>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is "Breaking Analysis" with Dave Vellante. >> Virtually all tech companies have expressed caution in their respective earnings calls, and why not? I know you're sick in talking about the macroeconomic environment, but it's full of uncertainties and there's no upside to providing aggressive guidance when sellers are in control. They punish even the slightest miss. Moreover, the spending data confirms the softening market across the board, so it's becoming expected that CFOs will guide cautiously. But companies facing execution challenges, they can't hide behind the macro, which is why it's important to understand which firms are best positioned to maintain momentum through the headwinds and come out the other side stronger. Hello, and welcome to this week's Wikibon Cube Insights powered by ETR. In this "Breaking Analysis," we'll do three things. First, we're going to share a high-level view of the spending pinch that almost all sectors are experiencing. Second, we're going to highlight some of those companies that continue to show notably strong momentum and relatively high spending velocity on their platforms, albeit less robust than last year. And third, we're going to give you a peak at how one senior technology leader in the financial sector sees the competitive dynamic between AWS, Snowflake, and Databricks. So I landed on the red eye this morning and opened my eyes, and then opened my email to see this. My Barron's Daily had a headline telling me how bad things are and why they could get worse. The S&P Thursday hit a new closing low for the year. The safe haven of bonds are sucking wind. The market hasn't seemed to find a floor. Central banks are raising rates. Inflation is still high, but the job market remains strong. Oh, not to mention that the US debt service is headed toward a trillion dollars per year, and the geopolitical situation is pretty tense, and Europe seems to be really struggling. Yeah, so the Santa Claus rally is really looking pretty precarious, especially if there's a liquidity crunch coming, like guess why they call Barron's Barron's. Last week, we showed you this graphic ahead of the UiPath event. For months, the big four sectors, cloud, containers, AI, and RPA, have shown spending momentum above the rest. Now, this chart shows net score or spending velocity on specific sectors, and these four have consistently trended above the 40% red line for two years now, until this past ETR survey. ML/AI and RPA have decelerated as shown by the squiggly lines, and our premise was that they are more discretionary than the other sectors. The big four is now the big two: cloud and containers. But the reality is almost every sector in the ETR taxonomy is down as shown here. This chart shows the sectors that have decreased in a meaningful way. Almost all sectors are now below the trend line and only cloud and containers, as we showed earlier, are above the magic 40% mark. Container platforms and container orchestration are those gray dots. And no sector has shown a significant increase in spending velocity relative to October 2021 survey. In addition to ML/AI and RPA, information security, yes, security, virtualizations, video conferencing, outsourced IT, syndicated research. Syndicated research, yeah, those Gartner, IDC, Forrester, they stand out as seemingly the most discretionary, although we would argue that security is less discretionary. But what you're seeing is a share shift as we've previously reported toward modern platforms and away from point tools. But the point is there is no sector that is immune from the macroeconomic environment. Although remember, as we reported last week, we're still expecting five to 6% IT spending growth this year relative to 2021, but it's a dynamic environment. So let's now take a look at some of the key players and see how they're performing on a relative basis. This chart shows the net score or spending momentum on the y-axis and the pervasiveness of the vendor within the ETR survey measured as the percentage of respondents citing the vendor in use. As usual, Microsoft and AWS stand out because they are both pervasive on the x-axis and they're highly elevated on the vertical axis. For two companies of this size that demonstrate and maintain net scores above the 40% mark is extremely impressive. Although AWS is now showing much higher on the vertical scale relative to Microsoft, which is a new trend. Normally, we see Microsoft dominating on both dimensions. Salesforce is impressive as well because it's so large, but it's below those two on the vertical axis. Now, Google is meaningfully large, but relative to the other big public clouds, AWS and Azure, we see this as disappointing. John Blackledge of Cowen went on CNBC this past week and said that GCP, by his estimates, are 75% of Google Cloud's reported revenue and is now only five years behind AWS in Azure. Now, our models say, "No way." Google Cloud Platform, by our estimate, is running at about $3 billion per quarter or more like 60% of Google's reported overall cloud revenue. You have to go back to 2016 to find AWS running at that level and 2018 for Azure. So we would estimate that GCP is six years behind AWS and four years behind Azure from a revenue performance standpoint. Now, tech-wise, you can make a stronger case for Google. They have really strong tech. But revenue is, in our view, a really good indicator. Now, we circle here ServiceNow because they have become a generational company and impressively remain above the 40% line. We were at CrowdStrike with theCUBE two weeks ago, and we saw firsthand what we see as another generational company in the making. And you can see the company spending momentum is quite impressive. Now, HashiCorp and Snowflake have now surpassed Kubernetes to claim the top net score spots. Now, we know Kubernetes isn't a company, but ETR tracks it as though it were just for context. And we've highlighted Databricks as well, showing momentum, but it doesn't have the market presence of Snowflake. And there are a number of other players in the green: Pure Storage, Workday, Elastic, JFrog, Datadog, Palo Alto, Zscaler, CyberArk, Fortinet. Those last ones are in security, but again, they're all off their recent highs of 2021 and early 2022. Now, speaking of AWS, Snowflake, and Databricks, our colleague Eric Bradley of ETR recently held an in-depth interview with a senior executive at a large financial institution to dig into the analytics space. And there were some interesting takeaways that we'd like to share. The first is a discussion about whether or not AWS can usurp Snowflake as the top dog in analytics. I'll let you read this at your at your leisure, but I'll pull out some call-outs as indicated by the red lines. This individual's take was quite interesting. Note the comment that quote, this is my area of expertise. This person cited AWS's numerous databases as problematic, but Redshift was cited as the closest competitors to Snowflake. This individual also called out Snowflake's current cross-cloud Advantage, what we sometimes call supercloud, as well as the value add in their marketplace as a differentiator. But the point is this person was actually making, the point that this person was actually making is that cloud vendors make a lot of money from Snowflake. AWS, for example, see Snowflake as much more of a partner than a competitor. And as we've reported, Snowflake drives a lot of EC2 and storage revenue for AWS. Now, as well, this doesn't mean AWS does not have a strong marketplace. It does. Probably the best in the business, but the point is Snowflake's marketplace is exclusively focused on a data marketplace and the company's challenge or opportunity is to build up that ecosystem and to continue to add partners and create network effects that allow them to create long-term sustainable moat for the company, while at the same time, staying ahead of the competition with innovation. Now, the other comment that caught our attention was Snowflake's differentiators. This individual cited three areas. One, the well-known separation of compute and storage, which, of course, AWS has replicated sort of, maybe not as elegant in the sense that you can reduce the compute load with Redshift, but unlike Snowflake, you can't shut it down. Two, with Snowflake's data sharing capability, which is becoming quite well-known and a key part of its value proposition. And three, its marketplace. And again, key opportunity for Snowflake to build out its ecosystem. Close feature gaps that it's not necessarily going to deliver on its own. And really importantly, create governed and secure data sharing experiences for anyone on the data cloud or across clouds. Now, the last thing this individual addressed in the ETR interview that we'll share is how Databricks and Snowflake are attacking a similar problem, i.e. simplifying data, data sharing, and getting more value from data. The key messages here are there's overlap with these two platforms, but Databricks appeals to a more techy crowd. You open a notebook, when you're working with Databricks, you're more likely to be a data scientist, whereas with Snowflake, you're more likely to be aligned with the lines of business within sometimes an industry emphasis. We've talked about this quite often on "Breaking Analysis." Snowflake is moving into the data science arena from its data warehouse strength, and Databricks is moving into analytics and the world of SQL from its AI/ML position of strength, and both companies are doing well, although Snowflake was able to get to the public markets at IPO, Databricks has not. Now, even though Snowflake is on the quarterly shock clock as we saw earlier, it has a larger presence in the market. That's at least partly due to the tailwind of an IPO, and, of course, a stronger go-to market posture. Okay, so we wanted to share some of that with you, and I realize it's a bit of a tangent, but it's good stuff from a qualitative practitioner perspective. All right, let's close with some final thoughts. Look forward a little bit. Things in the short-term are really hard to predict. We've seen these oversold rallies peter out for the last couple of months because the world is such a mess right now, and it's really difficult to reconcile these counterveiling trends. Nothing seems to be working from a public policy perspective. Now, we know tech spending is softening, but let's not forget it, five to 6% growth. It's at or above historical norms, but there's no question the trend line is down. That said, there are certain growth companies, several mentioned in this episode, that are modern and vying to be generational platforms. They're well-positioned, financially sound, disciplined, with strong cash positions, with inherent profitability. What I mean by that is they can dial down growth if they wanted to, dial up EBIT, but being a growth company today is not what it was a year ago. Because of rising rates, the discounted cash flows are just less attractive. So earnings estimates, along with revenue multiples on these growth companies, are reverting toward the mean. However, companies like Snowflake, and CrowdStrike, and some others are able to still command a relative premium because of their execution and continued momentum. Others, as we reported last week, like UiPath for example, despite really strong momentum and customer spending, have had execution challenges. Okta is another example of a company with strong spending momentum, but is absorbing off zero for example. And as a result, they're getting hit harder from evaluation standpoint. The bottom line is sellers are still firmly in control, the bulls have been humbled, and the traders aren't buying growth tech or much tech at all right now. But long-term investors are looking for entry points because these generational companies are going to be worth significantly more five to 10 years down the line. Okay, that's it for today. Thanks for watching this "Breaking Analysis" episode. Thanks to Alex Myerson and Ken Schiffman on production. And Alex manages our podcast as well. Kristen Martin and Cheryl Knight. They help get the word out on social media and in our newsletters. And Rob Hof is our editor-in-chief over at SiliconANGLE do some wonderful editing for us, so thank you. Thank you all. Remember that all these episodes are available as podcast wherever you listen. All you do is search "Breaking Analysis" podcast. I publish each week on wikibon.com and siliconangle.com and you can email me at david.vellante@siliconangle.com, or DM me @dvellante, or comment on my LinkedIn post. And please check out etr.ai for the very best survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching, and we'll see you next time on "Breaking Analysis." (gentle music)

