fund is really about that. It's finding the next cybersecurity company working closely together, and it's been a huge success. You had banter and salt on earlier, and there's so much excitement about what they do. >>Yeah. I mean, it's clear, clear, compliment to what you guys are doing. I want to ask you about your lightweight agent. There, there are other firms that say they have a lightweight agent too. You know, what, what makes your lightweight agent so different? So special? >>Yeah. I've never seen a PowerPoint presentation. That's wrong. It's very easy to, to say your lightweight agent is, is, you know, super lightweight. And many times when you look at them, they're, they're not lightweight. They take a lot of effort to install. They need reboots. If you've got security, that's part of the operating system. If you've got security that requires to reboot, you can't go to a bank and say, Hey, you've got a hundred thousand machines. We're gonna install all of this technology, but you've gotta reboot it once, twice, three times. So what ends up happening is you see deployment cycles that go on for 12 months. I've spoken to organizations here this week that said we had budgeted to roll out your product in 18 months because of what we experienced in the past. And we did it in seven weeks. That's a lightweight agent with no reboot. And then you look at the updates. You look at the CPU resource utilization. So again, very easy to say lightweight. I haven't seen anything like what we've built at crowd strike. >>How do you keep an agent lightweight when you're both acquiring in companies and adding modules? I think you're, you're over 20 modules now. How, how is it that the, the agent can remain so lightweight? >>So we spent a lot of time building out the agent cloud architecture that we have, the, the concept of our agent is very different. It's not collecting data, storing it, trying to sell, send it up. We have a smart agent with smart filtering built in. So we're very careful in terms of the data that we collect, but think of the aperture on a camera. You know, if you wanna let more light in you, you widen the aperture. It's the same as our, our agent. If we wanna bring in more telemetry, we, we widen that aperture. So we're very efficient on the network. And we collect data. When machine process runs, we collect that telemetry. We use it in different ways, but we collect once and reuse it many times. So it's the same agent for NextGen AV for EDR, for our spotlight vulnerability management module. And when we're looking at M M and a, so coming back to your, your question, we will look at technology. And if we can't bring that technology and incorporate it into the agent that we already have, we won't acquire it. Worst thing in security is complexity. When you give an organization, 1, 2, 3, 5 plus agents, and then they have 3, 4, 5 plus management consoles. It's too hard when they're under attack. >>Well, it's like my, my business partner co-host John furrier says is that as an industry, we tend to solve complexity with more complexity. And it's, that's problematic. Can you talk about your, your threat graph? Like, what is that? Is it a, is it a graph database? Is it a purpose built? Is it a time series, database, a combination? What, what is >>That? Yeah, it is a graph database. When we, when, when the company was started, obviously the vision was to crowdsource telemetry from so many machines from millions of devices around the world. And the thesis at the time was as that capability scales out, there's nothing commercially available that will be able to ingest all of that data. And today we are processing over 7 trillion events every single week. We, we can't go and get something off the shelf. So we've had to build the, the technology from the ground up. That's the first part. Secondly, there is a temporal element to this. There's a time element. And we, we have an ontology built where we track the relationship between all the telemetry that we get. The reason why I believe we stand alone in EDI is because of that time element, the relationship that we have, and we just have so much context that makes it easy for the threat hunter speed and, and ease of use is critical in cyber. >>So you see in data in the database world, everything's kind of converging with all this function, you know, 11 years ago, these were pretty rudimentary. I shouldn't say rudimentary, but immature markets they've come a long way. If you had to start, if, if those capabilities that are there today with graph databases and time series databases were available in, in 2010, would you have used off the shelf technology, or would you have still developed your >>Own? We would've done the same thing that we've done today. >>And, and why can you explain what that, what that is it a performance thing? Is it just control? >>Yeah, look, it, it, it's everything that I talked about before, the, the benefit that you get from the approach that we've taken and the scalability that the requirements that we need, we still today, there's nothing that we can, we can go and get off the shelf that can scale and give us the performance that we need that can give us the ability to, to have that relationship data, the ontology of, of what we have in the platform and the way that we inter operate with all of the different modules that just wouldn't exist. We wouldn't have that capability. And what you'd find is we'd be pretty much the same as every other vendor where they have on-prem solutions, they have hybrid hosted solutions. And when you have those trade offs, you see it in the product. >>Yeah. So the, the point is you're very focused on the purpose of your, your proprietary technology. You're not trying to serve the all things to all people. You used the term yesterday in your keynote, which it, it caught my attention. You used the term ground truth, and it has very specific meaning. Can you explain what you meant by what is ground truth, you know, in the world? And what, what, what does it mean to CrowdStrike? Yeah, >>I was talking about ground truth as it relates to the acquisition of reify and the big thing for us, we wanted to bring additional capability to the platform, to give our customers external and internal visibility of all their assets and all their vulnerabilities. What's important with us, with our agent is today, we give you a single source of truth. When we put that agent onto a device, we tell you everything about the hardware. We tell you everything about who's logged in. We tell you everything about the applications that are running the relationships between the, of the device and the application. We're not a CMDB. We feed CMDB with information that is instant, that is live. And when we look at reify, it broadens again, I'll use the same word. It broadens the aperture. It gives us more visibility around what's going on. So we're, we're super excited about that because having information about all of your assets, all of your users, the applications they use, whether they're vulnerable, how you need to protect them, having it at your finger fingertips, it's a game changer >>Contract, can CrowdStrike be a generational company. And what do you have to do to ensure that that outcome occurs? We, >>We, I think we absolutely are. And, and we're we're path paving a path to, you know, really continuing to build out that platform. I said, in my keynote that I think we're at an early innings. I, if you buy, for example, as a customer, our insight module, cuz you wanna start with EDR, you've got 21 modules to go yesterday. Today we, we talked about discover 2.0, we talked about discover for IOT. I talked about the, the repository acquisition, a whole range of technology built on that single cloud agent architecture. And we've heard the success stories here this week from customers that have just gotten so much benefit. They've rolled out one agent and they've turned off eight or nine from other security vendors. So absolutely we can be a generational company with what we're doing. What >>Are the blockers to customers turning on those additional modules? Cause not, not all customers are using our modules. Is it that they've made an investment in an alternative technology and they're sort of hugging onto it or are there other technical blockers? Yes. >>It many times it's the investment, right? So if you've made a, an investment in the company, you've got a year to go, you might wanna sweat that asset. But typically what we find is the benefit that we have. It's a very simple conversation. If we can give people a cost and a technology benefit, they're gonna make the transition to move. There's so many technical benefits. We talked about the single agent, but the actual features of the modules themselves. But the big thing for us is we've done over 4,700 business value assessments where we sit down with an organization and we look at what they have. We look at what their spend is. We look at their FTEs, we look at the security outcomes that they get. And then we come out with a model that shows them technology and business value. And that's what really drives them to make the switch. >>So the business value in that VVA is not just a, a reduction in expected loss. That's part of it, better security you're gonna, you know, be, be, be lower your risk. But you're saying it's also the labor associated with that. Yeah, >>Absolutely. It's it's how do you operationalize the solution? How many people do you need? How long does it take you to respond? You know, how do you interact with third parties with your suppliers is taking in all of that data. We've spent a long time building out that model and it's, it's proving to be very successful customers. Love it. Is >>That, is that sort of novel ROI thinking in the security business or I'm trying to think of, I mean, I know for years it would watch art. Coviello stand up at RSA and tell us how, how this year's worse than last year. And so, but, but, but I never really heard, you know, a strong business case that would resonate with the, with the P and L manager, other than, you know, we gotta do this or we're gonna get hacked and you're gonna be screwed. Is that new thinking? Or am I, did I just miss it? >>I don't know if I wanna size new thinking. I think what happened, what changed was 10, 15 years ago at a conference you'd stand up and everybody would tell you ransomwares up and fishing is up. And at the end of it, people are trying to work out. Is that good? Or is that bad? It went up 20% based off what that doesn't work anymore. Everyone, you know, got tired of that. And a few of us have been doing it for a while. I I'm, I'm sort of two and a half decades into this. And if you, if you try to use that model of scaring people, they switch off, they want to understand the benefit. You know, the break in the car is so you can go and stop safely when you need it. And I look at security the same way we want to accelerate the company. We want to help companies do their job, but security is there to make sure they don't get into trouble. >>Yeah. It's like having two security guards by your side, right? I mean, they're gonna help you get through the crowd and move forward. So Michael, thanks so much for coming to the cube. Thanks for having me your time. You're you're very welcome. All right. Keep it right there. After this short break, Dave ante will be back with the cube live coverage from Falcon 22 at the area in Las Vegas.

(upbeat music) >> Hello everyone, and welcome to Fal.Con 2022, CrowdStrike's big user conference. You're watching the Cube. My name is Dave Vallante. I'm here with my co-host David Nicholson. CrowdStrike is a company that was founded over 10 years ago. This is about 11 years, almost to the day. They're 2 billion company in revenue terms. They're growing at about 60% a year. They've got a path they've committed to wall street. They've got a path to $5 billion by mid decade. They got a $40 billion market cap. They're free, free cash flow positive and trying to build essentially a generational company with a very growing Tam and a modern platform. CrowdStrike has the fundamental belief that the unstoppable breach is a myth. David Nicholson, even though CSOs don't believe that, CrowdStrike is on a mission. Right? >> I didn't hear the phrase. Zero trust mentioned in the keynote >> Right. >> What was mentioned was this idea that CrowdStrike isn't simply a tool, it's a platform. And obviously it takes a platform to get to 5 billion. >> Yeah. So let's talk about the keynote. George Kurtz, the CEO came on. I thought the keynote was, was measured, but very substantive. It was not a lot of hype in there. Most security conferences, the two exceptions are this one and Reinforce, Amazon's big security conference. Steven Schmidt. The first time I was at a Reinforce said "All this narrative about security is such a bad industry" and "We're not doing a great job." And "It's so scary." That doesn't help the industry. George Kurtz sort of took a similar message. And you know what, Dave? When I think of security outside the context of IT I think of like security guards >> Right. >> Like protecting the billionaires. Right? That's a powerful, you know, positive thing. It's not really a defensive movement even though it is defensive but so that was kind of his posture there. But he talked about essentially what I call, not his words permanent changes in the, in the in the cyber defense industry, subsequent to the pandemic. Again, he didn't specifically mention the pandemic but he alluded to, you know, this new world that we live in. Fal.Con is a hundred sessions, eight tracks. And really his contention is we're in the early innings. These guys got 20,000 customers. And I think they got the potential to have hundreds of thousands. >> Yeah. Yeah. So, if I'm working with a security company I want them to be measured. I'm not looking for hype. I don't want those. I don't want those guards to be in disco shirts. I want them in black suits. So, you know, so the, the, the point about measured is is I think a positive one. I was struck by the competence of the people who were on stage today. I have seen very very large companies become kind of bureaucratic. And sometimes you don't get the best of the best up on stage. And we saw a lot of impressive folks. >> Yeah. Michael Santonis get up, but before we get to him. So, a couple points that Kurtz made he said, "digital transformation is needed to bring modern architectures to IT. And that brings modern security." And he laid out that whole sort of old way, new way very Andy Jassy-like old guard, new guard. He didn't hit on it that hard but he basically said "security is all about mitigating risk." And he mentioned that the the CSO I say CSO, he says CSO or CSO has a seat at the board. Now, many CSOs are board level participants. And then he went into the sort of four pillars of, of workload, and the areas that they focus on. So workload to them is end point, identity, and then data. They don't touch network security. That's where they partner with the likes of Cisco, >> Right. >> And Palo Alto networks. But then they went deep into identity threat protection, data, which is their observability platform from an acquisition called Humio. And then they went big time into XDR. We're going to talk about all this stuff. He said, "data is the new digital currency." Talked a lot about how they're now renaming, Humio, Log Scale. That's their Splunk killer. We're going to talk about that all week. And he talked a little bit about the single agent architecture. That is kind of the linchpin of CrowdStrike's architecture. And then Michael Santonis, the CTO came on and did a deep dive into each of those, and really went deep into XDR extended, right? Detection and response. XDR building on EDR. >> Yeah. I think the subject of XDR is something we'll be, we'll be touching on a lot. I think in the next two days. I thought the extension into observability was very, very interesting. When you look at performance metrics, where things are gathering those things in and being able to use a single agent to do so. That speaks to this idea that they are a platform and not just a tool. It's easy to say that you aspire to be a platform. I think that's a proof point. On the subject, by the way of their fundamental architecture. Over the years, there have been times when saying that your infrastructure requires an agent that would've been a deal killer. People say "No agents!" They've stuck to their guns because they know that the best way to deliver what they deliver is to have an agent in the environment. And it has proven to be the right strategy. >> Well, this is one of the things I want to explore with the technical architects that come on here today is, how do you build a lightweight agent that can do everything that you say it's going to do? Because they started out at endpoint, and then they've extended it to all these other modules, you know, identity. They're now into observability. They've got this data platform. They just announced that acquisition of another company they bought Preempt, which is their identity. They announced Responsify, responsify? Reposify, which is sort of extends the observability and gives them visualization or visibility. And I'm like, how do you take? How do you keep an agent lightweight? That's one of the things I want to better understand. And then the other is, as you get into XDR I thought Michael Santonis was pretty interesting. He had black hat last month. He did a little video, you know. >> That was great >> Man in the street, what's XDR what's XDR what's XDR. I thought the best response was, somebody said "a holistic approach to end point security." And so it's really an evolution of, of EDR. So we're going to talk about that. But, how do you keep an agent lightweight and still support all these other capabilities? That's something I really want to dig into, you know, without getting bloated. >> Yeah, Yeah. I think it's all about the TLAs, Dave. It's about the S, it's about SDKs and APIs and having an ecosystem of partners that will look at the lightweight agent and then develop around it. Again, going back to the idea of platform, it's critical. If you're trying to do it all on your own, you get bloat. If you try to be all things to all people with your agent, if you try to reverse engineer every capability that's out there, it doesn't work. >> Well that's one of the things that, again I want to explore because CrowdStrike is trying to be a generational company. In the Breaking Analysis that we published this week. One of the things I said, "In order to be a generational company you have to have a strong ecosystem." Now the ecosystem here is respectable, you know, but it's obviously not AWS class. You know, I think Snowflake is a really good example, ServiceNow. This feels to me like ServiceNow circa 2013. >> Yeah. >> And we've seen how ServiceNow has evolved. You know, Okta, bought Off Zero to give them the developer angle. We heard a little bit about a developer platform today. I want to dig into that some more. And we heard a lot about everybody hates their DLP. I want to get rid of my DLP, data loss prevention. And so, and the same thing with the SIM. One of the ETR round table, Eric Bradley, our colleague at a round table said "If it weren't for the compliance requirements, I would replace my SIM with XDR." And so that's again, another interesting topic. CrowdStrike, cloud native, lightweight agent, you know, some really interesting tuck in acquisitions. Great go-to-market, you know, not super hype just product that works and gets stuff done, you know, seems to have a really good, bright future. >> Yeah, no, I would agree. Definitely. No hype necessary. Just constant execution moving forward. It's clearly something that will be increasingly in demand. Another subject that came up that I thought was interesting, in the keynote, was this idea of security for elections, extending into the realm of misinformation and disinformation which are both very very loaded terms. It'll be very interesting to see how security works its way into that realm in the future. >> Yeah, yeah, >> Yeah. >> Yeah, his guy, Kevin Mandia, who is the CEO of Mandiant, which just got acquired. Google just closed the deal for $5.4 billion. I thought that was kind of light, by the way, I thought Mandiant was worth more than that. Still a good number, but, and Kevin, you know was the founder and, >> Great guy. >> they were self-funded. >> Yeah, yeah impressive. >> So. But I thought he was really impressive. He talked about election security in terms of hardening you know, the election infrastructure, but then, boom he went right to what I see as the biggest issue, disinformation. And so I'm sitting there asking myself, okay how do you deal with that? And what he talked about was mapping network effects and monitoring network effects, >> Right. >> to see who's pumping the disinformation and building career streams to really monitor those network effects, positive, you know, factual or non-factual network or information. Because a lot of times, you know, networks will pump factual information to build credibility. Right? >> Right. >> And get street cred, earn that trust. You know, you talk about zero trust. And then pump disinformation into the network. So they've now got a track. We'll get, we have Kevin Mandia on later with Sean Henry who's the CSO yeah, the the CSO or C S O, chief security officer of CrowdStrike >> more TLA. Well, so, you can think of it as almost the modern equivalent of the political ad where the candidate at the end says I support this ad or I stand behind whatever's in this ad. Forget about trying to define what is dis or misinformation. What is opinion versus fact. Let's have a standard for finding, for exposing where the information is coming from. So if you could see, if you're reading something and there is something that is easily de-code able that says this information is coming from a troll farm of a thousand bots and you can sort of examine the underlying ethos behind where this information is coming from. And you can take that into consideration. Personally, I'm not a believer in trying to filter stuff out. Put the garbage out there, just make sure people know where the garbage is coming from so they can make decisions about it. >> So I got a thought on that because, Kevin Mandia touched on it. Again, I want to ask about this. He said, so this whole idea of these, you know detecting the bots and monitoring the networks. Then he said, you can I think he said something that's to the effect of. "You can go on the offensive." And I'm thinking, okay, what does that mean? So for instance, you see it all the time. Anytime I see some kind of fact put out there, I got to start reading the comments and like cause I like to see both sides, you know. I'm right down the middle. And you'll go down and like 40 comments down, you're like, oh this is, this is fake. This video was edited, >> Right. >> Da, da, da, da, and then a bunch of other people. But then the bots take over and that gets buried. So, maybe going on the offensive is to your point. Go ahead and put it out there. But then the bots, the positive bots say, okay, by the way, this is fake news. This is an edited video FYI. And this is who put it out and here's the bot graph or something like that. And then you attack the bots with more bots and then now everybody can sort of of see it, you know? And it's not like you don't have to, you know email your friend and saying, "Hey dude, this is fake news." >> Right, right. >> You know, Do some research. >> Yeah. >> Put the research out there in volume is what you're saying. >> Yeah. So, it's an, it's just I thought it was an interesting segue into another area of security under the heading of election security. That is fraught with a lot of danger if done wrong, if done incorrectly, you know, you you get into the realm of opinion making. And we should be free to see information, but we also should have access to information about where the information is coming from. >> The other narrative that you hear. So, everything's down today again and I haven't checked lately, but security generally, we wrote about this in our Breaking Analysis. Security, somewhat, has held up in the stock market better than the broad tech market. Why? And the premise is, George Kurt said this on the last conference call, earnings call, that "security is non-discretionary." At the same time he did say that sales cycles are getting a little longer, but we see this as a positive for CrowdStrike. Because CrowdStrike, their mission, or one of their missions is to consolidate all these point tools. We've talked many, many times in the Cube, and in Breaking Analysis and on Silicon Angle, and on Wikibon, how the the security business use too many point tools. You know this as a former CTO. And, now you've got all these stove pipes, the number one challenge the CSOs face is lack of talent. CrowdStrike's premise is they can consolidate that with the Fal.Con platform, and have a single point of control. "Single pane of glass" to use that bromide. So, the question is, is security really non-discretionary? My answer to that is yes and no. It is to a sense, because security is the number one priority. You can't be lax on security. But at the same time the CSO doesn't have an open checkbook, >> Right. >> He or she can't just say, okay, I need this. I need that. I need this. There's other competing initiatives that have to be taken in balance. And so, we've seen in the ETR spending data, you know. By the way, everything's up relative to where it was, pre you know, right at the pandemic, right when, pandemic year everything was flat to down. Everything's up, really up last year, I don't know 8 to 10%. It was expected to be up 8% this year, let's call it 6 to 7% in 21. We were calling for 7 to 8% this year. It's back down to like, you know, 4 or 5% now. It's still healthy, but it's softer. People are being more circumspect. People aren't sure about what the fed's going to do next. Interest rates, you know, loom large. A lot of uncertainty out here. So, in that sense, I would say security is not non-discretionary. Sorry for the double negative. What's your take? >> I think it's less discretionary. >> Okay. >> Food, water, air. Non-discretionary. (David laughing) And then you move away in sort of gradations from that point. I would say that yeah, it is, it falls into the category of less-discretionary. >> Alright. >> Which is a good place to be. >> Dave Nicholson and David Vallante here. Two days of wall to wall coverage of Fal.Con 2022, CrowdStrike's big user conference. We got some great guests. Keep it right there, we'll be right back, right after this short break. (upbeat music)

>>Hi, everybody. We're wrapping up day two of AWS reinforced the Cube's continuous coverage. My business partner, John furrier, and co-host is actually a Monaco, um, you know, getting ready to do a big crypto show over there. So they'll be reporting from there tomorrow. Check that out in the cube.net. Jeff Swain is here. He is the vice president of global programs store and tech alliances at CrowdStrike. Jeff, thanks for coming on. Thanks >>David. >>So tell us about your role, what store, help us understand that? >>Yeah, so CrowdStrike has a CrowdStrike store, which is, uh, effectively our marketplace within our application, and also available externally that allows customers to be able to review decide and trial products, not only from CrowdStrike, but also from our third party partners. So wherever we have a tech Alliance customer can come in, see the value of the integration, see how it works on our platform and the third parties platform, and then go and request a trial. So it's a very easy and dynamic way for a customer to understand that joint value proposition CrowdStrike has with various other, other vendors and our own products as well. >>So your role is to bring all these cool tech companies together and create incremental value. >>Yes. Um, we believe that the ecosystem is really a, a natural evolution of what's happened in terms of the crowd struck story. If you think that we started out with a, uh, you know, a very simple product in the very early days, 10, 10, 11 years ago, services company built a product. That product then became a platform with various modules in it. The next evolution of that is expanding out beyond our own platform and working into other areas of, of, of interest and value. So that's where the ecosystem comes into play. So you have to underpin that with some automations things like marketplaces and stores, you have to have integrations in place, joint applications and commercial vehicles to make that work. >>So I was walking around the other day and I, and it caught my eye and I sat there and listened for a better part of the presentation had to get back and do the queue, but it was a presentation between a CrowdStrike expert and an Okta expert. Yep. You know, better together was the whole thing. And, you know, I know it's kind of, and then they were describing how you guys compliment each other. So that would be an example, >>A perfect example. I mean, we, we, we compliment Okta and Okta complements us for very, in various different ways. And in fact, we sort of assemble that into different narratives that work well for our customers. So as an example with Okta, we ASEM, we work very well with them in zero trust. So we have a zero trust narrative that talks about how it works with Okta and also Zscaler. In fact, we have a, um, an Alliance through the cloud security Alliance where we're working to build practitioner guides, build, um, uh, a community of value across the different products to bring zero trust into some standardized, you know, uh, reference architectures and some standardized training that brings all of our products together for, for, for the user. That be example of a, of, one of the narratives that we have, they'd also play in our XDR narrative. Obviously XDR helps us bring telemetry in from different products. And again, we use XDR right across, you know, various, various, uh, tech >>Alliances. So, so take zero choice. So you'll take the concept of least privilege. Yep. And you'll apply that to what to end point to, you know, using identity Zscaler, you bring the cloud component. >>Correct. So then we are actually able to see how someone's traversing the entire organization. We can see who they are. We can see where they land. We can see what data they're accessing, where they're accessing. It gather a whole bunch of different telemetry around that and provide the security team with the ability to be able to see what someone's doing, enforce the, um, the, you know, access rights as, and where they need to see any anomalies or anomalous behavior within that and close it down before anything bad happens. So zero trust is a really important part of our, uh, of our, of, of, of our, um, narratives. >>And you have these plays or narratives with, with a bunch of ecosystem partners. Right? Correct. Mean, so take log management. >>Yep. >>Maybe add some context that, >>So, so around that happens, you may know we acquired, um, uh, humo, uh, right around that, where obviously we have to be able to ingest and have bridges out to a large variety of different platforms to be able to ship data into our platform. I mean, one of the values of humo is its ability to massively scale, um, and very, very easily cheaply bring, bring a lot of data into a simple place and have very fast searching. Well, what are you searching? You gotta go and have data sources. So, you know, very quickly we've built out a large number of integrations with, I think, over 30 partners to easily bring data into the Humira platform to let customers be able to have that advantage. >>So what role does AWS play in all this? >>AWS is a fantastic role in, um, both coordinating some of this in terms of, especially through the marketplace, the ability to, uh, coordinate our transactions between us and help us work together from a transactional basis, help the customer procure the right solutions together. But also AWS's nature. Natural, uh, inclination towards innovation means that they'll, they like to work with partners who, especially partners who are on their platform to drive a lot of innovation, to build out how customers are bringing more data together. Obviously it's beneficial to them in terms of the volumes of data that go computers that go across the AWS platform. But also they encourage us to work together. They, they, they say in some cases invest in those integrations. Um, they work with programs. They bring in third party reseller programs, uh, through C P O. So it gives us a, a platform gives us innovation. It gives us some structure. Um, it's been really exciting working with them. >>Now talk about CrowdStrike and your cloud strategy. How would you Des describe your cloud strategy? >>So we've been cloud native from day one. It's one of the, one of the founding principles of CrowdStrike. Um, as, as we were set up, uh, by a founder, so two elements, cloud native, and a single agent, and those two design principles have not been broken by us at any point through our history. It's very important that we, we stick to those two principles. Our cloud is, um, was born in AWS, um, and they've been supportive of us right through, right through our growth period. So we started out with one module, as I said, now we have, I think, 23 different modules and we're continually growing that. We also then have a lot of support for the cloud. So, you know, helping us understand what's happening within cloud environments so that our customers are better protected. In fact, the show here, we've announced two separate, um, uh, uh, incremental products to, to the cloud space. One that's very much focused on, um, adding, uh, better container or better visibility inside containers in our CNA product. And, um, and, and another area around how we do our threat hunting across the cloud. So we have a team of threat hunters, global best engineers who hunt right across our customers environments. We have a whole, whole bunch of additional cloud telemetry. So that's, that's been included into our, into our Overwatch threat hunting. >>So you'll ingest data from multiple clouds, right? You're running on AWS. Yes. But you can take data from anywhere from >>Anywhere, >>Including OnPrem. >>Um, so our sensor sits on laptops, servers, virtual servers devices. Do I devices wherever they need to say. Um, and then of it needs to be cloud connected. It comes into our, into our cloud. So we can, we can take information from instances in any cloud environment and any laptop, uh, to pretty much bring them in. And, uh, that's how it works, but it's a single cloud. I mean, our value proposition is that huge, um, uh, graph threat graph that we've built over the years, um, trillions and trillions of events per day, that we're now searching and using AI technologies to suite out. What's good. And what's bad. >>Yeah. So CrowdStrike, obviously we've reported on CrowdStrike in breaking analysis, a lot, CrowdStrike, Zscaler, Okta, a number of other, those, those companies you're partnering with all those guys, which is quite interesting. Yeah. You're all growing, you know, really nice, nice clips. I wonder, I always wonder in these situations, okay. As things get bigger and bigger and growth slows, we haven't seen that. See, you actually see the, we saw the cloud growth accelerating during the pandemic. Yeah. Right. But, but you know, you wonder, you see it all the time in this, in this industry is companies get big, they start doing M and a, they start getting it to adjacencies, you know, Google, apple, you know, uh, Cisco VMware, do you think you'll ever see a collision course with all these wonderful partners? Are we years away from that? Um, >>I think we're very careful with how we partner and who we partner with. Obviously we, we have discussions on what our future plans are to make sure that what we partner on is, is beneficial to both sides. Um, crowd strike itself. We're, we're growing all the time. You know, our platform has grown, as I said, the modules have grown, but in general, we've found is that our partners are taking the journey with us. Um, it's one of the advantages of, of the success that we've had is most of the partners want to be part of that journey rather than sort of, um, trying to go head on. But, you know, there's always opportunities for us to have open conversations and real dialogue to make sure that we do the right thing for the customer. And that's what drives everything that we do, you know, we're focused on the right products for the right >>Customers. What, what what's reinforcement like, what's the experience been? What, what's your takeaways from the show? >>Um, it's been a really excellent show for us in terms of, uh, getting out, meeting a lot, a lot of customers at a very decent senior level here. Actually's been very, very worthwhile. Um, we've had great response to the announcements that we've made. There's been a lot of, lot of activity through the booth, which is always great to see, um, from a, actually from a partnership perspective from my world, you know, I've had a large number of really great meetings with the AWSs leadership as well about what we can do together. Um, and the future looks really bright. >>Who's the, when you, when you think in thinking about, and I know you're not, you know, selling direct, but when you think about the constituencies, when you think about all the, the partners in your ecosystem that you're, you're building and collaborating with, who do you guys collectively talk to? You know, who do you appeal to? Is it the CISO? Is it the, you know, other security practitioners? Yeah. Is it the line of business? Is it the CIO architect who are the actors that you're sort of collaborating with in your customer >>Side? Yeah, it's really interesting obviously, cuz there's different personas depending on what it is that we're doing. Um, someone who's really interested in our log management narrative for example, is probably going to be maybe from the, the DevOps, um, uh, team or from, from that area for a C app. It's going to be someone in the cloud architecture, cloud security architecture space. Um, zero trust again will be someone who's got a bit of an identity, our area and privacy to them as well. Um, a lot of this comes up to the CISO and that's often our, you know, our, our, our economic buyer would be be in that space. But one of the things we have to do is we go into adjacent markets is learn the personas there and understand their habits and their buying cycles and, and, and build value propositions that work for those people. So it's an ongoing exercise. >>How do you see the CISO role evolving, uh, given, you know, cloud? One of my takeaways from Mr event is like, I feel like cloud is becoming the first line of defense. Mm-hmm <affirmative> the CISO and the developers becoming the second line of defense audit is like the third line of defense. Some people agree with that. Some people do so just merit bear said, no, no, it's all integrated into one thing. And I'm like, no, it's not, but okay. Yeah. But, but how is the CSO role evolving given that the cloud is becoming so much more prominent today? >>I think it's it's at this point, everyone said, you know, the CSO needs to evolve to being a direct member of the directly responsible to the board. This is something that we've all said for many years. Sure. If you look at what we see in the threat report, if you look at what we're seeing from the threat landscape, you know, the volume of threats that are coming through, not diminishing in any way, but in fact, the size and the impact of what they're doing is getting worse. So it, the risk that's being, um, uh, uh, that's being experienced is just getting worse all the time. However, we have different options for resolving that issue. You can go down a services led path with a, with an MDR player, like our file can complete, uh, process, or you can go down with an MSP. So the CISO's role is now not just on what products and how to Def, how to use them to best defend, but also what products, what services are available. >>What am I gonna invest in, in my team versus what am I going to push to a, to a, to a third party to look after for me. And we're seeing more and more companies at the going up the light up the, the, the enterprise stack, trusting us in our Falcon complete team, um, uh, with, with, with parts of their defense portfolio. So I think that role that you, you know, the CISO's role is developing all the time into something that's portfolio oriented. How am I getting value for service as well as value for money from products? It's a really interesting, it's really interesting development, um, in terms of what they have to deal with. Uh, you know, I still think that the, the visibility that you see from the endpoint is where's where it's where the, the Decron jewels are still it's where the data is. Mm-hmm <affirmative>. Um, and I think that's really why crowd strike is a unique proposition in that space. It's what >>We protect. So when you say the end point is where the data is, paint a picture of that. >>Well, if you think about, if a, if an actor is after at a personal information or IP, they're often going to be going down to the laptop or the, or the, or the virtual instance level to look for that within the weakest part, we've always said is people, um, and the more dive, the more open you are with that, the wider your audience there, the, the more risk you carry within that space, you know, we don't think endpoints laptops or phones, you know, servers, um, comput instances inside the cloud. They're all endpoint to us. Workloads is a better word. In fact, >>Those work, sorry, what's a better word >>Workloads >>Workloads. >>Okay. Yeah. We often talk about workloads rather than >>Is it data store and >>Endpoint? Yeah. If it's computer or not, it's, it's, it's basically, uh, it's a workload where, where we can put a sensor. How >>About a, how about a backup Corpus, uh, a backup backup Corpus of data? >>Well, I think if there's a, if there's a place that we can put a sensor on it to see whether it's being, you know, active or not, and we can track the telemetry from it, we would consider >>That sensor would be an agent. Yeah. An agent. Yeah. Yeah. Okay. And so you said single agent, >>We have one agent that runs all of our products this way, again, one of the design principles and, and the basics of our company, >>Because one of the things that we've seen, maybe tell me if you don't see this, is, is that a lot of times ransomware attackers will go after the, the, the backup Corpus mm-hmm <affirmative> disable it. Yeah. Because, you know, once you get that, you can't recover a hundred percent. Yeah. And they'll encrypt the, all the data on the network, and then they'll, they'll hold the backup Corpus hostage. >>This is one of the great advantages of how CrowdStrike and how our platform works. In fact, you know, um, a lot of other vendors talk in terms of, uh, you know, known bad known good, and, and, and indicators of compromise. Right. You know, I know this IP address has been compromised. I know that anything originating from here is bad. Um, what CrowdStrike looks at is, is, is we've built up a very, very, um, substantial, uh, library of what we call indicators of attack. Indications of attack are looking at the potential for attack. And whether, whether that in conjunction that specific piece of telemetry in conjunction with others makes the attack more likely. So for example, if someone, um, opens an email, we don't think that's necessarily, you know, a, a, a risk point, right. Um, but if someone opens an email and they click on an attachment, we think, well, maybe there's, there's, you know, that's happens billions of times a day, so still not bad, but if that then spills up, you know, a process, and if that process then starts to enumerate hard drives and start to look for backups, you know, we're getting more suspicious all the time. >>Um, and if they're then cause an encryption routine, we can be pretty certain at that point that what we've got in play is, is ransomware attack. Um, by looking at the holistic attack, the whole process of it, and having that sort of fingerprint of what that may look like. And in combining that with our knowledge of bad actors, our intelligence in the field, we've got a very good view on what may happen there. So exactly to your point, if we see, um, someone going after backups as part of a wider process that helps us identify that something of something bad is, is about to happen in terms of ransomware attack allows us to take action against it, put in the appropriate containment or blocking, >>And then explain. So, you know, when people hear agents, they're like, oh, another agent to manage, but I was talking to somebody the other day and saying, know, we're gonna integrate with the CrowdStrike agent because it's so robust. Correct. And what we are doing is, which is agent list is it's good, it's lightweight, but we can't get the data. Yep. You know, so explain that. So there's a trade off, right? I mean, you gotta manage an agent, right. But obviously it's working, your customers are, are adopting. >>So it's an extremely lightweight agent. That's always been the, the premise for this. And I think when George founded the company, one of the things he noticed was, you know, how long it was taking for someone to scan it, get us, get through a scan while they were trying to get an email out before a plane took off. And he said, you know, we can't have this. So, so he was looking at how do we make this as light as possible? Um, and, uh, and so that's one of been principle for us, right from day one. And you're right. Um, third parties do want to leverage our agent because of it's robustness. We look at pretty much everything that's happening as a telemetry event, once, once power hits the CPU through, till it drops out. So we've got very rich knowledge of what's happening on every single device or, or workload that's out there. >>And it's very usable for other people, as far as the customer's concerned, if a third party can use that information rather than have to deploy another agent, that's a huge win for the customer. I think we all know that proliferation of agents, Harrison, that's what, that was the old way of doing things. You know, people would acquire products and try and bundle 'em together and what they ended up with multiple agents competing for resources on the, on the system, by having one agent well defined, well architected, what we have is a modern, a modern software architecture to solve modern problems. >>Okay. So, uh, last question. Yep. When during the pandemic, we noticed that the, um, everything changed, obviously work from home remote work, and that the implications on the CISO were these permanent changes. And we reported on this and breaking analysis and other except endpoint, uh, you guys CrowdStrike, uh, uh, identity Okta got a boost, uh, cloud security, Zscaler. Yep. You know, got a boost, rethinking the network network. Security became top of mind that, and that we said is these are permanent changes, but now as we exit, but they were rushed as we exit the isolation economy. What can we expect going forward? >>I think to earlier point the ability for us to work across all of those areas and work better, you know, everyone was very much concentrating on delivered their own product as best as they could, as quickly as they could to meet the demands of the pandemic. Now we can go through a place of making sure that we work really, really well together as different units to solve the customer problem. So trim some of the trim trim, some of the, of, of, of the, the fat out of any integrations that we may have built quickly to solve a problem. Now we can focus on doing it really well. What we're seeing is a proliferation in our world of more applications in our store. So tighter integration inside our UI with our third party products, um, and a lot of demand for that. So really the, the customer experience is as seamless as possible. We talk about, you know, frictionless is what we want to see. Um, and that's, you know, the boost that the, the, the disruption got from the pan from the pandemic was fantastic start of the innovation. Right now, we have the opportunity to bring everything together, to really solve some excellent problems for customers, um, and make the world safer place. >>Jeff, great summary. Thank you for coming on. I'm gonna, I'm gonna give my quick take on, on this reinforc. I mean, I think very clearly AWS is, is enforcing the notion that that security is, is job one for them from the, the nitro chip, you know, all the way up the stack all the way through the culture. I mean, I think we heard that at, at this event. Um, I think you heard, you know, some great announcements, a lot of the stuff around, you know, threat detection and, and, and automation and, and, and reasoning, which is great. I don't think you heard a lot on how AWS are making the CISO's life simpler. I think a lot of that goes to the ecosystem. Mm-hmm <affirmative> maybe, uh, but the other thing is AWS leaving a lot of room, a lot of meat in the bone, as we like to say sometimes for the, for the ecosystem. >>Mm. Um, you know, security is a good example. I mean, you know, Microsoft makes a lot of money and security. AWS doesn't make a ton of money in security. It's just sort of comes with it. I think we're also seeing the changing role, the CISO, I think the cloud is becoming the first line of the fence, CISO and developers. The next line audit is really the third line and developer. The developer role is becoming increasingly important and, and frankly sophisticated, they gotta worry about securing the containers. They gotta worry about the run time. They have to worry about the platform as a service. And so, you know, developers need the team with the, with the, with the security operations team. So that's kind of my takeaway here. I think the event was, was, was good. It was not, it wasn't oversubscribed. I think people in, in Boston this time of year at the beach, um, whereas last 2019, you know, it was June. And so you get, you had a, a bigger attendance, but that's kind of my takeaway. Anything you'd add to that, Jeff, >>I think the quality has been here. Yeah. Um, you know, maybe not the quantity the quality has certainly been here. Um, I think, you know, there is, uh, a lot of innovation that's happening in the security industry. I think AWS has got some good products that they they're helping deliver, but as you said, they're there to help us support us and, and the other ISVs to really come together and build our best of breed overall solution that helps our customers and solve some of that complexity that you're seeing. And some of that uncertainty you're seeing is who has to solve what problem in the stack. Yeah. >>Well, thanks for that. Thanks for that. Thanks for help me wrap up here. The, the security space remains one that's highly fragmented, highly complex, you know, lack of talent is, is the, the problem that most organizations have. Lena smart of MongoDB doesn't have that problem nor does AWS, I guess cuz they're AWS and, and Mongo. Uh, but that's a wrap here from, from day two, the cube go to the cube.net. You'll see all these videos, youtube.com/silicon angle. If you want, you know, the YouTube link. Yeah. You can go there. Silicon angle.com is where we publish all the, the news of the day. wikibon.com for, for the research. This is Dave ante. Look for John furrier from Monica at, uh, the, the crypto event, uh, all this week. And we will see you next time. Thanks for watching.

