>> From theCUBE studios in Palo Alto in Boston, bringing you data-driven insights from the cube and ETR, this is Breaking Analysis with Dave Vellante. >> Organizations have considerable room to improve their performance without making expensive changes to their talent, their structure, or their fundamental business model. You don't need a slew of consultants to tell you what to do. You already know. What you need is to immediately ratchet up expectations, energy, urgency, and intensity. You have to fight mediocrity every step of the way. Amp it up and the results will follow. This is the fundamental premise of a hard-hitting new book written by Frank Slootman, CEO of Snowflake, and published earlier this year. It's called "Amp It Up, Leading for Hypergrowth "by Raising Expectations, Increasing Urgency, "and Elevating Intensity." Hello and welcome to this week's Wikibon CUBE Insights, powered by ETR. At Snowflake Summit last month, I was asked to interview Frank on stage about his new book. I've read it several times. And if you haven't read it, you should. Even if you have read it, in this Breaking Analysis, we'll dig deeper into the book and share some clarifying insights and nuances directly from Slootman himself from my one-on-one conversation with him. My first question to Slootman was why do you write this book? Okay, it's kind of a common throwaway question. And how the heck did you find time to do it? It's fairly well-known that a few years ago, Slootman put up a post on LinkedIn with the title Amp It Up. It generated so much buzz and so many requests for Frank's time that he decided that the best way to efficiently scale and share his thoughts on how to create high-performing companies and organizations was to publish a book. Now, he wrote the book during the pandemic. And I joked that they must not have Netflix in Montana where he resides. In a pretty funny moment, he said that writing the book was easier than promoting it. Take a listen. >> Denise, our CMO, you know, she just made sure that this process wasn't going to. It was more work for me to promote this book with all these damn podcasts and other crap, than actually writing the book, you know. And after a while, I was like I'm not doing another podcast. >> Now, the book gives a lot of interesting background information on Slootman's career and what he learned at various companies that he led and participated in. Now, I'm not going to go into most of that today, which is why you should read the book yourself. But Slootman, he's become somewhat of a business hero to many people, myself included. Leaders like Frank, Scott McNealy, Jayshree Ullal, and my old boss, Pat McGovern at IDG, have inspired me over the years. And each has applied his or her own approach to building cultures and companies. Now, when Slootman first took over the reins at Snowflake, I published a Breaking Analysis talking about Snowflake and what we could expect from the company now that Slootman and CFO Mike Scarpelli were back together. In that post, buried toward the end, I referenced the playbook that Frank used at Data Domain and ServiceNow, two companies that I followed quite closely as an analyst, and how it would be applied at Snowflake, that playbook if you will. Frank reached out to me afterwards and said something to the effect of, "I don't use playbooks. "I am a situational leader. "Playbooks, you know, they work in football games. "But in the military, they teach you "situational leadership." Pretty interesting learning moment for me. So I asked Frank on the stage about this. Here's what he said. >> The older you get, the more experience that you have, the more you become a prisoner of your own background because you sort of think in terms of what you know as opposed to, you know, getting outside of what you know and trying to sort of look at things like a five-year-old that has never seen this before. And then how would you, you know, deal with it? And I really try to force myself into I've never seen this before and how do I think about it? Because at least they're very different, you know, interpretations. And be open-minded, just really avoid that rinse and repeat mentality. And you know, I've brought people in from who have worked with me before. Some of them come with me from company to company. And they were falling prey to, you know, rinse and repeat. I would just literally go like that's not what we want. >> So think about that for a moment. I mean, imagine coming in to lead a new company and forcing yourself and your people to forget what they know that works and has worked in the past, put that aside and assess the current situation with an open mind, essentially start over. Now, that doesn't mean you don't apply what has worked in the past. Slootman talked to me about bringing back Scarpelli and the synergistic relationship that they have and how they build cultures and the no BS and hard truth mentality they bring to companies. But he bristles when people ask him, "What type of CEO are you?" He says, "Do we have to put a label on it? "It really depends on the situation." Now, one of the other really hard-hitting parts of the book was the way Frank deals with who to keep and who to let go. He uses the Volkswagen tagline of drivers wanted. He says in his book, in companies there are passengers and there are drivers, and we want drivers. He said, "You have to figure out really quickly "who the drivers are and basically throw the wrong people "off the bus, keep the right people, bring in new people "that fit the culture and put them "in the right seats on the bus." Now, these are not easy decisions to make. But as it pertains to getting rid of people, I'm reminded of the movie "Moneyball." Art Howe, the manager of the Oakland As, he refused to play Scott Hatteberg at first base. So the GM, Billy Bean played by Brad Pitt says to Peter Brand who was played by Jonah Hill, "You have to fire Carlos Pena." Don't learn how to fire people. Billy Bean says, "Just keep it quick. "Tell him he's been traded and that's it." So I asked Frank, "Okay, I get it. "Like the movie, when you have the wrong person "on the bus, you just have to make the decision, "be