(upbeat music) >> Hello, brilliant humans and welcome back to theCUBE. We're live from Detroit, Michigan. My name is Savannah Peterson. Joined here with John Furrier, John, so exciting, day three. >> Day three, cranking along, doing great, final day of KubeCon, it wraps up. This next segment's going to be great. It's about WebAssembly, the hottest trend here, at KubeCon that nobody knows about cause they just got some funding and it's got some great traction. Multiple players in here. People are really interested in this and they're really discovering it. They're digging into it. So, we're going to hear from one of the founders of the company that's involved. So, it'll be great. >> Yeah, I think we're right at the tip of the iceberg really. We started off the show with Scott from Docker talking about this, but we have a thought leader in this space. Please welcome Matt Butcher the CEO and co-founder of Fermyon Thank you for being here. Welcome. >> Yeah, thanks so much for having me. Favorite thing to talk about is WebAssembly after that is coffee but WebAssembly first. >> Hey, it's the morning. We can talk about both those on the show. (all chuckles) >> It might get confusing, but I'm willing to try. >> If you can use coffee as a metaphor to teach everyone about WebAssembly throughout the rest of the show. >> All right. That would be awesome. >> All right I'll keep that in mind. >> So when we were talking before we got on here I thought it was really fun because I think the hype is just starting in the WebAssembly space. Very excited about it. Where do you think we're at, set the stage? >> Honestly, we were really excited to come here and see that kind of first wave of hype. We came here expecting to have to answer the question you know, what is WebAssembly and why is anybody looking at it in the cloud space, and instead people have been coming up to us and saying, you know this WebAssembly thing, we're hearing about it. What are the problems it's solving? >> Savannah: Yeah. >> We're really excited to hear about it. So, people literally have been stopping us in restaurants and walking down the street, hey, "You're at KubeCon, you're the WebAssembly people. Tell us more about what's going on." >> You're like awesome celeb. I love this. >> Yeah, and I, >> This is great >> You know the, the description I used was I expected to come here shouting into the void. Hey, you know anybody, somebody, let me tell you about WebAssembly. Instead it's been people coming to us and saying "We've heard about it. Get us excited about it," and I think that's a great place to be. >> You know, one of the things that's exciting too is that this kind of big trend with this whole extraction layer conversation, multicloud, it reminds me of the old app server days where, you know there was a separation between the back end and front end, and then we're kind of seeing that now with this WebAssembly Wasm trend where the developers just want to have the apps run everywhere and the coding to kind of fall in, take a minute to explain what this is, why it's important, why are people jazzed about there's other companies like Cosmonic is in there. There's a lot of open source movement behind it. You guys are out there, >> Savannah: Docker. >> 20 million in fresh funding. Why is this important? What is it and why is it relevant right now? Why are people talking about it? >> I mean, we can't... There is no penasia in the tech world much for the good of all of us, right? To keep us employed. But WebAssembly seems to be that technology that just sort of arose at the right time to solve a number of problems that were really feeling intractable not very long ago. You know, at the core of what is WebAssembly? Well it's a binary format, right? But there's, you know, built on the same, strain of development that Java was built on in the 90's and then the .net run time. But with a couple of little fundamental changes that are what have made it compelling today. So when we think about the cloud world, we think about, okay well security's a big deal to us. Virtual machines are a way for us to run other people's untrusted operating systems on our hardware. Containers come along, they're a... The virtual machine is really the heavyweight class. This is the big thing. The workhorse of the cloud. Then along come Containers, they're a little slimmer. They're kind of the middleweight class. They provide us this great way to sort of package up just the application, not the entire operating system just the application and the bits we care about and then be able to execute those in a trusted environment. Well you know, serverless was the buzzword a few years ago. But one thing that serverless really identified for us is that we didn't actually have the kind of cloud side architecture that was the compute layer that was going to be able to fulfill the promise of serverless. >> Yeah. >> And you know, at that time I was at Microsoft we got to see behind the curtain and see how Azure operates and see the frustration with going, okay how do we get this faster? How do we get this startup time down from seconds to hundreds of milliseconds, WebAssembly comes along and we're able to execute these things in sub one millisecond, which means there is almost no cost to starting up one of these. >> Sub one millisecond. I just want to let everyone rest on that for a second. We've talked a lot about velocity and scale on the show. I mean everyone here is trying to do things faster >> Yep >> Obviously, but that is a real linchpin that makes a very big difference when we're talking about deploying things. Yeah. >> Yeah, and I mean when you think about the ecological and the cost impact of what we're building with the cloud. When we leave a bunch of things running in idle we're consuming electricity if nothing else. The electricity bill keeps going up and we're paying for it via cloud service charges. If you can start something in sub one millisecond then there's no reason you have to leave it running when nobody's using it. >> Savannah: Doesn't need to be in the background. >> That's right. >> So the lightweight is awesome. So, this new class comes up. So, like Java was a great metaphor there. This is kind of like that for the modern era of apps. >> Yeah. >> Where is this going to apply most, do you think? Where's it going to impact most? >> Well, you know, I think there are really four big categories. I think there's the kind of thing I was just talking about I think serverless and edge computing and kind of the server class of problem space. I think IOT is going to benefit, Amazon, Disney Plus, >> Savannah: Yes, edge. >> And PBS, sorry BBC, they all use WebAssembly for the players because they need to run the same player on thousands of different devices. >> I didn't even think about that use case. What a good example. >> It's a brilliant way to apply it. IOT is a hard space period and to be able to have that kind of layer of abstraction. So, that's another good use case >> Savannah: Yeah. >> And then I think this kind of plugin model is another one. You see it was Envoy proxy using this as a way to extend the core features. And I think that one's going to be very, very promising as well. I'm forgetting one, but you know. (all chuckles) I think you end up with these kind of discreet compartments where you can easily fit WebAssembly in here and it's solving a problem that we didn't have the technology that was really adequately solving it before. >> No, I love that. One of the things I thought was interesting we were all at dinner, we were together on Tuesday. I was chatting with Paris who runs Deliveroo at Apple and I can't say I've heard this about too many tools but when we were talking about WebAssembly she said "This is good for everybody" And, it's really nice when technologies come along that will raise the water level across the board. And I love that you're leading this. Speaking of you just announced a huge series aid, 20 million dollars just a few days ago. What does that mean for you and the team? >> I mean there's a little bit of economic uncertainty and it's always nice, >> Savannah: Just a little bit. >> Little bit. >> Savannah: It's come up on the show a little bit this week >> Just smidge. and it's nice to know that we're at a critical time developing this kind of infrastructure layer developing this kind of developer experience where they can go from, you know, blinking cursor to deployed application in two minutes or less. It would be a tragedy if that got forestalled merely because you can't achieve the velocity you need to carry it out. So, what's very exciting about being able to raise around like that at this critical time is that gives us the ability to grow strategically, be able to continue releasing products, building a community around WebAssembly as a whole and of course around our products at Fermyon is a little smaller circle in the bigger circle, and that's why we are so excited about having closed around, that's the perfect one to extend a runway like that. >> Well I'm super excited by this because one I love the concept. I think it's very relevant, like how you progress heavyweight, middleweight, maybe this is lightweight class. >> I know, I'm here for the analogy. No, it's great, its great. >> Maybe it's a lightweight class. >> And we're slimming, which not many of us can say in these times so that's awesome. >> Maybe it's more like the tractor trailer, the van, now you got the sports car. >> Matt: Yeah, I can go.. >> Now you're getting Detroit on us. >> I was trying for a coffee, when I just couldn't figure it out. (all chuckles) >> So, you got 20 million. I noticed the investors amplify very good technical VC and early stage firm. >> Amazing, yeah. >> Insight, they do early stage, big early stage like this. Also they're on the board of Docker. Docker was intent to put a tool out there. There's other competition out there. Cosmonic is out there. They're funded. So you got VC funded companies like yourselves and Cosmonic and others. What's that mean? Different tool chains, is it going to create fragmentation? Is there a common mission? How do you look at the competition as you get into the market >> When you see an ecosystem form. So, here we are at KubeCon, the cloud native ecosystem at this point I like to think of them as like concentric rings. You have the kind of core and then networking and storage and you build these rings out and the farther out you get then the easier it is to begin talking about competition and differentiation. But, when you're looking at that core piece everybody's got to be in there together working on the same stuff, because we want interoperability, we want standards based solutions. We want common ways of building things. More than anything, we want the developers and operators and users who come into the ecosystem to be able to like instantly feel like, okay I don't have to learn. Like you said, you know, 50 different tools for 50 different companies. "I see how this works", and they're doing this and they're doing this. >> Are you guys all contributing into the same open source? >> Yep, yeah, so... >> All the funding happens. >> Both CNCF and the ByteCode Alliance are organizations that are really kind of pushing forward that core technology. You know, you mentioned Cosmonic, Microsoft, SOSA, Red Hat, VMware, they're all in here too. All contributing and again, with all of us knowing this is that nascent stage where we got to execute it. >> How? >> Do it together. >> How are you guys differentiating? Because you know, open source is a great thing. Rising Tide floats all boats. This is a hot area. Is there a differentiation discussion or is it more let's see how it goes, kind of thing? >> Well for us, we came into it knowing very specifically what the problem was we wanted to solve. We wanted this serverless architecture that executed in sub one millisecond to solve, to really create a new wave of microservices. >> KubeCon loves performance. They want to run their stuff on the fastest platform possible. >> Yeah, and it shouldn't be a roadblock, you know, yeah. >> And you look at someone like SingleStore who's a database company and they're in it because they want to be able to run web assemblies close to the data. Instead of doing a sequel select and pulling it way out here and munging it and then pushing it back in. They move the code in there and it's executing in there. So everybody's kind of finding a neat little niche. You know, Cosmonic has really gone more for an enterprise play where they're able to provide a lot of high level security guarantees. Whereas we've been more interested in saying, "Hey, this your first foray into WebAssembly and you're interested in serverless we'll get you going in like a couple of minutes". >> I want to ask you because we had Scott Johnston on earlier opening keynote so we kind of chatted one-on-one and I went off form cause I really wanted to talk to him because Docker is one of the most important companies since their pivot, when they did their little reset after the first Docker kind of then they sold the enterprise off to Mirantis they've been doing really, really well. What's your relationship to Docker? He was very bullish with you guys. Insights, joint investor. Is there a relationship? You guys talk, what's going on there? >> I mean, I'm going to have to admit a little bit of hero worship on my part. I think Scott is brilliant. I just do, and having come from the Kubernetes world the Fermyon team, we've always kind of kept an eye on Docker communicated with a lot of them. We've known Justin Cormack for years. Chris Cornett. (indistinct) I mean yeah, and so it has been a very natural >> Probably have been accused of every Docker Con and we've did the last three years on the virtual side with them. So, we know them really well. >> You've always got your finger on the pulse for them. >> Do you have a relationship besides a formal relationship or is it more of pass shoot score together in the industry? >> Yeah. No, I think it is kind of the multi-level one. You come in knowing people. You've worked together before and you like working with each other and then it sort of naturally extends onto saying, "Hey, what can we do together?" And also how do we start building this ecosystem around us with Docker? They've done an excellent job of articulating why WebAssembly is a complimentary technology with Containers. Which is something I believe very wholeheartedly. You need all three of the heavyweight, middleweight, lightweight. You can't do all the with just one, and to have someone like that sort of with a voice profoundly be able to express, look we're going to start integrating it to show you how it works this way and prevent this sort of like needless drama where people are going, oh Dockers dead, now everything's WebAssembly, and that's been a great.. >> This fight that's been going on. I mean, Docker, Kubernetes, WebAssembly, Containers. >> Yeah. >> We've seen on the show and we both know this hybrid is the future. We're all going to be using a variety of different tools to achieve our goals and I think that you are obviously one of them. I'm curious because just as we were going on you mentioned that you have a PhD in philosophy. (Matt chuckles) >> Matt: Yeah. >> Which is a wild card. You're actually our second PhD in philosophy working in a very technical role on the show this week, which is kind of cool. So, how does that translate into the culture at Fermyon? What's it like on the team? >> Well, you know, a philosophy degree if nothing else teaches you to think in systems and both human systems and formal systems. So that helps and when you approach the process of building a company, you need to be thinking both in terms of how are we organizing this? How are we organizing the product? How do we organize the team? We have really learned that culture is a major deal and culture philosophy, >> Savannah: Why I'm bringing it up. >> We like that, you know, we've been very forward. We have our chip values, curiosity, humility inclusivity and passion, and those are kind of the four things that we feel like that each of us every day should strive to be exhibiting these kinds of things. Curiosity, because you can't push the envelope if you don't ask the hard questions. Humility, because you know, it's easy to get cocky and talk about things as if you knew all the answers. We know we don't and that means we can learn from Docker and Microsoft >> Savannah: That's why you're curious. >> And the person who stops by the booth that we've never met before and says, "hey" and inclusivity, of course, building a community if you don't execute on that well you can't build a good community. The diversity of the community is what makes it stronger than a singular.. >> You have to come in and be cohesive with the community. >> Matt: Yeah. >> The app focus is a