(upbeat bright music) >> Hello, welcome back to theCUBE's main stage coverage of DockerCon 2022. I'm John for your host of theCUBE. We have Knox Anderson, vice president of Product Management, Sysdig. Knox, welcome to theCUBE. >> Thanks for having me. Glad to be back. >> So IAC containers is going crazy madness in terms of adoption, standard, even mainstream enterprise, IT and cloud are all containerized. It's only getting better, and it increases the complications when you start thinking about scale and supportability. This is a huge discussion, and it ranges from how do you support, how do you run operations, how do you secure in the supply chain. All this is happening, and with the growth of cloud and server (indistinct) seeing Kubernetes at the center of everything. So I got to ask you, how has Kubernetes changed how you secure cloud infrastructure? >> Yeah, so Kubernetes is really the modern operating system for the cloud. And with that, you get a lot of facilities. So you get things like Kubernetes' network policies, you can use things like admission controllers. And with that, you're securing multiple layers, whether it's the control plane, individual workloads. And so there's a nice mixture of built-in tools, and part of the Kubernetes platform that then you can leverage to do prevention, auditing, and things like that. But it really requires an entire rethink of your stack and the tools you bring in alongside your people and processes. And so it's an exciting time because it gives you an opportunity to be more secure, but really have to rethink your approach there. >> And I want to get into the whole observability trend here 'cause you start thinking about the mobility, what containers enables. And getting all the data is everything. And then also that feeds into kind of having a good sense of what is going on. And when you hear about shift left and data as code, you know, developers don't want to get stopped coding, right? And then have to come back and go dig into things that they thought they had taken care of. So you kind of got this kind of flywheel going in the wrong direction. So that's causing teams to be disrupted. So how do teams keep up with the changes to the containerized applications or what to prioritize around that? Because if I shift left, am I done or what? And these are the things that come up all the time. >> Yeah. You have to shift left but also watch the right. Like, shifting left is a little bit harder from a people and process perspective. Like you put a tool in place, then it's a gating factor for getting in. And so that runtime context on the right is equally as important. And it's often easier to roll out a runtime tool just because you're not going in and introducing new processes. And that runtime visibility can also make shift left much better. If you're scanning a container image, you might get a thousand different vulnerabilities that you need to address, but only three of those are in packages that are actually executed at runtime. And so we recently released a feature called risk spotlight which does that exact feedback loop. And that's something that's important whether you're addressing vulnerabilities, misconfigurations, or responding to event. What's on the right, what's on the left, and then tie those together. >> Yeah, it's like left, right, it's like driving training here in the United States. You got a stop sign, you want to be moving, always be moving. I got to ask you what are some of the side effects of infrastructure automation and the result in code artifacts? >> Yeah, it's really, like, Kubernetes is nice because it's a declarative system, but it doesn't always work out that way. Like, someone might have a Helm chart and then someone else changes it in production. So understanding what is drift is really important in these environments. And then it also has enabled real remediation workflows. I think previously, you might patch something, a week later there's a new deploy, that patch gets written over. And so because Kubernetes and the rise of IAC, it's now easier to see a misconfiguration in production, open a poll request, and then fix that at source, which provides that full kind of visibility across those different environments. And it allows you to actually fix issues versus constantly being in that kind of whack-a-mole of patching things and moving on. >> Yeah, I mean this is all about cloud native development, and you look at, you know, some of the things going on, you're starting to see best practices developed. What do you guys see as a best practice for getting started with designing and securing cloud native applications? What are some of the tools that people should look at for beginners and for the entry-level position? And then as they get traction, what does that turn into? >> Yeah, so the pattern we've often seen is like someone gets started on the open source side, whether you're using Open Policy Agent or Falco, which Laurice who've you met with before created. And so really when you're starting, choose kind of the open source option. Learn from that. And then often what we've seen with customers is at scale, there's some companies like if you're in Uber, or Snapchat, and Apple, you can maybe build something around open source, but a lot of other people start to really consolidate platforms that are built on top of those open source technologies, and trying to get that really single view into what's happening in their environment, what are those events. And the thing that I would say, process wise, is most important is build that container center of excellence, that cloud center of excellence, whatever you call it, that brings together people from your ops team, your infrastructure team, your dev team, your security team. Everyone's got to have a seat at the table to have containers be successful. It's a big shift, and if you do it right, it really takes off, but each team really needs to be included there. >> Yeah, there's a lot of operational discussions going on around the devs, and the devs are being pulled to the front lines. We've been saying this for a decade, but now when you got edge computing, you got cloud native operations, on-premises, you start to see that they're getting pulled even further to the frontline. So, you know, what are you guys up to Sysdig? You know, they got a lot of developers here at DockerCon, what's in it for them? Why Sysdig, why should they care? What would you say to the old developers that are watching? What's in it for them? >> Yeah, we really make it easier for you to prioritize what to fix and what to address in your environment. I know I've built something before and like, my test suite or my scanner just lights up like a Christmas tree, and you just want to move to another task because it's just too much to deal with at that time. And so we really help you focus on what matters and get the most bang for your buck. Everyone has way too much time or too many things going on and not enough time. And so being able to understand effective risk, your different vulnerabilities, what to fix, is really key to delivering secure software. >> I mean, it's like a doctor needs to know what to work on with the patient, if you will, when to, and what's important, and then the dependencies, and you got, a system's mindset, you got to know what the consequences. So it sounds easy, just knock down a list of things, but isn't that easy. You got to want to hit things that you know that will be, to have an impact right away. That seems to be the big aha moment here. >> Yeah, definitely. >> So we're going to be at KubeCon in Europe, you guys going to have booth there, what's the quick plug for the company? Give a shout out to what's happening at Sysdig and cloud native world. >> Yeah, really excited to be in Valencia. We have a ton of people at, sorry, at DockerCon with, giving a couple different talks here. So the first is Master Your Container Security Model and then Software Supply Chain Security and Standards. On the supply chain one, we're getting deep into SBOMs. So if that's a topic that's important to you, please join that one. >> Awesome, and then that's a big topic supply chain. We've got a minute and a half left. What's the most important thing people should pay attention to as open source continues to grow in prominence, not just from a code standpoint, but as a social environment, as people's doing ventures and venture capitalists are mining the area, what should they pay attention to as supply chain becomes important, what's the big thing? >> There's a lot of companies I think going around the SBOM space, and kind of trying to certify like where did this come from, and have that providence across the entire supply chain. We, under the hood, use those SBOMs to understand kind of what have you built, what packages are used, and then tie that with that runtime data. So a lot of the things that we talked around before with RiskSpotlight is based on that deep SBOM knowledge. And that's something that, I think the standards are still getting kind of worked out where there's CycloneDX, SBX. And so people really are saying, "Hey, I need to generate SBOMs," and we're regenerating them, but there's going to be more and more applications on "Okay what do you do with that? How does it integrate with other tools?" So it's kind of I think in the little bit of the early data lake phases where it's like, "I've taken all my data, I put it here. Now I need to do more with it." And so that's where I think we'll start to see some pretty exciting things over the next year or two. >> It's super exciting. On one hand you got the attackers, and that's a zero trust environment, and you get the builders, the developers where trust is everything. You got to know what it's in the code. It's really interesting time and super important to scale. So Knox, thanks for for coming on theCUBE and sharing the Sysdig update. Appreciate it, thanks for coming on. Now back to you at the DockerCon main stage, this is theCUBE. I'm John for your host. Thanks for watching. (upbeat bright music)

(upbeat music) >> Okay, welcome back everyone to theCUBE's coverage of AWS re:Invent 2021. This is theCUBE. I'm John Furrier, my host Lisa Martin here, with some keynote guests who are on the big stage here at re:Invent, Linda Jojo, Chief Digital Officer at United Airlines. Thanks for coming on. >> Hey, great to be here. Thanks for having me. >> So up on the big stage, big transformation story in front of 27,000 people, on the virginity, >> Linda: That many? >> that's the number, >> It's a big room >> pretty small for Amazon web services, nearly 60,000, but you know, pandemic and all but great presentation. What was the, what was the transformation story for United? >> Well, I think there's two parts of the story. One is just how fast everything happened, you know. February of 2020, we're having a kickoff meeting with AWS about how we're going to really transform the airline and a month later the world shut down. And so it changed, we went from thinking about the future to really just trying to make it through the next few weeks. But as soon as that happened, we knew that we had to take advantage of the crisis and think about everything from what can we do with our onboard products, we've changed out a lot of things about our airplanes, we've doubled down on sustainability. We're really focused on the diversity of our workforce, but also we really said, what can we do about transforming our technology? And that's where AWS came in because one of the silver linings for our tech team was that we didn't always have a plane in the air. And so when that happens, we had no time to make a change and back it out, if it doesn't work or heaven forbid have an outage. We a little bit longer. So we got aggressive and we made a lot of changes and made a lot of move to AWS Cloud. >> Talk to me a little bit about the cultural shift involved. I mean, you talked about, you know, everybody was just scrambling. >> Yeah. So quickly, there was this instant, what do we do? How do we pivot? How do we survive mode? But from a cultural perspective, it sounds like you took, you leveraged the situation to be able to make a lot of improvements across the United, but culturally that's, that's challenging to get all those folks on board at the same time. How did you facilitate that? >> Well, you know what, the story I'm going to tell isn't all just about me. It's about the incredible team that we have, but you know, folks got focused and Amazon talks about having a two pizza team about how if your team should be no bigger than what can be fed by two pizzas, and that really keeps the decision-making streamlined and fast. For us since we were now all working from home, we called it a one screen team. And so the idea was no more than a number of people that could fit on that video call was the idea. So that was the number of people that we had on our teams. We branded them even call them scrappy teams, which was really kind of fun. And those are the groups that just kind of got their job done. And you know, the first part of their job was every week or every day it seemed like we were getting new rules from the U.S government about what countries you couldn't fly to. And it was chaotic. It was confusing for customers and frankly, our, that one screen team, they were up like every night making modifications to who could check in online and who couldn't. And we said when it's time to open back up, we can't, we got to do this better. And so that group came up with something we now call the Travel-Ready Center. Which is really pretty incredible. What you can do now is first of all, when you book your flight, we'll tell you what you need to fly. You need this type of a COVID test, this many days in advance. This is what fully vaccinated means in the country you're going to. And so this was the kind of vaccine card we need to see. You upload it all. We use Amazon SageMaker and we have machine learning models that actually now will within seven seconds validate that you're ready to fly. And what that means is just like always, you can get your boarding pass before you get to the airport. Now, if you guys travel a lot, I hope you still do, >> Yeah. what that means is that you can actually bypass the lobby of the airport and all the document checking that's going on because your travel ready. So customers love it. Gate agents love it too, because gate agents, the rules are changing so fast. They don't, you know, and they work the flight to Tel Aviv one day and the flight to Paris the next and the rules are different. And maybe in between, they changed. So having the software actually figured that out is what helps. >> So very dynamic and new innovations popped out of this pandemic. What else did Amazon help you with? Was there other Amazon innovations that you guys gravitated to SageMaker was one, what were some of the other? >> Yeah. You know, honestly, the team uses a lot of the tools and a lot of different ways. I would say the other big one was DynamoDB, and some of the things that we did to actually migrate some of our core systems to Amazon and actually, you know, instead of making phoning home to data centers all the time, we're now going right to the Cloud and getting some, some really great performance out of that. >> And, and, and the travel thing that you guys did that was came out of the innovation from the teams. >> Yeah. >> is there any other, other examples that popped out from you guys? >> Yeah. Well, I think another one is something that we call Agent on Demand. Agent on Demand is where you used it when you had to talk to an agent in the airport, you'd go get in line somewhere. And sometimes it was a long line, right? Because there's only two people there. And so the first thing we did was we made sure the technologies they used worked on a phone or an iPad. So now we weren't limited by the number of, of stations at the gate. The next thing we is that we made it QR code enabled. And now what customers can do is they can scan the QR code and they get a live agent, like a FaceTime call on their, on their phone. They can do it from anywhere from their seat at the gate or in line for a coffee, and they can solve their problem right there. And those agents, by the way, now maybe there's a snowstorm going on in Chicago, but the agents are in Houston where it's sunny. And so we can actually leverage the fact that those agents are there to help our customers. >> So you've got the user experience, you did some innovation. How about the operational things, I noticed when I traveled the United, the packaging's different ,the greetings are different. I get why all these operational impacts happened to the whole supply chain.(laughing) >> Yeah. Well, you know, the technology's great, but what makes you remember United are the people that you're going to interact with. And so we really focused on service for our, for our employees. And how do we give them information in the palm of their hand to, to treat you in a very personal way. We know that you flew last week and where you went. We know that you just made a million miles. And so we can give that information to our flight attendant and they can provide a really great experience. >> That experience is key. These days. One of the things that's been in short supply, during the pandemic is patience. And obviously you guys have to be very cognizant of that with some of the things that have happened across all the airlines and passengers not having the patience that they normally would have. >> Oh yeah. That is a real kudos to our flight attendants. And what we did with them, you know, wearing a mask is required on the aircraft and, you know, some folks don't like to be told what to do anywhere, right? And so people don't like that. Our flight attendants learned how to deescalate the situation and deal with it on the ground. So it's very simple. If you're not wearing a mask, flight attendant asked you nicely, you still don't put your mask on. They just give you a little card that says, by the way, if you don't put your mask on, this is going to be your last United flight. And the vast majority of customers put their masks on. So we have not seen some of that level of stress that's happened on some of other, other airlines. >> That's key. Cause it's been pretty rampant. But the fact that you're, you're making things much more accessible. And in real time, I think another thing we learned during the pandemic is that real time is no longer a nice to have. It's essential. We have this expectation as consumers, whether we're flying or we're buying something from an online retailer that we're going to be able to get whatever we want in the palm of our hand. >> Yeah. Well, you know what we like to say, we're very proud of our mobile app. We're very proud of it. But we like to say that are not comparing our mobile app to another airline mobile app. You're, you're comparing it to the last app you probably used. And that might've been the Amazon app. So we have to be as good as the Amazon app, but we have a lot of legacy technology behind it. And so we have really focused on that. >> Good, I want to ask you cause you're a Chief Digital Officer, because this comes up in a lot of our CUBE conversations and around the digital side is that obviously with the virtual now hybrid things, new innovations have happened. So I have to ask you what's changed for the better that's going to be around and what might not be around that you've learned from the pandemic, because these new things are emerging. New standards, new protocols, new digital experiences. What have you learned that's going to stay around and what kind of went away? >> Yeah. >> Well, I think nothing tells you about how important your customers are if you're standing in the middle of O'Hare and not seeing any. And that's what happened in April of 2020, when we actually, there was a day that year, that month that we had more pilots than passengers. It was just, you know, so you realize it's really all about the customer. And what we have to do is make sure that customers choose us. There might be less reasons to fly to certain places all the time, but when you do fly, we want you to pick United. And so it's got to be more than just where we fly. It's got to be the experiences you have with the people. And we have to use the technology to make it easier. I mean, Touchless, wasn't really a thing. QR codes are back. I mean, they were gone, right. And we have QR codes on everything now. Cause you want to get through that airport without having to touch anything, and you do that with your mobile app. >> Yeah. Great innovations. >> It is a great innovation. That contact list is key. You talk about QR cuts coming back. And just some of the things that we've, that we've, some of the silver linings and frankly there have been some the last 22 months or so, but being able to have that experience, that's tailored to me as a consumer. >> Right. I don't need to know what's under the hood enabling it. I just know I want to be able to make transactions or find whatever I need to in the palm of my hand, 24/7. >> Yeah. And you know, for airlines, it usually comes back to something went wrong and frankly, there's always something that going quite right. There's a, there's a weather delay somewhere or maybe your bag didn't get on the same flight you did. And so we want to give you transparency in that and control over what you can do. And so how make it, make it easier to rebook, make you understand what the situation is, be very transparent about it. And we even have something called Connection Saver. And what we do with that is we actually use real time data analytics. And what we do is we say, there's a person that's arriving late. And then we say with real-time weather, real-time connection data. We say, can we hold that flight for Lisa? And we, and we, yeah.(laughing) The worst thing is when that door closed, you run all the way through the airport and they closed the door. Right? We don't want to do, gate agents don't like doing that either. And so we use calculations that say, you know, the wind is blowing in the right direction. The pilots can make up the time. There isn't anybody on the other side, that's going to miss a connection. And so about 2000 times a day, we hold a connection for our customer. >> That's key. If you missed, sometimes just stay overnight. If you miss that connection. >> Especially on the last flight of the day we'll be, we'll be very generous because that doesn't do anybody any good. >> Well, great, great story. I love the keynote, Cloud has changed. I have to ask you this year at re:Invent, what's your observation on the Cloud as the cloud continues to expand, as Adam is talking about, how do you guys see the Cloud evolving for United? >> Well, you know, I, I think what's really impressive here is everybody is coming from every industry. It's not one or two industries that are here, are early adopters in the industry. It really is what you have to do to survive. But I probably would be remiss not to say that, which was really great was that there were two women on the, on the keynote stage and two men. So we were at 50 50 now there are 51% women in the world, but we'll take it. And I, in all seriousness, I do think that there is, there's a lot more diversity here and I think that's good. Not just for AWS. That's good for everybody. >> I couldn't agree more. That was one of the first things I noticed this morning when you took the keynote stage was a strong female leader before you even started telling the story. And that's something from an optics perspective. I know that Amazon is really keen on, but it's nice to hear from your perspective as well that there's, there's that diversity. There's also that thought diversity when you have different perspectives come into play because there's so many dynamics going on these days. But I have to ask you one question. We know we talked to, we, we, we talk about every company, these days being a data company, being a digital company needing to be, to be competitive. >> Right. Do you think of United, should, should we be thinking about United as a digital first company? >> Well, we, we, we connect people, right? And so we are physically moving people from one destination to another and they really want to get there. So we're not going to always be digital, but I would tell you that I often speak with our Chief Customer Officer and our Chief Operating Officer. And it's really hard for us to talk about anything without talking about technology or how it impacts the operation or how it impacts our customer. It's really, really meshing together for sure. >> Great stuff, Linda, thanks for coming on theCUBE. Really appreciate it. United Airlines, Chief Digital Officer on the main stage here at re:Invent and now on theCUBE. I'm John Furrier, Lisa Martin. You're watching theCUBE, the tech leader in event coverage. Thanks for watching. (upbeat music)

(upbeat music) >> Hi everyone, thank you for joining us at the Data Cloud Summit. The last couple of months have been an exciting time at Snowflake. And yet, what's even more compelling to all of us at Snowflake is what's ahead. Today I have the opportunity to share new product developments that will extend the reach and impact of our Data Cloud and improve the experience of Snowflake users. Our product strategy is focused on four major areas. First, Data Cloud content. In the Data Cloud silos are eliminated and our vision is to bring the world's data within reach of every organization. You'll hear about new data sets and data services available in our data marketplace and see how previous barriers to sourcing and unifying data are eliminated. Second, extensible data pipelines. As you gain frictionless access to a broader set of data through the Data Cloud, Snowflakes platform brings additional capabilities and extensibility to your data pipelines, simplifying data ingestion, and transformation. Third, data governance. The Data Cloud eliminates silos and breaks down barriers and in a world where data collaboration is the norm, the importance of data governance is ratified and elevated. We'll share new advancements to support how the world's most demanding organizations mobilize your data while maintaining high standards of compliance and governance. Finally, our fourth area focuses on platform performance and capabilities. We remain laser focused on continuing to lead with the most performant and capable data platform. We have some exciting news to share about the core engine of Snowflake. As always, we love showing you Snowflake in action, and we prepared some demos for you. Also, we'll keep coming back to the fact that one of the characteristics of Snowflake that we're proud as staff is that we offer a single platform from which you can operate all of your data workloads, across clouds and across regions, which workloads you may ask, specifically, data warehousing, data lake, data science, data engineering, data applications, and data sharing. Snowflake makes it possible to mobilize all your data in service of your business without the cost, complexity and overhead of managing multiple systems, tools and vendors. Let's dive in. As you heard from Frank, the Data Cloud offers a unique capability to connect organizations and create collaboration and innovation across industries fueled by data. The Snowflake data marketplace is the gateway to the Data Cloud, providing visibility for organizations to browse and discover data that can help them make better decisions. For data providers on the marketplace, there is a new opportunity to reach new customers, create new revenue streams, and radically decrease the effort and time to data delivery. Our marketplace dramatically reduces the friction of sharing and collaborating with data opening up new possibilities to all participants in the Data Cloud. We introduced the Snowflake data marketplace in 2019. And it is now home to over 100 data providers, with half of them having joined the marketplace in the last four months. Since our most recent product announcements in June, we have continued broadening the availability of the data marketplace, across regions and across clouds. Our data marketplace provides the opportunity for data providers to reach consumers across cloud and regional boundaries. A critical aspect of the Data Cloud is that we envisioned organizations collaborating not just in terms of data, but also data powered applications and services. Think of instances where a provider doesn't want to open access to the entirety of a data set, but wants to provide access to business logic that has access and leverages such data set. That is what we call data services. And we want Snowflake to be the platform of choice for developing discovering and consuming such rich building blocks. To see How the data marketplace comes to live, and in particular one of these data services, let's jump into a demo. For all of our demos today, we're going to put ourselves in the shoes of a fictional global insurance company. We've called it Insureco. Insurance is a data intensive and highly regulated industry. Having the right access control and insight from data is core to every insurance company's success. I'm going to turn it over to Prasanna to show how the Snowflake data marketplace can solve a data discoverability and access problem. >> Let's look at how Insureco can leverage data and data services from the Snowflake data marketplace and use it in conjunction with its own data in the Data Cloud to do three things, better detect fraudulent claims, arm its agents with the right information, and benchmark business health against competition. Let's start with detecting fraudulent claims. I'm an analyst in the Claims Department. I have auto claims data in my account. I can see there are 2000 auto claims, many of these submitted by auto body shops. I need to determine if they are valid and legitimate. In particular, could some of these be insurance fraud? By going to the Snowflake data marketplace where numerous data providers and data service providers can list their offerings, I find the quantifying data service. It uses a combination of external data sources and predictive risk typology models to inform the risk level of an organization. Quantifying external sources include sanctions and blacklists, negative news, social media, and real time search engine results. That's a wealth of data and models built on that data which we don't have internally. So I'd like to use Quantifind to determine a fraud risk score for each auto body shop that has submitted a claim. First, the Snowflake data marketplace made it really easy for me to discover a data service like this. Without the data marketplace, finding such a service would be a lengthy ad hoc process of doing web searches and asking around. Second, once I find Quantifind, I can use Quantifind service against my own data in three simple steps using data sharing. I create a table with the names and addresses of auto body shops that have submitted claims. I then share the table with Quantifind to start the risk assessment. Quantifind does the risk scoring and shares the data back with me. Quantifind uses external functions which we introduced in June to get results from their risk prediction models. Without Snowflake data sharing, we would have had to contact Quantifind to understand what format they wanted the data in, then extract this data into a file, FTP the file to Quantifind, wait for the results, then ingest the results back into our systems for them to be usable. Or I would have had to write code to call Quantifinds API. All of that would have taken days. In contrast, with data sharing, I can set this up in minutes. What's more, now that I have set this up, as new claims are added in the future, they will automatically leverage Quantifind's data service. I view the scores returned by Quantifind and see the two entities in my claims data have a high score for insurance fraud risk. I open up the link returned by Quantifind to read more, and find that this organization has been involved in an insurance crime ring. Looks like that is a claim that we won't be approving. Using the Quantifind data service through the Snowflake data marketplace gives me access to a risk scoring capability that we don't have in house without having to call custom APIs. For a provider like Quantifind this drives new leads and monetization opportunities. Now that I have identified potentially fraudulent claims, let's move on to the second part. I would like to share this fraud risk information with the agents who sold the corresponding policies. To do this, I need two things. First, I need to find the agents who sold these policies. Then I need to share with these agents the fraud risk information that we got from Quantifind. But I want to share it such that each agent only sees the fraud risk information corresponding to claims for policies that they wrote. To find agents who sold these policies, I need to look up our Salesforce data. I can find this easily within Insureco's internal data exchange. I see there's a listing with Salesforce data. Our sales Ops team has published this listing so I know it's our officially blessed data set, and I can immediately access it from my Snowflake account without copying any data or having to set up ETL. I can now join Salesforce data with my claims to identify the agents for the policies that were flagged to have fraudulent claims. I also have the Snowflake account information for each agent. Next, I create a secure view that joins on an entitlements table, such that each agent can only see the rows corresponding to policies that they have sold. I then share this directly with the agents. This share contains the secure view that I created with the names of the auto body shops, and the fraud risk identified by Quantifind. Finally, let's move on to the third and last part. Now that I have detected potentially fraudulent claims, I'm going to move on to building a dashboard that our executives have been asking for. They want to see how Insureco compares against other auto insurance companies on key metrics, like total claims paid out for the auto insurance line of business nationwide. I go to the Snowflake data marketplace and find SNL U.S. Insurance Statutory Data from SNP. This data is included with Insureco's existing subscription with SMP so when I request access to it, SMP can immediately share this data with me through Snowflake data sharing. I create a virtual database from the share, and I'm ready to query this data, no ETL needed. And since this is a virtual database, pointing to the original data in SNP Snowflake account, I have access to the latest data as it arrives in SNPs account. I see that the SNL U.S. Insurance Statutory Data from SNP has data on assets, premiums earned and claims paid out by each us insurance company in 2019. This data is broken up by line of business and geography and in many cases goes beyond the data that would be available from public financial filings. This is exactly the data I need. I identify a subset of comparable insurance companies whose net total assets are within 20% of Insureco's, and whose lines of business are similar to ours. I can now create a Snow site dashboard that compares Insureco against similar insurance companies on key metrics, like net earned premiums, and net claims paid out in 2019 for auto insurance. I can see that while we are below median our net earned premiums, we are doing better than our competition on total claims paid out in 2019, which could be a reflection of our improved claims handling and fraud detection. That's a good insight that I can share with our executives. In summary, the Data Cloud enabled me to do three key things. First, seamlessly fine data and data services that I need to do my job, be it an external data service like Quantifind and external data set from SNP or internal data from Insureco's data exchange. Second, get immediate live access to this data. And third, control and manage collaboration around this data. With Snowflake, I can mobilize data and data services across my business ecosystem in just minutes. >> Thank you Prasanna. Now I want to turn our focus to extensible data pipelines. We believe there are two different and important ways of making Snowflakes platform highly extensible. First, by enabling teams to leverage services or business logic that live outside of Snowflake interacting with data within Snowflake. We do this through a feature called external functions, a mechanism to conveniently bring data to where the computation is. We announced this feature for calling regional endpoints via AWS gateway in June, and it's currently available in public preview. We are also now in public preview supporting Azure API management and will soon support Google API gateway and AWS private endpoints. The second extensibility mechanism does the converse. It brings the computation to Snowflake to run closer to the data. We will do this by enabling the creation of functions and procedures in SQL, Java, Scala or Python ultimately providing choice based on the programming language preference for you or your organization. You will see Java, Scala and Python available through private and public previews in the future. The possibilities enabled by these extensibility features are broad and powerful. However, our commitment to being a great platform for data engineers, data scientists and developers goes far beyond programming language. Today, I am delighted to announce Snowpark a family of libraries that will bring a new experience to programming data in Snowflake. Snowpark enables you to write code directly against Snowflake in a way that is deeply integrated into the languages I mentioned earlier, using familiar concepts like DataFrames. But the most important aspect of Snowpark is that it has been designed and optimized to leverage the Snowflake engine with its main characteristics and benefits, performance, reliability, and scalability with near zero maintenance. Think of the power of a declarative SQL statements available through a well known API in Scala, Java or Python, all these against data governed in your core data platform. We believe Snowpark will be transformative for data programmability. I'd like to introduce Sri to showcase how our fictitious insurance company Insureco will be able to take advantage of the Snowpark API for data science workloads. >> Thanks Christian, hi, everyone? I'm Sri Chintala, a product manager at Snowflake focused on extensible data pipelines. And today, I'm very excited to show you a preview of Snowpark. In our first demo, we saw how Insureco could identify potentially fraudulent claims. Now, for all the valid claims InsureCo wants to ensure they're providing excellent customer service. To do that, they put in place a system to transcribe all of their customer calls, so they can look for patterns. A simple thing they'd like to do is detect the sentiment of each call so they can tell which calls were good and which were problematic. They can then better train their claim agents for challenging calls. Let's take a quick look at the work they've done so far. InsureCo's data science team use Snowflakes external functions to quickly and easily train a machine learning model in H2O AI. Snowflake has direct integrations with H2O and many other data science providers giving Insureco the flexibility to use a wide variety of data science libraries frameworks or tools to train their model. Now that the team has a custom trained sentiment model tailored to their specific claims data, let's see how a data engineer at Insureco can use Snowpark to build a data pipeline that scores customer call logs using the model hosted right inside of Snowflake. As you can see, we have the transcribed call logs stored in the customer call logs table inside Snowflake. Now, as a data engineer trained in Scala, and used to working with systems like Spark and Pandas, I want to use familiar programming concepts to build my pipeline. Snowpark solves for this by letting me use popular programming languages like Java or Scala. It also provides familiar concepts in APIs, such as the DataFrame abstraction, optimized to leverage and run natively on the Snowflake engine. So here I am in my ID, where I've written a simple scalar program using the Snowpark libraries. The first step in using the Snowpark API is establishing a session with Snowflake. I use the session builder object and specify the required details to connect. Now, I can create a DataFrame for the data in the transcripts column of the customer call logs table. As you can see, the Snowpark API provides native language constructs for data manipulation. Here, I use the Select method provided by the API to specify the column names to return rather than writing select transcripts as a string. By using the native language constructs provided by the API, I benefit from features like IntelliSense and type checking. Here you can see some of the other common methods that the DataFrame class offers like filters like join and others. Next, I define a get sentiment user defined function that will return a sentiment score for an input string by using our pre trained H2O model. From the UDF, we call the score method that initializes and runs the sentiment model. I've built this helper into a Java file, which along with the model object and license are added as dependencies that Snowpark will send to Snowflake for execution. As a developer, this is all programming that I'm familiar with. We can now call our get sentiment function on the transcripts column of the DataFrame and right back the results of the score transcripts to a new target table. Let's run this code and switch over to Snowflake to see the score data and also all the work that Snowpark has done for us on the back end. If I do a select star from scored logs, we can see the sentiment score of each call right alongside the transcript. With Snowpark all the logic in my program is pushed down into Snowflake. I can see in the query history that Snowpark has created a temporary Java function to host the pre trained H20 model, and that the model is running right in my Snowflake warehouse. Snowpark has allowed us to do something completely new in Snowflake. Let's recap what we saw. With Snowpark, Insureco was able to use their preferred programming language, Scala and use the familiar DataFrame constructs to score data using a machine learning model. With support for Java UDFs, they were able to run a train model natively within Snowflake. And finally, we saw how Snowpark executed computationally intensive data science workloads right within Snowflake. This simplifies Insureco's data pipeline architecture, as it reduces the number of additional systems they have to manage. We hope that extensibility with Scala, Java and Snowpark will enable our users to work with Snowflake in their preferred way while keeping the architecture simple. We are very excited to see how you use Snowpark to extend your data pipelines. Thank you for watching and with that back to you, Christian. >> Thank you Sri. You saw how Sri could utilize Snowpark to efficiently perform advanced sentiment analysis. But of course, if this use case was important to your business, you don't want to fully automate this pipeline and analysis. Imagine being able to do all of the following in Snowflake, your pipeline could start far upstream of what you saw in the demo. By storing your actual customer care call recordings in Snowflake, you may notice that this is new for Snowflake. We'll come back to the idea of storing unstructured data in Snowflake at the end of my talk today. Once you have the data in Snowflake, you can use our streams and past capabilities to call an external function to transcribe these files. To simplify this flow even further, we plan to introduce a serverless execution model for tasks where Snowflake can automatically size and manage resources for you. After this step, you can use the same serverless task to execute sentiment scoring of your transcript as shown in the demo with incremental processing as each transcript is created. Finally, you can surface the sentiment score either via snow side, or through any tool you use to share insights throughout your organization. In this example, you see data being transformed from a raw asset into a higher level of information that can drive business action, all fully automated all in Snowflake. Turning back to Insureco, you know how important data governance is for any major enterprise but particularly for one in this industry. Insurance companies manage highly sensitive data about their customers, and have some of the strictest requirements for storing and tracking such data, as well as managing and governing it. At Snowflake, we think about governance as the ability to know your data, manage your data and collaborate with confidence. As you saw in our first demo, the Data Cloud enables seamless collaboration, control and access to data via the Snowflake data marketplace. And companies may set up their own data exchanges to create similar collaboration and control across their ecosystems. In future releases, we expect to deliver enhancements that create more visibility into who has access to what data and provide usage information of that data. Today, we are announcing a new capability to help Snowflake users better know and organize your data. This is our new tagging framework. Tagging in Snowflake will allow user defined metadata to be attached to a variety of objects. We built a broad and robust framework with powerful implications. Think of the ability to annotate warehouses with cost center information for tracking or think of annotating tables and columns with sensitivity classifications. Our tagging capability will enable the creation of companies specific business annotations for objects in Snowflakes platform. Another key aspect of data governance in Snowflake is our policy based framework where you specify what you want to be true about your data, and Snowflake enforces those policies. We announced one such policy earlier this year, our dynamic data masking capability, which is now available in public preview. Today, we are announcing a great complimentary a policy to achieve row level security to see how role level security can enhance InsureCo's ability to govern and secure data. I'll hand it over to Artin for a demo. >> Hello, I'm Martin Avanes, Director of Product Management for Snowflake. As Christian has already mentioned, the rise of the Data Cloud greatly accelerates the ability to access and share diverse data leading to greater data collaboration across teams and organizations. Controlling data access with ease and ensuring compliance at the same time is top of mind for users. Today, I'm thrilled to announce our new row access policies that will allow users to define various rules for accessing data in the Data Cloud. Let's check back in with Insureco to see some of these in action and highlight how those work with other existing policies one can define in Snowflake. Because Insureco is a multinational company, it has to take extra measures to ensure data across geographic boundaries is protected to meet a wide range of compliance requirements. The Insureco team has been asked to segment what data sales team members have access to based on where they are regionally. In order to make this possible, they will use Snowflakes row access policies to implement row level security. We are going to apply policies for three Insureco's sales team members with different roles. Alice, an executive must be able to view sales data from both North America and Europe. Alex in North America sales manager will be limited to access sales data from North America only. And Jordan, a Europe sales manager will be limited to access sales data from Europe only. As a first step, the security administrator needs to create a lookup table that will be used to determine which data is accessible based on each role. As you can see, the lookup table has the row and their associated region, both of which will be used to apply policies that we will now create. Row access policies are implemented using standard SQL syntax to make it easy for administrators to create policies like the one our administrators looking to implement. And similar to masking policies, row access policies are leveraging our flexible and expressive policy language. In this demo, our admin users to create a row access policy that uses the row and region of a user to determine what row level data they have access to when queries are executed. When users queries are executed against the table protected by such a row access policy, Snowflakes query engine will dynamically generate and apply the corresponding predicate to filter out rows the user is not supposed to see. With the policy now created, let's log in as our Sales Users and see if it worked. Recall that as a sales executive, Alice should have the ability to see all rows from North America and Europe. Sure enough, when she runs her query, she can see all rows so we know the policy is working for her. You may also have noticed that some columns are showing masked data. That's because our administrator's also using our previously announced data masking capabilities to protect these data attributes for everyone in sales. When we look at our other users, we should notice that the same columns are also masked for them. As you see, you can easily combine masking and row access policies on the same data sets. Now let's look at Alex, our North American sales manager. Alex runs to st Korea's Alice, row access policies leverage the lookup table to dynamically generate the corresponding predicates for this query. The result is we see that only the data for North America is visible. Notice too that the same columns are still masked. Finally, let's try Jordan, our European sales manager. Jordan runs the query and the result is only the data for Europe with the same columns also masked. And you reintroduced masking policies, today you saw row access policies in action. And similar to our masking policies, row access policies in Snowflake will be accepted Hands of capability integrated seamlessly across all of Snowflake everywhere you expect it to work it does. If you're accessing data stored in external tables, semi structured JSON data, or building data pipelines via streams or plan to leverage Snowflakes data sharing functionality, you will be able to implement complex row access policies for all these diverse use cases and workloads within Snowflake. And with Snowflakes unique replication feature, you can instantly apply these new policies consistently to all of your Snowflake accounts, ensuring governance across regions and even across different clouds. In the future, we plan to demonstrate how to combine our new tagging capabilities with Snowflakes policies, allowing advanced audit and enforcing those policies with ease. And with that, let's pass it back over to Christian. >> Thank you Artin. We look forward to making this new tagging and row level security capabilities available in private preview in the coming months. One last note on the broad area of data governance. A big aspect of the Data Cloud is the mobilization of data to be used across organizations. At the same time, privacy is an important consideration to ensure the protection of sensitive, personal or potentially identifying information. We're working on a set of product capabilities to simplify compliance with privacy related regulatory requirements, and simplify the process of collaborating with data while preserving privacy. Earlier this year, Snowflake acquired a company called Crypto Numerix to accelerate our efforts on this front, including the identification and anonymization of sensitive data. We look forward to sharing more details in the future. We've just shown you three demos of new and exciting ways to use Snowflake. However, I want to also remind you that our commitment to the core platform has never been greater. As you move workloads on to Snowflake, we know you expect exceptional price performance and continued delivery of new capabilities that benefit every workload. On price performance, we continue to drive performance improvements throughout the platform. Let me give you an example comparing an identical set of customers submitted queries that ran both in August of 2019, and August of 2020. If I look at the set of queries that took more than one second to compile 72% of those improved by at least 50%. When we make these improvements, execution time goes down. And by implication, the required compute time is also reduced. Based on our pricing model to charge for what you use, performance improvements not only deliver faster insights, but also translate into cost savings for you. In addition, we have two new major announcements on performance to share today. First, we announced our search optimization service during our June event. This service currently in public preview can be enabled on a table by table basis, and is able to dramatically accelerate lookup queries on any column, particularly those not used as clustering columns. We initially support equality comparisons only, and today we're announcing expanded support for searches in values, such as pattern matching within strings. This will unlock a number of additional use cases such as analytics on logs data for performance or security purposes. This expanded support is currently being validated by a few customers in private preview, and will be broadly available in the future. Second, I'd like to introduce a new service that will be in private preview in a future release. The query acceleration service. This new feature will automatically identify and scale out parts of a query that could benefit from additional resources and parallelization. This means that you will be able to realize dramatic improvements in performance. This is especially impactful for data science and other scan intensive workloads. Using this feature is pretty simple. You define a maximum amount of additional resources that can be recruited by a warehouse for acceleration, and the service decides when it would be beneficial to use them. Given enough resources, a query over a massive data set can see orders of magnitude performance improvement compared to the same query without acceleration enabled. In our own usage of Snowflake, we saw a common query go 15 times faster without changing the warehouse size. All of these performance enhancements are extremely exciting, and you will see continued improvements in the future. We love to innovate and continuously raise the bar on what's possible. More important, we love seeing our customers adopt and benefit from our new capabilities. In June, we announced a number of previews, and we continue to roll those features out and see tremendous adoption, even before reaching general availability. Two have those announcements were the introduction of our geospatial support and policies for dynamic data masking. Both of these features are currently in use by hundreds of customers. The number of tables using our new geography data type recently crossed the hundred thousand mark, and the number of columns with masking policies also recently crossed the same hundred thousand mark. This momentum and level of adoption since our announcements in June is phenomenal. I have one last announcement to highlight today. In 2014, Snowflake transformed the world of data management and analytics by providing a single platform with first class support for both structured and semi structured data. Today, we are announcing that Snowflake will be adding support for unstructured data on that same platform. Think of the abilities of Snowflake used to store access and share files. As an example, would you like to leverage the power of SQL to reason through a set of image files. We have a few customers as early adopters and we'll provide additional details in the future. With this, you will be able to leverage Snowflake to mobilize all your data in the Data Cloud. Our customers rely on Snowflake as the data platform for every part of their business. However, the vision and potential of Snowflake is actually much bigger than the four walls of any organization. Snowflake has created a Data Cloud a data connected network with a vision where any Snowflake customer can leverage and mobilize the world's data. Whether it's data sets, or data services from traditional data providers for SaaS vendors, our marketplace creates opportunities for you and raises the bar in terms of what is possible. As examples, you can unify data across your supply chain to accelerate your time and quality to market. You can build entirely new revenue streams, or collaborate with a consortium on data for good. The possibilities are endless. Every company has the opportunity to gain richer insights, build greater products and deliver better services by reaching beyond the data that he owns. Our vision is to enable every company to leverage the world's data through seamless and governing access. Snowflake is your window into this data network into this broader opportunity. Welcome to the Data Cloud. (upbeat music)