straightforward, and do it." But I asked him, "What if you're on the fence? "What if you're not completely sure if this person "is a driver or a passenger, if he or she "should be on the bus or not on the bus? "How do you handle that?" Listen to what he said. >> I have a very simple way to break ties. And when there's doubt, there's no doubt, okay? >> When there's doubt, there's no doubt. Slootman's philosophy is you have to be emphatic and have high conviction. You know, back to the baseball analogy, if you're thinking about taking the pitcher out of the game, take 'em out. Confrontation is the single hardest thing in business according to Slootman but you have to be intellectually honest and do what's best for the organization, period. Okay, so wow, that may sound harsh but that's how Slootman approaches it, very Belichickian if you will. But how can you amp it up on a daily basis? What's the approach that Slootman takes? We got into this conversation with a discussion about MBOs, management by objective. Slootman in his book says he's killed MBOs at every company he's led. And I asked him to explain why. His rationale was that individual MBOs invariably end up in a discussion about relief of the MBO if the person is not hitting his or her targets. And that detracts from the organizational alignment. He said at Snowflake everyone gets paid the same way, from the execs on down. It's a key way he creates focus and energy in an organization, by creating alignment, urgency, and putting more resources into the most important things. This is especially hard, Slootman says, as the organization gets bigger. But if you do approach it this way, everything gets easier. The cadence changes, the tempo accelerates, and it works. Now, and to emphasize that point, he said the following. Play the clip. >> Every meeting that you have, every email, every encounter in the hallway, whatever it is, is an opportunity to amp things up. That's why I use that title. But do you take that opportunity? >> And according to Slootman, if you don't take that opportunity, if you're not in the moment, amping it up, then you're thinking about your golf game or the tennis match that's going on this weekend or being out on your boat. And to the point, this approach is not for everyone. You're either built for it or you're not. But if you can bring people into the organization that can handle this type of dynamic, it creates energy. It becomes fun. Everything moves faster. The conversations are exciting. They're inspiring. And it becomes addictive. Now let's talk about priorities. I said to Frank that for me anyway, his book was an uncomfortable read. And he was somewhat surprised by that. "Really," he said. I said, "Yeah. "I mean, it was an easy read but uncomfortable "because over my career, I've managed thousands of people, "not tens of thousands but thousands, "enough to have to take this stuff very seriously." And I found myself throughout the book, oh, you know, on the one hand saying to myself, "Oh, I got that right, good job, Dave." And then other times, I was thinking to myself, "Oh wow, I probably need to rethink that. "I need to amp it up on that front." And the point is to Frank's leadership philosophy, there's no one correct way to approach all situations. You have to figure it out for yourself. But the one thing in the book that I found the hardest was Slootman challenged the reader. If you had to drop everything and focus on one thing, just one thing, for the rest of the year, what would that one thing be? Think about that for a moment. Were you able to come up with that one thing? What would happen to all the other things on your priority list? Are they all necessary? If so, how would you delegate those? Do you have someone in your organization who can take those off your plate? What would happen if you only focused on that one thing? These are hard questions. But Slootman really forces you to think about them and do that mental exercise. Look at Frank's body language in this screenshot. Imagine going into a management meeting with Frank and being prepared to share all the things you're working on that you're so proud of and all the priorities you have for the coming year. Listen to Frank in this clip and tell me it doesn't really make you think. >> I've been in, you know, on other boards and stuff. And I got a PowerPoint back from the CEO and there's like 15 things. They're our priorities for the year. I'm like you got 15, you got none, right? It's like you just can't decide, you know, what's important. So I'll tell you everything because I just can't figure out. And the thing is it's very hard to just say one thing. But it's really the mental exercise that matters. >> Going through that mental exercise is really important according to Slootman. Let's have a conversation about what really matters at this point in time. Why does it need to happen? And does it take priority over other things? Slootman says you have to pull apart the hairball and drive extraordinary clarity. You could be wrong, he says. And he admits he's been wrong on many things before. He, like everyone, is fearful of being wrong. But if you don't have the conversation according to Slootman, you're already defeated. And one of the most important things Slootman emphasizes in the book is execution. He said that's one of the reasons he wrote "Amp It Up." In our discussion, he referenced Pat Gelsinger, his former boss, who bought Data Domain when he was working for Joe Tucci at EMC. Listen to Frank describe the interaction with Gelsinger. >> Well, one of my prior bosses, you know, Pat Gelsinger, when they acquired Data Domain through EMC, Pat was CEO of Intel. And he quoted Andy Grove as saying, 'cause he was Intel for a long time when he was younger man. And he said no strategy is better than its execution, which if I find one of the most brilliant things. >> Now, before you go changing your strategy, says Slootman, you have to eliminate execution as a potential point of failure. All too often, he says, Silicon Valley wants to change strategy without really understanding whether the execution is right. All too often companies don't consider that