really, I think, relevant right now. The timing of this is right online. I think Scott had a good answer I thought on the relationship and how he sees it. I think it's going to be a nice extension to not a extension that way, but like. >> It probably will be as well. >> Almost a pun there John, almost a pun. >> There actually might be an extension, but evolution what we're going to get to which I think is going to be pure application server, like. >> Yep, yep. Like performance for new class of developer. Then now the question comes up and we've been watching developer productivity. That is a big theme and our belief is that if you take digital transformation to its conclusion IT and developers aren't a department serving the business they are the business. That means the developer workflows will have to be radically rebuilt to handle the velocity and new tech for just coding. I call it architectural list. >> I like that. I might steal that. >> It's a pun, but it's also brings up the provocative question. You shouldn't have to need an architecture to code. I mean, Java was great for that reason in many ways. So, if that happens if the developers are running the business that means more apps. The apps is the business. You got to have tool chains and productivity. You can't have fragmentation. Some people are saying WebAssembly might, fork tool chains, might challenge the developer productivity. what's your answer to that? How would you address that objection? >> I mean the threat of forking is always lurking in the corner in open source. In a way it's probably a positive threat because it keeps us honest it keeps us wanting to be inclusive again and keep people involved. Honestly though, I'm not particularly worried about it. I know that the W-3 as a standards body, of course, one of the most respected standards bodies on the planet. They do html, they do cascading style sheets. WebAssembly is in that camp and those of us in the core are really very interested in saying, you know, come on in, let's build something that's going to be where the core is solid and you know what you got and then you can go into the resurgence of the application server. I mean, I wholeheartedly agree with you on that, and we can only get there if we say, all right, here are the common paradigms that we're all going to agree to use, now let's go build stuff. >> And as we've been saying, developers are setting, I think are going to set the standards and they're going to vote with their code and their feet, if you will. >> Savannah: A hundred percent. >> They will decide if you're not aligning with what they want to do. okay. On how they want to self-serve and or work, you'll figure that out. >> Yep, yep. >> You'll get instant feedback. >> Yeah. >> Well, you know, again, I tell you a huge fan of Docker. One of the things that Docker understood at the very outset, is that they had an infrastructure tool and developers were the way to get adoption, and if you look at how fast they got adoption versus many, many other technologies that are profoundly impacted. >> Savannah: Wild. >> Yeah. >> Savannah: It's a cool story. >> It's because they got the developers to go, "This is amazing, hey infrastructure folks, here's an infrastructure tool that we like" and the infrastructure folks are used to code being tossed over the wall are going, "Are you for real?" I mean, and that was a brilliant way to do it and I think that what.. >> John: Yeah, yeah. >> We want to replay in the WebAssembly world is making it developer friendly and you know the kind of infrastructure that we can actually operate. >> Well congratulations to the entire community. We're huge fans of the concept. I kind of see where it's going with connect the dots. You guys getting a lot of buzz. I have to ask you, my final question is the hype is beyond all recognition at this point. People are super pumped and enthusiastic about it and people are looking at it maybe some challenging it, but that's all good things. How do you get to the next level where people are confident that this is actually going to go the next step? Hype to confidence. We've seen great hype. Envoy was hyped up big time before it came in, then it became great. That was one of my favorite examples. Hype is okay, but now you got to put some meat on the bone. The sizzle on the stake so to speak. So what's going to be the stake for you guys as you see this going forward? What's the need? >> Yeah, you know, I talk about our first guiding story was, you know, blinking cursor to deployed application in two minutes. That's what you need to win developers initially. So, what's the next story after that? It's got to be, Fermyon can run real world applications that solve real world problems. That's where hype often fails. If you can build something that's neat but nobody's quite sure what to do with it, to use it, maybe somebody will discover a good use. But, if you take that gambling asset, >> Savannah: It's that ending answer that makes the difference. >> Yeah, yeah. So we say, all right, what are developers trying to build with our platform and then relentlessly focus on making that easier and solving the real world problem that way. That's the crucial thing that's going to drive us out of that sort of early hype stage into a well adopted technology and I talk from Fermyon point of view but really that's for all of us in the WebAssembly. >> John: Absolutely. >> Very well stated Matt, just to wrap us up when we're interviewing you here on theCUBE next year, what do you hope to be able to say then that you can't say today? >> All this stuff about coffee we didn't cover today, but also.. (all chuckles) >> Savannah: Here for the coffee show. Only analogies, that's a great analogy. >> I want to walk here and say, you know last time we talked about being able to achieve density in servers that was, you know, 10 times Kubernetes. Next year I want to say no, we're actually thousands of times beyond Kubernetes that we're lowering people's electricity bill by making these servers more efficient and the developers love it. >> That your commitment to the environment is something I want to do an entirely different show on. We learned that 7-8% of all the world's powers actually used on data centers through the show this week which is jarring quite frankly. >> Yeah, yeah. Tragic would be a better way of saying that. >> Yeah, I'm holding back so that we don't go over time here quite frankly. But anyways, Matt Butcher thank you so much for being here with us. >> Thank you so much for having me it was pleasure.. >> You are worth the hype you are getting. I am grateful to have you as our WebAssembly thought leader. In addition to Scott today from Docker earlier in the show. John Furrier, thanks for being my co-host and thank all of you for tuning into theCUBE here, live from Detroit. I'm Savannah Peterson and we'll be back with more soon. (ambient music)

>>Welcome everyone to the cubes presentation of the AWS startup showcase open cloud innovations. This is season two episode one of the ongoing series and we're covering exciting and innovative startups from the AWS ecosystem. Today. We're going to focus on the open source community. I'm your host, Dave Vellante. And right now we're going to talk about open source security and mitigating risk in light of a recent discovery of a zero day flaw in log for J a Java logging utility and a related white house executive order that points to the FTC pursuing companies that don't properly secure consumer data as a result of this vulnerability and with me to discuss this critical issue and how to more broadly address software supply chain risk is Don Fisher. Who's the CEO of tide lift. Thank you for coming on the program, Donald. >>Thanks for having me excited to be here. Yeah, pleasure. >>So look, there's a lot of buzz. You open the news, you go to your favorite news site and you see this, you know, a log for J this is an, a project otherwise known as logged for shell. It's this logging tool. My understanding is it's, it's both ubiquitous and very easy to exploit. Maybe you could explain that in a little bit more detail. And how do you think this vulnerability is going to affect things this year? >>Yeah, happy to, happy to dig in a little bit in orient around this. So, you know, just a little definitions to start with. So log for J is a very widely used course component that's been around for quite a while. It's actually an amazing piece of technology log for J is used in practically every serious enterprise Java application over the last 10 going on 20 years. So it's, you know, log for J itself is fantastic. The challenge that organization organizations have been facing relate to a specific security vulnerability that was discovered in log for J and that has been given this sort of brand's name as it happens these days. Folks may remember Heartbleed around the openness to sell vulnerability some years back. This one has been dubbed logged for shell. And the reason why it was given that name is that this is a form of security vulnerability that actually allows attackers. >>You know, if a system is found that hasn't been patched to remediate it, it allows hackers to get full control of a, of a system of a server that has the software running on it, or includes this log for J component. And that means that they can do anything. They can access, you know, private customer data on that system, or really do anything and so-called shell level access. So, you know, that's the sort of definitions of what it is, but the reason why it's important is in the, in the small, you know, this is a open door, right? It's a, if, if organizations haven't patched this, they need to respond to it. But one of the things that's kind of, you know, I think important to recognize here is that this log for J is just one of literally thousands of independently created open source components that flow into the applications that almost every organization built and all of them all software is going to have security vulnerabilities. And so I think that log for J is, has been a catalyst for organizations to say, okay, we've got to solve this specific problem, but we all also have to think ahead about how is this all gonna work. If our software supply chain originates with independent creators across thousands of projects across the internet, how are we going to put a better plan in place to think ahead to the next log for J log for shell style incident? And for sure there will be more >>Okay. So you see this incident as a catalyst to maybe more broadly thinking about how to secure the, the digital supply chain. >>Absolutely. Yeah, it's a, this is proving a point that, you know, a variety of folks have been making for a number of years. Hey, we depend, I mean, honestly these days more than 70% of most applications, most custom applications are comprised of this third party open source code. Project's very similar in origin and governance to log for J that's just reality. It's actually great. That's an amazing thing that the humans collaborating on the internet have caused to be possible that we have this rich comments of open source software to build with, but we also have to be practical about it and say, Hey, how are we going to work together to make sure that that software as much as possible is vetted to ensure that it meets commercial standards, enterprise standards ahead of time. And then when the inevitable issues arise like this incident around the log for J library, that we have a great plan in place to respond to it and to, you know, close the close the door on vulnerabilities when they, when they show up. >>I mean, you know, when you listen to the high level narrative, it's easy to point fingers at organizations, Hey, you're not doing enough now. Of course the U S government has definitely made attempts to emphasize this and, and shore up in, in, in, in, in push people to shore up the software supply chain, they've released an executive order last may, but, but specifically, I mean, it's just a complicated situation. So what steps should organizations really take to make sure that they don't fall prey to these future supply chain attacks, which, you know, are, as you pointed out are inevitable. >>Yeah. I mean, it's, it's a great point that you make that the us federal government has taken proactive steps starting last year, 2021 in the fallout of the solar winds breach, you know, about 12 months ago from the time that we're talking, talking here, the U S government actually was a bit ahead of the game, both in flagging the severity of this, you know, area of concern and also directing organizations on how to respond to it. So the, in May, 2021, the white house issued an executive order on cybersecurity and it S directed federal agencies to undertake a whole bunch of new measures to ensure the security of different aspects of their technology and software supply chain specifically called out open source software as an area where they put, you know, hard requirements around federal agencies when they're acquiring technology. And one of the things that the federal government that the white house cybersecurity executive order directed was that organizations need to start with creating a list of the third-party open source. >>That's flowing into their applications, just that even have a table of contents or an index to start working with. And that's, that's called a, a software bill of materials or S bomb is how some people pronounce that acronym. So th the federal government basically requires federal agencies to now create Nessbaum for their applications to demand a software bill of materials from vendors that are doing business with the government and the strategy there has been to expressly use the purchasing power of the us government to level up industry as a whole, and create the necessary incentives for organizations to, to take this seriously. >>You know, I, I feel like the solar winds hack that you mentioned, of course it was widely affected the government. So we kind of woke them up, but I feel like it was almost like a stuck set Stuxnet moment. Donald were very sophisticated. I mean, for the first time patches that were supposed to be helping us protect, now we have to be careful with them. And you mentioned the, the bill of its software, bill of materials. We have to really inspect that. And so let's get to what you guys do. How do you help organizations deal with this problem and secure their open source software supply chain? >>Yeah, absolutely happy to tell you about, about tide lift and, and how we're looking to help. So, you know, the company, I co-founded the company with a couple of colleagues, all of whom are long-term open source folks. You know, I've been working in around commercializing open source for the last 20 years that companies like red hat and, and