>>Data is at the heart of transformation and the change. Every company needs to succeed, but it takes more than new technology. It's about teams, talent and cultural change. Empowering everyone on the front lines to make decisions all at the speed of digital. The transformation starts with you. It's time to lead the way it's time for thought leaders. >>Welcome to thought leaders, a digital event brought to you by ThoughtSpot. My name is Dave Volante. The purpose of this day is to bring industry leaders and experts together to really try and understand the important issues around digital transformation. We have an amazing lineup of speakers and our goal is to provide you with some best practices that you can bring back and apply to your organization. Look, data is plentiful, but insights are not. ThoughtSpot is disrupting analytics by using search and machine intelligence to simplify data analysis and really empower anyone with fast access to relevant data. But in the last 150 days, we've had more questions than answers. Creating an organization that puts data and insights at their core requires not only modern technology, but leadership, a mindset and a culture that people often refer to as data-driven. What does that mean? How can we equip our teams with data and fast access to quality information that can turn insights into action. >>And today we're going to hear from experienced leaders who are transforming their organizations with data insights and creating digital first cultures. But before we introduce our speakers, I'm joined today by two of my cohosts from ThoughtSpot first chief data strategy officer, the ThoughtSpot is Cindy Hausen. Cindy is an analytics and BI expert with 20 plus years experience and the author of successful business intelligence unlock the value of BI and big data. Cindy was previously the lead analyst at Gartner for the data and analytics magic quadrant. And early last year, she joined ThoughtSpot to help CDOs and their teams understand how best to leverage analytics and AI for digital transformation. Cindy. Great to see you welcome to the show. Thank you, Dave. Nice to join you virtually. Now our second cohost and friend of the cube is ThoughtSpot CEO, sedition air. Hello. Sudheesh how are you doing today? I am validating. It's good to talk to you again. That's great to see you. Thanks so much for being here now Sateesh please share with us why this discussion is so important to your customers and of course, to our audience and what they're going to learn today. >>Thanks, Dave. >>I wish you were there to introduce me into every room that I walk into because you have such an amazing way of doing it. It makes me feel also good. Um, look, since we have all been, you know, cooped up in our homes, I know that the vendors like us, we have amped up know sort of effort to reach out to you with invites for events like this. So we are getting very more invites for events like this than ever before. So when we started planning for this, we had three clear goals that we wanted to accomplish. And our first one that when you finish this and walk away, we want to make sure that you don't feel like it was a waste of time. We want to make sure that we value your time. Then this is going to be used. Number two, we want to put you in touch with industry leaders and thought leaders, generally good people that you want to hang around with long after this event is over. >>And number three, has we planned through this? You know, we are living through these difficult times. You want an event to be this event, to be more of an uplifting and inspiring event. Now, the challenge is how do you do that with the team being change agents? Because teens can, as much as we romanticize it, it is not one of those uplifting things that everyone wants to do, or like through the VA. I think of it changes sort of like if you've ever done bungee jumping and it's like standing on the edges waiting to make that one more step, uh, you know, all you have to do is take that one step and gravity will do the rest, but that is the hardest step to take change requires a lot of courage. And when we are talking about data and analytics, which is already like such a hard topic, not necessarily an uplifting and positive conversation, most businesses, it is somewhat scary. >>Change becomes all the more difficult, ultimately change requires courage, courage. To first of all, challenge the status quo. People sometimes are afraid to challenge the status quo because they are thinking that, you know, maybe I don't have the power to make the change that the company needs. Sometimes they feel like I don't have the skills. Sometimes they've may feel that I'm, I'm probably not the right person to do it. Or sometimes the lack of courage manifest itself as the inability to sort of break the silos that are formed within the organizations, when it comes to data and insights that you talked about, you know, that are people in the company who are going to have the data because they know how to manage the data, how to inquire and extract. They know how to speak data. They have the skills to do that, but they are not the group of people who have sort of the knowledge, the experience of the business to ask the right questions off the data. >>So there is the silo of people with the answers, and there is a silo of people with the questions. And there is gap. This sort of silos are standing in the way of making that necessary change that we all know the business needs. And the last change to sort of bring an external force. Sometimes it could be a tool. It could be a platform, it could be a person, it could be a process, but sometimes no matter how big the company is or how small the company is, you may need to bring some external stimuli to start the domino of the positive changes that are necessarily the group of people that we are brought in. The four people, including Cindy, that you will hear from today are really good at practically telling you how to make that step, how to step off that edge, how to trust the rope, that you will be safe. And you're going to have fun. You will have that exhilarating feeling of jumping for a bungee jump. >>So we're going to take a hard pivot now and go from football to Ternopil Chernobyl. What went wrong? 1986, as the reactors were melting down, they had the data to say, this is going to be catastrophic. And yet the culture said, no, we're perfect. Hide it. Don't dare tell anyone which meant they went ahead and had celebrations in Kiev. Even though that increased the exposure, the additional thousands, getting cancer and 20,000 years before the ground around there and even be inhabited again, this is how powerful and detrimental a negative culture, a culture that is unable to confront the brutal facts that hides data. This is what we have to contend with. And this is why I want you to focus on having fostering a data driven culture. I don't want you to be a laggard. I want you to be a leader in using data to drive your digital transformation. >>So I'll talk about culture and technology. Isn't really two sides of the same coin, real world impacts. And then some best practices you can use to disrupt and innovate your culture. Now, oftentimes I would talk about culture and I talk about technology. And recently a CDO said to me, you know, Cindy, I actually think this is two sides of the same coin. One reflects the other. What do you think? Let me walk you through this. So let's take a laggard. What does the technology look like? Is it based on 1990s BI and reporting largely parameterized reports on premises, data, warehouses, or not even that operational reports at best one enterprise, nice data warehouse, very slow moving and collaboration is only email. What does that culture tell you? Maybe there's a lack of leadership to change, to do the hard work that Sudheesh referred to, or is there also a culture of fear, afraid of failure, resistance to change complacency. >>And sometimes that complacency it's not because people are lazy. It's because they've been so beaten down every time a new idea is presented. It's like, no we're measured on least cost to serve. So politics and distrust, whether it's between business and it or individual stakeholders is the norm. So data is hoarded. Let's contrast that with a leader, a data and analytics leader, what is their technology look like? Augmented analytics search and AI driven insights, not on premises, but in the cloud and maybe multiple clouds. And the data is not in one place, but it's in a data Lake and in a data warehouse, a logical data warehouse, the collaboration is being a newer methods, whether it's Slack or teams allowing for that real time decisioning or investigating a particular data point. So what is the culture in the leaders? It's transparent and trust. There is a trust that data will not be used to punish that there is an ability to confront the bad news. >>It's innovation, valuing innovation in pursuit of the company goals, whether it's the best fan experience and player safety in the NFL or best serving your customers. It's innovative and collaborative. None of this. Oh, well, I didn't invent that. I'm not going to look at that. There's still proud of that ownership, but it's collaborating to get to a better place faster. And people feel empowered to present new ideas, fail fast, and they're energized knowing that they're using the best technology and innovating at the pace that business requires. So data is democratized and double monetized, not just for people, how are users or analysts, but really at the of impact what we like to call the new decision makers or really the front line workers. So Harvard business review partnered with us to develop this study to say, just how important is this? We've been working at BI and analytics as an industry for more than 20 years. >>Why is it not at the front lines? Whether it's a doctor, a nurse, a coach, a supply chain manager, a warehouse manager, a financial services advisor, 87% said they would be more successful if frontline workers were empowered with data driven insights, but they recognize they need new technology to be able to do that. It's not about learning hard tools. The sad reality only 20% of organizations are actually doing this. These are the data driven leaders. So this is the culture and technology. How did we get here? It's because state of the art keeps changing. So the first generation BI and analytics platforms were deployed on premises on small datasets, really just taking data out of ERP systems that were also on premises. And state-of-the-art was maybe getting a management report, an operational report over time, visual based data discovery vendors disrupted these traditional BI vendors, empowering now analysts to create visualizations with the flexibility on a desktop, sometimes larger data sometimes coming from a data warehouse, the current state of the art though, Gartner calls it augmented analytics at ThoughtSpot, we call it search and AI driven analytics. >>And this was pioneered for large scale data sets, whether it's on premises or leveraging the cloud data warehouses. And I think this is an important point. Oftentimes you, the data and analytics leaders will look at these two components separately, but you have to look at the BI and analytics tier in lockstep with your data architectures to really get to the granular insights and to leverage the capabilities of AI. Now, if you've never seen ThoughtSpot, I'll just show you what this looks like. Instead of somebody's hard coding of report, it's typing in search keywords and very robust keywords contains rank top bottom, getting to a visual visualization that then can be pinned to an existing Pinboard that might also contain insights generated by an AI engine. So it's easy enough for that new decision maker, the business user, the non analyst to create themselves modernizing the data and analytics portfolio is hard because the pace of change has accelerated. >>You use to be able to create an investment place. A bet for maybe 10 years, a few years ago, that time horizon was five years now, it's maybe three years and the time to maturity has also accelerated. So you have these different components, the search and AI tier the data science, tier data preparation and virtualization. But I would also say equally important is the cloud data warehouse and pay attention to how well these analytics tools can unlock the value in these cloud data warehouses. So thoughts about was the first to market with search and AI driven insights, competitors have followed suit, but be careful if you look at products like power BI or SAP analytics cloud, they might demo well, but do they let you get to all the data without moving it in products like snowflake, Amazon Redshift, or, or Azure synapse or Google big query, they do not. >>They re require you to move it into a smaller in memory engine. So it's important how well these new products inter operate the pace of change. It's acceleration Gartner recently predicted that by 2022, 65% of analytical queries will be generated using search or NLP or even AI. And that is roughly three times the prediction they had just a couple years ago. So let's talk about the real world impact of culture. And if you read any of my books or used any of the maturity models out there, whether the Gardner it score that I worked on, or the data warehousing Institute also has the maturity model. We talk about these five pillars to really become data driven. As Michelle spoke about it's focusing on the business outcomes, leveraging all the data, including new data sources, it's the talent, the people, the technology, and also the processes. >>And often when I would talk about the people in the talent, I would lump the culture as part of that. But in the last year, as I've traveled the world and done these digital events for thought leaders, you have told me now culture is absolutely so important. And so we've pulled it out as a separate pillar. And in fact, in polls that we've done in these events, look at how much more important culture is as a barrier to becoming data driven. It's three times as important as any of these other pillars. That's how critical it is. And let's take an example of where you can have great data, but if you don't have the right culture, there's devastating impacts. And I will say, I have been a loyal customer of Wells Fargo for more than 20 years. But look at what happened in the face of negative news with data, it said, Hey, we're not doing good cross selling customers do not have both a checking account and a credit card and a savings account and a mortgage. >>They opened fake accounts, basing billions in fines, change in leadership that even the CEO attributed to a toxic sales culture, and they're trying to fix this. But even recently there's been additional employee backlash saying the culture has not changed. Let's contrast that with some positive examples, Medtronic, a worldwide company in 150 countries around the world. They may not be a household name to you, but if you have a loved one or yourself, you have a pacemaker spinal implant diabetes, you know, this brand and at the start of COVID when they knew their business would be slowing down, because hospitals would only be able to take care of COVID patients. They took the bold move of making their IP for ventilators publicly available. That is the power of a positive culture or Verizon, a major telecom organization looking at late payments of their customers. And even though the us federal government said, well, you can't turn them off. >>He said, we'll extend that even beyond the mandated guidelines and facing a slow down in the business because of the tough economy, he said, you know what? We will spend the time upskilling our people, giving them the time to learn more about the future of work, the skills and data and analytics for 20,000 of their employees, rather than furloughing them. That is the power of a positive culture. So how can you transform your culture to the best in class? I'll give you three suggestions, bring in a change agent, identify the relevance, or I like to call it with them and organize for collaboration. So the CDO, whatever your title is, chief analytics, officer chief, digital officer, you are the most important change agent. And this is where you will hear that. Oftentimes a change agent has to come from outside the organization. So this is where, for example, in Europe, you have the CDO of just eat a takeout food delivery organization coming from the airline industry or in Australia, national Australian bank, taking a CDO within the same sector from TD bank going to NAB. >>So these change agents come in disrupt. It's a hard job. As one of you said to me, it often feels like Sisyphus. I make one step forward and I get knocked down again. I get pushed back. It is not for the faint of heart, but it's the most important part of your job. The other thing I'll talk about is with them, what is in it for me? And this is really about understanding the motivation, the relevance that data has for everyone on the frontline, as well as those analysts, as well as the executives. So if we're talking about players in the NFL, they want to perform better and they want to stay safe. That is why data matters to them. If we're talking about financial services, this may be a wealth management advisor, okay. We could say commissions, but it's really helping people have their dreams come true, whether it's putting their children through college or being able to retire without having to work multiple jobs still into your seventies or eighties for the teachers, teachers, you ask them about data. They'll say we don't, we don't need that. I care about the student. So if you can use data to help a student perform better, that is with them. And sometimes we spend so much time talking the technology, we forget, what is the value we're trying to deliver with this? And we forget the impact on the people that it does require change. In fact, the Harvard business review study found that 44% said lack of change. Management is the biggest barrier to leveraging both new technology, but also being empowered to act on those data driven insights. >>The third point organize for collaboration. This does require diversity of thought, but also bringing the technology, the data and the business people together. Now there's not a single one size fits all model for data and analytics. At one point in time, even having a BICC a BI competency center was considered state of the art. Now for the biggest impact, what I recommend is that you have a federated model centralized for economies of scale. That could be the common data, but then in bed, these evangelists, these analysts of the future within every business unit, every functional domain. And as you see this top bar, all models are possible, but the hybrid model has the most impact the most leaders. So as we look ahead to the months ahead to the year ahead and exciting time, because data is helping organizations better navigate a tough economy, lock in the customer loyalty. And I look forward to seeing how you foster that culture. That's collaborative with empathy and bring the best of technology, leveraging the cloud, all your data. So thank you for joining us at thought leaders. And next I'm pleased to introduce our first change agent, Tom Masa, Pharaoh, chief data officer of Western union. And before joining Western union, Tom made his Mark at HSBC and JP Morgan chase spearheading digital innovation in technology, operations, risk compliance, and retail banking. Tom, thank you so much for joining us today. >>Very happy to be here and, uh, looking forward to, uh, to talking to all of you today. So as we look to move organizations to a data-driven, uh, capability into the future, there is a lot that needs to be done on the data side, but also how did it connect and enable different business teams and technology teams into the future. As we look across, uh, our data ecosystems and our platforms and how we modernize that to the cloud in the future, it all needs to basically work together, right? To really be able to drive an organization from a data standpoint into the future. That includes being able to have the right information with the right quality of data at the right time to drive informed business decisions, to drive the business forward. As part of that, we actually have partnered with ThoughtSpot to actually bring in the technology to help us drive that as part of that partnership. >>And it's how we've looked to integrate it into our overall business as a whole we've looked at how do we make sure that our, that our business and our professional lives right, are enabled in the same ways as our personal lives. So for example, in your personal lives, when you want to go and find something out, what do you do? You go on to google.com or you go on to being, you gone to Yahoo and you search for what you want search to find an answer ThoughtSpot for us, it's the same thing, but in the business world. So using ThoughtSpot and other AI capability is it's allowed us to actually enable our overall business teams in our company to actually have our information at our fingertips. So rather than having to go and talk to someone or an engineer to go pull information or pull data, we actually can have the end users or the business executives, right. >>Search for what they need, what they want at the exact time that action needed to go and drive the business forward. This is truly one of those transformational things that we've put in place on top of that, we are on the journey to modernize our larger ecosystem as a whole. That includes modernizing our underlying data warehouses, our technology or our Elequil environments. And as we move that we've actually picked to our cloud providers going to AWS and GCP. We've also adopted snowflake to really drive into organize our information and our data then drive these new solutions and capabilities forward. So the portion of us though, is culture. So how do we engage with the business teams and bring the, the, the it teams together to really hit the drive, these holistic end to end solution, the capabilities to really support the actual business into the future. >>That's one of the keys here, as we look to modernize and to really enhance our organizations to become data driven. This is the key. If you can really start to provide answers to business questions before they're even being asked and to predict based upon different economic trends or different trends in your business, what does this is maybe be made and actually provide those answers to the business teams before they're even asking for it, that is really becoming a data driven organization. And as part of that, it's really then enables the business to act quickly and take advantage of opportunities as they come in based upon industries, based upon markets, as upon products, solutions or partnerships into the future. These are really some of the keys that, uh, that become crucial as you move forward, right, uh, into this, uh, into this new age, especially with COVID with COVID now taking place across the world, right? >>Many of these markets, many of these digital transformations are celebrating and are changing rapidly to accommodate and to support customers. And these, these very difficult times as part of that, you need to make sure you have the right underlying foundation ecosystems and solutions to really drive those, those capabilities. And those solutions forward as we go through this journey, uh, boasted both of my career, but also each of your careers into the future, right? It also needs to evolve, right? Technology has changed so drastically in the last 10 years, and that change has only a celebrating. So as part of that, you have to make sure that you stay up to speed up to date with new technology changes both on the platform standpoint tools, but also what our customers want, what our customers need and how do we then surface them with our information, with our data, with our platform, with our products and our services to meet those needs and to really support and service those customers into the future. >>This is all around becoming a more data driven organization, such as how do you use your data to support the current business lines, but how do you actually use your information, your data, to actually better support your customers and to support your business there's important, your employees, your operations teams, and so forth, and really creating that full integration in that ecosystem is really when he talked to get large dividends from his investments into the future. But that being said, uh, I hope you enjoyed the segment on how to become and how to drive a data driven organization. And I'm looking forward to talking to you again soon. Thank you, >>Tom. That was great. Thanks so much. Now I'm going to have to brag on you for a second as a change agent. You've come in this rusted. And how long have you been at Western union? >>Uh, well in nine months. So just, uh, just started this year, but, uh, there'd be some great opportunities and great changes and we were a lot more to go, but we're really driving things forward in partnership with our business teams and our colleagues to support those customers going forward. >>Tom, thank you so much. That was wonderful. And now I'm excited to introduce you to Gustavo Canton, a change agent that I've had the pleasure of working with meeting in Europe, and he is a serial change agent most recently, Schneider electric, but even going back to Sam's clubs. Gustavo. Welcome. >>So hi everyone. My name is Gustavo Canton and thank you so much, Cindy, for the intro, as you mentioned, doing transformations is a high effort, high reward situation. I have empowerment transformations and I have less many transformations. And what I can tell you is that it's really hard to predict the future, but if you have a North star and you know where you're going, the one thing that I want you to take away from this discussion today is that you need to be bold to evolve. And so in today I'm going to be talking about culture and data, and I'm going to break this down in four areas. How do we get started barriers or opportunities as I see it, the value of AI, and also, how do you communicate, especially now in the workforce of today with so many different generations, you need to make sure that you are communicating in ways that are nontraditional sometimes. >>And so how do we get started? So I think the answer to that is you have to start for you yourself as a leader and stay tuned. And by that, I mean, you need to understand not only what is happening in your function or your field, but you have to be very into what is happening, society, socioeconomically speaking, wellbeing. You know, the common example is a great example. And for me personally, it's an opportunity because the number one core value that I have is wellbeing. I believe that for human potential, for customers and communities to grow wellbeing should be at the center of every decision. And as somebody mentioned is great to be, you know, stay in tune and have the skillset and the Koresh. But for me personally, to be honest, to have this courage is not about Nadina afraid. You're always afraid when you're making big changes in your swimming upstream. >>But what gives me the courage is the empathy part. Like I think empathy is a huge component because every time I go into an organization or a function, I try to listen very attentively to the needs of the business and what the leaders are trying to do. What I do it thinking about the mission of how do I make change for the bigger, eh, you know, workforce? So the bigger, good, despite the fact that this might have a perhaps implication. So my own self interest in my career, right? Because you have to have that courage sometimes to make choices that are not well seeing politically speaking, what are the right thing to do and you have to push through it. So the bottom line for me is that I don't think they're transforming fast enough. And the reality is I speak with a lot of leaders and we have seen stories in the past. >>And what they show is that if you look at the four main barriers that are basically keeping us behind budget, inability to add cultural issues, politics, and lack of alignment, those are the top four. But the interesting thing is that as Cindy has mentioned, these topic about culture is sexually gaining, gaining more and more traction. And in 2018, there was a story from HBR and he wants about 45%. I believe today it's about 55%, 60% of respondents say that this is the main area that we need to focus on. So again, for all those leaders and all the executives who understand and are aware that we need to transform, commit to the transformation in set us state, eh, deadline to say, Hey, in two years, we're going to make this happen. Why do we need to do, to empower and enable this change engines to make it happen? >>You need to make the tough choices. And so to me, when I speak about being bold is about making the right choices now. So I'll give you examples of some of the roadblocks that I went through. As I think the transformations most recently, as Cindy mentioned in Schneider, there are three main areas, legacy mindset. And what that means is that we've been doing this in a specific way for a long time. And here is how having successful while working the past is not going to work. Now, the opportunity there is that there is a lot of leaders who have a digital mindset and their up and coming leaders that are perhaps not yet fully developed. We need to mentor those leaders and take bets on some of these talents, including young talent. We cannot be thinking in the past and just wait for people, you know, three to five years for them to develop because the world is going to in a, in a way that is super fast, the second area, and this is specifically to implementation of AI is very interesting to me because just the example that I have with ThoughtSpot, right? >>We went on implementation and a lot of the way the it team function. So the leaders look at technology, they look at it from the prison of the prior auth success criteria for the traditional BIS. And that's not going to work again, your opportunity here is that you need to really find what success look like. In my case, I want the user experience of our workforce to be the same as this experience you have at home is a very simple concept. And so we need to think about how do we gain that user experience with this augmented analytics tools and then work backwards to have the right talent processes and technology to enable that. And finally, and obviously with, with COVID a lot of pressuring organizations and companies to do more with less. And the solution that most leaders I see are taking is to just minimize costs sometimes and cut budget. >>We have to do the opposite. We have to actually invest some growth areas, but do it by business question. Don't do it by function. If you actually invest. And these kind of solutions, if you actually invest on developing your talent, your leadership to see more digitally, if you actually invest on fixing your data platform, it's not just an incremental cost. It's actually this investment is going to offset all those hidden costs and inefficiencies that you have on your system, because people are doing a lot of work in working very hard, but it's not efficiency, and it's not working in the way that you might want to work. So there is a lot of opportunity there. And you just to put into some perspective, there have been some studies in the past about, you know, how do we kind of measure the impact of data? And obviously this is going to vary by your organization. >>Maturity is going to be a lot of factors. I've been in companies who have very clean, good data to work with. And I've been with companies that we have to start basically from scratch. So it all depends on your maturity level, but in this study, what I think is interesting is they try to put a tagline or attack price to what is the cost of incomplete data. So in this case, it's about 10 times as much to complete a unit of work. When you have data that is flawed as opposed to have imperfect data. So let me put that just in perspective, just as an example, right? Imagine you are trying to do something and you have to do a hundred things in a project, and each time you do something, it's going to cost you a dollar. So if you have perfect data, the total cost of that project might be a hundred dollars. >>But now let's say you have 80% perfect data and 20% flow data by using this assumption that Florida is 10 times as costly as perfect data. Your total costs now becomes $280 as opposed to a hundred dollars. This just for you to really think about as a CIO CTO, CSRO CEO, are we really paying attention and really close in the gaps that we have on our data infrastructure. If we don't do that, it's hard sometimes to see this snowball effect or to measure the overall impact. But as you can tell, the price tag goes up very, very quickly. So now, if I were to say, how do I communicate this? Or how do I break through some of these challenges or some of these various, right. I think the key is I am in analytics. I know statistics obviously, and, and, and love modeling and, you know, data and optimization theory and all that stuff. >>That's what I came to analytics. But now as a leader and as a change agent, I need to speak about value. And in this case, for example, for Schneider, there was this tagline coffee of your energy. So the number one thing that they were asking from the analytics team was actually efficiency, which to me was very interesting. But once I understood that I understood what kind of language to use, how to connect it to the overall strategy and basically how to bring in the right leaders, because you need to focus on the leaders that you're going to make the most progress. You know, again, low effort, high value. You need to make sure you centralize all the data as you can. You need to bring in some kind of augmented analytics solution. And finally you need to make it super simple for the, you know, in this case, I was working with the HR teams and other areas, so they can have access to one portal. >>They don't have to be confused and looking for 10 different places to find information. I think if you can actually have those four foundational pillars, obviously under the guise of having a data driven culture, that's where you can actually make the impact. So in our case, it was about three years total transformation, but it was two years for this component of augmented analytics. It took about two years to talk to, you know, it, get leadership support, find the budgeting, you know, get everybody on board, make sure the success criteria was correct. And we call this initiative, the people analytics, I pulled up, it was actually launched in July of this year. And we were very excited and the audience was very excited to do this. In this case, we did our pilot in North America for many, many manufacturers. But one thing that is really important is as you bring along your audience on this, you know, you're going from Excel, you know, in some cases or Tablo to other tools like, you know, you need to really explain them. >>What is the difference in how these two can truly replace some of the spreadsheets or some of the views that you might have on these other kinds of tools? Again, Tableau, I think it's a really good tool. There are other many tools that you might have in your toolkit. But in my case, personally, I feel that you need to have one portal going back to Cindy's point. I really truly enable the end user. And I feel that this is the right solution for us, right? And I will show you some of the findings that we had in the pilot in the last two months. So this was a huge victory, and I will tell you why, because it took a lot of effort for us to get to the station. Like I said, it's been years for us to kind of lay the foundation, get the leadership in shape the culture so people can understand why you truly need to invest, but I meant analytics. >>And so what I'm showing here is an example of how do we use basically to capture in video the qualitative findings that we had, plus the quantitative insights that we have. So in this case, our preliminary results based on our ambition for three main metrics, our safe user experience and adoption. So for our safe or a mission was to have 10 hours per week per employee save on average user experience or ambition was 4.5 and adoption, 80% in just two months, two months and a half of the pilot, we were able to achieve five hours per week per employee savings. I used to experience for 4.3 out of five and adoption of 60%, really, really amazing work. But again, it takes a lot of collaboration for us to get to the stage from it, legal communications, obviously the operations teams and the users in HR safety and other areas that might be, eh, basically stakeholders in this whole process. >>So just to summarize this kind of effort takes a lot of energy. You hire a change agent, you need to have the courage to make this decision and understand that. I feel that in this day and age, with all this disruption happening, we don't have a choice. We have to take the risk, right? And in this case, I feel a lot of satisfaction in how we were able to gain all these very souls for this organization. And that gave me the confidence to know that the work has been done and we are now in a different stage for the organization. And so for me, it says to say, thank you for everybody who has believed, obviously in our vision, everybody wants to believe in, you know, the word that we were trying to do and to make the life for, you know, workforce or customers that in community better, as you can tell, there is a lot of effort. >>There is a lot of collaboration that is needed to do something like this. In the end, I feel very satisfied. We, the accomplishments of this transformation, and I just, I just want to tell for you, if you are going right now in a moment that you feel that you have to swim upstream, you know, what would mentors, where we, people in this industry that can help you out and guide you on this kind of a transformation is not easy to do is high effort bodies, well worth it. And with that said, I hope you are well. And it's been a pleasure talking to you. Take care. Thank you, Gustavo. That was amazing. All right, let's go to the panel. >>I think we can all agree how valuable it is to hear from practitioners. And I want to thank the panel for sharing their knowledge with the community. And one common challenge that I heard you all talk about was bringing your leadership and your teams along on the journey with you. We talk about this all the time, and it is critical to have support from the top. Why? Because it directs the middle and then it enables bottoms up innovation effects from the cultural transformation that you guys all talked about. It seems like another common theme we heard is that you all prioritize database decision making in your organizations and you combine two of your most valuable assets to do that and create leverage employees on the front lines. And of course the data, as you rightly pointed out, Tom, the pandemic has accelerated the need for really leaning into this. You know, the old saying, if it ain't broke, don't fix it. We'll COVID is broken everything. And it's great to hear from our experts, you know, how to move forward. So let's get right into, so Gustavo, let's start with you. If, if I'm an aspiring change agent and let's say I'm a, I'm a budding data leader. What do I need to start doing? What habits do I need to create for long lasting success? >>I think curiosity is very important. You need to be, like I say, in tune to what is happening, not only in your specific field, like I have a passion for analytics, I can do this for 50 years plus, but I think you need to understand wellbeing other areas across not only a specific business, as you know, I come from, you know, Sam's club, Walmart, retail, I mean energy management technology. So you have to try to push yourself and basically go out of your comfort zone. I mean, if you are staying in your comfort zone and you want to use lean continuous improvement, that's just going to take you so far. What you have to do is, and that's what I try to do is I try to go into areas, different certain transformations that make me, you know, stretch and develop as a leader. That's what I'm looking to do. So I can help to inform the functions organizations and do the change management decision of mindset as required for these kinds of efforts. A thank you for that, that is inspiring. And, and Sydney, you love data. And the data's pretty clear that diversity is a good business, but I wonder if you can add your perspective to this conversation. >>Yeah. So Michelle has a new fan here because she has found her voice. I'm still working on finding mine. And it's interesting because I was raised by my dad, a single dad. So he did teach me how to work in a predominantly male environment, but why I think diversity matters more now than ever before. And this is by gender, by race, by age, by just different ways of working in thinking is because as we automate things with AI, if we do not have diverse teams looking at the data and the models and how they're applied, we risk having bias at scale. So this is why I think I don't care what type of minority you are finding your voice, having a seat at the table and just believing in the impact of your work has never been more important. And as Michelle said more possible, >>Great perspectives. Thank you, Tom. I want to go to you. I mean, I feel like everybody in our businesses in some way, shape or form become a COVID expert, but what's been the impact of the pandemic on your organization's digital transformation plans. We've seen a massive growth actually in a digital business over the last 12 months, really, uh, even in celebration, right? Once, once COBIT hit, uh, we really saw that, uh, that, uh, in the 200 countries and territories that we operate in today and service our customers. And today that, uh, been a huge need, right? To send money, to support family, to support, uh, friends and loved ones across the world. And as part of that, uh, we, you know, we we're, we are, uh, very, uh, honored to get to support those customers that we across all the centers today. But as part of that acceleration, we need to make sure that we had the right architecture and the right platforms to basically scale, right, to basically support and provide the right kind of security for our customers going forward. >>So as part of that, uh, we, we did do some, uh, some the pivots and we did, uh, a solo rate, some of our plans on digital to help support that overall growth coming in there to support our customers going forward, because there were these times during this pandemic, right? This is the most important time. And we need to support those, those that we love and those that we care about and doing that it's one of those ways is actually by sending money to them, support them financially. And that's where, uh, really our part that our services come into play that, you know, we really support those families. So it was really a, a, a, a, a great opportunity for us to really support and really bring some of our products to the next level and supporting our business going forward. Awesome. Thank you. Now, I want to come back to Gustavo, Tom. I'd love for you to chime in too. Did you guys ever think like you were, you were pushing the envelope too much in, in doing things with, with data or the technology that was just maybe too bold, maybe you felt like at some point it was, it was, it was failing or you're pushing your people too hard. Can you share that experience and how you got through it? >>Yeah, the way I look at it is, you know, again, whenever I go to an organization, I ask the question, Hey, how fast you would like to conform. And, you know, based on the agreements on the leadership and the vision that we want to take place, I take decisions. And I collaborate in a specific way now, in the case of COVID, for example, right? It forces us to remove silos and collaborate in a faster way. So to me, it was an opportunity to actually integrate with other areas and drive decisions faster, but make no mistake about it. When you are doing a transformation, you are obviously trying to do things faster than sometimes people are comfortable doing, and you need to be okay with that. Sometimes you need to be okay with tension, or you need to be okay, you know, the varying points or making repetitive business cases onto people, connect with the decision because you understand, and you are seeing that, Hey, the CEO is making a one two year, you know, efficiency goal. >>The only way for us to really do more with less is for us to continue this path. We cannot just stay with the status quo. We need to find a way to accelerate it's information. That's the way, how, how about Utah? We were talking earlier was sedation Cindy, about that bungee jumping moment. What can you share? Yeah. You know, I think you hit upon, uh, right now, the pace of change will be the slowest pace that you see for the rest of your career. So as part of that, right, that's what I tell my team. This is that you need to be, need to feel comfortable being uncomfortable. I mean, that we have to be able to basically, uh, scale, right, expand and support that the ever changing needs in the marketplace and industry and our customers today, and that pace of change that's happening. >>Right. And what customers are asking for and the competition in the marketplace, it's only going to accelerate. So as part of that, you know, as you look at what, uh, how you're operating today and your current business model, right. Things are only going to get faster. So you have to plan into align and to drive the actual transformation so that you can scale even faster in the future. So as part of that is what we're putting in place here, right. Is how do we create that underlying framework and foundation that allows the organization to basically continue to scale and evolve into the future? Yeah, we're definitely out of our comfort zones, but we're getting comfortable with it. So, Cindy, last question, you've worked with hundreds of organizations, and I got to believe that, you know, some of the advice you gave when you were at Gartner, which is pre COVID, maybe sometimes clients didn't always act on it. You know, they're not on my watch for whatever variety of reasons, but it's being forced on them now. But knowing what you know now that you know, we're all in this isolation economy, how would you say that advice has changed? Has it changed? What's your number one action and recommendation today? >>Yeah. Well, first off, Tom just freaked me out. What do you mean? This is the slowest ever even six months ago. I was saying the pace of change in data and analytics is frenetic. So, but I think you're right, Tom, the business and the technology together is forcing this change. Now, um, Dave, to answer your question, I would say the one bit of advice, maybe I was a little more, um, very aware of the power and politics and how to bring people along in a way that they are comfortable. And now I think it's, you know, what? You can't get comfortable. In fact, we know that the organizations that were already in the cloud have been able to respond and pivot faster. So if you really want to survive as, as Tom and Gustavo said, get used to being uncomfortable, the power and politics are gonna happen. Break the rules, get used to that and be bold. Do not, do not be afraid to tell somebody they're wrong and they're not moving fast enough. I do think you have to do that with empathy, as Michelle said, and Gustavo, I think that's one of the key words today besides the bungee jumping. So I want to know where's the dish gonna go on to junk >>Guys. Fantastic discussion, really, thanks again, to all the panelists and the guests. It was really a pleasure speaking with you today. Really virtually all of the leaders that I've spoken to in the cube program. Recently, they tell me that the pandemic is accelerating so many things, whether it's new ways to work, we heard about new security models and obviously the need for cloud. I mean, all of these things are driving true enterprise wide digital transformation, not just as I said before, lip service is sometimes we minimize the importance and the challenge of building culture and in making this transformation possible. But when it's done, right, the right culture is going to deliver tournament, tremendous results. Know what does that mean? Getting it right? Everybody's trying to get it right. My biggest takeaway today is it means making data part of the DNA of your organization. >>And that means making it accessible to the people in your organization that are empowered to make decisions, decisions that can drive you revenue, cut costs, speed, access to critical care, whatever the mission is of your organization. Data can create insights and informed decisions that drive value. Okay. Let's bring back Sudheesh and wrap things up. So these please bring us home. Thank you. Thank you, Dave. Thank you. The cube team, and thanks. Thanks goes to all of our customers and partners who joined us and thanks to all of you for spending the time with us. I want to do three quick things and then close it off. The first thing is I want to summarize the key takeaways that I had from all four of our distinguished speakers. First, Michelle, I was simply put it. She said it really well. That is be brave and drive. >>Don't go for a drive along. That is such an important point. Often times, you know that I think that you have to make the positive change that you want to see happen when you wait for someone else to do it, not just, why not you? Why don't you be the one making that change happen? That's the thing that I picked up from Michelle's talk, Cindy talked about finding the importance of finding your voice, taking that chair, whether it's available or not, and making sure that your ideas, your voices are heard, and if it requires some force and apply that force, make sure your ideas are we start with talking about the importance of building consensus, not going at things all alone, sometimes building the importance of building the Koran. And that is critical because if you want the changes to last, you want to make sure that the organization is fully behind it, Tom, instead of a single take away. >>What I was inspired by is the fact that a company that is 170 years old, 170 years sold 200 companies, 200 countries they're operating in and they were able to make the change that is necessary through this difficult time. So in a matter of months, if they could do it, anyone could. The second thing I want to do is to leave you with a takeaway that is I would like you to go to topspot.com/nfl because our team has made an app for NFL on snowflake. I think you will find this interesting now that you are inspired and excited because of Michelle stock. And the last thing is these go to topspot.com/beyond our global user conferences happening in this December, we would love to have you join us. It's again, virtual, you can join from anywhere. We are expecting anywhere from five to 10,000 people, and we would love to have you join and see what we've been up to since last year, we, we have a lot of amazing things in store for you, our customers, our partners, our collaborators, they will be coming and sharing. You'll be sharing things that you have been working to release something that will come out next year. And also some of the crazy ideas or engineers. All of those things will be available for you at hotspot beyond. Thank you. Thank you so much.