maybe the product isn't that great. They will frequently, for example, make a change to sales leadership without questioning whether or not there's a product fit. According to Slootman, you have to drive hardcore intellectual honesty. And as uncomfortable as that may be, it's incredibly important and powerful. Okay, one of the other contrarian points in the book was whether or not to have a customer success department. Slootman says this became really fashionable in Silicon Valley with the SaaS craze. Everyone was following and pattern matching the lead of salesforce.com. He says he's eliminated the customer service department at every company he's led which had a customer success department. Listen to Frank Slootman in his own words talk about the customer success department. >> I view the whole company as a customer success function. Okay, I'm customer success, you know. I said it in my presentation yesterday. We're a customer-first organization. I don't need a department. >> Now, he went on to say that sales owns the commercial relationship with the customer. Engineering owns the technical relationship. And oh, by the way, he always puts support inside of the engineering department because engineering has to back up support. And rather than having a separate department for customer success, he focuses on making sure that the existing departments are functioning properly. Slootman also has always been big on net promoter score, NPS. And Snowflake's is very high at 72. And according to Slootman, it's not just the product. It's the people that drive that type of loyalty. Now, Slootman stresses amping up the big things and even the little things too. He told a story about someone who came into his office to ask his opinion about a tee shirt. And he turned it around on her and said, "Well, what do you think?" And she said, "Well, it's okay." So Frank made the point by flipping the situation. Why are you coming to me with something that's just okay? If we're going to do something, let's do it. Let's do it all out. Let's do it right and get excited about it, not just check the box and get something off your desk. Amp it up, all aspects of our business. Listen to Slootman talk about Steve Jobs and the relevance of demanding excellence and shunning mediocrity. >> He was incredibly intolerant of anything that he didn't think of as great. You know, he was immediately done with it and with the person. You know, I'm not that aggressive, you know, in that way. I'm a little bit nicer, you know, about it. But I still, you know, I don't want to give into expediency and mediocrity. I just don't, I'm just going to fight it, you know, every step of the way. >> Now, that story was about a little thing like some swag. But Slootman talked about some big things too. And one of the major ways Snowflake was making big, sweeping changes to amp up its business was reorganizing its go-to-market around industries like financial services, media, and healthcare. Here's some ETR data that shows Snowflake's net score or spending momentum for key industry segments over time. The red dotted line at 40% is an indicator of highly elevated spending momentum. And you can see for the key areas shown, Snowflake is well above that level. And we cut this data where responses were greater, the response numbers were greater than 15. So not huge ends but large enough to have meaning. Most were in the 20s. Now, it's relatively uncommon to see a company that's having the success of Snowflake make this kind of non-trivial change in the middle of steep S-curve growth. Why did they make this move? Well, I think it's because Snowflake realizes that its data cloud is going to increasingly have industry diversity and unique value by industry, that ecosystems and data marketplaces are forming around industries. So the more industry affinity Snowflake can create, the stronger its moat will be. It also aligns with how the largest and most prominent global system integrators, global SIs, go to market. This is important because as companies are transforming, they are radically changing their data architecture, how they think about data, how they approach data as a competitive advantage, and they're looking at data as specifically a monetization opportunity. So having industry expertise and knowledge and aligning with those customer objectives is going to serve Snowflake and its ecosystems well in my view. Slootman even said he joined the board of Instacart not because he needed another board seat but because he wanted to get out of his comfort zone and expose himself to other industries as a way to learn. So look, we're just barely scratching the surface of Slootman's book and I've pulled some highlights from our conversation. There's so much more that I can share just even from our conversation. And I will as the opportunity arises. But for now, I'll just give you the kind of bumper sticker of "Amp It Up." Raise your standards by taking every opportunity, every interaction, to increase your intensity. Get your people aligned and moving in the same direction. If it's the wrong direction, figure it out and course correct quickly. Prioritize and sharpen your focus on things that will really make a difference. If you do these things and increase the urgency in your organization, you'll naturally pick up the pace and accelerate your company. Do these things and you'll be able to transform, better identify adjacent opportunities and go attack them, and create a lasting and meaningful experience for your employees, customers, and partners. Okay, that's it for today. Thanks for watching. And thank you to Alex Myerson who's on production and he manages the podcast for Breaking Analysis. Kristin Martin and Cheryl Knight help get the word out on social and in our newsletters. And Rob Hove is our EIC over at Silicon Angle who does some wonderful and tremendous editing. Thank you all. Remember, all these episodes are available as podcasts. Wherever you listen, just 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 posts. And please do check out etr.ai for the best survey data in enterprise tech. This is Dave Vellante for theCUBE Insights, powered by ETR. Thanks for watching. Be well. And we'll see you next time on Breaking Analysis. (upbeat music)