a number of others as have my co-founders the opportunity that we saw is that, you know, while there have been vendors for some of the traditional systems level, open source components and stacks like Linux, you know, of course there's red hat and other vendors for Linux, or for Kubernetes, or for some of the databases, you know, there's standalone companies for these logs, for shell style projects, there just hasn't been a vendor for them. And part of it is there's a challenge to cover a really vast territory, a typical enterprise that we inspect has, you know, upwards of 10,000 log for shell log for J like components flowing into their application. >>So how do they get a hand around their hands around that challenge of managing that and ensuring it needs, you know, reasonable commercial standards. That's what tide lifts sets out to do. And we do it through a combination of two elements, both of which are fairly unique in the market. The first of those is a purpose-built software solution that we've created that keeps track of the third-party open source, flowing into your applications, inserts itself into your DevSecOps tool chain, your developer tooling, your application development process. And you can kind of think of it as next to the point in your release process, where you run your unit test to ensure the business logic in the code that your team is writing is accurate and sort of passes tests. We do a inspection to look at the state of the third-party open source packages like Apache log for J that are flowing into your, into your application. >>So there's a software element to it. That's a multi-tenant SAS service. We're excited to be partnered with, with AWS. And one of the reasons why we're here in this venue, talking about how we are making that available jointly with AWS to, to drink customers deploying on AWS platforms. Now, the other piece of the, of our solution is really, really unique. And that's the set of relationships that Tyler has built directly with these independent open source maintainers, the folks behind these open source packages that organizations rely on. And, you know, this is where we sort of have this idea. Somebody is making that software in the first place, right? And so would those folks be interested? Could we create a set of aligned incentives to encourage them, to make sure that that software meets a bunch of enterprise standards and areas around security, like, you know, relating to the log for J vulnerability, but also other complicated parts of open source consumption like licensing and open source license, accuracy, and compatibility, and also maintenance. >>Like if somebody looking after the software going forward. So just trying to basically invite open source creators, to partner with us, to level up their packages through those relationships, we get really, really clean, clear first party data from the folks who create, maintain the software. And we can flow that through the tools that I described so that end organizations can know that they're building with open source components that have been vetted to meet these standards, by the way, there's a really cool side effect of this business model, which is that we pay these open source maintainers to do this work with us. And so now we're creating a new income stream around what previously had been primarily a volunteer activity done for impact in this universe of open source software. We're helping these open source maintainers kind of GoPro on an aspect of what they do around open source. And that means they can spend more time applying more process and tools and methodology to making that open source software even better. And that's good for our customers. And it's good for everyone who relies on open source software, which is really everyone in society these days. That's interesting. I >>Was going to ask you what's their incentive other than doing the right thing. Can you give us an example of, of maybe a example of an open source maintainer that you're working with? >>Yeah. I mean, w we're working with hundreds of open source maintainers and a few of the key open source foundations in different areas across JavaScript, Java PHP, Ruby python.net, and, you know, like examples of categories of projects that we're working with, just to be clear, are things like, you know, web frameworks or parser libraries or logging libraries, like a, you know, log for J and all the other languages, right? Or, you know, time and date manipulation libraries. I mean, they, these are sort of the, you know, kind of core building blocks of applications and individually, they, you know, they may seem like, you know, maybe a minor, a minor thing, but when you multiply them across how many applications these get used in and log for J is a really, really clarifying case for folks to understand this, you know, what can seemingly a small part of your overall application estate can have disproportionate impact on, on your operations? As we saw with many organizations that spent, you know, a weekend or a week, or a large part of the holidays, scrambling to patch and remediate this, a single vulnerability in one of those thousands of packages in that case log. >>Okay, got it. So you have this two, two headed, two vectors that I'm going to call it, your ecosystem, your relationship with these open source maintainers is kind of a, that just didn't happen overnight, and it develop those relationships. And now you get first party data. You monetize that with a software service that is purpose built as the monitor of the probe that actually tracks that third, third party activity. So >>Exactly right. Got it. >>Okay. So a lot of companies, Donald, I mean, this is, like I said before, it's a complicated situation. You know, a lot of people don't have the skillsets to deal with this. And so many companies just kind of stick their head in the sand and, you know, hope for the best, but that's not a great strategy. What are the implications for organizations if they don't really put the tools and processes into place to manage their open source, digital supply chain. >>Yeah. Ignoring the problem is not a viable strategy anymore, you know, and it's just become increasingly clear as these big headline incidents that happened like Heartbleed and solar winds. And now this logged for shell vulnerability. So you can, you can bet on that. Continuing into the future and organizations I think are, are realizing the ones that haven't gotten ahead of this problem are realizing this is a critical issue that they need to address, but they have help, right. You know, the federal government, another action beyond that cybersecurity executive order that was directed at federal agencies early last year, just in the last week or so, the FTC of the U S federal trade commission has made a much more direct warning to private companies and industry saying that, you know, issues like this log for J vulnerability risk exposing private, you know, consumer data. That is one of the express mandates of the FTC is to avoid that the FTC has said that this is, you know, bears on both the federal trade commission act, as well as the Gramm-Leach-Bliley act, which relates to consumer data privacy. >>And the FTC just came right out and said it, they said they cited the $700 million settlements that Equifax was subject to for their data breach that also related to open source component, by the way, that that had not been patched by, by Equifax. And they said the FTC intents to use its full legal authority to pursue companies that failed to take reasonable steps, to protect consumer data from exposure as a result of log for J or similar known vulnerabilities in the future. So the FTC is saying, you know, this is a critical issue for consumer privacy and consumer data. We are going to enforce against companies that do not take reasonable precautions. What are reasonable precautions? I think it's kind of a mosaic of solutions, but I'm glad to say tide lift is contributing a really different and novel solution to the mix that we hope will help organizations contend with this and avoid that kind of enforcement action from FTC or other regulators. >>Well, and the good news is that you can tap a tooling like tide lift in the cloud as a service and you know, much easier today than it was 10 or 15 years ago to, to resolve, or at least begin to demonstrate that you're taking action against this problem. >>Absolutely. There's new challenges. Now I'm moving into a world where we build on a foundation of independently created open source. We need new solutions and new ideas, and that's a, you know, that's part of what we're, we're, we're showing up with from the tide lift angle, but there's many other elements that are going to be necessary to provide the full solution around securing the open source supply chain going forward. >>Well, Donald Fisher of tide lift, thanks so much for coming to the cube and best of luck to your organization. Thanks for the good work that you guys do. >>Thanks, Dave. Really appreciate your partnership on this, getting the word out and yeah, thanks so much for today. >>Very welcome. And you are watching the AWS startup showcase open cloud innovations. Keep it right there for more action on the cube, your leader in enterprise tech coverage.

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. Everyone welcome back to the cubes coverage of a Davis reinvent 2020. It's a virtual conference this year. This is the Cube virtual. I'm John for your host. We're not in person this year. We're doing it remote because of the pandemic, but it's gonna be wall to wall coverage for three weeks. We've got you covered. And we got a great interview signature interview here with Two Cube alumni's Matt Garment, vice president of sales and marketing at AWS, formerly head of the C two and, of course, Sanjay Poon in CEO of VM Ware. Both distinguished guests and alumni of the Cube. Good to see you, Sanjay. Matt. Thanks for coming on. Uh, let's just jump into it. How are you guys doing? >>Great. Exciting. Excited for reinvent and, uh, excited for the conversation. So thanks for having us on. >>Yeah, I'm great to be here. We are allowed to be 6 ft away from each other, so I came in, but super excited about the partnership. Matt and I have been friends for several years on. You were so excited about another reinvent, the different circumstances doing all virtual. But it's a fantastic partnership. >>You know, I look forward to reinvent one of my most favorite times of the year, and it's also kind of stressful because it's backs up against Thanksgiving. And but, you know, you get through it, you have your turkey and you do the Friday and you guys probably Kino, perhaps, and all things going on and then you go to Vegas is a few celebration. We're not doing it this year. Three weeks eso There's gonna be a lot of big content in the first week, and we're gonna roll that out. We're gonna cover it, But it's gonna be a different celebrations so mad. I know you're in front center on this, Uh, just real quick. What are what do you expect people to be doing on the system? What's your expectations and how is this all going to play out? >>Yeah, you know, it's gonna be different, but I think we have Justus much exciting news as ever. And, you know, it's gonna be over a three week period. I think it actually gives people an opportunity to Seymour things. I think a lot of times we heard from, uh, from customers before was they love the excitement of being in Vegas, and we're not gonna be able to exactly replicate that, but But we have a lot of exciting things planned, and it'll enables customers to get two more sessions Seymour of the content and really see more of the exciting things that are coming out of AWS. And there's a lot s over the three weeks I encourage folks toe to dive in and really learn things is a This is the opportunity for customers to learn about the cloud and and some really cool things coming out. We're excited. >>Well, congratulations on all the business performs. I know that there's been a tailwind with the pandemic as people wanna go faster and smarter with cloud and on premise and Sanjay, you guys have a great results as well. Before I get into some of my point. Of course, I have a lot of I know we don't a lot of time, but I want to get a nup date on the relationship we covered in three years ago when, uh, Andy Jassy and team came down to San Francisco with Pat Gelsinger, Raghu, Sanjay. All this went down. There were skeptics. Relationship has proven to be quite strong and successful for both parties because you guys take a minute so you will start with you and talk about the relationship update. Where you guys at, What's the status? The relationship people want to know. >>Yeah, I think John, the relationship is going really well. Uh, it's rooted in first off, a clear understanding that there's value for customers. Um, this is the best of the public cloud in the private cloud in a hybrid cloud journey. And then, secondly, a deep engineering effort. This wasn't a Barney announcement. We both decided Matt in his previous role, was running a lot of the engineering efforts. Uh, we were really keen to make this a deep engineering effort, and often when we have our connected Cube ers, we're doing one little later this afternoon. I often can't tell when a Amazon personal speaking when a VM ware person speaking we're so connected both the engineering and then the go to market efforts. And I think after the two or three years that the the solution has had to just state and now we have many, many customers started to get real value. The go to market side of the operations really starting take off. So we're very excited about it. It is the preferred and the best offering. We think in the market, Um, and for Vienna, where customers. We message it as the best place for Vienna workload that's running on V sphere to move into Amazon. >>Matt, what's your take on the relationship update from your >>standpoint, I agree with Sanjay. I think it's been it's been fantastic. I think like you said, some folks were skeptical when we first announced it. But But, you know, we knew that there was something there and I think as we've gotten even deeper into this partnership, Onda figured out how we can continue Thio integrate more deeply both with on Prem and into the cloud. Our customers have really guided us and I think that's that's enabled us to further strengthen that partnership, and customers continue to get more excited when they see how easy it is to move and operate their VM where in their V sphere workloads inside of a W S on how it integrates well with the AWS environment, Um on they can still use all of the same functions and capabilities that they they built their business on the inside of the sphere. We're seeing bigger and bigger customers really just