>> Voice Over: Data is at the heart of transformation, and the change every company needs to succeed. But it takes more than new technology. It's about teams, talent and cultural change. Empowering everyone on the front lines to make decisions, all at the speed of digital. The transformation starts with you, it's time to lead the way, it's time for thought leaders. (soft upbeat music) >> Welcome to Thought.Leaders a digital event brought to you by ThoughtSpot, my name is Dave Vellante. The purpose of this day is to bring industry leaders and experts together to really try and understand the important issues around digital transformation. We have an amazing lineup of speakers, and our goal is to provide you with some best practices that you can bring back and apply to your organization. Look, data is plentiful, but insights are not, ThoughtSpot is disrupting analytics, by using search and machine intelligence to simplify data analysis and really empower anyone with fast access to relevant data. But in the last 150 days, we've had more questions than answers. Creating an organization that puts data and insights at their core, requires not only modern technology but leadership, a mindset and a culture, that people often refer to as data-driven. What does that mean? How can we equip our teams with data and fast access to quality information that can turn insights into action? And today we're going to hear from experienced leaders who are transforming their organizations with data, insights, and creating digital first cultures. But before we introduce our speakers, I'm joined today by two of my co-hosts from ThoughtSpot. First, chief data strategy officer of the ThoughtSpot is Cindi Howson, Cindi is an analytics and BI expert with 20 plus years experience, and the author of Successful Business Intelligence: Unlock the Value of BI & Big Data. Cindi was previously the lead analyst at Gartner for the data and analytics Magic Quadrant. In early last year, she joined ThoughtSpot to help CEOs and their teams understand how best to leverage analytics and AI for digital transformation. Cindi great to see you, welcome to the show. >> Thank you Dave, nice to join you virtually. >> Now our second cohost and friend of theCUBE is ThoughtSpot CEO Sudheesh Nair Hello Sudheesh, how are you doing today? >> I'm well, good to talk to you again. >> That's great to see you, thanks so much for being here. Now Sudheesh, please share with us why this discussion is so important to your customers and of course to our audience, and what they're going to learn today. (upbeat music) >> Thanks Dave, I wish you were there to introduce me into every room that I walk into because you have such an amazing way of doing it. It makes me feel also good. Look, since we have all been you know, cooped up in our homes, I know that the vendors like us, we have amped up our sort of effort to reach out to you with, invites for events like this. So we are getting very more invites for events like this than ever before. So when we started planning for this, we had three clear goals that we wanted to accomplish. And our first one, that when you finish this and walk away, we want to make sure that you don't feel like it was a waste of time, we want to make sure that we value your time, then this is going to be used. Number two, we want to put you in touch with industry leaders and thought leaders, generally good people, that you want to hang around with long after this event is over. And number three, as we plan through this, you know we are living through these difficult times we want this event to be more of an uplifting and inspiring event too. Now, the challenge is how do you do that with the team being change agents, because teens and as much as we romanticize it, it is not one of those uplifting things that everyone wants to do or likes to do. The way I think of it, changes sort of like, if you've ever done bungee jumping, and it's like standing on the edges, waiting to make that one more step you know, all you have to do is take that one step and gravity will do the rest, but that is the hardest step today. Change requires a lot of courage, and when we are talking about data and analytics, which is already like such a hard topic not necessarily an uplifting and positive conversation most businesses, it is somewhat scary, change becomes all the more difficult. Ultimately change requires courage, courage to first of all, challenge the status quo. People sometimes are afraid to challenge the status quo because they are thinking that you know, maybe I don't have the power to make the change that the company needs, sometimes they feel like I don't have the skills, sometimes they may feel that I'm probably not the right person to do it. Or sometimes the lack of courage manifest itself as the inability to sort of break the silos that are formed within the organizations when it comes to data and insights that you talked about. You know, that are people in the company who are going to have the data because they know how to manage the data, how to inquire and extract, they know how to speak data, they have the skills to do that. But they are not the group of people who have sort of the knowledge, the experience of the business to ask the right questions off the data. So there is the silo of people with the answers, and there is a silo of people with the questions, and there is gap, this sort of silos are standing in the way of making that necessary change that we all know the business needs. And the last change to sort of bring an external force sometimes. It could be a tool, it could be a platform, it could be a person, it could be a process but sometimes no matter how big the company is or how small the company is you may need to bring some external stimuli to start the domino of the positive changes that are necessary. The group of people that we are brought in, the four people, including Cindi that you will hear from today are really good at practically telling you how to make that step, how to step off that edge, how to dress the rope, that you will be safe and you're going to have fun, you will have that exhilarating feeling of jumping for a bungee jump, all four of them are exceptional, but my owner is to introduce Michelle. And she's our first speaker, Michelle I am very happy after watching our presentation and reading your bio that there are no country vital worldwide competition for cool parents, because she will beat all of us. Because when her children were small, they were probably into Harry Potter and Disney and she was managing a business and leading change there. And then as her kids grew up and got to that age where they like football and NFL, guess what? She's the CIO of NFL, what a cool mom. I am extremely excited to see what she's going to talk about. I've seen this slides, a bunch of amazing pictures, I'm looking to see the context behind it, I'm very thrilled to make that client so far, Michelle, I'm looking forward to her talk next. Welcome Michelle, it's over to you. (soft upbeat music) >> I'm delighted to be with you all today to talk about thought leadership. And I'm so excited that you asked me to join you because today I get to be a quarterback. I always wanted to be one, and I thought this is about as close as I'm ever going to get. So I want to talk to you about quarterbacking our digital revolution using insights data, and of course as you said, leadership. First a little bit about myself, a little background as I said, I always wanted to play football, and this is something that I wanted to do since I was a child, but when I grew up, girls didn't get to play football. I'm so happy that that's changing and girls are now doing all kinds of things that they didn't get to do before. Just this past weekend on an NFL field, we had a female coach on two sidelines, and a female official on the field. I'm a lifelong fan and student of the game of football, I grew up in the South, you can tell from the accent and in the South is like a religion and you pick sides. I chose Auburn University working in the Athletic Department, so I'm testament to you can start the journey can be long it took me many, many years to make it into professional sports. I graduated in 1987 and my little brother, well, not actually not so little, he played offensive line for the Alabama Crimson Tide. And for those of you who know SEC football you know, this is a really big rivalry. And when you choose sides, your family is divided, so it's kind of fun for me to always tell the story that my dad knew his kid would make it to the NFL he just bet on the wrong one. My career has been about bringing people together for memorable moments at some of America's most iconic brands. Delivering memories and amazing experiences that delight from Universal Studios, Disney to my current position as CIO of the NFL. In this job I'm very privileged to have the opportunity to work with the team, that gets to bring America's game to millions of people around the world. Often I'm asked to talk about how to create amazing experiences for fans, guests, or customers. But today I really wanted to focus on something different and talk to you about being behind the scenes and backstage. Because behind every event every game, every awesome moment is execution, precise repeatable execution. And most of my career has been behind the scenes, doing just that, assembling teams to execute these plans, and the key way that companies operate at these exceptional levels, is making good decisions, the right decisions at the right time and based upon data, so that you can translate the data into intelligence and be a data-driven culture. Using data and intelligence is an important way that world-class companies do differentiate themselves. And it's the lifeblood of collaboration and innovation. Teams that are working on delivering these kinds of world-class experiences are often seeking out and leveraging next generation technologies and finding new ways to work. I've been fortunate to work across three decades of emerging experiences, which each required emerging technologies to execute. A little bit first about Disney, in the 90s I was at Disney, leading a project called destination Disney, which it's a data project, it was a data project, but it was CRM before CRM was even cool. And then certainly before anything like a data-driven culture was ever brought up. But way back then we were creating a digital backbone that enabled many technologies for the things that you see today, like the magic band, just these magical express. My career at Disney began in finance, but Disney was very good about rotating you around, and it was during one of these rotations that I became very passionate about data. I kind of became a pain in the butt to the IT team, asking for data more and more data. And I learned that all of that valuable data was locked up in our systems, all of our point of sales systems, our reservation systems, our operation systems, and so I became a shadow IT person in marketing, ultimately leading to moving into IT, and I haven't looked back since. In the early 2000s I was at Universal Studios Theme Park as their CIO, preparing for and launching the wizarding world of Harry Potter. Bringing one of history's most memorable characters to life required many new technologies and a lot of data. Our data and technologies were embedded into the rides and attractions. I mean, how do you really think a wand selects you at a wine shop. As today at the NFL, I am constantly challenged to do leading edge technologies using things like sensors, AI, machine learning, and all new communication strategies, and using data to drive everything from player performance, contracts to where we build new stadiums and hold events. With this year being the most challenging, yet rewarding year in my career at the NFL. In the middle of a global pandemic, the way we are executing on our season is leveraging data from contract tracing devices joined with testing data. Talk about data, actually enabling your business without it we wouldn't be having a season right now. I'm also on the board of directors of two public companies, where data and collaboration are paramount. First RingCentral, it's a cloud based unified communications platform, and collaboration with video message and phone, all in one solution in the cloud. And Quotient Technologies, whose product is actually data. The tagline at quotient is the result in knowing. I think that's really important, because not all of us are data companies, where your product is actually data. But we should operate more like your product is data. I'd also like to talk to you about four areas of things to think about, as thought leaders in your companies. First just hit on it is change, how to be a champion and a driver of change. Second, how to use data to drive performance for your company, and measure performance of your company. Third, how companies now require intense collaboration to operate, and finally, how much of this is accomplished through solid data-driven decisions. First let's hit on change. I mean, it's evident today more than ever, that we are in an environment of extreme change. I mean, we've all been at this for years and as technologists we've known it, believed it, lived it, and thankfully for the most part knock on wood we were prepared for it. But this year everyone's cheese was moved, all the people in the back rooms, IT, data architects and others, were suddenly called to the forefront. Because a global pandemic has turned out to be the thing that is driving intense change in how people work and analyze their business. On March 13th, we closed our office at the NFL in the middle of preparing for one of our biggest events, our kickoff event, the 2020 Draft. We went from planning, a large event in Las Vegas under the bright lights red carpet stage to smaller events in club facilities. And then ultimately to one where everyone coaches, GMs, prospects and even our commissioner were at home in their basements. And we only had a few weeks to figure it out. I found myself for the first time being in the live broadcast event space, talking about bungee dress jumping, this is really what it felt like. It was one in which no one felt comfortable, because it had not been done before. But leading through this, I stepped up, but it was very scary, it was certainly very risky but it ended up being Oh, so rewarding when we did it. And as a result of this, some things will change forever. Second, managing performance. I mean, data should inform how you're doing and how to get your company to perform at this level, highest level. As an example, the NFL has always measured performance obviously, and it is one of the purest examples of how performance directly impacts outcome. I mean, you can see performance on the field, you can see points being scored and stats, and you immediately know that impact, those with the best stats, usually win the games. The NFL has always recorded stats, since the beginning of time, here at the NFL a little this year as our 100 and first year and athletes ultimate success as a player has also always been greatly impacted by his stats. But what has changed for us, is both how much more we can measure, and the immediacy with which it can be measured. And I'm sure in your business, it's the same, the amount of data you must have has got to have quadrupled recently and how fast you need it and how quickly you need to analyze it, is so important. And it's very important to break the silos between the keys to the data and the use of the data. Our next generation stats platform is taking data to a next level, it's powered by Amazon Web Services, and we gathered this data real time from sensors that are on players' bodies. We gather it in real time, analyze it, display it online and on broadcast, and of course it's used to prepare week to week in addition to what is a normal coaching plan would be. We can now analyze, visualize, route patterns speed, matchups, et cetera, so much faster than ever before. We're continuing to roll out sensors too, that we'll gather more and more information about player's performance as it relates to their health and safety. The third trend is really I think it's a big part of what we're feeling today and that is intense collaboration. And just for sort of historical purposes it's important to think about for those of you that are IT professionals and developers, you know more than 10 years ago, agile practices began sweeping companies or small teams would work together rapidly in a very flexible, adaptive and innovative way, and it proved to be transformational. However today, of course, that is no longer just small teams the next big wave of change, and we've seen it through this pandemic is that it's the whole enterprise that must collaborate and be agile. If I look back on my career when I was at Disney, we owned everything 100%, we made a decision, we implemented it, we were a collaborative culture but it was much easier to push change because you own the whole decision. If there was buy in from the top down, you got the people from the bottom up to do it, and you executed. At Universal, we were a joint venture, our attractions and entertainment was licensed, our hotels were owned and managed by other third parties. So influence and collaboration and how to share across companies became very important. And now here I am at the NFL and even the bigger ecosystem. We have 32 clubs that are all separate businesses 31 different stadiums that are owned by a variety of people. We have licensees, we have sponsors, we have broadcast partners. So it seems that as my career has evolved centralized control has gotten less and less and has been replaced by intense collaboration not only within your own company, but across companies. The ability to work in a collaborative way across businesses and even other companies that has been a big key to my success in my career. I believe this whole vertical integration and big top down decision making is going by the wayside in favor of ecosystems that require cooperation, yet competition to coexist. I mean the NFL is a great example of what we call coopertition, which is cooperation and competition. When in competition with each other, but we cooperate to make the company the best it can be. And at the heart of these items really are data-driven decisions and culture. Data on its own isn't good enough, you must be able to turn it to insights, partnerships between technology teams who usually hold the keys to the raw data, and business units who have the knowledge to build the right decision models is key. If you're not already involved in this linkage, you should be, data mining isn't new for sure. The availability of data is quadrupling and it's everywhere. How do you know what to even look at? How do you know where to begin? How do you know what questions to ask? It's by using the tools that are available for visualization and analytics and knitting together strategies of the company. So it begins with first of all making sure you do understand the strategy of the company. So in closing, just to wrap up a bit, many of you joined today looking for thought leadership on how to be a change agent, a change champion, and how to lead through transformation. Some final thoughts are be brave, and drive, don't do the ride along program, it's very important to drive, driving can be high risk but it's also high reward. Embracing the uncertainty of what will happen, is how you become brave, get more and more comfortable with uncertainty be calm and let data be your map on your journey, thanks. >> Michelle, thank you so much. So you and I share a love of data, and a love of football. You said you want to be the quarterback, I'm more an old wine person. (Michelle laughing) >> Well, then I can do my job without you. >> Great, and I'm getting the feeling now you know, Sudheesh is talking about bungee jumping. My boat is when we're past this pandemic, we both take them to the Delaware Water Gap and we do the cliff jumping. >> That sounds good, I'll watch. >> You'll watch, okay, so Michelle, you have so many stakeholders when you're trying to prioritize the different voices, you have the players, you have the owners you have the league, as you mentioned to the broadcasters your, your partners here and football mamas like myself. How do you prioritize when there's so many different stakeholders that you need to satisfy? I think balancing across stakeholders starts with aligning on a mission. And if you spend a lot of time understanding where everyone's coming from, and you can find the common thread ties them all together you sort of do get them to naturally prioritize their work, and I think that's very important. So for us at the NFL, and even at Disney, it was our core values and our core purpose is so well known, and when anything challenges that we're able to sort of lay that out. But as a change agent, you have to be very empathetic, and I would say empathy is probably your strongest skill if you're a change agent. And that means listening to every single stakeholder even when they're yelling at you, even when they're telling you your technology doesn't work and you know that it's user error, or even when someone is just emotional about what's happening to them and that they're not comfortable with it. So I think being empathetic and having a mission and understanding it, is sort of how I prioritize and balance. >> Yeah, empathy, a very popular word this year. I can imagine those coaches and owners yelling. So I thank you for your metership here. So Michelle, I look forward to discussing this more with our other customers and disruptors joining us in a little bit. (soft upbeat music) >> So we're going to take a hard pivot now and go from football to Chernobyl, Chernobyl, what went wrong? 1986, as the reactors were melting down they had the data to say, this is going to be catastrophic and yet the culture said, "No, we're perfect, hide it. Don't dare tell anyone," which meant they went ahead and had celebrations in Kiev. Even though that increased the exposure the additional thousands getting cancer, and 20,000 years before the ground around there and even be inhabited again, This is how powerful and detrimental a negative culture, a culture that is unable to confront the brutal facts that hides data. This is what we have to contend with, and this is why I want you to focus on having fostering a data-driven culture. I don't want you to be a laggard, I want you to be a leader in using data to drive your digital transformation. So I'll talk about culture and technology, isn't really two sides of the same coin, real-world impacts and then some best practices you can use to disrupt and innovate your culture. Now, oftentimes I would talk about culture and I talk about technology, and recently a CDO said to me, "You know Cindi, I actually think this is two sides of the same coin. One reflects the other, what do you think?" Let me walk you through this, so let's take a laggard. What is the technology look like? Is it based on 1990s BI and reporting largely parameterized reports on-premises data warehouses, or not even that operational reports, at best one enterprise data warehouse very slow moving and collaboration is only email. What does that culture tell you? Maybe there's a lack of leadership to change, to do the hard work that Sudheesh referred to. Or is there also a culture of fear, afraid of failure, resistance to change complacency and sometimes that complacency it's not because people are lazy, it's because they've been so beaten down every time a new idea is presented. It's like, no we're measured on least cost to serve. So politics and distrust, whether it's between business and IT or individual stakeholders is the norm. So data is hoarded, let's contrast that with a leader, a data and analytics leader, what is their technology look like? Augmented analytics, search and AI-driven insights not on-premises, but in the cloud and maybe multiple clouds. And the data is not in one place, but it's in a data lake, and in a data warehouse, a logical data warehouse. The collaboration is being a newer methods whether it's Slack or teams allowing for that real time decisioning or investigating a particular data point. So what is the culture in the leaders? It's transparent and trust, there is a trust that data will not be used to punish, that there is an ability to confront the bad news. It's innovation, valuing innovation in pursuit of the company goals, whether it's the best fan experience and player safety in the NFL or best serving your customers. It's innovative and collaborative. There's none of this, oh, well, I didn't invent that, I'm not going to look at that. There's still pride of ownership, but it's collaborating to get to a better place faster. And people feel empowered to present new ideas to fail fast, and they're energized, knowing that they're using the best technology and innovating at the pace that business requires. So data is democratized and democratized, not just for power users or analysts, but really at the point of impact what we like to call the new decision makers. Or really the frontline workers. So Harvard business review partnered with us to develop this study to say, just how important is this? They've been working at BI and analytics as an industry for more than 20 years. Why is it not at the front lines? Whether it's a doctor, a nurse, a coach, a supply chain manager a warehouse manager, a financial services advisor. 87% said they would be more successful if frontline workers were empowered with data-driven insights, but they recognize they need new technology to be able to do that. It's not about learning hard tools, the sad reality only 20% of organizations are actually doing this, these are the data-driven leaders. So this is the culture and technology, how did we get here? It's because state of the art keeps changing. So the first generation BI and analytics platforms were deployed on-premises, on small datasets really just taking data out of ERP systems that were also on-premises, and state of the art was maybe getting a management report, an operational report. Over time visual based data discovery vendors, disrupted these traditional BI vendors, empowering now analysts to create visualizations with the flexibility on a desktop, sometimes larger data sometimes coming from a data warehouse, the current state of the art though, Gartner calls it augmented analytics, at ThoughtSpot, we call it search and AI-driven analytics. And this was pioneered for large scale data sets, whether it's on-premises or leveraging the cloud data warehouses, and I think this is an important point. Oftentimes you, the data and analytics leaders, will look at these two components separately, but you have to look at the BI and analytics tier in lockstep with your data architectures to really get to the granular insights, and to leverage the capabilities of AI. Now, if you've never seen ThoughtSpot I'll just show you what this looks like, instead of somebody's hard coding a report, it's typing in search keywords and very robust keywords contains rank, top, bottom getting to a visualization that then can be pinned to an existing Pinboard that might also contain insights generated by an AI engine. So it's easy enough for that new decision maker, the business user, the non analyst to create themselves. Modernizing the data and analytics portfolio is hard, because the pace of change has accelerated. You used to be able to create an investment, place a bet for maybe 10 years. A few years ago, that time horizon was five years, now it's maybe three years, and the time to maturity has also accelerated. So you have these different components the search and AI tier, the data science tier, data preparation and virtualization. But I would also say equally important is the cloud data warehouse. And pay attention to how well these analytics tools can unlock the value in these cloud data warehouses. So ThoughtSpot was the first to market with search and AI-driven insights. Competitors have followed suit, but be careful if you look at products like Power BI or SAP Analytics Cloud, they might demo well, but do they let you get to all the data without moving it in products like Snowflake, Amazon Redshift or Azure Synapse or Google BigQuery, they do not. They require you to move it into a smaller in memory engine. So it's important how well these new products inter operate. The pace of change, it's acceleration, Gartner recently predicted that by 2022, 65% of analytical queries will be generated using search or NLP or even AI, and that is roughly three times the prediction they had just a couple years ago. So let's talk about the real world impact of culture. And if you've read any of my books or used any of the maturity models out there whether the Gartner IT score that I worked on, or the data warehousing institute also has a maturity model. We talk about these five pillars to really become data-driven, as Michelle spoke about, it's focusing on the business outcomes, leveraging all the data, including new data sources. It's the talent, the people, the technology, and also the processes, and often when I would talk about the people in the talent, I would lump the culture as part of that. But in the last year, as I've traveled the world and done these digital events for thought leaders you have told me now culture is absolutely so important. And so we've pulled it out as a separate pillar, and in fact, in polls that we've done in these events, look at how much more important culture is, as a barrier to becoming data-driven. It's three times as important as any of these other pillars. That's how critical it is, and let's take an example of where you can have great data but if you don't have the right culture there's devastating impacts. And I will say, I have been a loyal customer of Wells Fargo for more than 20 years, but look at what happened in the face of negative news with data, that said, "Hey, we're not doing good cross selling, customers do not have both a checking account and a credit card and a savings account and a mortgage." They opened fake accounts, facing billions in fines, change in leadership, that even the CEO attributed to a toxic sales culture, and they're trying to fix this. But even recently there's been additional employee backlash saying that culture has not changed. Let's contrast that with some positive examples, Medtronic a worldwide company in 150 countries around the world, they may not be a household name to you, but if you have a loved one or yourself, you have a pacemaker, spinal implant, diabetes you know, this brand. And at the start of COVID when they knew their business would be slowing down, because hospitals would only be able to take care of COVID patients, they took the bold move of making their IP for ventilators publicly available, that is the power of a positive culture. Or Verizon, a major telecom organization, looking at late payments of their customers, and even though the US federal government said "Well, you can't turn them off." They said, "We'll extend that even beyond the mandated guidelines," and facing a slow down in the business because of the tough economy, he said, "You know what? We will spend the time upskilling our people giving them the time to learn more about the future of work, the skills and data and analytics," for 20,000 of their employees, rather than furloughing them. That is the power of a positive culture. So how can you transform your culture to the best in class? I'll give you three suggestions, bring in a change agent identify the relevance, or I like to call it WIIFM, and organize for collaboration. So the CDO whatever your title is, chief analytics officer chief digital officer, you are the most important change agent. And this is where you will hear, that oftentimes a change agent has to come from outside the organization. So this is where, for example in Europe, you have the CDO of Just Eat takeout food delivery organization, coming from the airline industry or in Australia, National Australian Bank, taking a CDO within the same sector from TD Bank going to NAB. So these change agents come in disrupt, it's a hard job. As one of you said to me, it often feels like Sisyphus, I make one step forward and I get knocked down again, I get pushed back. It is not for the faint of heart, but it's the most important part of your job. The other thing I'll talk about is WIIFM, what is in it for me? And this is really about understanding the motivation, the relevance that data has for everyone on the frontline as well as those analysts, as well as the executives. So if we're talking about players in the NFL they want to perform better, and they want to stay safe. That is why data matters to them. If we're talking about financial services this may be a wealth management advisor, okay, we could say commissions, but it's really helping people have their dreams come true whether it's putting their children through college, or being able to retire without having to work multiple jobs still into your 70s or 80s. For the teachers, teachers, you asked them about data, they'll say, "We don't need that, I care about the student." So if you can use data to help a student perform better that is WIIFM. And sometimes we spend so much time talking the technology, we forget what is the value we're trying to deliver with it. And we forget the impact on the people that it does require change. In fact, the Harvard Business Review Study, found that 44% said lack of change management is the biggest barrier to leveraging both new technology but also being empowered to act on those data-driven insights. The third point, organize for collaboration. This does require diversity of thought, but also bringing the technology, the data and the business people together. Now there's not a single one size fits all model for data and analytics. At one point in time, even having a BICC, a BI Competency Center was considered state of the art. Now for the biggest impact, what I recommend is that you have a federated model, centralized for economies of scale, that could be the common data, but then in bed, these evangelists, these analysts of the future, within every business unit, every functional domain, and as you see this top bar, all models are possible but the hybrid model has the most impact, the most leaders. So as we look ahead to the months ahead, to the year ahead, an exciting time, because data is helping organizations better navigate a tough economy lock in the customer loyalty, and I look forward to seeing how you foster that culture that's collaborative with empathy and bring the best of technology, leveraging the cloud, all your data. So thank you for joining us at thought leaders, and next I'm pleased to introduce our first change agent Thomas Mazzaferro, chief data officer of Western Union, and before joining Western Union, Tom made his mark at HSBC and JP Morgan Chase spearheading digital innovation in technology operations, risk compliance, and retail banking. Tom, thank you so much for joining us today. (soft upbeat music) >> Very happy to be here and looking forward to talking to all of you today. So as we look to move organizations to a data-driven capability into the future, there is a lot that needs to be done on the data side, but also how does data connect and enable, different business teams and technology teams into the future. As we look across our data ecosystems and our platforms and how we modernize that to the cloud in the future, it all needs to basically work together, right? To really be able to drive over the shift from a data standpoint, into the future. That includes being able to have the right information with the right quality of data at the right time to drive informed business decisions, to drive the business forward. As part of that, we actually have partnered with ThoughtSpot to actually bring in the technology to help us drive that, as part of that partnership, and it's how we've looked to integrated into our overall business as a whole. We've looked at how do we make sure that our business and our professional lives, right? Are enabled in the same ways as our personal lives. So for example, in your personal lives, when you want to go and find something out, what do you do? You go on to google.com or you go on to Bing, or go to Yahoo and you search for what you want, search to find an answer. ThoughtSpot for us as the same thing, but in the business world. So using ThoughtSpot and other AI capability is allowed us to actually enable our overall business teams in our company, to actually have our information at our fingertips. So rather than having to go and talk to someone or an engineer to go pull information or pull data, we actually can have the end users or the business executives, right? Search for what they need, what they want, at the exact time that action needed, to go and drive the business forward. This is truly one of those transformational things that we've put in place. On top of that, we are on the journey to modernize our larger ecosystem as a whole. That includes modernizing our underlying data warehouses, our technology or our (indistinct) environments, and as we move that we've actually picked to our cloud providers going to AWS and GCP. We've also adopted Snowflake to really drive into organize our information and our data, then drive these new solutions and capabilities forward. So big portion of us though is culture, so how do we engage with the business teams and bring the IT teams together to really drive these holistic end to end solutions and capabilities, to really support the actual business into the future. That's one of the keys here, as we look to modernize and to really enhance our organizations to become data-driven, this is the key. If you can really start to provide answers to business questions before they're even being asked, and to predict based upon different economic trends or different trends in your business, what does is be made and actually provide those answers to the business teams before they're even asking for it. That is really becoming a data-driven organization. And as part of that, it's really then enables the business to act quickly and take advantage of opportunities as they come in based upon industries, based upon markets, based upon products, solutions, or partnerships into the future. These are really some of the keys that become crucial as you move forward right into this new age, especially with COVID, with COVID now taking place across the world, right? Many of these markets, many of these digital transformations are celebrating, and are changing rapidly to accommodate and to support customers in these very difficult times. As part of that, you need to make sure you have the right underlying foundation, ecosystems and solutions to really drive those capabilities, and those solutions forward. As we go through this journey, both of my career but also each of your careers into the future, right? It also needs to evolve, right? Technology has changed so drastically in the last 10 years, and that change is only a celebrating. So as part of that, you have to make sure that you stay up to speed, up to date with new technology changes both on the platform standpoint, tools, but also what our customers want, what do our customers need, and how do we then surface them with our information, with our data, with our platform, with our products and our services, to meet those needs and to really support and service those customers into the future. This is all around becoming a more data-driven organization such as how do you use your data to support the current business lines. But how do you actually use your information your data, to actually better support your customers better support your business, better support your employees, your operations teams and so forth, and really creating that full integration in that ecosystem is really when you start to get large dividends from these investments into the future. With that being said I hope you enjoyed the segment on how to become and how to drive a data-driven organization, and looking forward to talking to you again soon, thank you. >> Tom, that was great, thanks so much. Now I'm going to have to brag on you for a second, as a change agent you've come in disrupted, and how long have you been at Western Union? >> Only nine months, I just started this year, but there'd be some great opportunities and big changes, and we have a lot more to go, but we're really driving things forward in partnership with our business teams, and our colleagues to support those customers forward. >> Tom, thank you so much that was wonderful. And now I'm excited to introduce you to Gustavo Canton, a change agent that I've had the pleasure of working with meeting in Europe, and he is a serial change agent. Most recently with Schneider Electric, but even going back to Sam's Club, Gustavo welcome. (soft upbeat music) >> So hi everyone my name is Gustavo Canton and thank you so much Cindi for the intro. As you mentioned, doing transformations is a you know, high effort, high reward situation. I have empowerment in transformation and I have led many transformations. And what I can tell you is that it's really hard to predict the future, but if you have a North Star and you know where you're going, the one thing that I want you to take away from this discussion today, is that you need to be bold to evolve. And so in today, I'm going to be talking about culture and data, and I'm going to break this down in four areas. How do we get started barriers or opportunities as I see it, the value of AI, and also how do you communicate, especially now in the workforce of today with so many different generations, you need to make sure that you are communicating in ways that are nontraditional sometimes. And so how do we get started? So I think the answer to that is, you have to start for you, yourself as a leader and stay tuned. And by that, I mean you need to understand not only what is happening in your function or your field, but you have to be very into what is happening in society, socioeconomically speaking, wellbeing, you know, the common example is a great example. And for me personally, it's an opportunity because the number one core value that I have is wellbeing. I believe that for human potential, for customers and communities to grow, wellbeing should be at the center of every decision. And as somebody mentioned, it's great to be you know, stay in tune and have the skillset and the courage. But for me personally, to be honest to have this courage is not about not being afraid. You're always afraid when you're making big changes and your swimming upstream. But what gives me the courage is the empathy part, like I think empathy is a huge component because every time I go into an organization or a function, I try to listen very attentively to the needs of the business, and what the leaders are trying to do, what I do it thinking about the mission of how do I make change for the bigger, you know workforce so the bigger good, despite the fact that this might have a perhaps implication, so my own self interest in my career, right? Because you have to have that courage sometimes to make choices, that are not well seeing politically speaking what are the right thing to do, and you have to push through it. So the bottom line for me is that, I don't think they're transforming fast enough. And the reality is I speak with a lot of leaders and we have seen stories in the past, and what they show is that if you look at the four main barriers, that are basically keeping us behind budget, inability to add, cultural issues, politics, and lack of alignment, those are the top four. But the interesting thing is that as Cindi has mentioned, this topic about culture is actually gaining more and more traction, and in 2018, there was a story from HBR and it was for about 45%. I believe today, it's about 55%, 60% of respondents say that this is the main area that we need to focus on. So again, for all those leaders and all the executives who understand, and are aware that we need to transform, commit to the transformation and set us deadline to say, "Hey, in two years, we're going to make this happen, what do we need to do to empower and enable these search engines to make it happen?" You need to make the tough choices. And so to me, when I speak about being bold is about making the right choices now. So I'll give you samples of some of the roadblocks that I went through, as I think the intro information most recently as Cindi mentioned in Schneider. There are three main areas, legacy mindset, and what that means is that we've been doing this in a specific way for a long time, and here is how we have been successful. We're working the past is not going to work now, the opportunity there is that there is a lot of leaders who have a digital mindset, and their up and coming leaders that are perhaps not yet fully developed. We need to mentor those leaders and take bets on some of these talents, including young talent. We cannot be thinking in the past and just wait for people you know, three to five years for them to develop, because the world is going to in a way that is super fast. The second area and this is specifically to implementation of AI is very interesting to me, because just example that I have with ThoughtSpot, right? We went to an implementation and a lot of the way the IT team functions, so the leaders look at technology, they look at it from the prism of the prior or success criteria for the traditional BIs, and that's not going to work. Again, your opportunity here is that you need to really find what success look like, in my case, I want the user experience of our workforce to be the same as your experience you have at home. It's a very simple concept, and so we need to think about how do we gain that user experience with this augmented analytics tools, and then work backwards to have the right talent, processes and technology to enable that. And finally, and obviously with COVID a lot of pressure in organizations and companies to do more with less, and the solution that most leaders I see are taking is to just minimize cost sometimes and cut budget. We have to do the opposite, we have to actually invest some growth areas, but do it by business question. Don't do it by function, if you actually invest in these kind of solutions, if you actually invest on developing your talent, your leadership, to see more digitally, if you actually invest on fixing your data platform is not just an incremental cost, it's actually this investment is going to offset all those hidden costs and inefficiencies that you have on your system, because people are doing a lot of work in working very hard but it's not efficiency, and it's not working in the way that you might want to work. So there is a lot of opportunity there, and you just to put it into some perspective, there have been some studies in the past about you know, how do we kind of measure the impact of data? And obviously this is going to vary by organization, maturity there's going to be a lot of factors. I've been in companies who have very clean, good data to work with, and I think with companies that we have to start basically from scratch. So it all depends on your maturity level, but in this study what I think is interesting is, they try to put a tagline or attack price to what is a cost of incomplete data. So in this case, it's about 10 times as much to complete a unit of work, when you have data that is flawed as opposed to have imperfect data. So let me put that just in perspective, just as an example, right? Imagine you are trying to do something and you have to do 100 things in a project, and each time you do something it's going to cost you a dollar. So if you have perfect data, the total cost of that project might be a $100. But now let's say you have any percent perfect data and 20% flow data, by using this assumption that flow data is 10 times as costly as perfect data, your total costs now becomes $280 as opposed to $100, this just for you to really think about as a CIO, CTO, you know CSRO, CEO, are we really paying attention and really closing the gaps that we have on our infrastructure? If we don't do that, it's hard sometimes to see the snowball effect or to measure the overall impact, but as you can tell, the price tag goes up very, very quickly. So now, if I were to say, how do I communicate this? Or how do I break through some of these challenges or some of these barriers, right? I think the key is I am in analytics, I know statistics obviously, and love modeling and you know, data and optimization theory and all that stuff, that's what I can do analytics, but now as a leader and as a change agent, I need to speak about value, and in this case, for example for Schneider, there was this tagline coffee of your energy. So the number one thing that they were asking from the analytics team was actually efficiency, which to me was very interesting. But once I understood that I understood what kind of language to use, how to connect it to the overall strategy and basically how to bring in the right leaders, because you need to, you know, focus on the leaders that you're going to make the most progress. You know, again, low effort, high value, you need to make sure you centralize all the data as you can, you need to bring in some kind of augmented analytics, you know, solution, and finally you need to make it super simple for the you know, in this case, I was working with the HR teams and other areas, so they can have access to one portal. They don't have to be confused and looking for 10 different places to find information. I think if you can actually have those four foundational pillars, obviously under the guise of having a data-driven culture, that's when you can actually make the impact. So in our case, it was about three years total transformation but it was two years for this component of augmented analytics. It took about two years to talk to, you know, IT, get leadership support, find the budgeting, you know, get everybody on board, make sure the success criteria was correct. And we call this initiative, the people analytics, I pulled up, it was actually launched in July of this year. And we were very excited and the audience was very excited to do this. In this case, we did our pilot in North America for many, many manufacturers, but one thing that is really important is as you bring along your audience on this, you know, you're going from Excel, you know in some cases or Tableau to other tools like you know, ThoughtSpot, you need to really explain them, what is the difference, and how these two can truly replace some of the spreadsheets or some of the views that you might have on these other kind of tools. Again, Tableau, I think it's a really good tool, there are other many tools that you might have in your toolkit. But in my case, personally I feel that you need to have one portal going back to seeing these points that really truly enable the end user. And I feel that this is the right solution for us, right? And I will show you some of the findings that we had in the pilot in the last two months. So this was a huge victory, and I will tell you why, because it took a lot of effort for us to get to these stations. Like I said it's been years for us to kind of lay the foundation, get the leadership and chasing culture, so people can understand why you truly need to invest what I meant analytics. And so what I'm showing here is an example of how do we use basically, you know a tool to capturing video, the qualitative findings that we had, plus the quantitative insights that we have. So in this case, our preliminary results based on our ambition for three main metrics, hours saved, user experience and adoption. So for hours saved, our ambition was to have 10 hours per week per employee save on average, user experience or ambition was 4.5 and adoption 80%. In just two months, two months and a half of the pilot we were able to achieve five hours, per week per employee savings. I used to experience for 4.3 out of five, and adoption of 60%. Really, really amazing work. But again, it takes a lot of collaboration for us to get to the stage from IT, legal, communications obviously the operations things and the users, in HR safety and other areas that might be basically stakeholders in this whole process. So just to summarize this kind of effort takes a lot of energy, you are a change agent, you need to have a courage to make these decision and understand that, I feel that in this day and age with all this disruption happening, we don't have a choice. We have to take the risk, right? And in this case, I feel a lot of satisfaction in how we were able to gain all these very souls for this organization, and that gave me the confidence to know that the work has been done, and we are now in a different stage for the organization. And so for me it safe to say, thank you for everybody who has believed obviously in our vision, everybody who has believed in, you know, the word that we were trying to do and to make the life for, you know workforce or customers that are in community better. As you can tell, there is a lot of effort, there is a lot of collaboration that is needed to do something like this. In the end, I feel very satisfied with the accomplishments of this transformation, and I just want to tell for you, if you are going right now in a moment that you feel that you have to swim upstream you know, what would mentors what people in this industry that can help you out and guide you on this kind of a transformation is not easy to do is high effort but is well worth it. And with that said, I hope you are well and it's been a pleasure talking to you, talk to you soon, take care. >> Thank you Gustavo, that was amazing. All right, let's go to the panel. (soft upbeat music) >> I think we can all agree how valuable it is to hear from practitioners, and I want to thank the panel for sharing their knowledge with the community, and one common challenge that I heard you all talk about was bringing your leadership and your teams along on the journey with you. We talk about this all the time, and it is critical to have support from the top, why? Because it directs the middle, and then it enables bottoms up innovation effects from the cultural transformation that you guys all talked about. It seems like another common theme we heard, is that you all prioritize database decision making in your organizations, and you combine two of your most valuable assets to do that, and create leverage, employees on the front lines, and of course the data. That was rightly pointed out, Tom, the pandemic has accelerated the need for really leaning into this. You know, the old saying, if it ain't broke, don't fix it, well COVID's broken everything. And it's great to hear from our experts, you know, how to move forward, so let's get right into it. So Gustavo let's start with you if I'm an aspiring change agent, and let's say I'm a budding data leader. What do I need to start doing? What habits do I need to create for long lasting success? >> I think curiosity is very important. You need to be, like I say, in tune to what is happening not only in your specific field, like I have a passion for analytics, I can do this for 50 years plus, but I think you need to understand wellbeing other areas across not only a specific business as you know, I come from, you know, Sam's Club Walmart retail, I mean energy management technology. So you have to try to push yourself and basically go out of your comfort zone. I mean, if you are staying in your comfort zone and you want to use lean continuous improvement that's just going to take you so far. What you have to do is and that's what I tried to do is I try to go into areas, businesses and transformations that make me, you know stretch and develop as a leader. That's what I'm looking to do, so I can help transform the functions organizations, and do these change management and decisions mindset as required for these kinds of efforts. >> Thank you for that is inspiring and Cindi, you love data, and the data is pretty clear that diversity is a good business, but I wonder if you can add your perspectives to this conversation. >> Yeah, so Michelle has a new fan here because she has found her voice, I'm still working on finding mine. And it's interesting because I was raised by my dad, a single dad, so he did teach me how to work in a predominantly male environment. But why I think diversity matters more now than ever before, and this is by gender, by race, by age, by just different ways of working and thinking is because as we automate things with AI, if we do not have diverse teams looking at the data and the models, and how they're applied, we risk having bias at scale. So this is why I think I don't care what type of minority, you are finding your voice, having a seat at the table and just believing in the impact of your work has never been more important. And as Michelle said more possible >> Great perspectives thank you, Tom, I want to go to you. I mean, I feel like everybody in our businesses in some way, shape or form become a COVID expert but what's been the impact of the pandemic on your organization's digital transformation plans? >> We've seen a massive growth actually you know, in a digital business over the last 12 months really, even in celebration, right? Once COVID hit, we really saw that in the 200 countries and territories that we operate in today and service our customers and today, that there's been a huge need, right? To send money, to support family, to support friends and loved ones across the world. And as part of that, you know, we are very honored to support those customers that we across all the centers today. But as part of that celebration, we need to make sure that we had the right architecture and the right platforms to basically scale, right? To basically support and provide the right kind of security for our customers going forward. So as part of that, we did do some pivots and we did celebrate some of our plans on digital to help support that overall growth coming in, and to support our customers going forward. Because there were these times during this pandemic, right? This is the most important time, and we need to support those that we love and those that we care about. And in doing that, it's one of those ways is actually by sending money to them, support them financially. And that's where really are part of that our services come into play that, you know, I really support those families. So it was really a great opportunity for us to really support and really bring some of our products to this level, and supporting our business going forward. >> Awesome, thank you. Now I want to come back to Gustavo, Tom, I'd love for you to chime in too. Did you guys ever think like you were pushing the envelope too much and doing things with data or the technology that was just maybe too bold, maybe you felt like at some point it was failing, or you pushing your people too hard, can you share that experience and how you got through it? >> Yeah, the way I look at it is, you know, again, whenever I go to an organization I ask the question, Hey, how fast you would like to conform?" And, you know, based on the agreements on the leadership and the vision that we want to take place, I take decisions and I collaborate in a specific way. Now, in the case of COVID, for example, right? It forces us to remove silos and collaborate in a faster way, so to me it was an opportunity to actually integrate with other areas and drive decisions faster. But make no mistake about it, when you are doing a transformation, you are obviously trying to do things faster than sometimes people are comfortable doing and you need to be okay with that. Sometimes you need to be okay with tension, or you need to be okay, you know debating points or making repetitive business cases onto people connect with the decision because you understand, and you are seeing that, hey, the CEO is making a one, two year, you know, efficiency goal, the only way for us to really do more with less is for us to continue this path. We cannot just stay with the status quo, we need to find a way to accelerate transformation... >> How about you Tom, we were talking earlier was Sudheesh had said about that bungee jumping moment, what can you share? >> Yeah you know, I think you hit upon it. Right now, the pace of change will be the slowest pace that you see for the rest of your career. So as part of that, right? That's what I tell my team is that you need to feel comfortable being uncomfortable. I mean, that we have to be able to basically scale, right? Expand and support that the ever changing needs the marketplace and industry and our customers today and that pace of change that's happening, right? And what customers are asking for, and the competition the marketplace, it's only going to accelerate. So as part of that, you know, as we look at what how you're operating today in your current business model, right? Things are only going to get faster. So you have to plan into align, to drive the actual transformation, so that you can scale even faster into the future. So as part of that, so we're putting in place here, right? Is how do we create that underlying framework and foundation that allows the organization to basically continue to scale and evolve into the future? >> We're definitely out of our comfort zones, but we're getting comfortable with it. So, Cindi, last question, you've worked with hundreds of organizations, and I got to believe that you know, some of the advice you gave when you were at Gartner, which is pre COVID, maybe sometimes clients didn't always act on it. You know, they're not on my watch for whatever variety of reasons, but it's being forced on them now, but knowing what you know now that you know, we're all in this isolation economy how would you say that advice has changed, has it changed? What's your number one action and recommendation today? >> Yeah well, first off, Tom just freaked me out. What do you mean this is the slowest ever? Even six months ago, I was saying the pace of change in data and analytics is frenetic. So, but I think you're right, Tom, the business and the technology together is forcing this change. Now, Dave, to answer your question, I would say the one bit of advice, maybe I was a little more, very aware of the power in politics and how to bring people along in a way that they are comfortable, and now I think it's, you know what? You can't get comfortable. In fact, we know that the organizations that were already in the cloud, have been able to respond and pivot faster. So if you really want to survive as Tom and Gustavo said, get used to being uncomfortable, the power and politics are going to happen. Break the rules, get used to that and be bold. Do not be afraid to tell somebody they're wrong and they're not moving fast enough. I do think you have to do that with empathy as Michelle said, and Gustavo, I think that's one of the key words today besides the bungee jumping. So I want to know where's Sudheesh going to go on bungee jumping? (all chuckling) >> That's fantastic discussion really. Thanks again to all the panelists and the guests, it was really a pleasure speaking with you today. Really virtually all of the leaders that I've spoken to in theCUBE program recently, they tell me that the pandemic is accelerating so many things, whether it's new ways to work, we heard about new security models and obviously the need for cloud. I mean, all of these things are driving true enterprise wide digital transformation, not just as I said before lip service. And sometimes we minimize the importance and the challenge of building culture and in making this transformation possible. But when it's done right, the right culture is going to deliver tremendous results. Yeah, what does that mean getting it right? Everybody's trying to get it right. My biggest takeaway today, is it means making data part of the DNA of your organization. And that means making it accessible to the people in your organization that are empowered to make decisions that can drive you revenue, cut costs, speed, access to critical care, whatever the mission is of your organization. Data can create insights and informed decisions that drive value. Okay, let's bring back Sudheesh and wrap things up. Sudheesh please bring us home. >> Thank you, thank you Dave, thank you theCUBE team, and thanks goes to all of our customers and partners who joined us, and thanks to all of you for spending the time with us. I want to do three quick things and then close it off. The first thing is I want to summarize the key takeaways that I had from all four of our distinguished speakers. First, Michelle, I was simply put it, she said it really well, that is be brave and drive. Don't go for a drive along, that is such an important point. Often times, you know that I think that you have to do to make the positive change that you want to see happen. But you wait for someone else to do it, why not you? Why don't you be the one making that change happen? That's the thing that I picked up from Michelle's talk. Cindi talked about finding the importance of finding your voice, taking that chair, whether it's available or not and making sure that your ideas, your voices are heard and if it requires some force then apply that force, make sure your ideas are good. Gustavo talked about the importance of building consensus, not going at things all alone sometimes building the importance of building the courtroom. And that is critical because if you want the changes to last, you want to make sure that the organization is fully behind it. Tom instead of a single take away, what I was inspired by is the fact that a company that is 170 years old, 170 years old, 200 companies and 200 countries they're operating in, and they were able to make the change that is necessary through this difficult time. So in a matter of months, if they could do it, anyone could. The second thing I want to do is to leave you with a takeaway that is I would like you to go to thoughtspot.com/nfl because our team has made an app for NFL on Snowflake. I think you will find this interesting now that you are inspired and excited because of Michelle's talk. And the last thing is, please go to thoughtspot.com/beyond, our global user conferences happening in this December, we would love to have you join us. It's again, virtual, you can join from anywhere, we are expecting anywhere from five to 10,000 people, and we would love to have you join and see what we would have been up to since the last year. We have a lot of amazing things in store for you, our customers, our partners, our collaborators, they will be coming and sharing, you'll be sharing things that you have been working to release something that will come out next year. And also some of the crazy ideas for engineers I've been cooking up. All of those things will be available for you at ThoughtSpot Beyond, thank you, thank you so much.