>>From around the globe, it's the cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. >>Oh, welcome back to the cube. As we continue our coverage of AWS reinvent 2020, you know, I know you're familiar with Moneyball, the movie, Brad Pitt, starting as Billy Bean, the Oakland A's general manager, where the A's were all over data, right. With the Billy Bean approach, it was a very, uh, data driven approach to building his team and a very successful team. Well, AWS is taking that to an extraordinary level and with us to talk about that as Matt Hearst, who was the head of global sports marketing and communications at AWS and Matt, thanks for joining us here on the queue. >>John is my pleasure. Thanks so much for having me. You >>Bet. Um, now we've already heard from a couple of folks, NFL folks, uh, at re-invent, uh, about the virtual draft. Um, but for those of our viewers who maybe aren't up to speed on that, or having a chance to see, uh, what those folks had to say, uh, let's just talk about that as an opener, um, about your involvement with the NFL and particularly with, with the draft and, and what that announcement was all about. >>Sure. We, we saw, we've seen a great evolution with our work with the NFL over the past few years. And you mentioned during the infrastructure keynote where Michelle McKenna who's, the CIO for the NFL talks about how they were able to stage the 2020 virtual draft, which was the NFL is much most watched ever, uh, you know, over 55 million viewers over three days and how they were unable to do it without the help and the power of AWS, you know, utilizing AWS is reliability, scalability, security, and network connectivity, where they were able to manage thousands of live feeds to flow to the internet and go to ESPN, to airline. Um, but additionally, Jennifer LinkedIn, who's the SVP of player health and innovation at the NFL spoke during the machine learning keynote during reinvent. And she talked about how we're working with the NFL, uh, to co-develop the digital athlete, which is a computer simulation model of a football player that can replicate infinite scenarios in a game environment to help better foster and understanding of how to treat and rehabilitate injuries in the short term and in the long-term in the future, ultimately prevent, prevent and predict injuries. >>And they're using machine learning to be able to do that. So there's, those are just a couple of examples of, uh, what the NFL talked about during re-invent at a couple of keynotes, but we've seen this work with the NFL really evolve over the past few years, you know, starting with next gen stats. Those are the advanced statistics that, uh, brings a new level of entertainment to football fans. And what we really like to do, uh, with the NFL is to excite, educate, and innovate. And those stats really bring fans closer to the game to allow the broadcasters to go a little bit deeper, to educate the fans better. And we've seen some of those come to life through some of our ads, uh, featuring Deshaun Watson, Christian McCaffrey, um, these visually compelling statistics that, that come to life on screen. Um, and it's not just the NFL. AWS is doing this with some of the top sports leagues around the world, you know, powering F1 insights, Buddhist league, and match facts, six nations, rugby match stats, all of which utilize AWS technology to uncover advanced stats and really help educate and engage fans around the world in the sports that they love. >>Let's talk about that engagement with your different partners then, because you just touched on it. This is a wide array of avenues that you're exploring. You're in football, you're in soccer, you're in sailing, uh, you're uh, racing formula one and NASCAR, for example, all very different animals, right? In terms of their statistics and their data and of their fan interest, what fans ultimately want. So, um, maybe on a holistic basis first, how are you, uh, kind of filtering through your partner's needs and their fans needs and your capabilities and providing that kind of merger of capabilities with desires >>Sports, uh, for AWS and for Amazon are no different than any other industry. And we work backwards from the customer and what their needs are. You know, when we look at the sports partners and customers that we work with and why they're looking to AWS to help innovate and transform their sports, it's really the innovative technologies like machine learning, artificial intelligence, high performance computing, internet of things, for example, that are really transforming the sports world and some of the best teams and leagues that we've talked about, that you touched on, you know, formula one, NASCAR, NFL, Buena, Sligo, six nations, rugby, and so on and so forth are using AWS to really improve the athlete and the team performance transform how fans view and engage with sports and deliver these real-time advanced statistics to give fans, uh, more of that excitement that we're talking about. >>Let me give you a couple of examples on some of these innovative technologies that our customers are using. So the Seattle Seahawks, I built a data Lake on AWS to use it for talent, evaluation and acquisition to improve player health and recovery times, and also for their game planning. And another example is, you know, formula and we talk about the F1 insights, those advanced statistics, but they're also using AWS high-performance computing that helped develop the next generation race car, which will be introduced in the 2022 season. And by using AWS F1 was able to reduce the average time to run simulations by 70% to improve the car's aerodynamics, reducing the downforce loss and create more wheel to wheel racing, to bring about more excitement on the track. And a third example, similar to, uh, F1 using HPC is any of those team UK. So they compete in the America's cup, which is the oldest trophy in international sports. And endosteum UK is using an HPC environment running on Amazon, easy to spot instances to design its boat for the upcoming competition. And they're depending on this