embrace us, and the partnerships only grown stronger. I think you know, Sanjay and I, we do joint sales calls together. I think that the business has really, really grown. It's been it's been a fantastic partnership. >>I was talking about that yesterday with being where in eight of us teams members as well. I want to get your thoughts on this cultural fit. Sanjay mentioned e think the engineering cultures air there. The also the corporate culture, both customer focused. Remember Andy Jassy told me, Hey, we're customer focused like you're making big. You make big, big statements Public Cloud and now he goes toe hybrid. He's very reactive to the customers and this is a cultural thing for me, was an VM where what are the customers saying to you now? What are you working backwards from this year? Because there's a lot to work backwards from. You got the pandemic. You got clear trends around at modernization automation under the covers, if you will. And you got VM Ware successful software running on their cloud on AWS. You got other customers. Matt, what's the big trends right now that are highlighted in your in your world? >>Yeah, it's a good question. And I think you know, it really does highlight the strength of this this hybrid model, I think, you know, pre pandemic. We had huge numbers of customers, obviously kind of looking at the cloud, but some of the largest enterprises in the world, in the more traditional enterprises, they really weren't doing a lot, you know, they were tipping their toes in, and some of the forward leaning enterprises were being really aggressive about getting into the cloud. But, you know, many people were just, you know, kind of hesitant or kind of telling, saying, Yes, we'll go learn about the cloud. I think as soon as the pandemic hit, we're really starting to see some of those more traditional enterprises realize it's a business imperative for them. Toe have ah, big cloud strategy and to move there quickly, and I I think our partnership with VM Ware and the VMC offering really is allowing many of these large enterprises to do that. And we see we see big traditional enterprise is really accelerating that move into the cloud. It gives them the business agility they need that allows them to operate their environment in uncertain world that allows them to operate remotely on DSO. We're seeing all of those trends, and I think I think we're going to continue to see the acceleration of our joint business. >>Sanjay, your thoughts. Virtualization has hit ah, whole nother level. It's not like server virtualization like it's cultural, it's societal. What's your take? >>Yeah, I think you know, virtualization is that fabric that connects the private cloud to the public cloud. It's the basis for a lot of the public cloud infrastructure. So when we listen to customers, I think the first kind of misconception we had to help them with was that it had to be choice between one or the other and being able to take Vienna Cloud, which was basically compute storage networking management and put that into the bare metal capabilities of AWS, an engineer deep into the stack and all the services that Matt and the engineering team were able to provide to us now allows that sort of application that sitting on premise to move like a house on wheels into a W s. And that's a beautiful experience we've even shown in in conferences, like a virtual reality moving of a workload, throwing a workload into a W s and a W s catches it. It's a good metaphor in a good way to think of those things that VM were like like the most playing the customers like like the emotional moves nicely. But then the other a misconception we had thio kind of illustrate to our customers was that you could once you were there, uh, let's take that metaphor. The house and wheels renovate the house with all the I think there's probably $200 services that Amazon AWS has. Um, all of a I data services be I I o t. Whatever. You have all the things that Andy and Matt kind of talk about in any of the reinvents. You get to participate and build on those services so it has. It's not like you take this there, and then it's sort of a dead end. You get to modernize your app after you migrated. So this migrate and modernize motion is something that we really start to reinforce with our customers, and it doesn't matter which one you do. First, you may modernize first and then migrate or migrate first and modernize. And in the modernized parts we've also made some significant investments and containers and Tan Xue. We could talk about that at this time and optimizing that for both the private cloud world and the public cloud world like Amazon. >>You know, Matt, this is something that we're talking about a lot this week. These few weeks with reinvent going on this everything is a service trend has a lot of things under it, like automation. Higher level services. One of the critics would say, Three years ago, when this announcement relationship between VM Ware enables came out was, Oh, Amazon's is going to steal all of their customers and VM we're screwed. Turns out that's not the case. You guys are both winning and rising. Tide floats all boats because VM Ware has an operator kind of market. People are operating their business with VM ware and they're adding higher level services with Cloud native, So it Xan overall win, so that was proven false. So clearly the new trend You guys are gaining a large enterprises that wanna go faster, have that existing operator kind of legacy stuff or pre conditions of the enterprise like VM ware. So how do you guide the technology teams and how do you look at this? Because this is where customers are like saying, Hey, I cannot operate my business house on wheels, modernize it in real time, come out a covert with the growth strategy and go faster your interview on all that. >>So I think you're exactly right. I think we see a lot of customers who see I don't want to necessarily lose what I have. I want to add on top of that, And so whether that's adding machine learning and kind of figuring out how they can take their data from various different data silos and put them into a large data lake and gets the machine learning insights on top of that, whether they want to do analytics, um, whether they want to d i o T. Whether they want to modernize two containers, I think there's there's a whole bunch of ways in which customers are looking at that. But you're absolutely right. It's not a I'm gonna go from a to B. It's I'm gonna take a and add B to it and, um, we see that's that's over and over again. I think what we've seen from customers doing it and, um and they're really taking advantage of that, right? And I think customers see all the announcements that we're making a reinvent over the next three weeks, and they wanna be able to take advantage of those things right? It's it's they want to be able to add that onto their production environment. They want to take a lot of the benefits they've gotten from their VM Ware environment, but also add some of these innovations from AWS. And I think that Z that really is what we focus on is what our engineering teams focus on. You know, we have joint engineering efforts to figure out how we can bridge that gap, right, so that they BMR environments can very easily reach into their A W s environment and take advantage of all the new services and offerings that we have there. So, um, that's that's exactly what our joint teams really pushed together. >>Sanjay, I wanna get your thoughts on this and we talk. Two years ago, we had a conversation with Cuba. I ask you since this is a great move for VM Ware because it simplifies the messaging and clears up the whole cloud strategy. And you had said something that I'm gonna bring this back today. You said it's not just simplifying the messaging to customers about what we're gonna do in the cloud. It's going to simplify their life is gonna make things easier. Have them set up for better bitterness. Goodness down the road. Can you take him in to explain what that what that goodness was? What came out of the simplicity of the messaging, the simplicity of solution? Where are we now? How does that all kind of Italian together? Can you take him in to explain that? >>Yeah, I think when the history books are written, John, um, this partnership will be one of the most seminal partnerships because from VM Ware's perspective, maybe a little from Amazon Let Matt talk about if you feel the same way. This is a headwind turning into a tailwind. I think that's sort of narrative that VM ware in Amazon were competing each others that maybe was the early story. In the early days of A W s Progress and VM, we're trying to build our own public cloud and then divesting that, uh, Mats, a Stanford grad. I'm a Harvard grad. So one day there'll be a case study. I think in both schools about how this partnership we have a strong partnership with deadlines, sometimes joke. That's a little bit of an arranged marriage we don't have. We didn't have much saying that because AMC Bardhyl so that's an important partnership. But this one we have to work hard to create. And I tell our customers, Del on AWS are top partners. And as you think about what we've been able to do here, the simplicity to the customer for you, as you describe this, is being able to really lower cost of ownership in any process, in terms of how they're building and migrating APs to be the best optimization of hardware, software and services. And the more you could make that better, simpler, cheaper through software and through the movement to the cloud. Um, I think customers benefit, and then you know, Of course, the innovation machine of both companies. Uh, Amazon's really building. I mean, every time I go to read and I'm just amazed at the Yeah, I think it's a near 200 services that they're building in all of these rich layers. All of those developers, services and, I don't know, two million customers. The whatever number of people that have it reinvent this year get to participate on top of all the applications and the virtualization infrastructure we built over the 20 years of our history. Uh eh. So I hope, you know, as we continue do this, this is all now, but customers success large and small customers being able to. And I'm very gratified to three years since we announced this that we're getting very good customer traction. And for us, that's gonna be a key focus to the reinvent, uh, presence we >>have at their show. It really just goes to show you when you built, when you invest in relationships up and down the spectrum from engineering Ah, product and executive. It kind of does pay off. Congratulations to you guys on that matter. I want to get your thoughts on where this kind of going because you're talking about the messaging from VM ware in the execution that comes behind it is the best, you know, Private public cloud hybrid cloud success. There's momentum there. What are the customers saying to you when you look at customer proof points? Um, what do you point to? Because you're now in charge of sales and marketing, you have to take now the installed base of Amazon Web services, which is you got the Debs and startups and, you know, cloud scale to large enterprises. Now you got the postcode growth. Go fast, cloud scale. You've got a huge customer base. You've got a target. These guys, you gotta bring this solution. What are they saying about the VM ware AWS success? Can you share some? Some >>days I'd be happy to, I think I mean, look, this this is what gets, uh, us excited. I know Sanjay gets just as excited about this. It's and it's really it's resonating across our customer base. You know, there's folks like S and P Global who's a large enterprise, right? They had, uh, they had a hardware procurement cycle. They were looking at them on front of implementation and they looked at a WSMV I'm wearing. They said, Look, we want to migrate. All of our applications want to migrate. Everything we have into the cloud, I think it was 150 critical financial applications that they seamlessly migrated with zero downtime Now all running on BMC in the cloud. Um, you look at governments, right? We have thing folks like the Scottish government on many government customers. We have folks that are like Penny Mac and regulated industries. Um, that really took critical parts of their application. Andi seamlessly migrated them to to A W S and BMC, and they looked at us. And when we talk to these customers, we really say, like, where is the best place for us to run these v sphere workloads? And, um and the great thing is we have a consistent message. We we know that it's the right that that aws nbn where's the best place to run those VCR workloads in the cloud? And so as we see enterprises as we see regulated industries as we see governments really looking to modernize and take advantage of the cloud, we're seeing them move whole swaths of their applications. And this is not just small parts. These are the critical really mission critical applications that they know that they need to get out flexibility on, and they want to get that agility. And so, um, you know, there's been a broad swath of customers like that that have really moved large large pieces of their application in date of us. So it's been fun to see. >>And John, if I might add to that what we've also sought to do is pick some of those great customers like the ones that Matt talked about and put them on stage. Uh, VM world. In previous, we had Freddie Mac and we had, you know, I h s market and these are good examples in the few that Matt talked about. So I'm super excited. I expect there'll be many more reinvent we did. Some also be in world. So we're getting these big customers to talk about this because then you get the 10 phenomenon. Everyone wants to come to this, tend to be able to participate in that momentum. The other thing I'm super excited about it started off as a US phenomenon. Just the U s customers, but I'm starting to see riel interest from European and a p J customers. Asia Pacific customers in countries Australia, Japan, U. K, France, Germany. So this becomes a global phenomenon where customers understand that this doesn't have to be just the U. S centric customers that are participating. And then that was, for me a very key objective because the early customers always gonna start in the Geo where, um, you know, there's the most resonance with the public cloud. But now we're starting to see this really take off in many parts of the world. >>Yeah, that's a great point at something we can talk about another conversation. Maybe we will bring you guys into some of our live check ins throughout the three weeks we're doing here. Reinvent. But this global regional approach Matt has been hugely successful. Um, we're on Amazon. We have Q breaches because by default, we're on top of Amazon. You're seeing companies