(speaks in foreign language) >> Narrator: Data is at the heart of transformation and the change every company needs to succeed, but it takes more than new technology. It's about teams, talent, and cultural change. Empowering everyone on the front lines to make decisions, all at the speed of digital. The transformation starts with you. It's time to lead the way, it's time for thought leaders. >> Welcome to Thought Leaders, a digital event brought to you by ThoughtSpot. My name is Dave Vellante. The purpose of this day is to bring industry leaders and experts together to really try and understand the important issues around digital transformation. We have an amazing lineup of speakers and our goal is to provide you with some best practices that you can bring back and apply to your organization. Look, data is plentiful, but insights are not. ThoughtSpot is disrupting analytics by using search and machine intelligence to simplify data analysis, and really empower anyone with fast access to relevant data. But in the last 150 days, we've had more questions than answers. Creating an organization that puts data and insights at their core, requires not only modern technology, but leadership, a mindset and a culture that people often refer to as data-driven. What does that mean? How can we equip our teams with data and fast access to quality information that can turn insights into action. And today, we're going to hear from experienced leaders, who are transforming their organizations with data, insights and creating digital-first cultures. But before we introduce our speakers, I'm joined today by two of my co-hosts from ThoughtSpot. First, Chief Data Strategy Officer for ThoughtSpot is Cindi Hausen. Cindi is an analytics and BI expert with 20 plus years experience and the author of Successful Business Intelligence Unlock The Value of BI and Big Data. Cindi was previously the lead analyst at Gartner for the data and analytics magic quadrant. And early last year, she joined ThoughtSpot to help CDOs and their teams understand how best to leverage analytics and AI for digital transformation. Cindi, great to see you, welcome to the show. >> Thank you, Dave. Nice to join you virtually. >> Now our second cohost and friend of theCUBE is ThoughtSpot CEO Sudheesh Nair. Hello Sudheesh, how are you doing today? >> I am well Dave, it's good to talk to you again. >> It's great to see you. Thanks so much for being here. Now Sudheesh, please share with us why this discussion is so important to your customers and of course, to our audience and what they're going to learn today? (gentle music) >> Thanks, Dave, I wish you were there to introduce me into every room that I walk into because you have such an amazing way of doing it. It makes me feel also good. Look, since we have all been cooped up in our homes, I know that the vendors like us, we have amped up our, you know, sort of effort to reach out to you with invites for events like this. So we are getting way more invites for events like this than ever before. So when we started planning for this, we had three clear goals that we wanted to accomplish. And our first one that when you finish this and walk away, we want to make sure that you don't feel like it was a waste of time. We want to make sure that we value your time, and this is going to be useful. Number two, we want to put you in touch with industry leaders and thought leaders, and generally good people that you want to hang around with long after this event is over. And number three, as we plan through this, you know, we are living through these difficult times, we want an event to be, this event to be more of an uplifting and inspiring event too. Now, the challenge is, how do you do that with the team being change agents? Because change and as much as we romanticize it, it is not one of those uplifting things that everyone wants to do or likes to do. The way I think of it, change is sort of like, if you've ever done bungee jumping. You know, it's like standing on the edges, waiting to make that one more step. You know, all you have to do is take that one step and gravity will do the rest, but that is the hardest step to take. Change requires a lot of courage and when we are talking about data and analytics, which is already like such a hard topic, not necessarily an uplifting and positive conversation, in most businesses it is somewhat scary. Change becomes all the more difficult. Ultimately change requires courage. Courage to to, first of all, challenge the status quo. People sometimes are afraid to challenge the status quo because they are thinking that, "You know, maybe I don't have the power to make the change that the company needs. Sometimes I feel like I don't have the skills." Sometimes they may feel that, I'm probably not the right person to do it. Or sometimes the lack of courage manifest itself as the inability to sort of break the silos that are formed within the organizations, when it comes to data and insights that you talked about. You know, there are people in the company, who are going to hog the data because they know how to manage the data, how to inquire and extract. They know how to speak data, they have the skills to do that, but they are not the group of people who have sort of the knowledge, the experience of the business to ask the right questions off the data. So there is this silo of people with the answers and there is a silo of people with the questions, and there is gap. These sort of silos are standing in the way of making that necessary change that we all I know the business needs, and the last change to sort of bring an external force sometimes. It could be a tool, it could be a platform, it could be a person, it could be a process, but sometimes no matter how big the company is or how small the company is. You may need to bring some external stimuli to start that domino of the positive changes that are necessary. The group of people that we have brought in, the four people, including Cindi, that you will hear from today are really good at practically telling you how to make that step, how to step off that edge, how to trust the rope that you will be safe and you're going to have fun. You will have that exhilarating feeling of jumping for a bungee jump. All four of them are exceptional, but my honor is to introduce Michelle and she's our first speaker. Michelle, I am very happy after watching her presentation and reading her bio, that there are no country vital worldwide competition for cool patents, because she will beat all of us because when her children were small, you know, they were probably into Harry Potter and Disney and she was managing a business and leading change there. And then as her kids grew up and got to that age, where they like football and NFL, guess what? She's the CIO of NFL. What a cool mom. I am extremely excited to see what she's going to talk about. I've seen the slides with a bunch of amazing pictures, I'm looking to see the context behind it. I'm very thrilled to make the acquaintance of Michelle. I'm looking forward to her talk next. Welcome Michelle. It's over to you. (gentle music) >> I'm delighted to be with you all today to talk about thought leadership. And I'm so excited that you asked me to join you because today I get to be a quarterback. I always wanted to be one. This is about as close as I'm ever going to get. So, I want to talk to you about quarterbacking our digital revolution using insights, data and of course, as you said, leadership. First, a little bit about myself, a little background. As I said, I always wanted to play football and this is something that I wanted to do since I was a child but when I grew up, girls didn't get to play football. I'm so happy that that's changing and girls are now doing all kinds of things that they didn't get to do before. Just this past weekend on an NFL field, we had a female coach on two sidelines and a female official on the field. I'm a lifelong fan and student of the game of football. I grew up in the South. You can tell from the accent and in the South football is like a religion and you pick sides. I chose Auburn University working in the athletic department, so I'm testament. Till you can start, a journey can be long. It took me many, many years to make it into professional sports. I graduated in 1987 and my little brother, well not actually not so little, he played offensive line for the Alabama Crimson Tide. And for those of you who know SEC football, you know this is a really big rivalry, and when you choose sides your family is divided. So it's kind of fun for me to always tell the story that my dad knew his kid would make it to the NFL, he just bet on the wrong one. My career has been about bringing people together for memorable moments at some of America's most iconic brands, delivering memories and amazing experiences that delight. From Universal Studios, Disney, to my current position as CIO of the NFL. In this job, I'm very privileged to have the opportunity to work with a team that gets to bring America's game to millions of people around the world. Often, I'm asked to talk about how to create amazing experiences for fans, guests or customers. But today, I really wanted to focus on something different and talk to you about being behind the scenes and backstage. Because behind every event, every game, every awesome moment, is execution. Precise, repeatable execution and most of my career has been behind the scenes doing just that. Assembling teams to execute these plans and the key way that companies operate at these exceptional levels is making good decisions, the right decisions, at the right time and based upon data. So that you can translate the data into intelligence and be a data-driven culture. Using data and intelligence is an important way that world-class companies do differentiate themselves, and it's the lifeblood of collaboration and innovation. Teams that are working on delivering these kind of world class experiences are often seeking out and leveraging next generation technologies and finding new ways to work. I've been fortunate to work across three decades of emerging experiences, which each required emerging technologies to execute. A little bit first about Disney. In '90s I was at Disney leading a project called Destination Disney, which it's a data project. It was a data project, but it was CRM before CRM was even cool and then certainly before anything like a data-driven culture was ever brought up. But way back then we were creating a digital backbone that enabled many technologies for the things that you see today. Like the MagicBand, Disney's Magical Express. My career at Disney began in finance, but Disney was very good about rotating you around. And it was during one of these rotations that I became very passionate about data. I kind of became a pain in the butt to the IT team asking for data, more and more data. And I learned that all of that valuable data was locked up in our systems. All of our point of sales systems, our reservation systems, our operation systems. And so I became a shadow IT person in marketing, ultimately, leading to moving into IT and I haven't looked back since. In the early 2000s, I was at Universal Studio's theme park as their CIO preparing for and launching the Wizarding World of Harry Potter. Bringing one of history's most memorable characters to life required many new technologies and a lot of data. Our data and technologies were embedded into the rides and attractions. I mean, how do you really think a wand selects you at a wand shop. As today at the NFL, I am constantly challenged to do leading edge technologies, using things like sensors, AI, machine learning and all new communication strategies, and using data to drive everything, from player performance, contracts, to where we build new stadiums and hold events. With this year being the most challenging, yet rewarding year in my career at the NFL. In the middle of a global pandemic, the way we are executing on our season is leveraging data from contact tracing devices joined with testing data. Talk about data actually enabling your business. Without it we wouldn't be having a season right now. I'm also on the board of directors of two public companies, where data and collaboration are paramount. First, RingCentral, it's a cloud based unified communications platform and collaboration with video message and phone, all-in-one solution in the cloud and Quotient Technologies, whose product is actually data. The tagline at Quotient is The Result in Knowing. I think that's really important because not all of us are data companies, where your product is actually data, but we should operate more like your product is data. I'd also like to talk to you about four areas of things to think about as thought leaders in your companies. First, just hit on it, is change. how to be a champion and a driver of change. Second, how to use data to drive performance for your company and measure performance of your company. Third, how companies now require intense collaboration to operate and finally, how much of this is accomplished through solid data-driven decisions. First, let's hit on change. I mean, it's evident today more than ever, that we are in an environment of extreme change. I mean, we've all been at this for years and as technologists we've known it, believed it, lived it. And thankfully, for the most part, knock on wood, we were prepared for it. But this year everyone's cheese was moved. All the people in the back rooms, IT, data architects and others were suddenly called to the forefront because a global pandemic has turned out to be the thing that is driving intense change in how people work and analyze their business. On March 13th, we closed our office at the NFL in the middle of preparing for one of our biggest events, our kickoff event, The 2020 Draft. We went from planning a large event in Las Vegas under the bright lights, red carpet stage, to smaller events in club facilities. And then ultimately, to one where everyone coaches, GMs, prospects and even our commissioner were at home in their basements and we only had a few weeks to figure it out. I found myself for the first time, being in the live broadcast event space. Talking about bungee jumping, this is really what it felt like. It was one in which no one felt comfortable because it had not been done before. But leading through this, I stepped up, but it was very scary, it was certainly very risky, but it ended up being also rewarding when we did it. And as a result of this, some things will change forever. Second, managing performance. I mean, data should inform how you're doing and how to get your company to perform at its level, highest level. As an example, the NFL has always measured performance, obviously, and it is one of the purest examples of how performance directly impacts outcome. I mean, you can see performance on the field, you can see points being scored and stats, and you immediately know that impact. Those with the best stats usually win the games. The NFL has always recorded stats. Since the beginning of time here at the NFL a little... This year is our 101st year and athlete's ultimate success as a player has also always been greatly impacted by his stats. But what has changed for us is both how much more we can measure and the immediacy with which it can be measured and I'm sure in your business it's the same. The amount of data you must have has got to have quadrupled recently. And how fast do you need it and how quickly you need to analyze it is so important. And it's very important to break the silos between the keys to the data and the use of the data. Our next generation stats platform is taking data to the next level. It's powered by Amazon Web Services and we gather this data, real-time from sensors that are on players' bodies. We gather it in real time, analyze it, display it online and on broadcast. And of course, it's used to prepare week to week in addition to what is a normal coaching plan would be. We can now analyze, visualize, route patterns, speed, match-ups, et cetera, so much faster than ever before. We're continuing to roll out sensors too, that will gather more and more information about a player's performance as it relates to their health and safety. The third trend is really, I think it's a big part of what we're feeling today and that is intense collaboration. And just for sort of historical purposes, it's important to think about, for those of you that are IT professionals and developers, you know, more than 10 years ago agile practices began sweeping companies. Where small teams would work together rapidly in a very flexible, adaptive and innovative way and it proved to be transformational. However today, of course that is no longer just small teams, the next big wave of change and we've seen it through this pandemic, is that it's the whole enterprise that must collaborate and be agile. If I look back on my career, when I was at Disney, we owned everything 100%. We made a decision, we implemented it. We were a collaborative culture but it was much easier to push change because you own the whole decision. If there was buy-in from the top down, you got the people from the bottom up to do it and you executed. At Universal, we were a joint venture. Our attractions and entertainment was licensed. Our hotels were owned and managed by other third parties, so influence and collaboration, and how to share across companies became very important. And now here I am at the NFL an even the bigger ecosystem. We have 32 clubs that are all separate businesses, 31 different stadiums that are owned by a variety of people. We have licensees, we have sponsors, we have broadcast partners. So it seems that as my career has evolved, centralized control has gotten less and less and has been replaced by intense collaboration, not only within your own company but across companies. The ability to work in a collaborative way across businesses and even other companies, that has been a big key to my success in my career. I believe this whole vertical integration and big top-down decision-making is going by the wayside in favor of ecosystems that require cooperation, yet competition to co-exist. I mean, the NFL is a great example of what we call co-oppetition, which is cooperation and competition. We're in competition with each other, but we cooperate to make the company the best it can be. And at the heart of these items really are data-driven decisions and culture. Data on its own isn't good enough. You must be able to turn it to insights. Partnerships between technology teams who usually hold the keys to the raw data and business units, who have the knowledge to build the right decision models is key. If you're not already involved in this linkage, you should be, data mining isn't new for sure. The availability of data is quadrupling and it's everywhere. How do you know what to even look at? How do you know where to begin? How do you know what questions to ask? It's by using the tools that are available for visualization and analytics and knitting together strategies of the company. So it begins with, first of all, making sure you do understand the strategy of the company. So in closing, just to wrap up a bit, many of you joined today, looking for thought leadership on how to be a change agent, a change champion, and how to lead through transformation. Some final thoughts are be brave and drive. Don't do the ride along program, it's very important to drive. Driving can be high risk, but it's also high reward. Embracing the uncertainty of what will happen is how you become brave. Get more and more comfortable with uncertainty, be calm and let data be your map on your journey. Thanks. >> Michelle, thank you so much. So you and I share a love of data and a love of football. You said you want to be the quarterback. I'm more an a line person. >> Well, then I can't do my job without you. >> Great and I'm getting the feeling now, you know, Sudheesh is talking about bungee jumping. My vote is when we're past this pandemic, we both take him to the Delaware Water Gap and we do the cliff jumping. >> Oh that sounds good, I'll watch your watch. >> Yeah, you'll watch, okay. So Michelle, you have so many stakeholders, when you're trying to prioritize the different voices you have the players, you have the owners, you have the league, as you mentioned, the broadcasters, your partners here and football mamas like myself. How do you prioritize when there are so many different stakeholders that you need to satisfy? >> I think balancing across stakeholders starts with aligning on a mission and if you spend a lot of time understanding where everyone's coming from, and you can find the common thread that ties them all together. You sort of do get them to naturally prioritize their work and I think that's very important. So for us at the NFL and even at Disney, it was our core values and our core purpose is so well known and when anything challenges that, we're able to sort of lay that out. But as a change agent, you have to be very empathetic, and I would say empathy is probably your strongest skill if you're a change agent and that means listening to every single stakeholder. Even when they're yelling at you, even when they're telling you your technology doesn't work and you know that it's user error, or even when someone is just emotional about what's happening to them and that they're not comfortable with it. So I think being empathetic, and having a mission, and understanding it is sort of how I prioritize and balance. >> Yeah, empathy, a very popular word this year. I can imagine those coaches and owners yelling, so thank you for your leadership here. So Michelle, I look forward to discussing this more with our other customers and disruptors joining us in a little bit. >> (gentle music) So we're going to take a hard pivot now and go from football to Chernobyl. Chernobyl, what went wrong? 1986, as the reactors were melting down, they had the data to say, "This is going to be catastrophic," and yet the culture said, "No, we're perfect, hide it. Don't dare tell anyone." Which meant they went ahead and had celebrations in Kiev. Even though that increased the exposure, additional thousands getting cancer and 20,000 years before the ground around there can even be inhabited again. This is how powerful and detrimental a negative culture, a culture that is unable to confront the brutal facts that hides data. This is what we have to contend with and this is why I want you to focus on having, fostering a data-driven culture. I don't want you to be a laggard. I want you to be a leader in using data to drive your digital transformation. So I'll talk about culture and technology, is it really two sides of the same coin? Real-world impacts and then some best practices you can use to disrupt and innovate your culture. Now, oftentimes I would talk about culture and I talk about technology. And recently a CDO said to me, "You know, Cindi, I actually think this is two sides of the same coin, one reflects the other." What do you think? Let me walk you through this. So let's take a laggard. What does the technology look like? Is it based on 1990s BI and reporting, largely parametrized reports, on-premises data warehouses, or not even that operational reports. At best one enterprise data warehouse, very slow moving and collaboration is only email. What does that culture tell you? Maybe there's a lack of leadership to change, to do the hard work that Sudheesh referred to, or is there also a culture of fear, afraid of failure, resistance to change, complacency. And sometimes that complacency, it's not because people are lazy. It's because they've been so beaten down every time a new idea is presented. It's like, "No, we're measured on least to serve." So politics and distrust, whether it's between business and IT or individual stakeholders is the norm, so data is hoarded. Let's contrast that with the leader, a data and analytics leader, what does their technology look like? Augmented analytics, search and AI driven insights, not on-premises but in the cloud and maybe multiple clouds. And the data is not in one place but it's in a data lake and in a data warehouse, a logical data warehouse. The collaboration is via newer methods, whether it's Slack or Teams, allowing for that real-time decisioning or investigating a particular data point. So what is the culture in the leaders? It's transparent and trust. There is a trust that data will not be used to punish, that there is an ability to confront the bad news. It's innovation, valuing innovation in pursuit of the company goals. Whether it's the best fan experience and player safety in the NFL or best serving your customers, it's innovative and collaborative. There's none of this, "Oh, well, I didn't invent that. I'm not going to look at that." There's still pride of ownership, but it's collaborating to get to a better place faster. And people feel empowered to present new ideas, to fail fast and they're energized knowing that they're using the best technology and innovating at the pace that business requires. So data is democratized and democratized, not just for power users or analysts, but really at the point of impact, what we like to call the new decision-makers or really the frontline workers. So Harvard Business Review partnered with us to develop this study to say, "Just how important is this? We've been working at BI and analytics as an industry for more than 20 years, why is it not at the front lines? Whether it's a doctor, a nurse, a coach, a supply chain manager, a warehouse manager, a financial services advisor." 87% said they would be more successful if frontline workers were empowered with data-driven insights, but they recognize they need new technology to be able to do that. It's not about learning hard tools. The sad reality only 20% of organizations are actually doing this. These are the data-driven leaders. So this is the culture and technology, how did we get here? It's because state-of-the-art keeps changing. So the first generation BI and analytics platforms were deployed on-premises, on small datasets, really just taking data out of ERP systems that were also on-premises and state-of-the-art was maybe getting a management report, an operational report. Over time, visual based data discovery vendors disrupted these traditional BI vendors, empowering now analysts to create visualizations with the flexibility on a desktop, sometimes larger data, sometimes coming from a data warehouse. The current state-of-the-art though, Gartner calls it augmented analytics. At ThoughtSpot, we call it search and AI driven analytics, and this was pioneered for large scale data sets, whether it's on-premises or leveraging the cloud data warehouses. And I think this is an important point, oftentimes you, the data and analytics leaders, will look at these two components separately. But you have to look at the BI and analytics tier in lock-step with your data architectures to really get to the granular insights and to leverage the capabilities of AI. Now, if you've never seen ThoughtSpot, I'll just show you what this looks like. Instead of somebody hard coding a report, it's typing in search keywords and very robust keywords contains rank, top, bottom, getting to a visual visualization that then can be pinned to an existing pin board that might also contain insights generated by an AI engine. So it's easy enough for that new decision maker, the business user, the non-analyst to create themselves. Modernizing the data and analytics portfolio is hard because the pace of change has accelerated. You used to be able to create an investment, place a bet for maybe 10 years. A few years ago, that time horizon was five years. Now, it's maybe three years and the time to maturity has also accelerated. So you have these different components, the search and AI tier, the data science tier, data preparation and virtualization but I would also say, equally important is the cloud data warehouse. And pay attention to how well these analytics tools can unlock the value in these cloud data warehouses. So ThoughtSpot was the first to market with search and AI driven insights. Competitors have followed suit, but be careful, if you look at products like Power BI or SAP analytics cloud, they might demo well, but do they let you get to all the data without moving it in products like Snowflake, Amazon Redshift, or Azure Synapse, or Google BigQuery, they do not. They require you to move it into a smaller in-memory engine. So it's important how well these new products inter-operate. The pace of change, its acceleration, Gartner recently predicted that by 2022, 65% of analytical queries will be generated using search or NLP or even AI and that is roughly three times the prediction they had just a couple of years ago. So let's talk about the real world impact of culture and if you've read any of my books or used any of the maturity models out there, whether the Gartner IT Score that I worked on or the Data Warehousing Institute also has a maturity model. We talk about these five pillars to really become data-driven. As Michelle spoke about, it's focusing on the business outcomes, leveraging all the data, including new data sources, it's the talent, the people, the technology and also the processes. And often when I would talk about the people in the talent, I would lump the culture as part of that. But in the last year, as I've traveled the world and done these digital events for thought leaders. You have told me now culture is absolutely so important, and so we've pulled it out as a separate pillar. And in fact, in polls that we've done in these events, look at how much more important culture is as a barrier to becoming data-driven. It's three times as important as any of these other pillars. That's how critical it is. And let's take an example of where you can have great data, but if you don't have the right culture, there's devastating impacts. And I will say I have been a loyal customer of Wells Fargo for more than 20 years, but look at what happened in the face of negative news with data. It said, "Hey, we're not doing good cross-selling, customers do not have both a checking account and a credit card and a savings account and a mortgage." They opened fake accounts facing billions in fines, change in leadership that even the CEO attributed to a toxic sales culture and they're trying to fix this, but even recently there's been additional employee backlash saying the culture has not changed. Let's contrast that with some positive examples. Medtronic, a worldwide company in 150 countries around the world. They may not be a household name to you, but if you have a loved one or yourself, you have a pacemaker, spinal implant, diabetes, you know this brand. And at the start of COVID when they knew their business would be slowing down, because hospitals would only be able to take care of COVID patients. They took the bold move of making their IP for ventilators publicly available. That is the power of a positive culture. Or Verizon, a major telecom organization looking at late payments of their customers and even though the U.S. Federal Government said, "Well, you can't turn them off." They said, "We'll extend that even beyond the mandated guidelines," and facing a slow down in the business because of the tough economy, They said, "You know what? We will spend the time upskilling our people, giving them the time to learn more about the future of work, the skills and data and analytics for 20,000 of their employees rather than furloughing them. That is the power of a positive culture. So how can you transform your culture to the best in class? I'll give you three suggestions. Bring in a change agent, identify the relevance or I like to call it WIIFM and organize for collaboration. So the CDO, whatever your title is, Chief Analytics Officer, Chief Digital Officer, you are the most important change agent. And this is where you will hear that oftentimes a change agent has to come from outside the organization. So this is where, for example, in Europe you have the CDO of Just Eat, a takeout food delivery organization coming from the airline industry or in Australia, National Australian Bank taking a CDO within the same sector from TD Bank going to NAB. So these change agents come in, disrupt. It's a hard job. As one of you said to me, it often feels like. I make one step forward and I get knocked down again, I get pushed back. It is not for the faint of heart, but it's the most important part of your job. The other thing I'll talk about is WIIFM What's In It For Me? And this is really about understanding the motivation, the relevance that data has for everyone on the frontline, as well as those analysts, as well as the executives. So, if we're talking about players in the NFL, they want to perform better and they want to stay safe. That is why data matters to them. If we're talking about financial services, this may be a wealth management advisor. Okay, we could say commissions, but it's really helping people have their dreams come true, whether it's putting their children through college or being able to retire without having to work multiple jobs still into your 70s or 80s. For the teachers, teachers you ask them about data. They'll say, "We don't need that, I care about the student." So if you can use data to help a student perform better, that is WIIFM and sometimes we spend so much time talking the technology, we forget, what is the value we're trying to deliver with this? And we forget the impact on the people that it does require change. In fact, the Harvard Business Review study found that 44% said lack of change management is the biggest barrier to leveraging both new technology, but also being empowered to act on those data-driven insights. The third point, organize for collaboration. This does require diversity of thought, but also bringing the technology, the data and the business people together. Now there's not a single one size fits all model for data and analytics. At one point in time, even having a BICC, a BI competency center was considered state of the art. Now for the biggest impact, what I recommend is that you have a federated model centralized for economies of scale. That could be the common data, but then embed these evangelists, these analysts of the future within every business unit, every functional domain. And as you see this top bar, all models are possible, but the hybrid model has the most impact, the most leaders. So as we look ahead to the months ahead, to the year ahead, an exciting time because data is helping organizations better navigate a tough economy, lock in the customer loyalty and I look forward to seeing how you foster that culture that's collaborative with empathy and bring the best of technology, leveraging the cloud, all your data. So thank you for joining us at Thought Leaders. And next, I'm pleased to introduce our first change agent, Tom Mazzaferro Chief Data Officer of Western Union and before joining Western Union, Tom made his Mark at HSBC and JP Morgan Chase spearheading digital innovation in technology, operations, risk compliance and retail banking. Tom, thank you so much for joining us today. (gentle music) >> Very happy to be here and looking forward to talking to all of you today. So as we look to move organizations to a data-driven capability into the future, there is a lot that needs to be done on the data side, but also how does data connect and enable different business teams and the technology teams into the future? As we look across our data ecosystems and our platforms, and how we modernize that to the cloud in the future, it all needs to basically work together, right? To really be able to drive an organization from a data standpoint, into the future. That includes being able to have the right information with the right quality of data, at the right time to drive informed business decisions, to drive the business forward. As part of that, we actually have partnered with ThoughtSpot to actually bring in the technology to help us drive that. As part of that partnership and it's how we've looked to integrate it into our overall business as a whole. We've looked at, how do we make sure that our business and our professional lives, right? Are enabled in the same ways as our personal lives. So for example, in your personal lives, when you want to go and find something out, what do you do? You go onto google.com or you go onto Bing or you go onto Yahoo and you search for what you want, search to find an answer. ThoughtSpot for us is the same thing, but in the business world. So using ThoughtSpot and other AI capability is it's allowed us to actually enable our overall business teams in our company to actually have our information at our fingertips. So rather than having to go and talk to someone, or an engineer to go pull information or pull data. We actually can have the end users or the business executives, right. Search for what they need, what they want, at the exact time that they actually need it, to go and drive the business forward. This is truly one of those transformational things that we've put in place. On top of that, we are on a journey to modernize our larger ecosystem as a whole. That includes modernizing our underlying data warehouses, our technology, our... The local environments and as we move that, we've actually picked two of our cloud providers going to AWS and to GCP. We've also adopted Snowflake to really drive and to organize our information and our data, then drive these new solutions and capabilities forward. So a big portion of it though is culture. So how do we engage with the business teams and bring the IT teams together, to really help to drive these holistic end-to-end solutions and capabilities, to really support the actual business into the future. That's one of the keys here, as we look to modernize and to really enhance our organizations to become data-driven. This is the key. If you can really start to provide answers to business questions before they're even being asked and to predict based upon different economic trends or different trends in your business, what decisions need to be made and actually provide those answers to the business teams before they're even asking for it. That is really becoming a data-driven organization and as part of that, it really then enables the business to act quickly and take advantage of opportunities as they come in based upon industries, based upon markets, based upon products, solutions or partnerships into the future. These are really some of the keys that become crucial as you move forward, right, into this new age, Especially with COVID. With COVID now taking place across the world, right? Many of these markets, many of these digital transformations are celebrating and are changing rapidly to accommodate and to support customers in these very difficult times. As part of that, you need to make sure you have the right underlying foundation, ecosystems and solutions to really drive those capabilities and those solutions forward. As we go through this journey, both in my career but also each of your careers into the future, right? It also needs to evolve, right? Technology has changed so drastically in the last 10 years, and that change is only accelerating. So as part of that, you have to make sure that you stay up to speed, up to date with new technology changes, both on the platform standpoint, tools, but also what do our customers want, what do our customers need and how do we then service them with our information, with our data, with our platform, and with our products and our services to meet those needs and to really support and service those customers into the future. This is all around becoming a more data-driven organization, such as how do you use your data to support your current business lines, but how do you actually use your information and your data to actually better support your customers, better support your business, better support your employees, your operations teams and so forth. And really creating that full integration in that ecosystem is really when you start to get large dividends from these investments into the future. With that being said, I hope you enjoyed the segment on how to become and how to drive a data-driven organization, and looking forward to talking to you again soon. Thank you. >> Tom, that was great. Thanks so much and now going to have to drag on you for a second. As a change agent you've come in, disrupted and how long have you been at Western Union? >> Only nine months, so just started this year, but there have been some great opportunities to integrate changes and we have a lot more to go, but we're really driving things forward in partnership with our business teams and our colleagues to support those customers going forward. >> Tom, thank you so much. That was wonderful. And now, I'm excited to introduce you to Gustavo Canton, a change agent that I've had the pleasure of working with meeting in Europe and he is a serial change agent. Most recently with Schneider Electric but even going back to Sam's Clubs. Gustavo, welcome. (gentle music) >> So, hey everyone, my name is Gustavo Canton and thank you so much, Cindi, for the intro. As you mentioned, doing transformations is, you know, a high reward situation. I have been part of many transformations and I have led many transformations. And, what I can tell you is that it's really hard to predict the future, but if you have a North Star and you know where you're going, the one thing that I want you to take away from this discussion today is that you need to be bold to evolve. And so, in today, I'm going to be talking about culture and data, and I'm going to break this down in four areas. How do we get started, barriers or opportunities as I see it, the value of AI and also, how you communicate. Especially now in the workforce of today with so many different generations, you need to make sure that you are communicating in ways that are non-traditional sometimes. And so, how do we get started? So, I think the answer to that is you have to start for you yourself as a leader and stay tuned. And by that, I mean, you need to understand, not only what is happening in your function or your field, but you have to be very in tune what is happening in society socioeconomically speaking, wellbeing. You know, the common example is a great example and for me personally, it's an opportunity because the number one core value that I have is wellbeing. I believe that for human potential for customers and communities to grow, wellbeing should be at the center of every decision. And as somebody mentioned, it's great to be, you know, stay in tune and have the skillset and the courage. But for me personally, to be honest, to have this courage is not about not being afraid. You're always afraid when you're making big changes and you're swimming upstream, but what gives me the courage is the empathy part. Like I think empathy is a huge component because every time I go into an organization or a function, I try to listen very attentively to the needs of the business and what the leaders are trying to do. But I do it thinking about the mission of, how do I make change for the bigger workforce or the bigger good despite the fact that this might have perhaps implication for my own self interest in my career. Right? Because you have to have that courage sometimes to make choices that are not well seen, politically speaking, but are the right thing to do and you have to push through it. So the bottom line for me is that, I don't think we're they're transforming fast enough. And the reality is, I speak with a lot of leaders and we have seen stories in the past and what they show is that, if you look at the four main barriers that are basically keeping us behind budget, inability to act, cultural issues, politics and lack of alignment, those are the top four. But the interesting thing is that as Cindi has mentioned, these topic about culture is actually gaining more and more traction. And in 2018, there was a story from HBR and it was about 45%. I believe today, it's about 55%, 60% of respondents say that this is the main area that we need to focus on. So again, for all those leaders and all the executives who understand and are aware that we need to transform, commit to the transformation and set a deadline to say, "Hey, in two years we're going to make this happen. What do we need to do, to empower and enable these change agents to make it happen? You need to make the tough choices. And so to me, when I speak about being bold is about making the right choices now. So, I'll give you examples of some of the roadblocks that I went through as I've been doing transformations, most recently, as Cindi mentioned in Schneider. There are three main areas, legacy mindset and what that means is that, we've been doing this in a specific way for a long time and here is how we have been successful. What worked in the past is not going to work now. The opportunity there is that there is a lot of leaders, who have a digital mindset and they're up and coming leaders that are perhaps not yet fully developed. We need to mentor those leaders and take bets on some of these talents, including young talent. We cannot be thinking in the past and just wait for people, you know, three to five years for them to develop because the world is going in a way that is super-fast. The second area and this is specifically to implementation of AI. It's very interesting to me because just the example that I have with ThoughtSpot, right? We went on implementation and a lot of the way the IT team functions or the leaders look at technology, they look at it from the prism of the prior or success criteria for the traditional BIs, and that's not going to work. Again, the opportunity here is that you need to redefine what success look like. In my case, I want the user experience of our workforce to be the same user experience you have at home. It's a very simple concept and so we need to think about, how do we gain that user experience with these augmented analytics tools and then work backwards to have the right talent, processes, and technology to enable that. And finally and obviously with COVID, a lot of pressure in organizations and companies to do more with less. And the solution that most leaders I see are taking is to just minimize costs sometimes and cut budget. We have to do the opposite. We have to actually invest on growth areas, but do it by business question. Don't do it by function. If you actually invest in these kind of solutions, if you actually invest on developing your talent and your leadership to see more digitally, if you actually invest on fixing your data platform, it's not just an incremental cost. It's actually this investment is going to offset all those hidden costs and inefficiencies that you have on your system, because people are doing a lot of work and working very hard but it's not efficient and it's not working in the way that you might want to work. So there is a lot of opportunity there and just to put in terms of perspective, there have been some studies in the past about, you know, how do we kind of measure the impact of data? And obviously, this is going to vary by organization maturity, there's going to be a lot of factors. I've been in companies who have very clean, good data to work with and I've been with companies that we have to start basically from scratch. So it all depends on your maturity level. But in this study, what I think is interesting is they try to put a tagline or a tag price to what is the cost of incomplete data. So in this case, it's about 10 times as much to complete a unit of work when you have data that is flawed as opposed to having perfect data. So let me put that just in perspective, just as an example, right? Imagine you are trying to do something and you have to do 100 things in a project, and each time you do something, it's going to cost you a dollar. So if you have perfect data, the total cost of that project might be $100. But now let's say you have 80% perfect data and 20% flawed data. By using this assumption that flawed data is 10 times as costly as perfect data, your total costs now becomes $280 as opposed to $100. This just for you to really think about as a CIO, CTO, you know CHRO, CEO, "Are we really paying attention and really closing the gaps that we have on our data infrastructure?" If we don't do that, it's hard sometimes to see the snowball effect or to measure the overall impact, but as you can tell, the price tag goes up very, very quickly. So now, if I were to say, how do I communicate this or how do I break through some of these challenges or some of these barriers, right? I think the key is, I am in analytics, I know statistics obviously and love modeling, and, you know, data and optimization theory, and all that stuff. That's what I came to analytics, but now as a leader and as a change agent, I need to speak about value and in this case, for example, for Schneider. There was this tagline, make the most of your energy. So the number one thing that they were asking from the analytics team was actually efficiency, which to me was very interesting. But once I understood that, I understood what kind of language to use, how to connect it to the overall strategy and basically, how to bring in the right leaders because you need to, you know, focus on the leaders that you're going to make the most progress, you know. Again, low effort, high value. You need to make sure you centralize all the data as you can, you need to bring in some kind of augmented analytics, you know, solution. And finally, you need to make it super-simple for the, you know, in this case, I was working with the HR teams and other areas, so they can have access to one portal. They don't have to be confused and looking for 10 different places to find information. I think if you can actually have those four foundational pillars, obviously under the guise of having a data-driven culture, that's when you can actually make the impact. So in our case, it was about three years total transformation, but it was two years for this component of augmented analytics. It took about two years to talk to, you know, IT, get leadership support, find the budgeting, you know, get everybody on board, make sure the success criteria was correct. And we call this initiative, the people analytics portal. It was actually launched in July of this year and we were very excited and the audience was very excited to do this. In this case, we did our pilot in North America for many, many, many factors but one thing that is really important is as you bring along your audience on this, you know. You're going from Excel, you know, in some cases or Tableu to other tools like, you know, ThoughtSpot. You need to really explain them what is the difference and how this tool can truly replace some of the spreadsheets or some of the views that you might have on these other kinds of tools. Again, Tableau, I think it's a really good tool. There are other many tools that you might have in your toolkit but in my case, personally, I feel that you need to have one portal. Going back to Cindi's points, that really truly enable the end user. And I feel that this is the right solution for us, right? And I will show you some of the findings that we had in the pilot in the last two months. So this was a huge victory and I will tell you why, because it took a lot of effort for us to get to this stage and like I said, it's been years for us to kind of lay the foundation, get the leadership, initiating culture so people can understand, why you truly need to invest on augmented analytics. And so, what I'm showing here is an example of how do we use basically, you know, a tool to capturing video, the qualitative findings that we had, plus the quantitative insights that we have. So in this case, our preliminary results based on our ambition for three main metrics. Hours saved, user experience and adoption. So for hours saved, our ambition was to have 10 hours per week for employee to save on average. User experience, our ambition was 4.5 and adoption 80%. In just two months, two months and a half of the pilot, we were able to achieve five hours per week per employee savings, a user experience for 4.3 out of five and adoption of 60%. Really, really amazing work. But again, it takes a lot of collaboration for us to get to the stage from IT, legal, communications, obviously the operations things and the users. In HR safety and other areas that might be basically stakeholders