computational power on AWS needing 2000 to 3000 simulations to design the dimension of just a single boat. Um, and so the power of the cloud and the power of the AWS innovative technologies are really helping, uh, these teams and leagues and sports organizations around the world transform their sport. >>Well, let's go back. Uh, you mentioned the Seahawks, um, just as, uh, an example of maybe, uh, the kind of insights that that you're providing. Uh, let's pretend I'm there, there's an outstanding running back and his name's Matt Hearst and, uh, and he's at a, you know, a college let's just pretend in California someplace. Um, what kind of inputs, uh, are you now helping them? Uh, and what kind of insights are you trying to, are you helping them glean from those inputs that maybe they didn't have before? And how are they actually applying that then in terms of their player acquisition and thinking about draft, right player development, deciding whether Matt Hertz is a good fit for them, maybe John Wallace is a good fit for them. Um, but what are the kinds of, of, uh, what's that process look like? >>So the way that the Seahawks have built the data Lake, they built it on AWFs to really, as you talk about this talent, evaluation and acquisition, to understand how a player, you know, for example, a John Walls could fit into their scheme, you know, that, that taking this data and putting it in the data Lake and figuring out how it fits into their schemes is really important because you could find out that maybe you played, uh, two different positions in high school or college, and then that could transform into, into the schematics that they're running. Um, and try to find, I don't want to say a diamond in the rough, but maybe somebody that could fit better into their scheme than, uh, maybe the analysts or others could figure out. And that's all based on the power of data that they're using, not only for the talent evaluation and acquisition, but for game planning as well. >>And so the Seahawks building that data Lake is just one of those examples. Um, you know, when, when you talk about a player, health and safety, as well, just using the NFL as the example, too, with that digital athlete, working with them to co-develop that for that composite NFL player, um, where they're able to run those infinite scenarios to ultimately predict and prevent injury and using Amazon SageMaker and AWS machine learning to do so, it's super important, obviously with the Seahawks, for the future of that organization and the success that they, that they see and continue to see, and also for the future of football with the NFL, >>You know, um, Roger Goodell talks about innovation in the national football league. We hear other commissioners talking about the same thing. It's kind of a very popular buzz word right now is, is leagues look to, uh, ways to broaden their, their technological footprint in innovative ways. Again, popular to say, how exactly though, do you see AWS role in that with the national football league, for example, again, or maybe any other league in terms of inspiring innovation and getting them to perhaps look at things differently through different prisms than they might have before? >>I think, again, it's, it's working backwards from the customer and understanding their needs, right? We couldn't have predicted at the beginning of 2020, uh, that, you know, the NFL draft will be virtual. And so working closely with the NFL, how do we bring that to life? How do we make that successful, um, you know, working backwards from the NFL saying, Hey, we'd love to utilize your technology to improve Clare health and safety. How are we able to do that? Right. And using machine learning to do so. So the pace of innovation, these innovative technologies are very important, not only for us, but also for these, uh, leagues and teams that we work with, you know, using F1 is another example. Um, we talked about HPC and how they were able to, uh, run these simulations in the cloud to improve, uh, the race car and redesign the race car for the upcoming seasons. >>But, uh, F1 is also using Amazon SageMaker, um, to develop new F1 insights, to bring fans closer to the action on the track, and really understand through technology, these split-second decisions that these drivers are taking in every lap, every turn, when to pit, when not to pit things of that nature and using the power of the cloud and machine learning to really bring that to life. And one example of that, that we introduced this year with, with F1 was, um, the fastest driver insight and working F1, worked with the Amazon machine learning solutions lab to bring that to life and use a data-driven approach to determine the fastest driver, uh, over the last 40 years, relying on the years of historical data that they store in S3 and the ML algorithms that, that built between AWS and F1 data scientists to produce this result. So John, you and I could sit here and argue, you know, like, like two guys that really love F1 and say, I think Michael Schumacher is the fastest drivers. It's Lewis, Hamilton. Who's great. Well, it turned out it was a arts incentive, you know, and Schumacher was second. And, um, Hamilton's third and it's the power of this data and the technology that brings this to life. So we could still have a fun argument as fans around this, but we actually have a data-driven results through that to say, Hey, this is actually how it, how it ranked based on how everything works. >>You know, this being such a strange year, right? With COVID, uh, being rampant and, and the major influence that it has been in every walk of global life, but certainly in the American sports. Um, how has that factored into, in terms of the kinds of services that you're looking to provide or to help your partners provide in order to increase that fan engagement? Because as you've pointed out, ultimately at the end of the day, it's, it's about the consumer, right? The fan, and giving them info, they need at the time they want it, that they find useful. Um, but has this year been, um, put a different point on that for you? Just because so many eyeballs have been on the screen and not