build on top of Amazon. Look a snowflake. The largest I po in the history of Wall Street behind VM Ware. They run Amazon, right? And I will probably have other clouds to down the road. But the point is you guys are enabling this. >>Yeah, global. And it's it is one of the things that we hear from customers that they that they love about running in the cloud is that, you know, think about if you had Teoh, you know you mentioned snowflake. Imagine if your snowflake and you have to go build data centers everywhere. If you had to go roll out toe to Europe and then you have to build data centers in Germany and then you have to build data centers and the U. K. And then you had to go build data centers in Australia like that would be an enormous cost and complexity, and they probably wouldn't do it frankly, at their early stage, Um, you know, now they just they spin up another stack and their ableto serve their customers anywhere around the world. And we're seeing that from our VM or customers where, you know, they actually are spinning up brand new vmc clusters, uh, where they weren't able to do it before, where they either had toe operate from a single stack. Um, now they're able to say, you know what? I'd love to have Ah, vm or stack in Australia, and they're able to get that up and running quickly. And so I do think that this is actually enabling new business it z, enabling customers to think about. How do they put their computer environment close to where their end users are or where they need that computer environment to be sometime just close to end users? Sometimes it's for data residency requirements, but it really kind of enables customers to do that. Where think about in a cove in world, if you have to go launch a data center in a new country, you probably just I mean, maybe it wouldn't even be possible to do that way are today. And now it's just FBI calls. So >>I mean, your point about going slows in an option. The imperative we have, you know, even expression here inside silicon and on the Cube team. Is there a problem? Yes. Is it important? Yes. What are the consequences if you don't solve the problem? Can you quantify those consequences? And then you gotta look at solutions and look at the timing. So you got timing. You got cost. You got the consequences of not doing it. And speed all those things. No. No one's gonna roll out of data center in six months if they if they tried so again, Cloud. And I'm trying to come into play here. You gotta operate something. It's a hand in the glove, its's. I'm seeing the cream rise to the top with covert. You're seeing real examples of riel scale riel value problems that you solve that important that have consequences that can be quantified. I mean, it's simple. Is that >>you know, John, I was gonna say, in addition to this via McLeod on aws were also pretty, you know, prominent AWS customer for some of our services. So some of the services that we've seen accelerate through Covic Are these distributed workforce security capabilities? Eso we resume internally, that obviously runs on AWS. But then surrounding that with workspace one and carbon like to secure the laptop that goes home. Those services of us running A W. S two. So this is one of those places where we're grateful that we could run those cloud services because we're also just like Snowflake and Zoom and others. Many of the services that we build that our SAS type services run on Amazon, and that reinforces the partnership for us. Almost like a SAS customer. >>Well, gentlemen, really appreciate your insight. As always, a great conversation. We could go for another hour. You guys with leaders of your organizations, you're at the front lines as managing through the pandemic will have you guys come into our check ins throughout the three weeks now here during reinvent from or commentary. But I'd like to end this segment by sharing. In your opinion, what is the most important thing that the audience should pay attention to this year at Reinvent? I know there's a lot of things going on. It's three weeks, not four days. It's so it's longer, but still there's a lot of announcements, man, on your side vm where you got the moment and you got your announcements. What should customers pay attention to this reinvent Virtual 2020. >>So, do you wanna go first? >>No, man, it's your show. You go first. E >>I would encourage folks toe Really think about and plan the three weeks out. This this is the opportunity to really dive in and learn. Right? Reinvent is as as many of you know, this This is just a different type of conference. It's not American Conference. This is a learning conference, and and even virtually that doesn't change. And so I encourage. Look across the broad swath of things that we're doing. Learn about machine learning and what we're doing in that space. Learn about the new compute capabilities or container capabilities. Learn about you know what, what is most relevant to your business if you're looking about. Hey, I have an on premise data center, and I'm looking about how I extend into the cloud. There's a lot of new capabilities around BMC and AWS that makes sense, but there's also a lot of cool announcements around just other services. Um, that could be interesting. We have a ton of customers. They're giving talks. And learning from other customers is often the best way to really understand how you can get the most value out of the cloud. And so I encourage folks toe really kind of block that time. I think it's easy when your remote to get distracted by, you know, watching Netflix or answering emails or things like that. But this is this is a great opportunity to block that schedule. Find the time that you have to really spend time and dive into the sessions because we have a ton of great content on a lot of really cool launches coming up. >>Yeah, I'm just very quickly. I would like one of things I love about Amazon's culture and were similar. VM Ware is that sort of growth mindset. Learn it all and I'm looking forward myself personally to going to reinvent university. This is three weeks of learning, uh, listening to many of those those things. I learned a ton and I've tried to have my own sort of mindset of have being a learn it all as opposed to know it. Also these air incredible sessions and I would also reinforce what Matt said which is going find pure customers of yours that are in your same vertical. We're seeing enormous success in the key verticals Vienna plays in which itself called financial services public sector healthcare manufacturing, CPG retail. I mean, whatever it is so and many of those customers will be, uh, you know, doing virtual talks or we have case studies of use cases because often these sort of birds of a feather allow you to then plan your migration of modernization journey in a similar >>fashion, Matt Sanjay, always great to get the leaders of the two biggest companies in our world A, W s and VM where to share their perspectives. Uh, this year is gonna be different. I'm looking forward to, you know, really kinda stepping up and leaning into the virtual because, you know, we're gonna do three weeks of cube coverage. We have, like, special coverage days, Tuesday, Wednesday, Thursday for each of the three weeks that we're in. And we're gonna try to make this fun as possible. Keep everyone engaged on tryto navigate, help people navigate through the virtual world. So looking forward to having you guys back on and and sharing. Thanks for coming. I appreciate it. Thank you very much. Okay, this is the cubes. Virtual coverage of virtual reinvent 2020. I'm John for your host. Stay with us. Silicon angle dot com. The cube will be checking in with our live coverage in and out of the sessions and stay with us for more wall to wall coverage. Thanks for watching. Yeah,

>> 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) >> Live from Time Square in New York City, it's The Cube. Covering IBM's change the game, winning with AI. Brought to you by IBM. >> Hi everybody, welcome back to The Big Apple. My name is Dave Vellante. We're here in the Theater District at The Westin Hotel covering a Special Cube event. IBM's got a big event today and tonight, if we can pan here to this pop-up. Change the game: winning with AI. So IBM has got an event here at The Westin, The Tide at Terminal 5 which is right up the Westside Highway. Go to IBM.com/winwithAI. Register, you can watch it online, or if you're in the city come down and see us, we'll be there. Uh, we have a bunch of customers will be there. We had Rob Thomas on earlier, he's kind of the host of the event. IBM does these events periodically throughout the year. They gather customers, they put forth some thought leadership, talk about some hard dues. So, we're very excited to have John Thomas here, he's a distinguished engineer and Director of IBM Analytics, long time Cube alum, great to see you again John >> Same here. Thanks for coming on. >> Great to have you. >> So we just heard a great case study with Niagara Bottling around the Data Science Elite Team, that's something that you've been involved in, and we're going to get into that. But give us the update since we last talked, what have you been up to?? >> Sure sure. So we're living and breathing data science these days. So the Data Science Elite Team, we are a team of practitioners. We actually work collaboratively with clients. And I stress on the word collaboratively because we're not there to just go do some work for a client. We actually sit down, expect the client to put their team to work with our team, and we build AI solutions together. Scope use cases, but sort of you know, expose them to expertise, tools, techniques, and do this together, right. And we've been very busy, (laughs) I can tell you that. You know it has been a lot of travel around the world. A lot of interest in the program. And engagements that bring us very interesting use cases. You know, use cases that you would expect to see, use cases that are hmmm, I had not thought of a use case like that. You know, but it's been an interesting journey in the last six, eight months now. >> And these are pretty small, agile teams. >> Sometimes people >> Yes. use tiger teams and they're two to three pizza teams, right? >> Yeah. And my understanding is you bring some number of resources that's called two three data scientists, >> Yes and the customer matches that resource, right? >> Exactly. That's the prerequisite. >> That is the prerequisite, because we're not there to just do the work for the client. We want to do this in a collaborative fashion, right. So, the customers Data Science Team is learning from us, we are working with them hand in hand to build a solution out. >> And that's got to resonate well with customers. >> Absolutely I mean so often the services business is like kind of, customers will say well I don't want to keep going back to a company to get these services >> Right, right. I want, teach me how to fish and that's exactly >> That's exactly! >> I was going to use that phrase. That's exactly what we do, that's exactly. So at the end of the two or three month period, when IBM leaves, my team leaves, you know, the client, the customer knows what the tools are, what the techniques are, what to watch out for, what are success criteria, they have a good handle of that. >> So we heard about the Niagara Bottling use case, which was a pretty narrow, >> Mm-hmm. How can we optimize the use of the plastic wrapping, save some money there, but at the same time maintain stability. >> Ya. You know very, quite a narrow in this case. >> Yes, yes. What are some of the other use cases? >> Yeah that's a very, like you said, a narrow one. But there are some use cases that span industries, that cut across different domains. I think I may have mentioned this on one of our previous discussions, Dave. You know customer interactions, trying to improve customer interactions is something that cuts across industry, right. Now that can be across different channels. One of the most prominent channels is a call center, I think we have talked about this previously. You know I hate calling into a call center (laughter) because I don't know Yeah, yeah. What kind of support I'm going to get. But, what if you could equip the call center agents to provide consistent service to the caller, and handle the calls in the best appropriate way. Reducing costs on the business side because call handling is expensive. And eventually lead up to can I even avoid the call, through insights on why the call is coming in in the first place. So this use case cuts across industry. Any enterprise that has got a call center is doing this. So we are looking at can we apply machine-learning techniques to understand dominant topics in the conversation. Once we understand with these have with unsupervised techniques, once we understand dominant topics in the conversation, can we drill into that and understand what are the intents, and does the intent change as the conversation progress? So you know I'm calling someone, it starts off with pleasantries, it then goes into weather, how are the kids doing? You know, complain about life in general. But then you get to something of substance why the person was calling in the first place. And then you may think that is the intent of the conversation, but you find that as the conversation progresses, the intent might actually change. And can you understand that real time? Can you understand the reasons behind the call, so that you could take proactive steps to maybe avoid the call coming in at the first place? This use case Dave, you know we are seeing so much interest in this use case. Because call centers are a big cost to most enterprises. >> Let's double down on that because I want to understand this. So you basically doing. So every time you call a call center this call may be recorded, >> (laughter) Yeah. For quality of service. >> Yeah. So you're recording the calls maybe using MLP to transcribe those calls. >> MLP is just the first step, >> Right. so you're absolutely right, when a calls come in there's already call recording systems in place. We're not getting into that space, right. So call recording systems record the voice calls. So often in offline batch mode you can take these millions of calls, pass it through a speech-to-text mechanism, which produces a text equivalent of the voice recordings. Then what we do is we apply unsupervised machine learning, and clustering, and topic-modeling techniques against it to understand what are the dominant topics in this conversation. >> You do kind of an entity extraction of those topics. >> Exactly, exactly, exactly. >> Then we find what is the most relevant, what are the relevant ones, what is the relevancy of topics in a particular conversation. That's not enough, that is just step two, if you will. Then you have to, we