in this whole process. So just to summarize, this kind of effort takes a lot of energy. You are a change agent, you need to have courage to make this decision and understand that, I feel that in this day and age with all this disruption happening, we don't have a choice. We have to take the risk, right? And in this case, I feel a lot of satisfaction in how we were able to gain all these great resource for this organization and that give me the confident to know that the work has been done and we are now in a different stage for the organization. And so for me, it's just to say, thank you for everybody who has belief, obviously in our vision, everybody who has belief in, you know, the work that we were trying to do and to make the life of our, you know, workforce or customers and community better. As you can tell, there is a lot of effort, there is a lot of collaboration that is needed to do something like this. In the end, I feel very satisfied with the accomplishments of this transformation and I just want to tell for you, if you are going right now in a moment that you feel that you have to swim upstream, you know, work with mentors, work with people in the industry that can help you out and guide you on this kind of transformation. It's not easy to do, it's high effort, but it's well worth it. And with that said, I hope you are well and it's been a pleasure talking to you. Talk to you soon. Take care. >> Thank you, Gustavo. That was amazing. All right, let's go to the panel. (light music) Now I think we can all agree how valuable it is to hear from practitioners and I want to thank the panel for sharing their knowledge with the community. Now one common challenge that I heard you all talk about was bringing your leadership and your teams along on the journey with you. We talk about this all the time and it is critical to have support from the top. Why? Because it directs the middle and then it enables bottoms up innovation effects from the cultural transformation that you guys all talked about. It seems like another common theme we heard is that you all prioritize database decision making in your organizations. And you combine two of your most valuable assets to do that and create leverage, employees on the front lines, and of course the data. Now as as you rightly pointed out, Tom, the pandemic has accelerated the need for really leaning into this. You know, the old saying, if it ain't broke, don't fix it, well COVID has broken everything and it's great to hear from our experts, you know, how to move forward, so let's get right into it. So Gustavo, let's start with you. If I'm an aspiring change agent and let's say I'm a budding data leader, what do I need to start doing? What habits do I need to create for long-lasting success? >> I think curiosity is very important. You need to be, like I said, in tune to what is happening, not only in your specific field, like I have a passion for analytics, I've been doing it for 50 years plus, but I think you need to understand wellbeing of the areas across not only a specific business. As you know, I come from, you know, Sam's Club, Walmart retail. I've been in energy management, technology. So you have to try to push yourself and basically go out of your comfort zone. I mean, if you are staying in your comfort zone and you want to just continuous improvement, that's just going to take you so far. What you have to do is, and that's what I try to do, is I try to go into areas, businesses and transformations, that make me, you know, stretch and develop as a leader. That's what I'm looking to do, so I can help transform the functions, organizations, and do the change management, the essential mindset that's required for this kind of effort. >> Well, thank you for that. That is inspiring and Cindi you love data and the data is pretty clear that diversity is a good business, but I wonder if you can, you know, add your perspectives to this conversation? >> Yeah, so Michelle has a new fan here because she has found her voice. I'm still working on finding mine and it's interesting because I was raised by my dad, a single dad, so he did teach me how to work in a predominantly male environment, but why I think diversity matters more now than ever before and this is by gender, by race, by age, by just different ways of working and thinking, is because as we automate things with AI, if we do not have diverse teams looking at the data, and the models, and how they're applied, we risk having bias at scale. So this is why I think I don't care what type of minority you are, finding your voice, having a seat at the table and just believing in the impact of your work has never been more important and as Michelle said, more possible. >> Great perspectives, thank you. Tom, I want to go to you. So, I mean, I feel like everybody in our businesses is in some way, shape, or form become a COVID expert, but what's been the impact of the pandemic on your organization's digital transformation plans? >> We've seen a massive growth, actually, in our digital business over the last 12 months really, even acceleration, right, once COVID hit. We really saw that in the 200 countries and territories that we operate in today and service our customers in today, that there's been a huge need, right, to send money to support family, to support friends, and to support loved ones across the world. And as part of that we are very honored to be able to support those customers that, across all the centers today, but as part of the acceleration, we need to make sure that we have the right architecture and the right platforms to basically scale, right? To basically support and provide the right kind of security for our customers going forward. So as part of that, we did do some pivots and we did accelerate some of our plans on digital to help support that overall growth coming in and to support our customers going forward, because during these times, during this pandemic, right, this is the most important time and we need to support those that we love and those that we care about. And doing that some of those ways is actually by sending money to them, support them financially. And that's where really our products and our services come into play that, you know, and really support those families. So, it was really a great opportunity for us to really support and really bring some of our products to the next level and supporting our business going forward. >> Awesome, thank you. Now, I want to come back to Gustavo. Tom, I'd love for you to chime in too. Did you guys ever think like you were pushing the envelope too much in doing things with data or the technology that it was just maybe too bold, maybe you felt like at some point it was failing, or you're pushing your people too hard? Can you share that experience and how you got through it? >> Yeah, the way I look at it is, you know, again, whenever I go to an organization, I ask the question, "Hey, how fast you would like to conform?" And, you know, based on the agreements on the leadership and the vision that we want to take place, I take decisions and I collaborate in a specific way. Now, in the case of COVID, for example, right, it forces us to remove silos and collaborate in a faster way. So to me, it was an opportunity to actually integrate with other areas and drive decisions faster, but make no mistake about it, when you are doing a transformation, you are obviously trying to do things faster than sometimes people are comfortable doing, and you need to be okay with that. Sometimes you need to be okay with tension or you need to be okay, you know, debating points or making repetitive business cases until people connect with the decision because you understand and you are seeing that, "Hey, the CEO is making a one, two year, you know, efficiency goal. The only way for us to really do more with less is for us to continue this path. We can not just stay with the status quo, we need to find a way to accelerate the transformation." That's the way I see it. >> How about Utah, we were talking earlier with Sudheesh and Cindi about that bungee jumping moment. What can you share? >> Yeah, you know, I think you hit upon it. Right now, the pace of change will be the slowest pace that you see for the rest of your career. So as part of that, right, this is what I tell my team, is that you need to be, you need to feel comfortable being uncomfortable. Meaning that we have to be able to basically scale, right? Expand and support the ever changing needs in the marketplace and industry and our customers today, and that pace of change that's happening, right? And what customers are asking for and the competition in the marketplace, it's only going to accelerate. So as part of that, you know, as you look at how you're operating today in your current business model, right? Things are only going to get faster. So you have to plan and to align and to drive the actual transformation, so that you can scale even faster into the future. So it's part of that, that's what we're putting in place here, right? It's how do we create that underlying framework and foundation that allows the organization to basically continue to scale and evolve into the future? >> Yeah, we're definitely out of our comfort zones, but we're getting comfortable with it. So Cindi, last question, you've worked with hundreds of organizations and I got to believe that, you know, some of the advice you gave when you were at Gartner, which was pre-COVID, maybe sometimes clients didn't always act on it. You know, not my watch or for whatever, variety of reasons, but it's being forced on them now. But knowing what you know now that, you know, we're all in this isolation economy, how would you say that advice has changed? Has it changed? What's your number one action and recommendation today? >> Yeah, well first off, Tom, just freaked me out. What do you mean, this is the slowest ever? Even six months ago I was saying the pace of change in data and analytics is frenetic. So, but I think you're right, Tom, the business and the technology together is forcing this change. Now, Dave, to answer your question, I would say the one bit of advice, maybe I was a little more very aware of the power in politics and how to bring people along in a way that they are comfortable and now I think it's, you know what, you can't get comfortable. In fact, we know that the organizations that were already in the cloud have been able to respond and pivot faster. So, if you really want to survive, as Tom and Gustavo said, get used to being uncomfortable. The power and politics are going to happen, break the rules, get used to that and be bold. Do not be afraid to tell somebody they're wrong and they're not moving fast enough. I do think you have to do that with empathy, as Michelle said and Gustavo, I think that's one of the key words today besides the bungee jumping. So I want to know where Sudheesh is going to go bungee jumping. (all chuckling) >> Guys, fantastic discussion, really. Thanks again to all the panelists and the guests, it was really a pleasure speaking with you today. Really, virtually all of the leaders that I've spoken to in theCUBE program recently, they tell me that the pandemic is accelerating so many things. Whether it's new ways to work, we heard about new security models and obviously the need for cloud. I mean, all of these things are driving true enterprise-wide digital transformation, not just as I said before, lip service. You know, sometimes we minimize the importance and the challenge of building culture and in making this transformation possible. But when it's done right, the right culture is going to deliver tournament results. You know, what does that mean? Getting it right. Everybody's trying to get it right. My biggest takeaway today is it means making data part of the DNA of your organization. And that means making it accessible to the people in your organization that are empowered to make decisions, decisions that can drive new revenue, cut costs, speed access to critical care, whatever the mission is of your organization, data can create insights and informed decisions that drive value. Okay, let's bring back Sudheesh and wrap things up. Sudheesh, please bring us home. >> Thank you, thank you, Dave. Thank you, theCUBE team, and thanks goes to all of our customers and partners who joined us, and thanks to all of you for spending the time with us. I want to do three quick things and then close it off. The first thing is I want to summarize the key takeaways that I heard from all four of our distinguished speakers. First, Michelle, I will simply put it, she said it really well. That is be brave and drive, don't go for a drive alone. That is such an important point. Often times, you know the right thing that you have to do to make the positive change that you want to see happen, but you wait for someone else to do it, not just, why not you? Why don't you be the one making that change happen? That's the thing that I picked up from Michelle's talk. Cindi talked about finding, the importance of finding your voice. Taking that chair, whether it's available or not, and making sure that your ideas, your voice is heard and if it requires some force, then apply that force. Make sure your ideas are heard. Gustavo talked about the importance of building consensus, not going at things all alone sometimes. The importance of building the quorum, and that is critical because if you want the changes to last, you want to make sure that the organization is fully behind it. Tom, instead of a single takeaway, what I was inspired by is the fact that a company that is 170 years old, 170 years old, 200 companies and 200 countries they're operating in and they were able to make the change that is necessary through this difficult time in a matter of months. If they could do it, anyone could. The second thing I want to do is to leave you with a takeaway, that is I would like you to go to ThoughtSpot.com/nfl because our team has made an app for NFL on Snowflake. I think you will find this interesting now that you are inspired and excited because of Michelle's talk. And the last thing is, please go to ThoughtSpot.com/beyond. Our global user conference is happening in this December. We would love to have you join us, it's, again, virtual, you can join from anywhere. We are expecting anywhere from five to 10,000 people and we would love to have you join and see what we've been up to since last year. We have a lot of amazing things in store for you, our customers, our partners, our collaborators, they will be coming and sharing. We'll be sharing things that we have been working to release, something that will come out next year. And also some of the crazy ideas our engineers have been cooking up. All of those things will be available for you at ThoughtSpot Beyond. Thank you, thank you so much.

>> Data is at the heart of transformation and the change every company needs to succeed, but it takes more than new technology. It's about teams, talent and cultural change. Empowering everyone on the front lines to make decisions all at the speed of digital. The transformation starts with you. It's time to lead the way it's time for Thought leaders. >> Welcome to "Thought Leaders" a digital event brought to you by ThoughtSpot. My name is Dave Vellante. The purpose of this day is to bring industry leaders and experts together to really try and understand the important issues around digital transformation. We have an amazing lineup of speakers and our goal is to provide you with some best practices that you can bring back and apply to your organization. Look, data is plentiful, but insights are not. ThoughtSpot is disrupting analytics by using search and machine intelligence to simplify data analysis and really empower anyone with fast access to relevant data. But in the last 150 days, we've had more questions than answers. Creating an organization that puts data and insights at their core requires not only modern technology, but leadership, a mindset and a culture that people often refer to as data-driven. What does that mean? How can we equip our teams with data and fast access to quality information that can turn insights into action. And today we're going to hear from experienced leaders who are transforming their organizations with data, insights and creating digital first cultures. But before we introduce our speakers, I'm joined today by two of my co-hosts from ThoughtSpot first chief data strategy officer at the ThoughtSpot is Cindi Howson. Cindi is an analytics and BI expert with 20 plus years experience and the author of "Successful Business Intelligence "Unlock the Value of BI & Big Data." Cindi was previously the lead analyst at Gartner for the data and analytics magic quadrant. And early last year, she joined ThoughtSpot to help CDOs and their teams understand how best to leverage analytics and AI for digital transformation. Cindi, great to see you welcome to the show. >> Thank you, Dave. Nice to join you virtually. >> Now our second cohost and friend of the cube is ThoughtSpot CEO Sudheesh Nair Hello, Sudheesh how are you doing today? >> I'm well Dave, it's good to talk to you again. >> It's great to see you thanks so much for being here. Now Sudheesh please share with us why this discussion is so important to your customers and of course, to our audience and what they're going to learn today. (upbeat music) >> Thanks, Dave. I wish you were there to introduce me into every room and that I walk into because you have such an amazing way of doing it. Makes me feel all so good. Look, since we have all been cooped up in our homes, I know that the vendors like us, we have amped up our sort of effort to reach out to you with invites for events like this. So we are getting very more invites for events like this than ever before. So when we started planning for this, we had three clear goals that we wanted to accomplish. And our first one that when you finish this and walk away, we want to make sure that you don't feel like it was a waste of time. We want to make sure that we value your time and this is going to be useful. Number two, we want to put you in touch with industry leaders and thought leaders, generally good people that you want to hang around with long after this event is over. And number three, as we plan through this, we are living through these difficult times. We want an event to be this event, to be more of an uplifting and inspiring event too. Now, the challenge is how do you do that with the team being change agents because change and as much as we romanticize it, it is not one of those uplifting things that everyone wants to do, or like to do. The way I think of it sort of like a, if you've ever done bungee jumping and it's like standing on the edges waiting to make that one more step, all you have to do is take that one step and gravity will do the rest, but that is the hardest step to take. Change requires a lot of courage. And when we are talking about data and analytics, which is already like such a hard topic, not necessarily an uplifting and positive conversation in most businesses, it is somewhat scary. Change becomes all the more difficult. Ultimately change requires courage. Courage to first of all challenge the status quo. People sometimes are afraid to challenge the status quo because they are thinking that maybe I don't have the power to make the change that the company needs. Sometimes they feel like I don't have the skills. Sometimes they may feel that I'm probably not the right person do it. Or sometimes the lack of courage manifest itself as the inability to sort of break the silos that are formed within the organizations, when it comes to data and insights that you talked about. There are people in the company who are going to hog the data because they know how to manage the data, how to inquire and extract. They know how to speak data. They have the skills to do that. But they are not the group of people who have sort of the knowledge, the experience of the business to ask the right questions off the data. So there is the silo of people with the answers, and there is a silo of people with the questions. And there is gap. This sort of silos are standing in the way of making that necessary change that we all know the business needs. And the last change to sort of bring an external force sometimes. It could be a tool. It could be a platform, it could be a person, it could be a process, but sometimes no matter how big the company is or how small the company is, you may need to bring some external stimuli to start the domino of the positive changes that are necessary. The group of people that we are brought in, the four people, including Cindi, that you will hear from today are really good at practically telling you how to make that step, how to step off that edge, how to dress the rope, that you will be safe and you're going to have fun. You will have that exhilarating feeling of jumping, for a bungee jump. All four of them are exceptional, but my honor is to introduce Michelle and she's our first speaker. Michelle, I am very happy after watching her presentation and reading our bio, that there are no country vital worldwide competition for cool patterns, because she will beat all of us because when her children were small, they were probably into Harry Potter and Disney. She was managing a business and leading change there. And then as her kids grew up and got to that age where they like football and NFL, guess what? She's the CIO of NFL. What a cool mom? I am extremely excited to see what she's going to talk about. I've seen the slides, tons of amazing pictures. I'm looking to see the context behind it. I'm very thrilled to make the acquaintance of Michelle and looking forward to her talk next. Welcome Michelle, it's over to you. (upbeat music) >> I'm delighted to be with you all today to talk about thought leadership. And I'm so excited that you asked me to join you because today I get to be a quarterback. I always wanted to be one. And I thought this is about as close as I'm ever going to get. So I want to talk to you about quarterbacking, our digital revolution using insights data. And of course, as you said, leadership, first a little bit about myself, a little background, as I said, I always wanted to play football. And this is something that I wanted to do since I was a child. But when I grew up, girls didn't get to play football. I'm so happy that that's changing and girls are now doing all kinds of things that they didn't get to do before. Just this past weekend on an NFL field, we had a female coach on two sidelines and a female official on the field. I'm a lifelong fan and student of the game of football. I grew up in the South. You can tell from the accent. And in the South football is like a religion and you pick sides. I chose Auburn university working in the athletic department. So I'm Testament to you can start the journey can be long. It took me many, many years to make it into professional sports. I graduated in 1987 and my little brother, well, not actually not so little. He played offensive line for the Alabama Crimson Tide. And for those of you who know SCC football, you know this is a really big rivalry. And when you choose sides, your family is divided. So it's kind of fun for me to always tell the story that my dad knew his kid would make it to the NFL. He just bet on the wrong one. My career has been about bringing people together for memorable moments at some of America's most iconic brands, delivering memories and amazing experiences that delight from Universal Studios, Disney to my current position as CIO of the NFL. In this job I'm very privileged to have the opportunity to work with the team that gets to bring America's game to millions of people around the world. Often I'm asked to talk about how to create amazing experiences for fans, guests, or customers. But today I really wanted to focus on something different and talk to you about being behind the scenes and backstage because behind every event, every game, every awesome moment is execution, precise, repeatable execution. And most of my career has been behind the scenes doing just that assembling teams to execute these plans. And the key way that companies operate at these exceptional levels is making good decisions, the right decisions at the right time and based upon data so that you can translate the data into intelligence and be a data-driven culture. Using data and intelligence is an important way that world-class companies do differentiate themselves. And it's the lifeblood of collaboration and innovation. Teams that are working on delivering these kinds of world casts experiences are often seeking out and leveraging next-generation technologies and finding new ways to work. I've been fortunate to work across three decades of emerging experiences, which each required emerging technologies to execute a little bit first about Disney in the 90s, I was at Disney leading a project called destination Disney, which it's a data project. It was a data project, but it was CRM before CRM was even cool. And then certainly before anything like a data-driven culture was ever brought up, but way back then we were creating a digital backbone that enabled many technologies for the things that you see today, like the magic band, Disney's magical express. My career at Disney began in finance, but Disney was very good about rotating you around. And it was during one of these rotations that I became very passionate about data. I kind of became a pain in the butt to the IT team asking for data more and more data. And I learned that all of that valuable data was locked up in our systems. All of our point of sales systems, our reservation systems, our operation systems. And so I became a shadow IT person in marketing, ultimately leading to moving into IT. And I haven't looked back since. In the early two thousands, I was at universal studios theme park as their CIO preparing for and launching "The Wizarding World of Harry Potter" bringing one of history's most memorable characters to life required many new technologies and a lot of data. Our data and technologies were embedded into the rides and attractions. I mean, how do you really think a wan selects you at a wan shop. As today at the NFL? I am constantly challenged to do leading edge technologies, using things like sensors, AI, machine learning, and all new communication strategies and using data to drive everything from player performance, contracts, to where we build new stadiums and hold events with this year being the most challenging yet rewarding year in my career at the NFL. In the middle of a global pandemic, the way we are executing on our season is leveraging data from contract tracing devices joined with testing data, talk about data, actually enabling your business without it w wouldn't be having a season right now. I'm also on the board of directors of two public companies where data and collaboration are paramount. First RingCentral, it's a cloud based unified communications platform and collaboration with video message and phone all in one solution in the cloud and Quotient technologies whose product is actually data. The tagline at Quotient is the result in knowing I think that's really important because not all of us are data companies where your product is actually data, but we should operate more like your product is data. I'd also like to talk to you about four areas of things to think about as thought leaders in your companies. First just hit on it is change how to be a champion and a driver of change. Second, how do you use data to drive performance for your company and measure performance of your company? Third, how companies now require intense collaboration to operate. And finally, how much of this is accomplished through solid data driven decisions. First let's hit on change. I mean, it's evident today more than ever, that we are in an environment of extreme change. I mean, we've all been at this for years and as technologists we've known it, believed it, lived it and thankfully for the most part, knock on what we were prepared for it. But this year everyone's cheese was moved. All the people in the back rooms, IT, data architects and others were suddenly called to the forefront because a global pandemic has turned out to be the thing that is driving intense change in how people work and analyze their business. On March 13th, we closed our office at the NFL in the middle of preparing for one of our biggest events, our kickoff event, the 2020 draft. We went from planning a large event in Las Vegas under the bright lights, red carpet stage to smaller events in club facilities. And then ultimately to one where everyone coaches GM's prospects and even our commissioner were at home in their basements. And we only had a few weeks to figure it out. I found myself for the first time being in the live broadcast event space, talking about bungee jumping. This is really what it felt like. It was one in which no one felt comfortable because it had not been done before. But leading through this, I stepped up, but it was very scary. It was certainly very risky, but it ended up being all so rewarding when we did it. And as a result of this, some things will change forever. Second, managing performance. I mean, data should inform how you're doing and how to get your company to perform at it's level. Highest level. As an example, the NFL has always measured performance, obviously, and it is one of the purest examples of how performance directly impacts outcome. I mean, you can see performance on the field. You can see points being scored in stats, and you immediately know that impact those with the best stats usually when the games. The NFL has always recorded stats since the beginning of time here at the NFL a little this year is our 101 year and athletes ultimate success as a player has also always been greatly impacted by his stats. But what has changed for us is both how much more we can measure and the immediacy with which it can be measured. And I'm sure in your business it's the same. The amount of data you must have has got to have quadrupled and how fast you need it and how quickly you need to analyze it is so important. And it's very important to break the silos between the keys, to the data and the use of the data. Our next generation stats platform is taking data to a next level. It's powered by Amazon web services. And we gathered this data real-time from sensors that are on players' bodies. We gather it in real time, analyze it, display it online and on broadcast. And of course it's used to prepare week to week in addition to what is a normal coaching plan would be. We can now analyze, visualize route patterns, speed match-ups, et cetera. So much faster than ever before. We're continuing to roll out sensors too that will gather more and more information about a player's performance as it relates to their health and safety. The third trend is really, I think it's a big part of what we're feeling today and that is intense collaboration. And just for sort of historical purposes, it's important to think about for those of you that are IT professionals and developers, more than 10 years ago, agile practices began sweeping companies where small teams would work together rapidly in a very flexible, adaptive, and innovative way. And it proved to be transformational. However, today, of course, that is no longer just small teams, the next big wave of change. And we've seen it through this pandemic is that it's the whole enterprise that must collaborate and be agile. If I look back on my career, when I was at Disney, we owned everything 100%. We made a decision, we implemented it. We were a collaborative culture, but it was much easier to push change because you own the whole decision. If there was buy-in from the top down, you've got the people from the bottom up to do it and you executed. At Universal we were a joint venture. Our attractions and entertainment was licensed. Our hotels were owned and managed by other third parties. So influence and collaboration and how to share across companies became very important. And now here I am at the NFL and even the bigger ecosystem, we have 32 clubs that are all separate businesses. 31 different stadiums that are owned by a variety of people. We have licensees, we have sponsors, we have broadcast partners. So it seems that as my career has evolved, centralized control has gotten less and less and has been replaced by intense collaboration, not only within your own company, but across companies. The ability to work in a collaborative way across businesses and even other companies that has been a big key to my success in my career. I believe this whole vertical integration and big top-down decision-making is going by the wayside in favor of ecosystems that require cooperation yet competition to co-exist. I mean, the NFL is a great example of what we call co-op petition, which is cooperation and competition. We're in competition with each other, but we cooperate to make the company the best it can be. And at the heart of these items really are data driven decisions and culture. Data on its own isn't good enough. You must be able to turn it to insights. Partnerships between technology teams who usually hold the keys to the raw data and business units who have the knowledge to build the right decision models is key. If you're not already involved in this linkage, you should be. Data mining isn't new for sure. The availability of data is quadrupling and it's everywhere. How do you know what to even look at? How do you know where to begin? How do you know what questions to ask it's by using the tools that are available for visualization and analytics and knitting together strategies of the company. So it begins with first of all, making sure you do understand the strategy of the company. So in closing, just to wrap up a bit, many of you joined today, looking for thought leadership on how to be a change agent, a change champion, and how to lead through transformation. Some final thoughts are be brave and drive. Don't do the ride along program. It's very important to drive. Driving can be high risk, but it's also high reward. Embracing the uncertainty of what will happen is how you become brave. Get more and more comfortable with uncertainty, be calm and let data be your map on your journey. Thanks. >> Michelle, tank you so much. So you and I share a love of data and a love of football. You said you want to be the quarterback. I'm more an old line person. (Michelle and Cindi laughing) >> Well, then I can do my job without you. >> Great. And I'm getting the feeling now, Sudheesh is talking about bungee jumping. My vote is when we're past this pandemic, we both take them to the Delaware water gap and we do the cliff jumping. >> That sounds good, I'll watch. >> Yeah, you'll watch, okay. So Michelle, you have so many stakeholders when you're trying to prioritize the different voices. You have the players, you have the owners, you have the league, as you mentioned, the broadcasters, your partners here and football mamas like myself. How do you prioritize when there's so many different stakeholders that you need to satisfy? >> I think balancing across stakeholders starts with, aligning on a mission. And if you spend a lot of time understanding where everyone's coming from, and you can find the common thread that ties them all together, you sort of do get them to naturally prioritize their work. And I think that's very important. So for us, at the NFL and even at Disney, it was our core values and our core purpose, is so well known and when anything challenges that we're able to sort of lay that out. But as a change agent, you have to be very empathetic. And I would say empathy is probably your strongest skill if you're a change agent. And that means listening to every single stakeholder, even when they're yelling at you, even when they're telling you your technology doesn't work and you know that it's user error, or even when someone is just emotional about what's happening to them and that they're not comfortable with it. So I think being empathetic and having a mission and understanding it is sort of how I prioritize and balance. >> Yeah, empathy, a very popular word this year. I can imagine those coaches and owners yelling. So, thank you for your leadership here. So Michelle, I look forward to discussing this more with our other customers and disruptors joining us in a little bit. (upbeat music) So we're going to take a hard pivot now and go from football to Chernobyl. Chernobyl what went wrong? 1986, as the reactors were melting down, they had the data to say, this is going to be catastrophic. And yet the culture said, "no, we're perfect, hide it. "Don't dare tell anyone." Which meant they went ahead and had celebrations in Kiev. Even though that increased the exposure, the additional thousands getting cancer and 20,000 years before the ground around there can even be inhabited again, this is how powerful and detrimental a negative culture, a culture that is unable to confront the brutal facts that hides data. This is what we have to contend with. And this is why I want you to focus on having, fostering a data-driven culture. I don't want you to be a laggard. I want you to be a leader in using data to drive your digital transformation. So I'll talk about culture and technology. Is it really two sides of the same coin, real-world impacts and then some best practices you can use to and innovate your culture. Now, oftentimes I would talk about culture and I talk about technology. And recently a CDO said to me, "Cindi, I actually think this is two sides "of the same coin. "One reflects the other." What do you think? Let me walk you through this. So let's take a laggard. What does the technology look like? Is it based on 1990s BI and reporting largely parametrized reports, on premises data, warehouses, or not even that operational reports at best one enterprise data warehouse, very slow moving and collaboration is only email. What does that culture tell you? Maybe there's a lack of leadership to change, to do the hard work that Sudheesh referred to, or is there also a culture of fear, afraid of failure, resistance to change complacency. And sometimes that complacency it's not because people are lazy. It's because they've been so beaten down every time a new idea is presented. It's like, no we're measured on least cost to serve. So politics and distrust, whether it's between business and IT or individual stakeholders is the norm. So data is hoarded. Let's contrast that with a leader, a data and analytics leader, what is their technology look like? Augmented analytics search and AI driven insights, not on premises, but in the cloud and maybe multiple clouds. And the data is not in one place, but it's in a data Lake and in a data warehouse, a logical data warehouse. The collaboration is being a newer methods, whether it's Slack or teams allowing for that real time decisioning or investigating a particular data point. So what is the culture in the leaders? It's transparent and trust. There is a trust that data will not be used to punish that there is an ability to confront the bad news. It's innovation, valuing innovation in pursuit of the company goals, whether it's the best fan experience and player safety in the NFL or best serving your customers. It's innovative and collaborative. There's none of this. Oh, well, I didn't invent that. I'm not going to look at that. There's still pride of ownership, but it's collaborating to get to a better place faster. And people feel empowered to present new ideas to fail fast, and they're energized knowing that they're using the best technology and innovating at the pace that business requires. So data is democratized. And democratized, not just for power users or analysts, but really at the point of impact what we like to call the new decision-makers or really the frontline workers. So Harvard business review partnered with us to develop this study to say, just how important is this? We've been working at BI and analytics as an industry for more than 20 years. Why is it not at the front lines? Whether it's a doctor, a nurse, a coach, a supply chain manager, a warehouse manager, a financial services advisor. Everyone said that if our 87% said, they would be more successful if frontline workers were empowered with data driven insights, but they recognize they need new technology to be able to do that. It's not about learning hard tools. The sad reality, only 20% of organizations are actually doing this. These are the data-driven leaders. So this is the culture in technology. How did we get here? It's because state-of-the-art keeps changing. So the first-generation BI and analytics platforms were deployed on premises on small datasets, really just taking data out of ERP systems that were also on premises. And state-of-the-art was maybe getting a management report, an operational report. Over time visual-based data discovery vendors disrupted these traditional BI vendors, empowering now analysts to create visualizations with the flexibility on a desktop, sometimes larger data, sometimes coming from a data warehouse. The current state of the art though, Gartner calls it augmented analytics at ThoughtSpot, we call it search and AI driven analytics. And this was pioneered for large scale datasets, whether it's on premises or leveraging the cloud data warehouses. And I think this is an important point. Oftentimes you, the data and analytics leaders will look at these two components separately, but you have to look at the BI and analytics tier in lockstep with your data architectures to really get to the granular insights and to leverage the capabilities of AI. Now, if you've never seen ThoughtSpot, I'll just show you what this looks like. Instead of somebody hard coding, a report it's typing in search keywords and very robust keywords contains rank top bottom, getting to a visual visualization that then can be pinned to an existing Pin board that might also contain insights generated by an AI engine. So it's easy enough for that new decision maker, the business user, the non analyst to create themselves. Modernizing the data and analytics portfolio is hard because the pace of change has accelerated. You use to be able to create an investment place a bet for maybe 10 years, a few years ago, that time horizon was five years, now it's maybe three years and the time to maturity has also accelerated. So you have these different components, the search and AI tier, the data science tier, data preparation and virtualization. But I would also say equally important is the cloud data warehouse and pay attention to how well these analytics tools can unlock the value in these cloud data warehouses. So ThoughtSpot was the first to market with search and AI driven insights. Competitors have followed suit, but be careful if you look at products like power BI or SAP analytics cloud, they might demo well, but do they let you get to all the data without moving it in products like Snowflake, Amazon Redshift, or Azure synapse or Google big query, they do not. They require you to move it into a smaller in memory engine. So it's important how well these new products inter operate. the pace of change, its acceleration Gartner recently predicted that by 2022, 65% of analytical queries will be generated using search or NLP or even AI. And that is roughly three times the prediction they had just a couple years ago. So let's talk about the real world impact of culture. And if you read any of my books or used any of the maturity models out there, whether the Gartner IT score that I worked on, or the data warehousing Institute also has the money surety model. We talk about these five pillars to really become data-driven. As Michelle, I spoke about it's focusing on the business outcomes, leveraging all the data, including new data sources, it's the talent, the people, the technology, and also the processes. And often when I would talk about the people and the talent, I would lump the culture as part of that. But in the last year, as I've traveled the world and done these digital events for Thought leaders, you have told me now culture is absolutely so important. And so we've pulled it out as a separate pillar. And in fact, in polls that we've done in these events, look at how much more important culture is as a barrier to becoming data-driven it's three times as important as any of these other pillars. That's how critical it is. And let's take an example of where you can have great data, but if you don't have the right culture, there's devastating impacts. And I will say, I have been a loyal customer of Wells Fargo for more than 20 years. But look at what happened in the face of negative news with data, it said, "hey, we're not doing good cross selling, "customers do not have both a checking account "and a credit card and a savings account and a mortgage." They opened fake accounts facing billions in fines, change in leadership that even the CEO attributed to a toxic sales culture, and they're trying to fix this. But even recently there's been additional employee backlash saying the culture has not changed. Let's contrast that with some positive examples, Medtronic, a worldwide company in 150 countries around the world. They may not be a household name to you, but if you have a loved one or yourself, you have a pacemaker, spinal implant diabetes, you know this brand. And at the start of COVID when they knew their business would be slowing down, because hospitals would only be able to take care of COVID patients. They took the bold move of making their IP for ventilators publicly available. That is the power of a positive culture. Or Verizon, a major telecom organization looking at late payments of their customers. And even though the U.S federal government said, "well, you can't turn them off. They said, "we'll extend that even beyond "the mandated guidelines." And facing a slow down in the business because of the tough economy, they said, you know what? "We will spend the time up skilling our people, "giving them the time to learn more "about the future of work, the skills and data "and analytics," for 20,000 of their employees, rather than furloughing them. That is the power of a positive culture. So how can you transform your culture to the best in class? I'll give you three suggestions, bring in a change agent, identify the relevance, or I like to call it WIFM and organize for collaboration. So the CDO, whatever your title is, chief analytics officer, chief digital officer, you are the most important change agent. And this is where you will hear that oftentimes a change agent has to come from outside the organization. So this is where, for example, in Europe, you have the CDO of Just Eat a takeout food delivery organization coming from the airline industry or in Australia, National Australian bank, taking a CDO within the same sector from TD bank going to NAB. So these change agents come in disrupt. It's a hard job. As one of you said to me, it often feels like Sisyphus. I make one step forward and I get knocked down again. I get pushed back. It is not for the faint of heart, but it's the most important part of your job. The other thing I'll talk about is WIFM. What is in it for me? And this is really about understanding the motivation, the relevance that data has for everyone on the frontline, as well as those analysts, as well as the executives. So if we're talking about players in the NFL, they want to perform better and they want to stay safe. That is why data matters to them. If we're talking about financial services, this may be a wealth management advisor. Okay we could say commissions, but it's really helping people have their dreams come true, whether it's putting their children through college or being able to retire without having to work multiple jobs still into your 70s or 80s for the teachers, teachers, you ask them about data. They'll say we don't, we don't need that. I care about the student. So if you can use data to help a student perform better, that is WIFM. And sometimes we spend so much time talking the technology, we forget what is the value we're trying to deliver with it. And we forget the impact on the people that it does require change. In fact, the Harvard business review study found that 44% said lack of change management is the biggest barrier to leveraging both new technology, but also being empowered to act on those data-driven insights. The third point organize for collaboration. This does require diversity of thought, but also bringing the technology, the data and the business people together. Now there's not a single one size fits all model for data and analytics. At one point in time, even having a BICC, a BI competency center was considered state-of-the-art. Now for the biggest impact what I recommend is that you have a federated model centralized for economies of scale. That could be the common data, but then in bed, these evangelists, these analysts of the future within every business unit, every functional domain. And as you see this top bar, all models are possible, but the hybrid model has the most impact, the most leaders. So as we look ahead to the months ahead, to the year ahead an exciting time, because data is helping organizations better navigate a tough economy, lock in the customer loyalty. And I look forward to seeing how you foster that culture that's collaborative with empathy and bring the best of technology, leveraging the cloud, all your data. So thank you for joining us at Thought Leaders. And next I'm pleased to introduce our first change agent, Tom Mazzaferro chief data officer of Western union. And before joining Western union, Tom made his Mark at HSBC and JPMorgan Chase spearheading digital innovation in technology, operations, risk compliance, and retail banking. Tom, thank you so much for joining us today. (upbeat music) >> Very happy to be here and looking forward to talking to all of you today. So as we look to move organizations to a data-driven, capability into the future, there is a lot that needs to be done on the data side, but also how does data connect and enable different business teams and technology teams into the future. As you look across, our data ecosystems and our platforms and how we modernize that to the cloud in the future, it all needs to basically work together, right? To really be able to drive and over the shift from a data standpoint, into the future, that includes being able to have the right information with the right quality of data, at the right time to drive informed business decisions, to drive the business forward. As part of that, we actually have partnered with ThoughtSpot, to actually bring in the technology to help us drive that as part of that partnership. And it's how we've looked to integrate it into our overall business as a whole we've looked at how do we make sure that our business and our professional lives right, are enabled in the same ways as our personal lives. So for example, in your personal lives, when you want to go and find something out, what do you do? You go onto google.com or you go on to Bing we go onto Yahoo and you search for what you want search to find and answer. ThoughtSpot for us as the same thing, but in the business world. So using ThoughtSpot and other AI capability it's allowed us to actually, enable our overall business teams in our company to actually have our information at our fingertips. So rather than having to go and talk to someone or an engineer to go pull information or pull data, we actually can have the end-users or the business executives, right. Search for what they need, what they want at the exact time that action need it to go and drive the business forward. This is truly one of those transformational things that we've put in place. On top of that, we are on the journey to modernize our larger ecosystem as a whole. That includes modernizing our underlying data warehouses, our technology, or our Eloqua environments. And as we move that, we've actually picked two of our cloud providers going to AWS and GCP. We've also adopted Snowflake to really drive and to organize our information and our data then drive these new solutions and capabilities forward. So they portion of us though is culture. So how do we engage with the business teams and bring the IT teams together to really drive these holistic end to end solutions and capabilities to really support the actual business into the future? That's one of the keys here, as we look to modernize and to really enhance our organizations to