necessarily in person >>Yeah. T 20, 20 as, you know, a year, unlike any other, um, you know, in our lifetimes and hopefully going forward, you know, it's, it's not like that. Um, but we're able to understand that we can still bring fans closer to the sports that they love and working with, uh, these leagues, you know, we talk about NFL draft, but with formula one, we, uh, in the month of may developed the F1 Pro-Am deep racer event that featured F1 driver, uh, Daniel Ricardo, and test driver TA Sianna Calderon in this deep racer league and deep racers, a one 18th scale, fully autonomous car, um, that uses reinforcement learning, learning a type of machine learning. And so we had actual F1 driver and test driver racing against developers from all over the world. And technology is really playing a role in that evolution of F1. Um, but also giving fans a chance to go head to head against the Daniel Ricardo, which I don't know that anyone else could ever say that. >>Yeah, I raced against an F1 driver for head to head, you know, and doing that in the month of may really brought forth, not only an appreciation, I think for the drivers that were involved on the machine learning and the technology involved, but also for the developers on these split second decisions, these drivers have to make through an event like that. You know, it was, it was great and well received. And the drivers had a lot of fun there. Um, you know, and that is the national basketball association. The NBA played in the bubble, uh, down in Orlando, Florida, and we work with second spectrum. They run on AWS. And second spectrum is the official optical provider of the NBA and they provide Clippers court vision. So, uh, it's a mobile live streaming experience for LA Clippers fans that uses artificial intelligence and machine learning to visualize data through on-screen graphic overlays. >>And second spectrum was able to rely on, uh, AWS is reliability, connectivity, scalability, and move all of their equipment to the bubble in Orlando and still produce a great experience for the fans, um, by reducing any latency tied to video and data processing, um, they needed that low latency to encode and compress the media to transfer an edit with the overlays in seconds without losing quality. And they were able to rely on AWS to do that. So a couple of examples that even though 2020 was, uh, was a little different than we all expected it to be, um, of how we worked closely with our sports partners to still deliver, uh, an exceptional fan experience. >>So, um, I mean, first off you have probably the coolest job at AWS. I think it's so, uh, congratulations. I mean, it's just, it's fascinating. What's on your want to do less than in terms of 20, 21 and beyond and about what you don't do now, or, or what you would like to do better down the road, any one area in particular that you're looking at, >>You know, our, our strategy in sports is no different than any other industry. We want to work backwards from our customers to help solve business problems through innovation. Um, and I know we've talked about the NFL a few times, but taking them for, for another example, with the NFL draft, improving player health and safety, working closely with them, we're able to help the NFL advance the game both on and off the field. And that's how we look at doing that with all of our sports partners and really helping them transform their sport, uh, through our innovative technologies. And we're doing this in a variety of ways, uh, with a bunch of engaging content that people can really enjoy with the sports that they love, whether it's, you know, quick explainer videos, um, that are short two minute or less videos explaining what these insights are, these advanced stats. >>So when you see them on the screening and say, Oh yeah, I understand what that is at a, at a conceptual level or having blog posts from a will, Carlin who, uh, has a long storied history in six nations and in rugby or Rob Smedley, along story history and F1 writing blog posts to give fans deeper perspective as subject matter experts, or even for those that want to go deeper under the hood. We've worked with our teams to take a deeper look@howsomeofthesecometolifedetailingthetechnologyjourneyoftheseadvancedstatsthroughsomedeepdiveblogsandallofthiscanbefoundataws.com slash sports. So a lot of great rich content for, uh, for people to dig into >>Great stuff, indeed. Um, congratulations to you and your team, because you really are enriching the fan experience, which I am. One of, you know, hundreds of millions are enjoying that. So thanks for that great work. And we wish you all the continued success down the road here in 2021 and beyond. Thanks, Matt. Thanks so much, Sean.

>> From theCUBE studios in Palo Alto in Boston, connecting with thought leaders all around the world. This is theCUBE conversation. >> Hello everyone, David Vellante here and welcome to the special CUBE conversation with a colleague and friend of mine, Randy Seidl is a accomplished CEO, he's an executive, sales pro, and he's a founder of the Sales Community, this newly formed social network, Randy, good to see you again, welcome. >> Hey, great to see you, it's been a lot of great years, great relationship with you and congratulations with all your success with SiliconANGLE and theCUBE. I was remembering back, I think it's been probably since 1985, so 35 years ago when we were both Cub Scouts, I was at EMC, and you were at IDC. >> Yeah, I mean, first of all, I love where you are, your man-cave there, we heard you held a great little networking event that you do periodically with some of our joint colleagues. And yeah, wow, we were both in our twenties, I was a young pop and Dicky Eagan, and Jack and Mike, and they would have me talk to you guys, you know, sort of brief you on the market, what little I knew now looking back. But wow, Randy, I mean. >> We knew! >> Right, I mean, and then just the whole thing just took off, but we had a good instinct, that storage was going to matter, everything back then was mainframe and IBM was the king of the world, and then you guys just crushed it. Wow, what a run, amazing. >> Yeah, absolutely. >> So