build what is called an intent hierarchy. So this is at top most level will be let's say payments, the call is about payments. But what about payments, right? Is it an intent to make a late payment? Or is the intent to avoid the payment or contest a payment? Or is the intent to structure a different payment mechanism? So can you get down to that level of detail? Then comes a further level of detail which is the reason that is tied to this intent. What is a reason for a late payment? Is it a job loss or job change? Is it because they are just not happy with the charges that I have coming? What is a reason? And the reason can be pretty complex, right? It may not be in the immediate vicinity of the snippet of conversation itself. So you got to go find out what the reason is and see if you can match it to this particular intent. So multiple steps off the journey, and eventually what we want to do is so we do our offers in an offline batch mode, and we are building a series of classifiers instead of classifiers. But eventually we want to get this to real time action. So think of this, if you have machine learning models, supervised models that can predict the intent, the reasons, et cetera, you can have them deployed operationalize them, so that when a call comes in real time, you can screen it in real time, do the speech to text, you can do this pass it to the supervise models that have been deployed, and the model fires and comes back and says this is the intent, take some action or guide the agent to take some action real time. >> Based on some automated discussion, so tell me what you're calling about, that kind of thing, >> Right. Is that right? >> So it's probably even gone past tell me what you're calling about. So it could be the conversation has begun to get into you know, I'm going through a tough time, my spouse had a job change. You know that is itself an indicator of some other reasons, and can that be used to prompt the CSR >> Ah, to take some action >> Ah, oh case. appropriate to the conversation. >> So I'm not talking to a machine, at first >> no no I'm talking to a human. >> Still talking to human. >> And then real time feedback to that human >> Exactly, exactly. is a good example of >> Exactly. human augmentation. >> Exactly, exactly. I wanted to go back and to process a little bit in terms of the model building. Are there humans involved in calibrating the model? >> There has to be. Yeah, there has to be. So you know, for all the hype in the industry, (laughter) you still need a (laughter). You know what it is is you need expertise to look at what these models produce, right. Because if you think about it, machine learning algorithms don't by themselves have an understanding of the domain. They are you know either statistical or similar in nature, so somebody has to marry the statistical observations with the domain expertise. So humans are definitely involved in the building of these models and claiming of these models. >> Okay. >> (inaudible). So that's who you got math, you got stats, you got some coding involved, and you >> Absolutely got humans are the last mile >> Absolutely. to really bring that >> Absolutely. expertise. And then in terms of operationalizing it, how does that actually get done? What tech behind that? >> Ah, yeah. >> It's a very good question, Dave. You build models, and what good are they if they stay inside your laptop, you know, they don't go anywhere. What you need to do is, I use a phrase, weave these models in your business processes and your applications. So you need a way to deploy these models. The models should be consumable from your business processes. Now it could be a Rest API Call could be a model. In some cases a Rest API Call is not sufficient, the latency is too high. Maybe you've got embed that model right into where your application is running. You know you've got data on a mainframe. A credit card transaction comes in, and the authorization for the credit card is happening in a four millisecond window on the mainframe on all, not all, but you know CICS COBOL Code. I don't have the time to make a Rest API call outside. I got to have the model execute in context with my CICS COBOL Code in that memory space. >> Yeah right. You know so the operationalizing is deploying, consuming these models, and then beyond that, how do the models behave over time? Because you can have the best programmer, the best data scientist build the absolute best model, which has got great accuracy, great performance today. Two weeks from now, performance is going to go down. >> Hmm. How do I monitor that? How do I trigger a loads map for below certain threshold. And, can I have a system in place that reclaims this model with new data as it comes in. >> So you got to understand where the data lives. >> Absolutely. You got to understand the physics, >> Yes. The latencies involved. >> Yes. You got to understand the economics. >> Yes. And there's also probably in many industries legal implications. >> Oh yes. >> No, the explainability of models. You know, can I prove that there is no bias here. >> Right. Now all of these are challenging but you know, doable things. >> What makes a successful engagement? Obviously you guys are outcome driven, >> Yeah. but talk about how you guys measure success. >> So um, for our team right now it is not about revenue, it's purely about adoption. Does the client, does the customer see the value of what IBM brings to the table. This is not just tools and technology, by the way. It's also expertise, right? >> Hmm. So this notion of expertise as a service, which is coupled with tools and technology to build a successful engagement. The way we measure success is has the client, have we built out the use case in a way that is useful for the business? Two, does a client see value in going further with that. So this is right now what we look at. It's not, you know yes of course everybody is scared about revenue. But that is not our key metric. Now in order to get there though, what we have found, a little bit of hard work, yes, uh, no you need different constituents of the customer to come together. It's not just me sending a bunch of awesome Python Programmers to the client. >> Yeah right. But now it is from the customer's side we need involvement from their Data Science Team. We talk about collaborating with them. We need involvement from their line of business. Because if the line of business doesn't care about the models we've produced you know, what good are they? >> Hmm. And third, people don't usually think about it, we need IT to be part of the discussion. Not just part of the discussion, part of being the stakeholder. >> Yes, so you've got, so IBM has the chops to actually bring these constituents together. >> Ya. I have actually a fair amount of experience in herding cats on large organizations. (laughter) And you know, the customer, they've got skin in the IBM game. This is to me a big differentiator between IBM, certainly some of the other technology suppliers who don't have the depth of services, expertise, and domain expertise. But on the flip side of that, differentiation from many of the a size who have that level of global expertise, but they don't have tech piece. >> Right. >> Now they would argue well we do anybodies tech. >> Ya. But you know, if you've got tech. >> Ya. >> You just got to (laughter) Ya. >> Bring those two together. >> Exactly. And that's really seems to me to be the big differentiator >> Yes, absolutely. for IBM. Well John, thanks so much for stopping by theCube and explaining sort of what you've been up to, the Data Science Elite Team, very exciting. Six to nine months in, >> Yes. are you declaring success yet? Still too early? >> Uh, well we're declaring success and we are growing, >> Ya. >> Growth is good. >> A lot of lot of attention. >> Alright, great to see you again, John. >> Absolutely, thanks you Dave. Thanks very much. Okay, keep it right there everybody. You're watching theCube. We're here at The Westin in midtown and we'll be right back after this short break. I'm Dave Vellante. (tech music)

>> From Boston, Massachusetts, it's theCUBE. Covering LiveWorx 18, brought to you by PTC. >> Welcome back to Boston, everybody. This is theCUBE, the leader in live tech coverage, and we are here, day one of the PTC LiveWorx conference, IOT, blockchain, AI, all coming together in a confluence of innovation. I'm Dave Vellante with my co-host, Stu Miniman. Wolfgang Ulaga is here. He's the AT&T Professor of Services Leadership and Co-Executive Director, the Center for Services Leadership at Arizona State University. Wolfgang, welcome to theCUBE, thank you so much for coming on. >> Thank you. >> So services leadership, what should we know? Where do we start this conversation around services leadership? >> The Center of Services Leadership is a center that has been created 30 years ago around a simple idea, and that is putting services front and center of everything a company does. So this is all about service science, service business, service operations, people and culture. When you touch service, you immediately see that you have to be 360 in your approach. You have to look at all the aspects. You have to look at structures and people. You have to look at operations with a service-centric mindset. >> I mean, it sounds so obvious. Anytime we experience, as consumers, great service, we maybe fall in love with a company, we're loyal, we tell everybody. But so often, services fall down. I mean, it seems obvious. Why is it just not implemented in so many organizations? >> One of the problems is that companies tend to look at services as an afterthought. Think about the word after-sales service, which in my mind is already very telling about how it's from a cultural perspective perceived. It's something that you do after the sale has been done. That's why oftentimes, there is the risk that it falls back, it slips from the priority list. You do it once, you have done all the other things. But in reality, businesses are there to serve customers. Service should be the center of what the company does, not at the periphery. >> Or even an embedded component of what the company, I mean, is Amazon a good example of a company that has embraced that? Or is Netflix maybe even a better example? I don't even know what the service department looks like at Netflix, it's just there. Is that how we should envision modern-day service? >> It excites me at the conference at LiveWorx. We see so many companies talking about technology and changes. And you really can sense and see how all of them are thinking about how can they actually grow the business from historic activities into new data-enabled activities. But the interesting challenge for many firms is that this is going to be also journey of learning how to serve its customers through data analytics. So data-enabled services is going to be a huge issue in the next coming years. >> Wolfgang, you're speaking here at the conference. I believe you also wrote a book about advanced services. For those that aren't familiar with the term, maybe walk us through a little bit about what that is. >> Earlier this morning, I presented the book "Service Strategy in Action", which is a very managerial book that we wrote over 10 years of experience of doing studies, working with companies on this journey from a product-centric company that wants to go into a service and solution-centric world and business. Today we see many of the companies picking up the pace, going into that direction, and I would say that with data analytics, this is going to be an even more important phenomenon for the next years to come. >> A lot of companies struggle with service as well because they don't see it as a scale component of their business. It's harder to scale services than it is to scale software, for example. In thinking about embedding services into your core business, how do you deal as an organization with the scale problem? Is it a false problem? How are organizations dealing with that? >> No, you're absolutely right. Many companies know and learn when they are small and they control operations. It's easy to actually have your eyes on service excellence. Once you scale up, you run into this issue of how do you maintain service quality. How do you make sure that each and every time to replicate into different regions, into different territories, into different operations, that you keep that quality up and running. One way to do it is to create a service culture among the people because one way to control that quality level is to push responsibility as low as possible down so that each and every frontline employee knows what he or she has to do, can take action if something goes wrong, and can maintain that service quality at the level we want. That's where sometimes you see challenges and issues popping up. >> What role do you see machines playing? You're seeing a lot of things like Chatbox or voice response. What role will machines play in the services of the future? >> I think it's a fascinating movement that is now put in place where, machine, artificial intelligence, is there to actually enhance value being created for customers. Sometimes you hear this as a threat or as a danger, but I would rather see it as an opportunity to raise levels of service qualities, have this symbiosis between human and machine to actually provide better, outstanding service for customers. >> Could you share some examples of successes there or things that you've studied or researched? >> Yeah so for example, if I take a consumer marketing example. In Europe I worked with a company, which is Nespresso. They do this coffee machines and capsules. In their boutique, they don't call it a store, by the way, they call it a boutique, they have injected a lot of new technology into helping customers to have different touchpoints, get served the way they want to, at the time they want to, how they want to. So this multi-channel, multi-experience for customers, is actually a growing activity. When you look at it from a consumer perspective, I get more opportunities, I get more choices. I can pick and choose when, where, and how I want to be served. A similar example is Procter & Gamble here in the United States. P&G has recently rolled out a new service business, taking a brand, Tide, and creating Tide Dry Cleaners here in America. It's a fascinating example. They use technology like apps on a smartphone to give the customer a much better experience. I think there's many of these example we'll see in the future. >> When we talk about IOT, one of the things that caught our ear in the keynote this morning is, it's going to take 20 to 25 partners putting together this solution. Not only is there integration of software, but one of the big challenges there, I think, is how do you set up services and transform