become data-driven, this is the key. If you can really start to provide answers to business questions before they're even being asked and to predict based upon different economic trends or different trends in your business, what does this is maybe be made and actually provide those answers to the business teams before they're even asking for it, that is really becoming a data-driven organization. And as part of that, it's really then enables the business to act quickly and take advantage of opportunities as they come in based upon, industries based upon markets, based upon products, solutions, or partnerships into the future. These are really some of the keys that become crucial as you move forward, right, into this new age, especially with COVID. With COVID now taking place across the world, right? Many of these markets, many of these digital transformations are accelerating and are changing rapidly to accommodate and to support customers in these very difficult times, as part of that, you need to make sure you have the right underlying foundation ecosystems and solutions to really drive those capabilities and those solutions forward. As we go through this journey, both of my career, but also each of your careers into the future, right? It also needs to evolve, right? Technology has changed so drastically in the last 10 years, and that change is only accelerating. So as part of that, you have to make sure that you stay up to speed, up to date with new technology changes both on the platform standpoint tools, but also what do our customers want? What do our customers need and how do we then service them with our information, with our data, with our platform and with our products and our services to meet those needs and to really support and service those customers into the future. This is all around becoming a more data organization such as how do you use your data to support the current business lines, but how do you actually use your information, your data to actually put a better support your customers, better support your business, better support your employees, your operations teams, and so forth, and really creating that full integration in that ecosystem is really when you start to get large dividends from this investments into the future. But that being said, hope you enjoy the segment on how to become and how to drive it data driven organization. And, looking forward to talking to you again soon. Thank you. >> Tom that was great thanks so much. Now I'm going to have to brag on you for a second as a change agent you've come in disrupted and how long have you been at Western union? >> Only nine months, so just started this year, but, doing some great opportunities and great changes. And we have a lot more to go, but, we're really driving things forward in partnership with our business teams and our colleagues to support those customers going forward. >> Tom, thank you so much. That was wonderful. And now I'm excited to introduce you to Gustavo Canton, a change agent that I've had the pleasure of working with meeting in Europe, and he is a serial change agent, most recently with Schneider electric, but even going back to Sam's clubs, Gustavo welcome. (upbeat music) >> So, hey everyone, my name is Gustavo Canton and thank you so much, Cindi, for the intro, as you mentioned, doing transformations is high effort, high reward situation. I have empowered many transformations and I have led many transformations. And what I can tell you is that it's really hard to predict the future, but if you have a North star and where you're going, the one thing that I want you to take away from this discussion today is that you need to be bold to evolve. And so in today, I'm going to be talking about culture and data, and I'm going to break this down in four areas. How do we get started barriers or opportunities as I see it, the value of AI, and also, how do you communicate, especially now in the workforce of today with so many different generations, you need to make sure that you are communicating in ways that are non-traditional sometimes. And so how do we get started? So I think the answer to that is you have to start for you yourself as a leader and stay tuned. And by that, I mean, you need to understand not only what is happening in your function or your field, but you have to be varying into what is happening in society, socioeconomically speaking wellbeing. The common example is a great example. And for me personally, it's an opportunity because the one core value that I have is well-being, I believe that for human potential, for customers and communities to grow wellbeing should be at the center of every decision. And as somebody mentioned is great to be, stay in tune and have the skillset and the courage. But for me personally, to be honest, to have this courage is not about not being afraid. You're always afraid when you're making big changes when you're swimming upstream, but what gives me the courage is the empathy part. Like I think empathy is a huge component because every time I go into an organization or a function, I try to listen very attentively to the needs of the business and what the leaders are trying to do. What I do it thinking about the mission of how do I make change for the bigger, workforce? for the bigger good. Despite this fact that this might have a perhaps implication on my own self-interest in my career, right? Because you have to have that courage sometimes to make choices that I know we'll see in politically speaking, what are the right thing to do? And you have to push through it. And you have to push through it. So the bottom line for me is that I don't think they're transforming fast enough. And the reality is I speak with a lot of leaders and we have seen stories in the past. And what they show is that if you look at the four main barriers that are basically keeping us behind budget, inability to act cultural issues, politics, and lack of alignment, those are the top four. But the interesting thing is that as Cindi has mentioned, these topics culture is actually gaining, gaining more and more traction. And in 2018, there was a story from HBR and it was about 45%. I believe today it's about 55%, 60% of respondents say that this is the main area that we need to focus on. So again, for all those leaders and all the executives who understand and are aware that we need to transform, commit to the transformation and set a state, deadline to say, "hey, in two years, we're going to make this happen. "What do we need to do to empower and enable "this change engines to make it happen?" You need to make the tough choices. And so to me, when I speak about being bold is about making the right choices now. So I'll give you samples of some of the roadblocks that I went through as I think transformation most recently, as Cindi mentioned in Schneider. There are three main areas, legacy mindset. And what that means is that we've been doing this in a specific way for a long time and here is how we have been successful what was working the past is not going to work now. The opportunity there is that there is a lot of leaders who have a digital mindset and there're up and coming leaders that are not yet fully developed. We need to mentor those leaders and take bets on some of these talent, including young talent. We cannot be thinking in the past and just wait for people, three to five years for them to develop because the world is going to in a way that is super fast. The second area, and this is specifically to implementation of AI is very interesting to me because just example that I have with ThoughtSpot, right, we went to implementation and a lot of the way is the IT team function of the leaders look at technology, they look at it from the prism of the prior all success criteria for the traditional Bi's. And that's not going to work. Again the opportunity here is that you need to really find what successful look like. In my case, I want the user experience of our workforce to be the same as user experience you have at home is a very simple concept. And so we need to think about how do we gain the user experience with this augmented analytics tools and then work backwards to have the right talent processes and technology to enable that. And finally, with COVID a lot of pressuring organizations, and companies to do more with less. And the solution that most leaders I see are taking is to just minimize costs, sometimes in cut budget, we have to do the opposite. We have to actually invest some growth areas, but do it by business question. Don't do it by function. If you actually invest in these kind of solutions, if you actually invest on developing your talent, your leadership to see more digitally, if you actually invest on fixing your data platform, it's not just an incremental cost. It's actually this investment is going to offset all those hidden costs and inefficiencies that you have on your system, because people are doing a lot of work and working very hard, but it's not efficiency, and it's not working in the way that you might want to work. So there is a lot of opportunity there. And you just to put into some perspective, there have studies in the past about, how do we kind of measure the impact of data. And obviously this is going to vary by your organization maturity, is going to, there's going to be a lot of factors. I've been in companies who have very clean, good data to work with. And I think with companies that we have to start basically from scratch. So it all depends on your maturity level, but in this study, what I think is interesting is they try to put attack line or attack price to what is the cost of incomplete data. So in this case, it's about 10 times as much to complete a unit of work when you have data that is flawed as opposed to have perfect data. So let me put that just in perspective, just as an example, right? Imagine you are trying to do something and you have to do 100 things in a project, and each time you do something, it's going to cost you a dollar. So if you have perfect data, the total cost of that project might be $100. But now let's say you have any percent perfect data and 20% flawed data by using this assumption that flawed data is 10 times as costly as perfect data. Your total costs now becomes $280 as opposed to $100. This is just for you to really think about as a CIO CTO, CHRO CEO, are we really paying attention and really closing the gaps that we have on our data infrastructure. If we don't do that, it's hard sometimes to see the snowball effect or to measure the overall impact. But as you can tell the price that goes up very, very quickly. So now, if I were to say, how do I communicate this? Or how do I break through some of these challenges or some of these various, right. I think the key is I am in analytics. I know statistics obviously, and love modeling and data and optimization theory and all that stuff. That's what I came to analytics. But now as a leader and as a change agent, I need to speak about value. And in this case, for example, for Schneider, there was this tagline called free up your energy. So the number one thing that they were asking from the analytics team was actually efficiency, which to me was very interesting. But once I understood that I understood what kind of language to use, how to connect it to the overall strategy and basically how to bring in the, the right leaders, because you need to focus on the leaders that you're going to make the most progress. Again, low effort, high value. You need to make sure you centralize all the data as you can. You need to bring in some kind of augmented analytics solution. And finally you need to make it super simple for the, in this case, I was working with the HR teams in other areas, so they can have access to one portal. They don't have to be confused in looking for 10 different places to find information. I think if you can actually have those four foundational pillars, obviously under the guise of having a data-driven culture, that's when you can actually make the impact. So in our case, it was about three years total transformation, but it was two years for this component of augmented analytics. It took about two years to talk to IT get leadership support, find the budgeting, get everybody on board, make sure the safe criteria was correct. And we call this initiative, the people analytics portal, it was actually launched in July of this year. And we were very excited and the audience was very excited to do this. In this case, we did our pilot in North America for many, many manufacturers. But one thing that is really important is as you bring along your audience on this, you're going from Excel, in some cases or Tableau to other tools like, ThoughtSpot, you need to really explain them what is the difference and how these tools can truly replace, some of the spreadsheets or some of the views that you might have on these other kind of tools. Again, Tableau, I think it's a really good tool. There are other many tools that you might have in your toolkit. But in my case, personally, I feel that you need to have one portal going back to Cindi's point. I really truly enable the end user. And I feel that this is the right solution for us, right? And I will show you some of the findings that we had in the pilot in the last two months. So this was a huge victory, and I will tell you why, because it took a lot of effort for us to get to the station. Like I said, it's been years for us to kind of lay the foundation, get the leadership, and shaping culture so people can understand why you truly need to invest on (indistinct) analytics. And so what I'm showing here is an example of how do we use basically, a tool to capture in video the qualitative findings that we had, plus the quantitative insights that we have. So in this case, our preliminary results based on our ambition for three main metrics, hours saved user experience and adoption. So for hours saved or a mission was to have 10 hours per week per employee save on average user experience, or ambition was 4.5. And adoption, 80%. In just two months, two months and a half of the pilot, we were able to achieve five hours per week per employee savings. Our user experience for 4.3 out of five and adoption of 60%. Really, really amazing work. But again, it takes a lot of collaboration for us to get to the stage from IT, legal, communications, obviously the operations teams and the users in HR safety and other areas that might be, basically stakeholders in this whole process. So just to summarize this kind of effort takes a lot of energy. You are a change agent. You need to have a courage to make the decision and understand that I feel that in this day and age, with all this disruption happening, we don't have a choice. We have to take the risk, right? And in this case, I feel a lot of satisfaction in how we were able to gain all these very source for this organization. And that gave me the confidence to know that the work has been done and we are now in a different stage for the organization. And so for me, it to say, thank you for everybody who has believed, obviously in our vision, everybody who has believe in the word that we were trying to do and to make the life of four workforce or customers or in community better. As you can tell, there is a lot of effort. There is a lot of collaboration that is needed to do something like this. In the end, I feel very satisfied. With the accomplishments of this transformation, and I just want to tell for you, if you are going right now in a moment that you feel that you have to swim upstream what would mentors, what would people in this industry that can help you out and guide you on this kind of a transformation is not easy to do is high effort, but is well worth it. And with that said, I hope you are well, and it's been a pleasure talking to you. Talk to you soon, take care. >> Thank you, Gustavo, that was amazing. All right, let's go to the panel. (air whooshing) >> Okay, now we're going to go into the panel and bring Cindi, Michelle, Tom, and Gustavo back and have an open discussion. And I think we can all agree how valuable it is to hear from practitioners. And I want to thank the panel for sharing their knowledge with the community. And one common challenge that I heard you all talk about was bringing your leadership and your teams along on the journey with you. We talk about this all the time, and it is critical to have support from the top. Why? Because it directs the middle and then it enables bottoms up innovation effects from the cultural transformation that you guys all talked about. It seems like another common theme we heard is that you all prioritize database decision-making in your organizations and you combine two of your most valuable assets to do that and create leverage, employees on the front lines. And of course the data. And as you rightly pointed out, Tom, the pandemic has accelerated the need for really leaning into this. The old saying, if it ain't broke don't fix it. Well COVID is broken everything. And it's great to hear from our experts, how to move forward. So let's get right into it. So Gustavo, let's start with you if I'm an aspiring change agent and let's say I'm a budding data leader. What do I need to start doing? What habits do I need to create for long lasting success? >> I think curiosity is very important. You need to be, like I say, in tune to what is happening, not only in your specific field, like I have a passion for analytics, I can do this for 50 years plus, but I think you need to understand wellbeing other areas across not only a specific business, as you know I come from, Sam's club Walmart, retail, I mean energy management technology. So you have to try to push yourself and basically go out of your comfort zone. I mean, if you are staying in your comfort zone and you want to use lean continuous improvement, that's just going to take you so far. What you have to do is, and that's what I try to do is I try to go into areas, businesses, and transformation that make me stretch and develop as a leader. That's what I'm looking to do so I can help transform the functions organizations and do the change management, change of mindset required for these kinds of efforts. >> Michelle, you're at the intersection of tech and sports and what a great combination, but they're both typically male oriented fields. I mean, we've talked a little bit about how that's changing, but two questions. Tell us how you found your voice and talk about why diversity matters so much more than ever now. >> No, I found my voice really as a young girl, and I think I had such amazing support from men in my life. And I think the support and sponsorship as well as sort of mentorship along the way, I've had amazing male mentors who have helped me understand that my voice is just as important as anyone else's. I mean, I have often heard, and I think it's been written about that a woman has to believe they'll 100% master topic before they'll talk about it where a man can feel much less mastery and go on and on. So I was that way as well. And I learned just by watching and being open, to have my voice. And honestly at times demand a seat at the table, which can be very uncomfortable. And you really do need those types of, support networks within an organization. And diversity of course is important and it has always been. But I think if anything, we're seeing in this country right now is that diversity among all types of categories is front and center. And we're realizing that we don't all think alike. We've always known this, but we're now talking about things that we never really talked about before. And we can't let this moment go unchecked and on, and not change how we operate. So having diverse voices within your company and in the field of tech and sports, I am often the first and only I'm was the first, CIO at the NFL, the first female senior executive. It was fun to be the first, but it's also, very challenging. And my responsibility is to just make sure that, I don't leave anyone behind and make sure that I leave it good for the next generation. >> Well, thank you for that. That is inspiring. And Cindi, you love data and the data's pretty clear that diversity is a good business, but I wonder if you can add your perspectives to this conversation? >> Yeah, so Michelle has a new fan here because she has found her voice. I'm still working on finding mine. And it's interesting because I was raised by my dad, a single dad. So he did teach me how to work in a predominantly male environment, but why I think diversity matters more now than ever before. And this is by gender, by race, by age, by just different ways of working in thinking is because as we automate things with AI, if we do not have diverse teams looking at the data and the models and how they're applied, we risk having bias at scale. So this is why I think I don't care what type of minority you are finding your voice, having a seat at the table and just believing in the impact of your work has never been more important. And as Michelle said more possible. >> Great perspectives, thank you. Tom I want to go to you. I mean, I feel like everybody in our businesses in some way, shape or form become a COVID expert, but what's been the impact of the pandemic on your organization's digital transformation plans? >> We've seen a massive growth actually in a digital business over the last, 12 months, really, even in celebration, right? Once COVID hit, we really saw that in the 200 countries and territories that we operate in today and service our customers, today, that there's been a huge need, right? To send money, to support family, to support, friends and support loved ones across the world. And as part of that we are very, honored to get to support those customers that we, across all the centers today. But as part of that acceleration we need to make sure that we had the right architecture and the right platforms to basically scale, right, to basically support and provide the right kind of security for our customers going forward. So as part of that, we did do some pivots and we did accelerate some of our plans on digital to help support that overall growth coming in and to support our customers going forward, because there were these times during this pandemic, right? This is the most important time. And we need to support those that we love and those that we care about and doing that it's one of those ways is actually by sending money to them, support them financially. And that's where, really our part of that our services come into play that we really support those families. So it was really a great opportunity for us to really support and really bring some of our products to this level and supporting our business going forward. >> Awesome, thank you. Now I want to come back to Gustavo, Tom I'd love for you to chime in too. Did you guys ever think like you were, you were pushing the envelope too much in doing things with data or the technology that was just maybe too bold, maybe you felt like at some point it was failing or you're pushing your people too hard. Can you share that experience and how you got through it? >> Yeah, the way I look at it is, again, whenever I go to an organization, I ask the question, hey, how fast you would like transform. And, based on the agreements from the leadership and the vision that we want to take place, I take decisions. And I collaborate in a specific way now, in the case of COVID, for example, right. It forces us to remove silos and collaborate in a faster way. So to me, it was an opportunity to actually integrate with other areas and drive decisions faster, but make no mistake about it. When you are doing a transformation, you are obviously trying to do things faster than sometimes people are comfortable doing, and you need to be okay with that. Sometimes you need to be okay with tension, or you need to be okay debating points or making repetitive business cases until people connect with the decision because you understand, and you are seeing that, "hey, the CEO is making a one two year, efficiency goal. "The only way for us to really do more with less "is for us to continue this path. "We cannot just stay with the status quo. "We need to find a way to accelerate the transformation." That's the way I see it. >> How about you Tom, we were talking earlier with Sudheesh and Cindi, about that bungee jumping moment. What could you share? >> Yeah, I think you hit upon it, right now, the pace of change with the slowest pace that you see for the rest of your career. So as part of that, right, that's what I tell my team is that you need to be, you need to feel comfortable being uncomfortable. I mean, that we have to be able to basically scale, right, expand and support that the ever-changing needs in the marketplace and industry our customers today, and that pace of change that's happening, right. And what customers are asking for and the competition in the marketplace, it's only going to accelerate. So as part of that, as you look at what, how you're operating today in your current business model, right. Things are only going to get faster. So you have to plan into a line into drive the agile transformation so that you can scale even faster in the future. So as part of that, that's what we're putting in place here, right, is how do we create that underlying framework and foundation that allows the organization to basically continue to scale and evolve into the future? >> Yeah, we're definitely out of our comfort zones, but we're getting comfortable with it. So, Cindi, last question, you've worked with hundreds of organizations, and I got to believe that, some of the advice you gave when you were at Gartner, which is pre COVID, maybe sometimes clients didn't always act on it. They're not on my watch for whatever variety of reasons, but it's being forced on them now. But knowing what you know now that we're all in this isolation economy, how would you say that advice has changed? Has it changed? What's your number one action and recommendation today? >> Yeah, well, first off, Tom just freaked me out. What do you mean? This is the slowest ever even six months ago I was saying the pace of change in data and analytics is frenetic. So, but I think you're right, Tom, the business and the technology together is forcing this change. Now, Dave, to answer your question, I would say the one bit of advice, maybe I was a little more, very aware of the power and politics and how to bring people along in a way that they are comfortable. And now I think it's, you know what you can't get comfortable. In fact, we know that the organizations that were already in the cloud have been able to respond and pivot faster. So if you really want to survive as Tom and Gustavo said, get used to being uncomfortable, the power and politics are going to happen. Break the rules, get used to that and be bold. Do not be afraid to tell somebody they're wrong and they're not moving fast enough. I do think you have to do that with empathy, as Michelle said, and Gustavo, I think that's one of the key words today besides the bungee jumping. So I want to know where's the dish going to go bungee jumping. >> Guys fantastic discussion, really. Thanks again to all the panelists and the guests. It was really a pleasure speaking with you today. Really virtually all of the leaders that I've spoken to in the Cube program. Recently, they tell me that the pandemic is accelerating so many things, whether it's new ways to work, we heard about new security models and obviously the need for cloud. I mean, all of these things are driving true enterprise wide digital transformation, not just, as I said before, lip service. Sometimes we minimize the importance and the challenge of building culture and in making this transformation possible. But when it's done, right, the right culture is going to deliver tremendous results. Yeah, what does that mean getting it right? Everybody's trying to get it right. My biggest takeaway today is it means making data part of the DNA of your organization. And that means making it accessible to the people in your organization that are empowered to make decisions, decisions that can drive new revenue, cut costs, speed access to critical care, whatever the mission is of your organization. Data can create insights and informed decisions that drive value. Okay. Let's bring back Sudheesh and wrap things up. Sudheesh, please bring us home. >> Thank you. Thank you, Dave. Thank you, the Cube team, and thank goes to all of our customers and partners who joined us and thanks to all of you for spending the time with us. I want to do three quick things and then close it off. The first thing is I want to summarize the key takeaways that I had from all four of our distinguished speakers. First, Michelle, I will simply put it. She said it really well. That is be brave and drive. Don't go for a drive along. That is such an important point. Oftentimes, you know that I think that you have to do to make the positive change that you want to see happen but you wait for someone else to do it, not just, why not you? Why don't you be the one making that change happen? That's the thing that I've picked up from Michelle's talk. Cindi talked about finding the importance of finding your voice. Taking that chair, whether it's available or not, and making sure that your ideas, your voices are heard, and if it requires some force, then apply that force. Make sure your ideas are heard. Gustavo talked about the importance of building consensus, not going at things all alone sometimes building the importance of building the quorum. And that is critical because if you want the changes to last, you want to make sure that the organization is fully behind it. Tom, instead of a single takeaway, what I was inspired by is the fact that a company that is 170 years old, 170 years old, 200 companies and 200 countries they're operating in. And they were able to make the change that is necessary through this difficult time. So in a matter of months, if they could do it, anyone could. The second thing I want to do is to leave you with a takeaway that is I would like you to go to topspot.com/nfl because our team has made an app for NFL on Snowflake. I think you will find this interesting now that you are inspired and excited because of Michelle's talk. And the last thing is please go to thoughtspot.com/beyond our global user conference is happening in this December. We would love to have you join us. It's again, virtual, you can join from anywhere. We are expecting anywhere from five to 10,000 people, and we would love to have you join and see what we've been up to since last year. We have a lot of amazing things in store for you, our customers, our partners, our collaborators, they will be coming and sharing. We'll be sharing things that we've have been working to release something that will come out next year. And also some of the crazy ideas our engineers have been cooking up. All of those things will be available for you at the Thought Spot Beyond. Thank you. Thank you so much.

(upbeat music) >> Narrator: From the Cube Studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is the Cube Conversation. >> Welcome to this Cube Conversation. I'm Lisa Martin, excited to talk to the CEO of Styra, Bill Mann today. Bill, welcome to the Cube. >> Hi Lisa, how are you doing? >> I'm doing well. I should say welcome back. You've been on the Cube at a previous company, but we're excited to talk to you today about Styra, what's going on? So let's go ahead and start informing our audience who Styra is and what you do? >> Sure, so who Styra is and what do we do? So Styra is a company that's focused on reinventing policy and authorization in the cloud native stack. We're the company that created an open source project called Open Policy Agent, it's part of CNCF. And on top of Open Policy Agent, we built a control plane, a management plane to help organizations really put OPA into production and operationalized OPA. >> An OPA is Open Policy Agent. That's what the company actually developed with CNCF, correct? >> So, we actually founded Open Policy Agent and then we contributed Open Policy Agent to CNCF. And the real goal of contributing the Open Policy Agent to CNCF was we believe that we want to get authorization defacto in the market, right? And the only way to get something out there that everybody uses is to put it into the open source and having an entity like the CNCF supporting the project. So, really it's about getting everybody, all enterprises and vendors to use Open Policy Agent as a way of solving authorization for the cloud native environment. >> So you say Styra is reinventing policy and authorization for cloud native applications, your target audience, security folks, developer folks, what changes has cloud native brought to security and development teams? >> Sure, so what changes has cloud native brought to security and development teams? So fundamentally there've been three changes in the marketplace. One, as you know we're shifting from this monolithic architecture of building applications to now this new distributed architectures of kubernetes, microservices and Deep-coupled architecture. So fundamentally the way we build applications is fundamentally changed because everybody wants to have scale up and scale down and so forth. Second, the way we actually developed software, we've moved now to a DevOps model where we're doing more things earlier on in the cycle so we can innovate faster and we're producing code on an hourly basis versus when I joined the industry which was probably three releases a year. And then thirdly which is kind of a major topic that all of us kind of understand is our focus on privacy and security is higher than it's been before. And if these applications are going to be way more complex and more distributed and we're going to innovate faster than the way we focus on security and privacy has to be done differently as well. And if we don't do it differently, then we're going to have to all the breaches that we had in the previous generation of the app stack. >> And we don't want that, but you're right privacy and security are increasing concerns in any environment. How do you help address those and also with the thought of privacy and security are going to be concerned for quite a long time? >> Yeah, so let me take a step back. So how do we address privacy and security? So, at a fundamental level, authorization is a foundational part of security and authorization has never really been solved or re-imagined ever for the last 50 years or so. Every application developer or security vendor has built authorization into their own stack and done it in a very proprietary way. And it's been locked away within these applications and these stacks and so forth. So what happens now when you've got a highly distributed environment is that you've got so many moving parts, you still need to apply authorization. So, the way we've tackled it is by building Open Policy Agent. And there's three fundamental kind of tenants around Open Policy Agent that make it really ideal for this cloud native environment. Number one, it's policy as code and everything in the market now, everything is as code. You buy infrastructure as code. So this is now policy as code. So you can describe in a declarative model, how you want the policy for a system to be developed and you can use the language called Rego to do that. Second is the fact that all the cloud native projects out there which are all developed based upon open source technologies, kubernetes, microservices, envoy, SDO, cafco, all these kinds of buzzwords you hear in the marketplace, they all integrate with Open Policy Agent already. And then thirdly the architecture of Open Policy Agent is that it's distributed, which means that it's ideally suited for this distributed architecture for cloud native. And those are the three kind of characteristics of Open Policy Agent leading to developers loving it. And when I say they love it, we've got hundreds and thousands of users of Open Policy Agent. When you go to the CNCF shows co op con earlier this year and there's two more coming this year. There's many, many talks on it. You've got cloud vendors like Google and Microsoft adopting Open Policy Agent, got a lot of enterprises adopting Open Policy Agent. So, that's really fundamentally what we've built is we've built an authorization architecture for this new world to really address the security and privacy concerns, which have always existed and I'm going to be more exponential in this new world. >> And I think you've also built a community around OPA. Can you share a little bit of information about that and how they help with the co-development and even some of the other things that you're commercializing? >> Sure, yeah. So, now what have we done in from a community point of view with Open Policy Agents? So yeah, the community is a integral part of any open source project and we're lucky to have a great community. We've got a great community of enterprise users of Open Policy Agents and vendors as well, vendors like Microsoft and Google who are now contributing to OPA and building it up. And for me, the most important part of a community is that you learn how enterprises are using your software and they share ideas and they share use cases and you're able to innovate really, really fast. And what we've learned from that is the use cases that they use Open Policy Agent for, for instance, one of the major use cases for Open Policy Agent is for kubernetes Admission Control. So, essentially we can test the configuration of an application which is described in a file called YAML before it goes into production. So, think of it as pre-production tests, but companies are using it for microservices and applications and data and so forth. So, it helps us understand what they're using it for, but also we use it to help us develop our commercial product, which is the management control plane for OPA. So, we learn about what they're missing in the open source project that we can use to build our commercial product >> which is ready for enterprise use. >> So you've had a lot of success with OPA. Talk to me about Styra DAS and why the need for that? >> Sure, so why do we need Styra DAS recognizing that OPA is very, very successful. So, the fundamental difference is OPA is a very focused on developers and it's very focused on an environment for an individual node or cluster, but it doesn't have all the enterprise features necessary for a real enterprise to go into production. So what we notice is companies use OPA for pre-production, but when they want to go into production, they need a user interface. They need a way to author policies, distribute policies, monitor policies, do impact analysis and a whole bunch of other features and capabilities that are needed for enterprise deployments and so forth. So that's a fundamental difference between OPA and the commercial product. The commercial product is really operationalizing in OPA for an enterprise deployment. >> So the relationship between Styra and OPA seems very collaborative to me that what you just described with the commercial product of Styra DAS is really one that was developed based on what the OPA community and Styra have learned together? >> Correct, Yes. So, OPA was created by the CTO, the founders of the company saw early on several years ago, the need for distributed architectures and the need for unified policy so they left and created OPA. And from day one they wanted to get OPA into everybody's hands. That's why they contributed it to open source as part of CNCF. And then the next kind of strategy is to focus on the control apps aspects, the enterprise aspect. So yes, the same team that created OPA is the same team that's creating the Styra DAS commercial offering as well. >> So from the enterprise perspective, talk to me about some of the companies that you're talking to. I imagine any organization that's focused on cloud native, but any industry in particular that you see is really kind of leading edge right now? >> Yeah, so which industries are we talking to in terms of using Styra DAS and OPA? What we've actually found it's across the board. And we've seen in the early days that financial services and high tech were using OPA, but now it's really across the board. So it's all verticals really. And what we've noticed is any organization which is going through a cloud transformation project where they're either building new applications based upon cloud native app stacks like kubernetes and microservices and so forth or shift to the cloud are the companies that are also adopting OPA and the Styra DAS product, right? Because it's all part of the same solution set. And what we're noticing now and this is a fundamental difference is platform architects and developers are kind of prime to use these technologies. They learn about these technologies by going to the conferences and unlike the past which was very much top down selling from the sea level down, this is very much bottomed up. So developers learn about OPA from going to the conferences. They use it within their own environment and then they tell their management that, "Look, we're using OPA already. "We're missing these capabilities," or they come to us and we educate them about the Styra DAS product and so forth. So it's a very different sales model as well and that's why it's very important for ourselves and any open source company to really keep developers happy and provide a solution, that's meeting their requirements. >> On that side with so many of us and developers included working from home for the past nearly four months. We now are doing things like this virtual conversations, virtual events, how is Styra helping to continue to feed and educate those developers so that they can understand how you can impact their job functions and how they can then elevate you guys up the stack. >> Sure, so what's changed over the last three months or so in the market as a consequence of COVID-19 and from an educational point of view. So, what we've seen is fundamentally in the early days of COVID-19 everybody was kind of get the head around how to work from home and so forth, but what we've seen across the all verticals is developers have now really focused on educating themselves and just as a data point and the audience that we get to the OPA website is as high as it's ever been for the last three months. And what we're doing as a company is a lot of training sessions, video content, write-ups, blogs and so forth, right? And really helping the community learn about OPA and how to solve these kind of fundamental problems around policy and authorization within the environment. We've also been helped by the community as well. So there's been talks about a number of companies, Microsoft, Google, Palo Alto had a talk and many many companies are talking about OPA now and I love it because ultimately being an open source company and building a project which we want to become defacto, we want to raise the bar for security across the world, right? And if we can do that then it's going to be an achievement for us and it's very gratifying knowing that we're really fixing security problems for organizations because ultimately we always want to be able to use an application or a banking service and not worry about privacy and security concerns and that's ultimately what we're all after. But this is such a fundamental component that once we want to have developers learn this now because if they can incorporate this into the DevOps app stack then in future years when these applications are built and they're exposed there'll be more secure. >> And so it sounds like maybe there's even more engagement now during COVID when everybody is at home. Tell me about some of the things that are coming down the pipe for Styra in light of all of this exciting collaboration with the community. >> Sure, yeah. There's definitely been way more collaboration as a consequence of COVID-19. People are at home and they're focusing and they're going through learning sessions and browsing the website going through the video content and so forth. So what we're engaging as much as we have ever been, in fact I would argue that we're engaging even more so now, because it's just a different environment to work in. And what we're focused on now is really adding more features to the Styra DAS product, just to step back for a second, Open Policy Agent works across the cloud native stack and Styra DAS has been focused first on the kubernetes use case and now it also supports microservices as well. And then what we're continuing to do is add more of those enterprise features into Styra DAS and move up and up across the stack. But it is all driven by developers that we're talking to on a daily basis and that's leading to where the project is moving forward and the development for the roadmap and so forth. >> And Styra DAS was only launched in 2019, is that correct? >> 2019 yes, that's correct. That's correct. Yes, time flies, right? So, yes. >> A lot of change and a lot of development in a short period of time. >> That's right and 2019 was a big year for us, right? We started last 2019 with a soft launch at the RSA conference and we finished 2019 with series a funding led by Xcel. And yeah, it's great to see how the commercial product has been gaining traction in the marketplace as well as OPA as well and I think it's a combination of events. One, the fact that cloud native is now really well understood. Second, the fact that kubernetes at the beginning of 2019, it was still, "What does kubernetes mean, "is it going into production?" Now kubernetes is absolutely going into production and there's such a desire for organizations to make sure that security and policy and compliance are resolved before applications go into production otherwise we're going to have the same kind of challenges we had with previous app stacks. >> Well, the momentum is certainly with you. I can definitely hear that in your voice bell. Thank you so much for joining me talking about Styra, how you're reinventing policy and authorization for cloud native applications. >> Thank you, Lisa. >> For my guest Bill Mann, I'm Lisa Martin. You're watching the Cube Conversation. Thanks for your time. (upbeat music)