tell me about Sales Community. What are you trying to accomplish with this new social network? >> Well, it was kind of really my COVID moment. I was talking to Peter Bell I know, you know well as well, and it was right in the beginning of COVID we were kind of comparing notes and long story short, he said, hey Randy, you do all this work with these technology companies, and channel partners, and use your customers, CIO, CTO, CSOs, but you're really not doing much for those that you know the best, which are really technology sales professionals, CROs, STRs kind of up and down the food chain. And that really got me thinking, then he introduced me to one of his companies that sells to CROs and I was going through with them and they were kind of calling me on the carpet saying, okay, do I really know these people? I'm like, oh my gosh! They basically just said, I'm a dope, I haven't really done anything here. So, one thing led to another and ended up developing a Sales Community, a big thing and big help for me was talking to probably 150 or so during the course of the summer, CROs, VPs of sales, Reps STRs to really kind of help get some feedback from them in terms of I caught now they call product-market fit, but kind of what they think it's missing, what's needed, what are their teams need, what do they want? So, it's kind of all a perfect storm, which to be honest without COVID probably wouldn't have created Sales Community. >> Well, I joined and it was a great onboarding experience and love participating with colleagues. I mean, sales is hard, I mean, you've got your ups and your downs and you just got to keep pressing on, but who's participating in Sales Community. >> We're targeting STRs on up to CROs and the kind of the tagline is learn more so you can sell more. We have a lot of great different kind of content areas and we're going to kind of bob and weave based on the feedback that we get, but we've got some great virtual events and interviews. We have an executive coach, Tony Jerry, who's doing nine sessions on designing your life. We did a recording, a live session last week on personal goal setting. We did one yesterday, it was a live session that'll be posted shortly on strategic health. Next one's on branding, so that's not necessarily specific to tech sales, but kind of adding value. We also have Dave Knorr, another executive coach doing a weekly interview series that we're calling tech sales insights with some of the leading CROs, CEOs, Jim Sullivan, who I know you know well, he's going to be the first one, it's going to be next Wednesday, he runs a NWN and he's done a lot of great things and a lot of other great leaders from there. Also still on the interview virtual events side, Michael Cotoia from Tech Target he's going to do a CMO insights series. His Tech Target International editors are also going to do regional ones. So CIO interviews from AMEA, Asia Pac, Latin America, Australia, also on the CSO side, we have somebody focused on doing a CSO interviews, Paul Salamanca of channel interviews, I think this channel, by and large gets missed a lot. CEO's and then Steve Duplessie, I know you know well as well is going to do and focus on CIO, sub-CIO insights, but basically creating virtual events and interview series that are really targeted at people that we sell to. So that covers the kind of virtual event and interview side. And I maybe more quickly go through some of the other key segments. So another one is a content library. There's the guy who's a STR at ServiceNow went through, send me note the other day that said, hey, I found out you have some great feedback on prospecting cold calling, I shared it with my team helped me a lot. So a lot of good things in terms of content library, also opportunity to network. So you could be say selling to Fidelity, you could send a note to the community and members and say anybody else trying to sell the Fidelity, let's network, let's compare notes, also great opportunities for channel partners. So channel partner could raise their hand and say, hey, I know Fidelity, let me help with you. A lot of sharing of best practices. And also just in terms of communication, slack channels, and then opportunities to create round tables. So you might have CROs from startups that want to have maybe six to 10 of them get together. So they can kind of commiserate, ask questions, you could have CROs, companies that are maybe transforming going from on-prem to kind of SAS model. So a lot of different great things, ultimately really to serve the folks in the tech Sales Community. >> Yeah, it sounds like, I mean, first of all tons of content, the other thing I like about it is we all read books on sales, some of them are so like gimmicky, some of them are inspirational. Some of them have really great suggestions. Some of them can be life changing, but what's always been missing in my opinion, is this notion of a network, a social network, if you will, where people can help each other, you just gave a ton of good examples. So you're really trying to differentiate from a lot of the things that have worked over the years, but have really sort of one way communication, some sales guru either training or you're reading his or her book. >> Yes, and we're also fortunate on the content side, we have some of the best kind of consulting sales methodology companies that love what we're doing. So they're likewise providing a lot of content and as you said, it's crazy. You think of any other industry, restaurant, hotel, lawyers, landscape, they have these big, kind of user groups, even technology companies user groups within the larger field of technology sales enterprise B2B sales, there's really nothing that looks like this that exists. So far the feedback's been great. >> Well, so just to what you're describing, I mean, I've known you for a long, long time, and one of the principles of great salespeople is, you help others, right? You make as many friends as you can, and you're the master of that. But essentially you're bringing a lot of the things that have worked, a lot of the principles that have worked in your career to this community. Maybe talk about that