services to be able to live in this multi-vendor environment. I wonder if you could comment on that? >> I agree, I agree. What I see, which makes me as a business professor very excited and that is, of course there's technology, of course there's hardware and software. But one of the biggest challenges will be the business challenges. How do you implement all of these offers? How do you roll it out? One of my talk topics today were how do you commercialize it? How do you actually make money with it? How do you get paid for it? One of my research areas is what they call free to fee. How do you get the r out of the free, and make customers pay for value you create? What I find, especially in the digital services space, there's so much value being created, but not every company is able to capture the value. Getting adequately paid for the value, this is a huge challenge. In sum, I would say it's really an issue about business challenges as much as it's a technological issue or technical challenges. >> I think about IOT, so many of the different transfer protocols, it's open source, that free to fee. Any advice you can give to people out there as to how they capture that value and capture revenue? >> I think you have to be super careful where the commoditization will kick in. If over time, something that was a differentiator yesterday, with the open sources and everything, will become not so much differentiator tomorrow. So where is your competitive edge? How do you stand out from competition? I know these are very classic questions, but you know what? In the IOT and digital space, they resurface, they come back, and having the right answers on these questions will make the difference between you and competition. >> Last question, we got to go. The trend toward self-service, is that a good thing, a bad thing, a depends thing? >> I think everything that allows customers to have choices. Customers today want to be in charge. They want to be in control. They, in fact, want all of it. They want to have service when they want it, but they want to have a non-self-service option if they feel like. So I think the trick is to know, how can I be nimble and give customers all of these choices so that they are in charge and pick and choose. >> Wolfgang, thanks so much for coming to theCUBE. >> Appreciate it, >> It's a pleasure having you, >> thank you very much, >> good to see you. All right, keep it right there, everybody. Stu and I will be back with our next guest right after this short break. We're here at the PTC LiveWorx show, you're watching theCUBE. (electronic music)

>> [Announcer] Live from Los Angeles, it's theCUBE! Covering E3 2018, brought to you by SiliconANGLE Media. >> Hey, welcome back here everybody, Jeff Frick here with theCUBE. We're at the Los Angeles Convention Center with 68,000 of our closest friends. It's E3, it's the biggest industry event in gaming and we're pretty psyched to be here. It's our first time, but our next guest has been comin', I think he said for like 19 years. So we're really excited to invite Chase to the set. PR Director from Twitch. Chase, great to see you. >> Yeah, great to see you, too, and you've oversold my time here. It's actually only been 18 years. >> 18 years, that's 'cause you missed one, I think, right? >> Yeah, I took a break. It was during one of the slower years and then I came back into the fold. >> So I'd just love to get your perspective with kinda looking back at how the industry has changed, how the event has changed, and how gaming ecosystem has changed, and the way people interact with these things. >> Yeah, it's interesting. E3 has definitely gone through almost a roller coaster in terms of what it's like on the show floor. My first year in '99, I was working with the PR Team for the Sega Dreamcast launch and we had a full stage show that every other hour we'd have Ulala from Space Channel 5. She would come out on stage and with a full dance troupe and it would be like a vacuum. All of the attendees in E3 would all be sucked into our booth and then it would dissipate after that. But every two hours it was like the tidal wave comes crashing back in. Every other hour we had in-line skaters and graffiti artists for for Jet Grind Radio. We had a second floor where local broadcast crews could come and film the whole E3 'cause there's so much happening. And everywhere you went, it was a bombast of noise. And then, in the years that followed, booths started getting more smaller, not because of the scope of the show, but because they were trying to make it more industry-friendly, less of a carnival ride and less of a competition of brands trying to outdo each other. But more of let's make this more about the games than the booth babes and those things. But then slowly, it started building back up and it's gone through peaks and valleys. So it's definitely been interesting to watch. >> [Jeff] Right. >> And we were talking earlier about, you know, what are some of the biggest changes I've seen. And, from the Twitch perspective, it's seeing the validation of content creators grow. You know, live streaming is a fairly new aspect to the convention space, to the convention era. I mean, obviously we've been doing it for about a half decade or so, but in terms of the validity of the creators themselves, like in the past, they weren't treated as media, you wouldn't see 'em on preregistration lists. Now we have hundreds here at E3, you know, where every year it doubles, the amount of content creators. And it's not just because of E3 saying, oh they're as relevant as traditional media if not more so, but all the brands are leveraging them. So what you'll find is, a lot of live stream setups from booths. >> People are streaming their contents. When they're doing their press conferences, they bring a lot of content creators in, you know, put 'em in the front row. You know, one thing I love about the content creator era is that there's people like me who, I'm a hard-core gamer, but I've been doing this for so long that, even if I see a game I love, I don't jump out of my seat goin', oh my gosh, they've done it. But when you have all these new gamers who might've been gaming for a while, getting that treatment that I did traditionally, they're so vibrant about it, there's so much more excitement. And that's why E3 is so important, but it's definitely so for the content creators who traditional media might feel threatened by. But I love seeing the energy they bring to the space. >> It's such an interesting twist on the content creators. 'Cause the developers have always been, you know, in high demand, they've always been rock stars. You want to get people developing on your platform, but the content creators is a very different kind of flavor of that, where now people are sharing their experience and they're becoming like little mini rock stars in their own voice and the way that they interact with these games, which is really an adjunct to the actual gameplay itself. So it has been a pretty interesting growth and you guys pioneered it early on. But one of the other things I think is pretty interesting in the content creator space, is the monetization. Can these people make living, and we know that you can't really do it on advertising, there's really not that much advertising. But you guys have pioneered a ton of kind of direct monetization options and opportunities to help these people actually make money while they're creating this great content. >> Yeah, so content creators on Twitch, you know, people stream for a number of reason. Some do it for the attention, some do it for the money, and some do it for fame, well they do it for the love, like the attention, to get famous, or they do it for the money. And so, you know, it terms of monetization, we want to help support those who are trying to do it for a career. And so, at Twitch we have the broadest means of ways to monetize, but also the lowest barrier of entry to take advantage of them. And so what I mean by that is that we have what's called our partner program. And that's where all the best streamers want to be. 'Cause that has the most monetization options. But we also recently introduced what we call our affiliate program, which is a stepping stone to partnership. And while it doesn't have all the whistles and bells of being a partner, it does have ways to monetize so they can start making a living as well. And when I talk about having the most means to monetize, we have a whole laundry list of ways. We have revenue share from advertising, we have the ability to offer subscriptions to your viewers, and while every channel is free to watch, with subscriptions you can offer special perks to your viewers. You give them special emotes, you make it so that chat is only for subscribers, there's a lot of perks you can give your subscribers. And our subscribers, by the way, they know that they're supporting you and they're all frequently proud to do so. They enjoy supporting their kind of careers 'cause they know if they didn't support you, you might not be streaming and they love playing a role in keeping their favorite creators around. We have a program called Cheering with Bits. And it's a little complicated to always explain, but it's where we have Bits, which is a virtual good, and with these goods, you put them the into chat, you purchase these Bits, you put them in the chat, and they become these animated emotes. And the more you put in, the bigger the emotes get and the more animated they get. So the creator can see who their biggest fans are. And that's another way they can monetize. We have a really successful program in partnership with Amazon called Twitch Prime. Twitch Prime is a benefit of Amazon Prime. So if you have Amazon Prime, all you have to do is connect it to your Twitch account and you can start taking advantage of all these great perks. >> [Jeff] I haven't done that yet. >> Yeah, and the one that benefits our Twitch Prime members, Amazon Prime members, both of 'em, the most is that you get a free 30 day subscription to any content creator of your choice. And so, the way that helps is it's the same as if somebody were to go hit the Sub button on that channel directly. And so we've seen huge amount of revenue being generated by our creators just from people using their free 30 day subscription. >> Well, that's great. It's just interesting to me, that before to pay content creators in the old media model, they create their content, they sell advertising, you buy some Tide, Tide gives some money to ABC, they give it to the content creator. But this has really opened this whole democratization of this kind of this direct support, if you will, of the type of content that you're interested in without really going through the middle man. With all these micro-payments and as you said, all these kind of fun and different options to compensate for 'em, to enable just this massive explosion of these creator types. >> Right, but you also have the advertisers... >> [Jeff] You still have the advertisers. >> But what's they're doing is that, our creators are getting a lot of sponsorship opportunities, they're being part of influencer programs. We actually have a full advertising sales team who works with brands to do what we call custom solutions, which is where they will, instead of just run an ad on a channel, they will do like an activation. For example, we work with Totino's for their pizza rolls, where we create a bucking couch. So we had a couch like a buffalo, there was a content creator playing a video game on it, and the people in chat could control it by saying up, down, up, down, or right, left, and they would move the couch. >> [Jeff] Tryin' to throw 'em off the couch. >> Because it was very in-line with what our community enjoys, they like the personality involved in it, they like being able to play a part in it, so those types of custom activations are something that really resonate with our community and by default, they resonate with brands. And there are things you can actually only do on Twitch. We sort of pioneered this new field of advertising. >> Interesting. So, as we look down the road, and I'll let you go back, I know you're super busy and I really appreciate you takin' a few minutes. You look at the future right, we see these tremendous booths that are here. Fabulous graphics, VR comin' down the pike, we're getting ton more CPU, and graphical chips are all over the place. So basically, power and internet and 5G's coming, mobility's gonna be way, way faster. Where do you see it going? What are some of the things that, in your vision, as you sat around, you would love to be able to do, but just haven't been able to? Where do you see some of these kinda new visions being enabled by some of this new leading-edge technology? >> Well, I can speak in terms of where we see Twitch going, which is, we recently introduced a product called extensions. And what extensions are, they're created by outside developers and what they are is, they add interactive functionality to broadcasters' channel pages. Whether it's a widget underneath the screen or it's an overlay that goes on top of it. And with these overlays, it's creating a more interactive experience for the viewers, and that's where we see the future of gaming going, which is that, it's not a sit-back experience, it's a lean forward. For example, if you're playing Hearthstone, there's a Hearthstone extension where you could literally click on the screen and see what cards the person's holding. And you know, we worked with G League, which is that live MBA minor league system >> [Jeff] Right, right, no longer the D League, now the G League (laughs). >> Yeah, and so you could actually click on the player or find stats on the players who are on the court, you could find stats on the league. Where also with extensions you could do leaderboards, you can do polls, you can do mini-games. It's actually unlimited, the amount of creative ideas. You could have viewers vote during an award show on what games they think are gonna win. We did this with the game awards last year, where viewers would vote on what games they thought were going to win and then the game awards put a leaderboard to show which communities got it closest. >> [Jeff] Right, right. >> So there's so much with it and that's where we're putting a lot of attention on. So extensions is definitely gonna be one of the futures for spectators. >> Right, and just overlaying all these different things over that baseline content, over that baseline creator. >> Yeah. >> All right Chase, well thanks for takin' a few minutes. I was gonna bring you a 20th anniversary tee shirt next year, but you got two more to go (laughs). >> There ya go, I'll have to wait. >> All right. He's Chase, I'm Jeff. We are at the Los Angeles Convention Center at E3. Thanks for watchin'.