(upbeat music) >> Narrator: From the Cube Studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is the Cube Conversation. >> Welcome to this Cube Conversation. I'm Lisa Martin, excited to talk to the CEO of Styra, Bill Mann today. Bill, welcome to the Cube. >> Hi Lisa, how are you doing? >> I'm doing well. I should say welcome back. You've been on the Cube at a previous company, but we're excited to talk to you today about Styra, what's going on? So let's go ahead and start informing our audience who Styra is and what you do? >> Sure, so who Styra is and what do we do? So Styra is a company that's focused on reinventing policy and authorization in the cloud native stack. We're the company that created an open source project called Open Policy Agent, it's part of CNCF. And on top of Open Policy Agent, we built a control flame, a management plane to help organizations really put OPA into production and operationalized OPA. >> An OPA is Open Policy Agent. That's what the company actually developed with CNCF, correct? >> So, we actually founded Open Policy Agent and then we contributed Open Policy Agent to CNCF. And the real goal of contributing the Open Policy Agent to CNCF was we believe that we want to get authorization defacto in the market, right? And the only way to get something out there that everybody uses is to put it into the open source and having an entity like the CNCF supporting the project. So, really it's about getting everybody, all enterprises and vendors to use Open Policy Agent as a way of solving authorization for the cloud native environment. >> So you say Styra is reinventing policy and authorization for cloud native applications, your target audience, security folks, developer folks, what changes has cloud native brought to security and development teams? >> Sure, so what changes has cloud native brought to security and development teams? So fundamentally there've been three changes in the marketplace. One, as you know we're shifting from this monolithic architecture of building applications to now this new distributed architectures of kubernetes, microservices and Deep-coupled architecture. So fundamentally the way we build applications is fundamentally changed because everybody wants to have scale up and scale down and so forth. Second, the way we actually developed software, we've moved now to a DevOps model where we're doing more things earlier on in the cycle so we can innovate faster and we're producing code on an hourly basis versus when I joined the industry which was probably three releases a year. And then thirdly which is kind of a major topic that all of us kind of understand is our focus on privacy and security is higher than it's been before. And if these applications are going to be way more complex and more distributed and we're going to innovate faster than the way we focus on security and privacy has to be done differently as well. And if we don't do it differently, then we're going to have to all the breaches that we had in the previous generation of the app stack. >> And we don't want that, but you're right privacy and security are increasing concerns in any environment. How do you help address those and also with the thought of privacy and security are going to be concerned for quite a long time? >> Yeah, so let me take a step back. So how do we address privacy and security? So, at a fundamental level, authorization is a foundational part of security and authorization has never really been solved or re-imagined ever for the last 50 years or so. Every application developer or security vendor has built authorization into their own stack and done it in a very proprietary way. And it's been locked away within these applications and these stacks and so forth. So what happens now when you've got a highly distributed environment is that you've got so many moving parts, you still need to apply authorization. So, the way we've tackled it is by building Open Policy Agent. And there's three fundamental kind of tenants around Open Policy Agent that make it really ideal for this cloud native environment. Number one, it's policy as code and everything in the market now, everything is as code. You buy infrastructure as code. So this is now policy as code. So you can describe in a declarative model, how you want the policy for a system to be developed and you can use the language called Rego to do that. Second is the fact that all the cloud native projects out there which are all developed based upon open source technologies, kubernetes, microservices, envoy, SDO, cafco, all these kinds of buzzwords you hear in the marketplace, they all integrate with Open Policy Agent already. And then thirdly the architecture of Open Policy Agent is that it's distributed, which means that it's ideally suited for this distributed architecture for cloud native. And those are the three kind of characteristics of Open Policy Agent leading to developers loving it. And when I say they love it, we've got hundreds and thousands of users of Open Policy Agent. When you go to the CNCF shows co op con earlier this year and there's two more coming this year. There's many, many talks on it. You've got cloud vendors like Google and Microsoft adopting Open Policy Agent, got a lot of enterprises adopting Open Policy Agent. So, that's really fundamentally what we've built is we've built an authorization architecture for this new world to really address the security and privacy concerns, which have always existed and I'm going to be more exponential in this new world. >> And I think you've also built a community around OPA. Can you share a little bit of information about that and how they help with the co-development and even some of the other things that you're commercializing? >> Sure, yeah. So, now what have we done in from a community point of view with Open Policy Agents? So yeah, the community is a integral part of any open source project and we're lucky to have a great community. We've got a great community of enterprise users of Open Policy Agents and vendors as well, vendors like Microsoft and Google who are now contributing to OPA and building it up. And for me, the most important part of a community is that you learn how enterprises are using your software and they share ideas and they share use cases and you're able to innovate really, really fast. And what we've learned from that is the use cases that they use Open Policy Agent for, for instance, one of the major use cases for Open Policy Agent is for kubernetes Admission Control. So, essentially we can test the configuration of an application which is described in a file called Yammer before it goes into production. So, think of it as pre-production tests, but companies are using it for microservices and applications and data and so forth. So, it helps us understand what they're using it for, but also we use it to help us develop our commercial product, which is the management control plane for OPA. So, we learn about what they're missing in the open source project that we can use to build our commercial product which is ready for enterprise use. >> So you've had a lot of success with OPA. Talk to me about Styra DAS and why the need for that? >> Sure, so why do we need Styra DAS recognizing that OPA is very, very successful. So, the fundamental difference is OPA is a very focused on developers and it's very focused on an environment for an individual node or cluster, but it doesn't have all the enterprise features necessary for a real enterprise to go into production. So what we notice is companies use OPA for pre-production, but when they want to go into production, they need a user interface. They need a way to author policies, distribute policies, monitor policies, do impact analysis and a whole bunch of other features and capabilities that are needed for enterprise deployments and so forth. So that's a fundamental difference between OPA and the commercial product. The commercial product is really operationalizing in OPA for an enterprise deployment. >> So the relationship between Styra and OPA seems very collaborative to me that what you just described with the commercial product of Styra DAS is really one that was developed based on what the OPA community and Styra have learned together? >> Correct, Yes. So, OPA was created by the CTO, the founders of the company when the team was actually part of Nicira and they left Nicira which got acquired by VMware and so on early on several years ago, the need for distributed architectures and the need for unified policy so they left and created OPA. And from day one they wanted to get over into everybody's hands. That's why they contributed it to open source as part of CNCF. And then the next kind of strategy is to focus on the control apps aspects, the enterprise aspect. So yes, the same team that created OPA is the same team that's creating the Styra DAS commercial offering as well. >> So from the enterprise perspective, talk to me about some of the companies that you're talking to. I imagine any organization that's focused on cloud native, but any industry in particular that you see is really kind of leading edge right now? >> Yeah, so which industries are we talking to in terms of using Styra DAS and OPA? What we've actually found it's across the board. And we've seen in the early days that financial services and high tech were using OPA, but now it's really across the board. So it's all verticals really. And what we've noticed is any organization which is going through a cloud transformation project where they're either building new applications based upon cloud native app stacks like kubernetes and microservices and so forth or shift to the cloud are the companies that are also adopting OPA and the Styra DAS product, right? Because it's all part of the same solution set. And what we're noticing now and this is a fundamental difference is platform architects and developers are kind of prime to use these technologies. They learn about these technologies by going to the conferences and unlike the past which was very much top down selling from the sea level down, this is very much bottomed up. So developers learn about OPA from going to the conferences. They use it within their own environment and then they tell their management that, "Look, we're using OPA already. "We're missing these capabilities," or they come to us and we educate them about the Styra DAS product and so forth. So it's a very different sales model as well and that's why it's very important for ourselves and any open source company to really keep developers happy and provide a solution, that's meeting their requirements. >> On that side with so many of us and developers included working from home for the past nearly four months. We now are doing things like this virtual conversations, virtual events, how is Styra helping to continue to feed and educate those developers so that they can understand how you can impact their job functions and how they can then elevate you guys up the stack. >> Sure, so what's changed over the last three months or so in the market as a consequence of COVID-19 and from an educational point of view. So, what we've seen is fundamentally in the early days of COVID-19 everybody was kind of get the head around how to work from home and so forth, but what we've seen across the all verticals is developers have now really focused on educating themselves and just as a data point and the audience that we get to the OPA website is as high as it's ever been for the last three months. And what we're doing as a company is a lot of training sessions, video content, write-ups, blogs and so forth, right? And really helping the community learn about OPA and how to solve these kind of fundamental problems around policy and authorization within the environment. We've also been helped by the community as well. So there's been talks about a number of companies, Microsoft, Google, Palo Alto had a talk and many many companies are talking about OPA now and I love it because ultimately being an open source company and building a project which we want to become defacto, we want to raise the bar for security across the world, right? And if we can do that then it's going to be an achievement for us and it's very gratifying knowing that we're really fixing security problems for organizations because ultimately we always want to be able to use an application or a banking service and not worry about privacy and security concerns and that's ultimately what we're all after. But this is such a fundamental component that once we want to have developers learn this now because if they can incorporate this into the DevOps app stack then in future years when these applications are built and they're exposed there'll be more secure. >> And so it sounds like maybe there's even more engagement now during COVID when everybody is at home. Tell me about some of the things that are coming down the pipe for Styra in light of all of this exciting collaboration with the community. >> Sure, yeah. There's definitely been way more collaboration as a consequence of COVID-19. People are at home and they're focusing and they're going through learning sessions and browsing the website going through the video content and so forth. So what we're engaging as much as we have ever been, in fact I would argue that we're engaging even more so now, because it's just a different environment to work in. And what we're focused on now is really adding more features to the Styra DAS product, just to step back for a second, Open Policy Agent works across the cloud native stack and Styra DAS has been focused first on the kubernetes use case and now it also supports microservices as well. And then what we're continuing to do is add more of those enterprise features into Styra DAS and move up and up across the stack. But it is all driven by developers that we're talking to on a daily basis and that's leading to where the project is moving forward and the development for the roadmap and so forth. >> And Styra DAS was only launched in 2019, is that correct? >> 2019 yes, that's correct. That's correct. Yes, time flies, right? So, yes. >> A lot of change and a lot of development in a short period of time. >> That's right and 2019 was a big year for us, right? We started last 2019 with a soft launch at the RSA conference and we finished 2019 with series a funding led by Xcel. And yeah, it's great to see how the commercial product has been gaining traction in the marketplace as well as OPA as well and I think it's a combination of events. One, the fact that cloud native is now really well understood. Second, the fact that kubernetes at the beginning of 2019, it was still, "What does kubernetes mean, "is it going into production?" Now kubernetes is absolutely going into production and there's such a desire for organizations to make sure that security and policy and compliance are resolved before applications go into production otherwise we're going to have the same kind of challenges we had with previous app stacks. >> Well, the momentum is certainly with you. I can definitely hear that in your voice bell. Thank you so much for joining me talking about Styra, how you're reinventing policy and authorization for cloud native applications. >> Thank you, Lisa. >> For my guest Bill Mann, I'm Lisa Martin. You're watching the Cube Conversation. Thanks for your time. (upbeat music)

>> Narrator: Live from Washington, D.C. It's the CUBE. Covering Boomi World 19. Brought to you by Boomi. >> Welcome to the CUBE, about the leader in live tech coverage. I am Lisa Martin with John Furrier. We're at Boomi World 19 in Washington, D.C. Please welcome one of Boomi's award winners to the program from Gilead Sciences we have the Director of IT, Murali Anakavur. Welcome Murali and congratulations on Gilead being the 2019 Change Agent Award winner for North America. >> Thank you so much Lisa. It's good to receive the award. Lot of efforts have been put in place by our folks. I'm very honored and privileged to receive this award. >> Fantastic. So give our audience an overview of Gilead Sciences. What you guys do and then we'll start getting into the IT infrastructure and all of the great things that you have done with Boomi. >> Definitely. Gilead has been in the forefront of meeting an aspect of medical needs of patients worldwide. Clearly, it's the company, if you recollect, solve the (mumbles) problem in the world. There were the cured from the cure for it that started the company originally to come up to where they are today. They are in the forefront of science and R and D and technology when putting therapeutics for inflammatory infectious, and recently in big cancer treatments and other treatments. So the world is opening up big time. Our focus is to resolve and make medical needs. The company is so focused and they want to provide the cure for all these and it's so passionately too. So all kinds of R and D going on. I'm so honored to be working for a company which is doing this great need for humanity, frankly. >> Absolutely. So the cure for Hepatitis C, that's huge. Whenever we talk about technology where it impacts every single person on this planet, infectious diseases, cancer as you mentioned, it's really... It's pulverizing people understand it. It's--there's a lot of gravity around it. Talk to us about what you needed to implement, from a technology infrastructure perspective, to connect all of these different data sources, so that the next cure for all these different diseases has a foundation from which providers can actually link data. >> Obviously. >> Talk about it. There are some backing sources company, any company needs, let's say ERP system, need some CRM system. Those are good. But our company has the complexity of manufacturing system that needs to make medicines. Company's complexity is the lab systems, R and D systems, product life cycle management systems where things originated in a little molecule for the compound they call it, and it expands into what they say clinical studies on a medicine. So you can imagine the plethora of system that make this happen. So what happens in this environment is now people bring up systems for what they need and ERP does what they need. All of the sudden, "I can't do without customer data." "I can't do without my patient data." "I can't do without my item data." "How do we get the data?" So it becomes--begs the question like, "Oh my gosh, okay we got all these complex systems in place, how are you going to share the data? Who's the master? Where's the source of truth? So all those sort of begging question is that, kind of start up the landscape of integration. So that's where we are. Launched that previous legacy systems for SOA that we have currently. Mostly call it the SD enterprise service. that shares data within the premises. Guess what today? They want, "Hey I've got this Cloud system that I'm accessing. I'm going to buy this sales force commercial systems that could enable me to launch my commerce market better. How do we deal with these guys? How do we reach out to those folks? How do I make my engagement app on the events for doctors? How do I connect with my patients? All these are big question that've been asked. There was a need for system that'll kind of take care of all these diverse platforms in the Cloud on Prim, connect them together, so the data sharing happens. That was the biggest challenge that we have kind of solve right now. And then with Boomi coming on to our platform since a couple of years from in the past, we have matured into a place where we're going to launch a lot of things on Boomi and we are looking forward to it eagerly to consolidate all those legacy innovation platforms into the Boomi world infrastructure. So i's exciting. >> Talk about the IT landscape in your company. What's going on there? How is the structure? What are some of the environment look like? Is it transforming the roles of the people? Stacking and wrecking, is it Cloud, Hybrid, what? Talk about your environment. >> Fantastic. I think the very question getting into our pillars or what we do in IT, right? Our pillars are very simple. First thing is core services, you've got to make it--keep the lights on you've got to sure things are working fine. The next thing we adhere to is people. Who do we need to make all this happen? ITs people, acknowledged management, retain people, the best talent, get the best talent. The third pillar we have is the enabling of technology. And that's where some of us come in to enables. How do we migrate Cloud? Let's say we have a big data platform on an infrastructure, adopt infrastructure, tear down infrastructure on-prem. And you what, it's a plan's base. So the data growth, it's enormous these days. So we are talking about Cloud. We are already have plans, we already have infrastructure in Cloud that we are moving to. So if you look at it, the company's so focused not only on technology which is required to, in this day and age, to talking about data, talking about expansion, elasticity and a computing power you need, yeah, here we are with opting we'll be multicloud recipient and beneficiary, but at the same time we're also focusing on people and the core services we provide as IT. IT is technical, non-technical-- >> So you have multiple Clouds right now? >> Exactly. >> Amazon, Azure. >> Yup, we will have a multi Cloud eventually. Not that everything is online and in perfection, but our plan is to have a multi Cloud strategy going forward because the amount of things that coming to our landscape. >> You're on classic hybrid right now, you've got it all on premises. >> Yes. >> Some Cloud going on. >> Absolutely, absolutely. >> So let's talk about business transformation, digital transformation. You did a great job of articulating the business challenge, the challenges that you needed to solve. From an IT perspective, you have all the hybrid multi Cloud environment. Where did the digital transformation initiative come from? Was it the business saying, "We have so much data and desperate systems. We want to be solving more real world problems. Hi, IT, help us build the foundation that allows that." >> It's fantastic. If you look at our company, our sheer full task is digital transformation. Not just IT or COO. CEO talks about our digital transformation. So everybody, in fact, it was questioned. "Hey, we want to be digital." What does it mean to be digital? Because thing comes up. So in the landscape of ITVR, we are going to be a digital-enabled company. We're going to define what it means. To me personally, digital-enabled means, "Hey, I need to share a piece of data across the landscape, whoever needs it, whenever they need it or where they need it." That's called the digital transformation if you ask me because that enables other systems to consume it, and then provide the care and attention it needs. Be at our customers. Customers are patients. Be at our hospitals that we work with. They're our customers. Employ our customers and turn that, it could be your portal. So we are attacking it from multiple points of view. You want to make sure the technology enablement moving forward in innovation. We care for all these areas of customers where we can really digitally enable them. So focus is not just one point of digitalization, it's customers and patients. How can we give them access? How can we get the feedback? All of them fall into 360 degrees of data enablement. It's so focused and we're so thrilled to have such (mumbles) that can pay a lot of attention to all these things. I think it'll be transforming our company a big time in the next few years with the digitalization that we're looking forward to. Mobile applications. All kinds of things are coming up. >> So why Boomi? Boomi is a Cloud native platform. We saw the video and if you saw that technical keynote this morning that the first videos started up with a few minutes of all the areas in which they were first. But they took this big bet back in 2007 when they were found that they are this single instance multi technic Cloud application. What differentiated Boomi when you guys were looking for the right partner with which is standardized? >> It's interesting because we like the Cloud part. Same time being (mumbles) country and industry, they said, " I can't (mumbles) put it on the Cloud." I mean this was about four years back. Remember, things were not really stable at that time. Or people are wondering, "What? Cloud?" "Where can I put my data?" We chose the Boomi hybrid model which is awesome because it gave us the benefit of both, of material that's in Cloud, I'm taking care of anything that you need to do material, I'm taking care of my processing on site. So that key was that bang say, "Oh wow, that's a fantastic option to have. It's a (mumbles) infrastructure. People can build things faster on Prim, run your case, data cases on Prim, but you have all Cloud metadatas protecting you (mumbles) Everything is easy, (mumbles) SHA. So all those were factors when we decided to go in to Boomi. But we see among others as full. But then the speed of market, less call framework, and also the roadmap they'll have for them. That's very important for us. I mean first thing in technology I want to go for next five years, ten years. Are you welcome with me in the technology? Are you making insights as we talked about today? (laughs) I'm just paraphrasing it. But those all things matter to us. In words, mine is protected. We don't end up with some debt, right? Like they model this platforms to be up to date. So those were our key factors in moving forward with Dell Boomi. >> And so let's talk about some of the business outcomes. You've mentioned a few. But let's look at them kind of categorically. If we look at kind of this over this polarizing industry, being able to study different aspect of man diseases and identify cures for them hopefully, what are some of the business outcomes that you guys are achieving so far with them. You're a Change Agent Award winner, so give us some of those really big wins that you've seen to dates? >> How to be proactive, right? It's a game, it's a data game these days. The more data you have aboard the decision you can make, you're going to differentiate in solving problems, and mean competitive as well. We are trying to see these aspects in the data that we can collect from all places. Now once you have the data, you need some kind of integration that needs to happen to process the data, to share the data to people who need them. That's why integration comes in. Obviously there are other areas where we do big data processing. We need to have some kind of a cluster to compute them and cue some analytics for scientist to see, "Hey, I've got this data. This was inference." And now we can introduce that integration to cue them all the data that they need. What does it take? In my opinion, days and months too can infer through these files and files of data, takes less than 10 minutes for people to now infer. >> Dramatic speed of (mumbles) here. Wow, elaborate on that a little bit. >> And what happens is when you get this huge epidemiology data on the world, you've got thousands and thousands tera bytes of data. Without proper computing and the resources and the modern platform, it's tough for you to count those data to come out with some analytic that people can use. You can ask queries like, "Hey, this disease happens in this area. Tell me the percentage that is relevant to this disease in this area that I need to concentrate on solving the problem." You want to solve big problems and you want to make sure the population benefits from that. So this kind of data gives you inferences that people can research on and say, "Hey, I'm going to focus on this area. It's very predominant." And let's say Africa nation, population is almost about 3 billion, 4 billion people in the world. So let's focus on that disease that gives some traction going on. And that's how you solve the world's problem, one by one, one step at a time. I'm so happy to be involved in that kind of enablement because I'm a very very minuscule part of the whole deal because we work with scientists who are fantastic, who are biologists, who are researchers. Our act in this helps them get to what they need to do. We are completely at their service for what they need and then we just want to enable things for them, make things faster, make the hope comes for them to an R and D, to be more clearer. So that's where we come in. It's more like a service, but industry aspect within the company, but then we are fully fortunate to work for a company that cures diseases and we are part of that journey that they're going through. >> You've just articulated beautifully why you guys won in the Change Agent category. Morally that was outstanding. Congratulations on what you've achieved so far. I'm sure, I'm excited to hear next year where the business goes. We appreciate your time. >> Thanks a lot, Lisa. Nice to talk to you guys today. >> Likewise, thank you. >> For John Furrier, I'm Lisa Martin. You're watching the CUBE from Boomi World 19. (lively music)

>> Live from Orlando, Florida It's the que Covering Enterprise Connect twenty nineteen. Brought to you by five nine. >> Hello from Orlando, Florida Lisa Martin with the cubes to amendments here with me as well. We are at Enterprise Connect twenty nineteen, and we've been graciously hosted this week by five nine. We're pleased to welcome to the Cube for the first time the V p of product marketing from five nine. Scott Coleman Scott Thank you so much for joining me today >> to be here. >> So Day three of this event. Biggest enterprise Connect. If they've had sixty five hundred attendees expected, we're in the Expo Hall, which you could hear all the buzz behind US one hundred forty or so exhibitors announcing new products, new services, etcetera, all talking about putting the customer at the heart of the contact center. Why is that so important >> now? It's a great question, and to your point about the show itself in the floor. Really, The Context center is very much at the center of actual floor itself, in terms of who's hear what they're talking about. It's not an after thought. It's really I think it's an acknowledgement that companies are realising that they have to take the customer experience seriously. And the context center is that point where you either reinforce the brand or you rode it right. So this is now the opportunity for companies to think a little differently about what role in place and how they're going to use it to really build a better relationship. >> Scott. It's been interesting. Lease and I came in tow this show being the first time that we've been at the show. But, you know, we're both consumers. We've looked through it, you know? I think back to the last decade or so there was outsourcing. There was technology, which is I'm just going to say, you know, some of the big technology companies I want to call them. Are you kidding? You can't write hide that. I can't even email them if I wanted to it. You know that the customer relation stupid, very different. But today it feels like the pendulum is swinging back the other way, right, that that customer relations we know when I need to talk to somebody. It's important that I do get to talk to a person and technologies an enabler of that, >> Yeah, absolutely, you know, And the question is, why? What changed? Right? And there's a couple things that really changed to make that happened. Probably the primary thing is customers had more choice. And then the voice right there more choice. Never before. It's no longer the issue, depending on whatever industry you're in, that you're only stuck with a certain cable provider or a retailer down the street I can buy from anywhere in the world, you know. And so I have choice there. There's disrupters in every industry as we've seen over the last decade, and so that that's one element. And just as importantly, they have a voice used to be. I could go home and complained to my my wife I could claim by family members my friends. Now I can actually amplify that through social media and other elements. So not only do I have a ability to move, but also in terms of the voice. I actually have a bigger impact on the brand, right, and those there is really big elements there. >> So along those lines, if you look at the consumer behavior is being so influential companies are they looking at it as more of an opportunity. Go. All right. Maybe we have a few channels. Maybe we're voice only. What? How does finding help a customer that might be voice only, Or maybe multi channel get to Omni Channel so that they can, as I loved what you study. No thiss contact senator. Moment in time is an opportunity to improve the brand or eroded. So how are they working with you guys to enable a customer to be able to have their issues identified, resolved quickly through various channels? >> What's the first thing is when you look at Omni Channel is why, what? Ultimately you want to make sure that you're o engaging with your customer over them channel on the method that they prefer. Right? That's the most important element there. So it's not about having ten, fifteen different ways to communicate. It's letting them do it when, where and how they choose to. That's the most important thing, and it's also then understanding. What else do they expect? Well, first in the expect is they want you. They want you to know them. You know, our research that we've done through our customer service index and a light consistently shows that people first and they want to know is Nomi understand my relationship. So when we work with our customers, we really focus on that as they engage over a phone call and email a chat, another channel. Always make sure that you, at the heart of it, you understand who they are. And one of the ways to do that is draw that information and make it available to the agent. So integration with serum systems with workforce optimization, others is critical so that when they're at the point of engagement, that moment of truth, they're able. Teo acknowledge the customer and probably have a really good understanding of not only their history, but why they're why they're engaging with you. Why they're calling are contacting >> Scott. Wait. We had a great conversation with Darrell, who's part part of your team, about how cloud not only enables the speed and agility, but, you know, I could start using new features much faster and easier. Then, in a non cloud environment. Wonder if you might have some customer stories to help illustrate some of these journeys as to you know, maybe just what they've gotten from Day one, but also, you know, subsequent to your customers that have been with you for a while. The rights that they keep innovating and adopting new things along the road. You >> know, it's funny. I I think of a couple examples. One. We had a customer who, newer, a newer company, a bit of a destructor in their industry, and they actually started out with digital channels on Lee. They had no voice. So they were offering email and Chad and other methods. And then, to their surprise, they found that they needed to introduce voice. They were deal with more millennials folks that they assumed were going to communicate over the right. Well, what happened was there were certain times when they wanted to actually communicate over Voice Channel. Maybe it was a financial issue. Maybe it was emotionally charged or something like that. So they brought. That is, we were able to help them by integrating in first. So they're there Syria to be able to digital channels and then open up voice. Now the other side of it is, we have customers who will start me with Voice Channel, and then they again understanding your customer, your end customers what do they want? Introducing a chat and making sure that those agents have all the relevant information they need to be able to do that. Realizing that email is still around after all these years, there's sometimes you want to communicate that way because you can send a lot of information. So it's really about building out a plan with the customer understanding. What is that customer journey of their customers? And how do they best a treated and helped him along the way >> on that customer journey front, I'm wondering, are the majority of customers that you're meeting with not aware of their customer journey and their customer preferences for different channels? Is that something that you're finding that you're actually from a consul? Tate of Perspective saying. Actually, what's idea here is to really not make assumptions on DH to actually do some investigations, and some studies tto learn. Is that a part of the process with you guys? It's a little >> bit a little bit of that. It's also sometimes that there's a journey purchase journey, a service journey in account management journey. You know the change. Change certain things about your service profile, but it's been developed over time, just through kind of osmosis, right? And so sometimes it's stepping back and understanding. What is that? Defining that journey and saying Where Artless critical path, where it may break down where problems occur So really drawn from that and understanding where those two points where we can Actually, and I say we being with customer helped them to be able to make that better overcome frustrations and delays and so on. So that's a really important element there in terms of channels. It's really just listening, listening to customers. Listen to agents listening to people that are on the front line talking to customers day in, day out and in realizing also, what's the profile of your customer? Your buyer? You know, not everybody is the same, and it doesn't always fit based on age or other demographics. You know, I have my father's eighty nine years old and weighs text messages all the time, you know, And once he embraced that, it's a wonderful method of communication. So, you know, there's a lot of things you have to look at along the way. >> Scott one of one of the biggest challenges in technologies we need to balance simplicity with the custom, ization and all of the choice in the world. I wonder if you might be able to comment. We know you know, from a customer standpoint, from agent standpoint. We wantto get them. The information they want when they need it is simple. It's possible. But on the back end, you know, we look at how many partners five nines has in all the different technologies you work with. You know, my business needs, you know, thes seven letters in the alphabet, not these other things. So how do you balance that from a messaging? And from a product standpoint, well, >> one of the >> things I realized is that one size doesn't fit. All right, companies have are different sizes. They're different complexity preferences along the way. So we really focus on how do you adapt the context center to the needs of that business? And that could be. Sometimes they have preferred vendors. So I'm a sales force, or Oracle or Mike saw for service now or whom you name it shop. I want to continue to use that it may be on work first optimization that I want. I have a certain set of capabilities I required that fits a particular vendor. Not so we really try to. And this is the beauty of the cloud is we can host. You know, elements in there in the case of, like, workforce optimization or in a grate in the case of serum to make that seamless. When you look at it from an agent perspective, it's all about giving them a common look and feel, you know, one term that's been really used. A lot of the show is the single pane of glass, the one agent desktop where they can really navigate because we've all experienced when you call into a context center and the agent is frustrated and these are complaining about the system, I'm sorry I'm trying to figure this out O this darn system. Oh, it's gotta wait or I have to find your information. I don't care. I'm the consumer. I just want my problem solved and frankly, the agents frustrated. But by integrating it within a with the serum, we could have all that information on the desktop on ly the relevant information that the agencies at that moment, you know, if I'm dealing with the purchase. Then I need that information on agent that's going to help me along the way. I don't need to worry about other factors, and I want to be able to customize that a little bit, too. My the way I behaved as an agent. So it is about convenience, intuitiveness, you know, and just ease of use. Long way. >> I'm curious. So here we are. Day three, Almost time with Enterprise Connect. Nineteen. You've been at the event the whole time. What are some of the things that you're hearing say from the analyst community? That is exciting. You about one. The direction that the contact center market is going into, what five nine is going to be able to deliver the rest of the year and beyond. >> You know, it's interesting. A couple of years ago, the buzz and the talk wass voices dead. It's all about everybody's going digital. And that was because of the increase in the number of transaction interacts that occurred over email chat social life. Now I was just talking to an analyst a little bit ago today, said You know, it's really interesting. Voice is hot again. Voice is cool because people are realizing voice has a very distinct role. And so it's not your only digital channels. It's not. You're it's really part of that mix back to comment we had before. So that's one thing you're seeing that you're seeing that with other vendors. You're seeing that with the conversations with customers, that it's really it's part of the mix and it's appropriate. Um, the other thing is, contexts enters hot again. It's kind of, you know, cool. And it's because of that change that we talked about earlier that, uh, it's no longer about cost center. It's no longer about Oh, I have tto answer that customer question. But now I play an integral role in that relationship my company has with the customer and how I can really reinforce the brand. So those are the things I think we're also seeing and talking to the analyst as well. They're saying that excitement and and also conversations that are occurring at the event are very engaging. People are really thinking about how they could change their business, >> and you could feel that and you could hear that here. So, Scott, as you say, the contact center is hot again stew. And I thank you for joining us on the program this afternoon. >> My pleasure. Thank you >> for student a man. I'm Lisa Martin. You're watching the Cube.

>> Live from San Francisco. It's the Cube covering artists. A conference twenty nineteen brought to you by for scout. >> Hey, welcome back already, Geoffrey here with the Cube were in downtown San Francisco at the brand new Open. I think it's finally complete. Mosconi Center for our conference. Twenty nineteen were really excited this year. For the first time ever in the four Scout booth, we've been coming to our say for a long time. We had Mike on last last year by Caesar. President Seo >> for scout. I appreciate you having me >> because we had the last year and you're so nice. You You invited us to the way we must both done something right? Absolutely it Also, before we get too far into it, Congratulations. Doing some homework. The stock is going well. You're making acquisitions, You said it's the anniversary of going out in public. So things are things are looking good for Four. Scout >> things have been good. We've been public company now for four quarters. We've beaten, raised on every metric we had out there. So we're feeling good about >> life. So I don't think the security threats are going down. I don't think you're Tamas is shrinking by any stretch of the imagination. Definitely >> does not feel like the threat landscape is getting less challenging these days, right? I mean, when you look at all the geopolitical stuff going on between the US and China and Russia, that that usually spills into the cybersecurity world and kind of makes things a little bit more tense, >> right? So the crazy talk and all confidence now is machine learning an a I and obviously one of the big themes that came up, we had a great interview. A googol is you just can't hire enough professionals regardless of the field, especially in this one to take care of everything So automation, really key. Hey, I really key. But the same time the bad guys have access to many of the same tools so that you're in the middle of this arm raise. How are you? You kind of taken a strategic view of machine learning an A I in this world. >> So what's amazing about cyber security in two thousand nineteen is the fact that the pace of innovation is exploding at an unprecedented rate, Right? I mean, we're bringing Maur devices online every quarter now, then the first ten years of the Internet combined. So the pace of adoption of new technologies is really what is driving the need for machine learning and a I a human being. Historically, in the cybersecurity world, most corporations approach was, I'm gonna have a whole bunch of different cyber products. They all have their own dashboards. I'm going to build this thing called a cyber Operations Center of Sock. That is going to be the input of all those. But a human being is going to be involved in a lot of the research and prioritization of attacks. And I think just the volume and sophistication of the breaches these days and attacks is making those same companies turn towards automation. You have to be willing to let your cyber security products take action on their own and machine learning in a I play a very large roll back. >> Yeah, it's really interesting because there's very few instances where the eye in the M L actually generate an action. Oftentimes will generate a flag, though they'll bring in a human to try to make one of the final analysis. But it's not, not often that way, actually give them the power to do something. Is that changing? Do you see that changing are people more accepting of that when you can't give it up that >> control when you when you look at for scouts kind of core value Proposition the category that were in his device. Visibility in control device visibility. What's on the network control? When I find something that shouldn't be, there are customers. Want to block that so way? Have a front row seat on watching customers that for decades have been unwilling to allow cybersecurity products to actually take action, turning our product on everyday and allowing us to do exactly that. So when we look at the way that they approached the breaches in every one of these scenarios, they're trying to figure out how they can augment the personal staff they have with products that can provide that level of intelligence >> on nothing to >> see over and over is that people are so falih. Fallible interview to Gala Grasshopper A couple of years he was one hundred percent a social engineering her way into any company that she tried. She had a kind of cool trick. She looked at Instagram photos. He would see the kind of browser that you had, and you know the company picnic. Paige won't let me in. Can you please try this? You're one hundred percent success. So you guys really act in a very different way. You're kind of after the breaches happened. You're sensing and taking action, not necessarily trying to maintain that that print Big Mo >> we're actually on the front end were before the breach takes place. So the way our product works is way plug into the network and then we turned that network ten years ago. A CEO would would would control everything on their networks. They would buy servers and load them with products and put them in their data centers. And they bite, you know, end points and they give those to their to their employees. Those same CEOs now need to allow everything to connect and try to make sense of this growing number of devices. So both the role that we play is preventative. We are on the front end. When a device first joins that network, you need to make sure that device is allowed to be there. So before we worry about what credentials that device is trying to log in with, let's make sure that's a device that the company wants to be on the network to begin with. So to your point, exactly your right. I mean, I think my CFO and I probably every week have some very sophisticated email that makes it sound like one of us asked the other to approve a check request. But it's but they're getting good and you're right. They go on the They know that I went to Villanova, where I'm a Phish fan, and they'll leverage some form of thing. All Post online has tried to make that seem a little bit more personalized, but our philosophy is a company is very basic, which is you need situational awareness of what devices are allowed to be on that network to begin with. If you get that in place, there's a lot less examples that what you described a couple of minutes >> ago and that you said to really instinct philosophy, having kind of an agent list methodology to identify and profile everything that's connected to the network, as opposed to having having you know an OS or having a little bug on there, Which would put you in good shape for this operations technology thing, which is such a critical piece of the i O. T and the I O T transfer >> there. Now there's there's no doubt, You know, that's one of the most fourth sight ful things that, for Scout has ever done is we made the decision to go Agent Lis ten years ago, Way saw that the world was moving from you, Nick and and Lenox and Windows and all of these basic operating systems that were open and only a few of them to the world that we're in today, where every TV has a different operating system, every OT manufacturer has their own operating system, right? It's example I uses that is the Google, you know, the nest thermostat where you you, you buy that, you put it on the wall of your house, you pair with your network, and it's sitting right on line next to your work laptop, right? And and there's been Brit breaches shown that attacks can come in through a device like that and get on to a more more trusted asset, right? So just having that situational awareness is a big part to begin with. But, oh, teams, let's talk about OT for a couple of seconds is almost in front of us post Wanna cry? I am seeing almost every sea, so in the world not having had but the cyber responsibilities for OT being pulled into the O. T part of the business. And it makes sense. You know that the when you watch it a cry, a breach like Wanna cry? Most companies didn't think they bought something from Windows. They thought they bought a controller from Siemens or Gear, one of the larger manufacturers. What they realized on wanna cry was that those controllers have embedded versions of an old operating system from Microsoft called X that had vulnerabilities. And that's how it was exploited so that the approach of devices being online, which changing in front of us, is not just the volume of devices. But they're not open anymore. So the Agent Lis approach of allowing devices to connect to the network and then using the network to do our thing and figure out what's on it makes us a really relevant and big player in that world of coyote and don't. So >> do you have to hold their hand when they when they break the air gap and connect the TV into the Heidi to say it'll be okay. We'll be able to keep an eye on these things before you go. You know, you talk about air gaps all the time is such a kind of fundamental security paradigm in the old way. But now the benefits of connectivity are outweighing, you know, the potential cost of very >> difficult, right? I mean, one of the examples I always uses. PG and E are local power company here. We're up until a few years ago, they'd have a human being. A band would come to your house and knock on your door, and all they wanted to do is get in your garage to read your meter, right? So they could bill you correctly. And then they put smart meters on the side of our houses. And I'm sure the roo I for them was incredible because they got rid of their entire fleet as a result, but recognized that my house is Theo T grid, now connected back to the side, which is Billy. So there's just so many examples in this connected world that we're in. Companies want to do business online, but online means interconnectivity. Interconnectivity means OT and connected so Yes, you're absolutely right. There's many companies believe they have systems air gapped off from each other. Most of those same cos once they get for Scout Live recognized they actually were not air gapped off from each other to begin with. That's part of the role that we play. >> This cure is to get your >> take. You talk to a lot of sizes about how kind of the the types of threats you know have evolved more recently. You know, we saw the stuff with presidential campaign. The targets and what they're trying to do has changed dramatically over the last several years in terms of what the bad guys actually want to do once they get in where they see the value. So how has that changed? No, it's not directly because you guys don't worry about what they're trying to do bad. You want to protect everything. But how is that kind of change from the size of perspective? >> Our customers are government's financial service companies, health care companies, manufacturing companies. Because every one of those companies, I mean, it sounds basic. But if you knew the bad thing was plugged into your network, doing something bad you would've blocked it. You didn't know it was there to begin with. So we actually have a role in all types of threats. But when you look at the threat landscape, it's shifted your right. I mean, ten years ago, it was mostly I p theft. You were hearing examples of somebody's blueprints being stolen before they got their product into the market. WeII. Then soft financial threat shifted. That's still where the bulk of it is today, right? No, they ransomware attacks. I mean, they're all money motivated. The swift breaches. They're all about trying to get a slice of money and more money moves online that becomes a good hunting ground for cybersecurity attackers. Right? But what? What is now being introduced? A CZ? Well, as all the geopolitical stuff. And I think you know with, with our commander in chief being willing to be online, tweeting that with other organism governments worldwide having a more social footprint, now that's on the table. And can you embarrass somebody? And what does that mean? And can you divide parties? But, yeah, there's there's a lot of different reasons for people to be online. What's amazing is the attacks behind them are actually fairly consistent. The mechanisms used right toe actually achieve those that you know that you know the objectives are actually quite similar. >> I'm curious from the site's perspective >> and trying to measure r A Y and, you know, kind of where they should invest in, not a vest, How the changing kind of value proposition of the things that they that are at risk really got to change the dynamic because they're not just feeling a little bit of money. You know, these air, these are much more complex and squishy kind of value propositions. If you're trying to influence our election or you're trying to embarrass somebody or you know, >> that's kind of different from anything. If it's state funded sheriff, it's believed to be state funded. It typically has a different roo. I model behind it, right, and there's different different organizations. But, you know, like on the OT side that you described a second ago, right? Why is OT so hot right now? Because it's one thing to have a bunch of employees have their laptops compromised with something you don't want to be on their right. It's embarrassing. Your emails get stolen it's embarrassing. It's a very different thing when you bring down a shipping line. When a company can't shift, you know can't ship their products. So the stakes are so high on the OT side for organizations that you know, they are obviously put a lot of energy and doing these days. >> You need talk about autonomous vehicles, you know, misreading signs and giving up control. And you know what kinds of things in this feature? Right, Mike? So if we let you go, you're busy. Guy, get thanks >> for having us in the booth. What do your superiors for twenty nineteen, you know for us at Four Scout, the priorities are continuing to execute. You know, we grow our business thirty three percent. Last year. We achieved free cash flow profitability, which is the first time in the company's history. So way of obligation to our investment community. And we intend to run a good, solid business from a product perspective. Our priorities are right in the category of device visibility and control its one of things. When you look around this conferences, you know cos cos had to be careful. They don't increase their product size too quickly. Before they have the financial means to do so. And we just see such a large market in helping answer that question. What is on my network? That's our focus, and we want to do it across the extent that enterprise at scale. >> Yeah, I've sought interesting quote from you on one of their earnings calls that I thought was was needed. A lot of people complain What, you go public. You're on the ninety day shot clock in that that becomes a focus. But your your take on it was now that everything's exposed country spending an already how much spinning a marketing I'm in shipping, it sails that it forces you to really take a deeper look and to make tougher decisions and to make sure you guys are prioritizing your resource is in the right way, knowing that a lot of other people now are making those judgments. >> You know, Listen, the process of raising money and then going public is that you have to be willing to understand that you have an investment community, but you have an obligation to share a lot of detail about the business. But from the other side of that, I get a chance to sit in front of some of the smartest people on the planet that look att my peer companies and me and then provide us input on areas that they're either excited about are concerned about. That's amazing input for me and helps me drive the business. And again, we're trying to build this into a big, organically large cybersecurity business, which is a rare thing these days. And we're quite were very how aboutthe trajectory that we're on. >> Right? Well, Mike, thank you. Like just out with smart people like, you know, I appreciate it and learned a lot. So you congrats on this very much. >> Sorry. He's Mike. I'm Jeff. You're watching The Cube were in the Fourth Scout booth at RC North America. Mosconi Center. Or in the north North Hall. Just find the Seibu. Thanks for watching. >> We'LL see you next time.