a little bit. >> Yeah, I mean, especially I think some of the younger sales folks, it's not kind of off the cuff as we know, but it's really kind of training, being disciplined, being prepared, what are you going to do, how are you going to do it in this COVID moment? You know, I'm seeing lots of friends where the companies that have great relationships, they can do really well and kind of lean in a lot. If you're kind of cold calling and this environment, and it's tough, so kind of, how can you be best prepared, how can you do the best homework? How can you have the kind of right agenda, when you're going to do the sales calls? And then it's not really as much follow up, but really follow through in terms of what you do afterwards. So kind of what is the training? What can you do, how can you do it? And, you know, it's crazy, a lot of companies spend lots of money on training, but if you think about it they're really tied in specifically to tech sales, hopefully this will be great. Plus being able to just kind of throw out questions here and there works out well as well. >> Well that's what I'm looking forward to, say, hey, I got some challenges, how do others deal with this? You know, one of the things that is, I think, paramount to being a great salesperson is the attitude you hear it all the time. How do you stay pumped up? (laughing) Like I said before, we've all been through ups and downs, and what do you tell people there? >> In terms of staying pumped up, interestingly enough, the session we did yesterday on strategic health, probably plays a key role. So yeah, there's the work aspects and how are you going to focus and wake up and get fired up. But ultimately, I think you really got to take several steps back and saying are you taking care of yourself? Are you sleeping, are you eating and drinking correctly? Are you drinking enough water, are you exercising? So, in this moment, I think that's probably something that gets missed a lot in terms of getting fired up. And then ultimately just being excited about kind of what you're doing, how are you doing it, taking care of the customers and serving those around you. And you had mentioned in terms of giving it back, but a lot of us that have been around, love the idea of kind of paying it forward, helping out others and seeing a lot of the great younger folks really rise up and become stars. >> I think that's one of the most exciting things is somebody has been around for awhile. Like (laughing) we all get cold calls and say, hey, how you doing today? You know, (laughing) you really had that dead air, and you actually want to reach out and help these individuals. A lot of times they'll call you, they have no idea what you do, well I've read your website, and I think we'd be a great fit for, you know, something that would not be a great fit. So, there's a level of preparation we always talk about in sales, you got to be prepared, but there's also sometimes... I was talking to a sales pro the other day, you know, sometimes you can over prepare he said, I've been on sales calls, I prepare for hours and hours and hours, and then they get there, and it was just a lot of wasted hours. I probably could have done it in 15 minutes. I mean, so there's a really a balance there. And it comes with experience, I guess. >> Yeah, I mean, I don't know how anybody could prepare hours and hours, so that's a whole different subject to think. >> Well, he said, my technique now is just 15 minutes before the call I'll jump on and just, you know, cram as much as I can. And it actually, it worked for him. So, different approaches, right? >> Yeah, absolutely. The other thing I'd like to mention is the advisory board I'm fortunate to have a work with, and be friends with several of the best in industry like you. So if anybody goes to the website, you can click on an advisory board and there's a 200 plus and haven't count them exactly. But you know, some of the best in technology, we've got them sorted on the sales side and the channel side, the consulting side, the coaching side, analyst side, but, really just such a tremendous each head of talent that can really help us continue to go and grow and pivot and you're making sure that we are serving our Sales Community and making sure everybody's learning more so they can sell more. And then I guess I should add onto that also, earning more and making more money. >> So I got to ask you where you land on this. I mean, you're a sports fan, I am too and for a while there once the "Moneyball" came out, you saw Billy Bean and it was this sort of formulaic approach. The guy, you know, we would joke the team with the best nerds would win. But it seems like there's an equilibrium. It used to be all gut feel and experience, and then it became the data nerds. And it seems like in our industry, it's following a similar pattern, the marketing ops, Martech, becoming very, very data driven. But it feels to me, Randy, especially in these COVID times that there really is this equilibrium, this balance between experience, and tribal knowledge, gut feel, network, which is something you're building and the data. How do you see that role, that CRO role, that sales role evolving, especially in the context of what I just talked about with the data nerds? (laughing) >> Yeah, absolutely, I think I heard two points there since you brought up Billy Bean, I forgot the guy's name, but in the movie is kind of nerd. I've got Jesse and Tucker who have been tremendously helpful for us putting together a Sales Community. But to answer the question on the CMOs side, the CMOs out there frankly not going to like this answer, but I think more and more, you see CMOs and CROs kind of separated and it's kind of different agendas, my belief is that eventually the CMO function or marketing is really going to come under sales and sales are really going to take a much more active role in driving and leveraging that marketing function in terms of what's the best bang for the buck, what are they doing, how are they doing it? And I've got a lot of friends, I won't name names, but they're not on the sales side and they're doing what they can, but they just see what I'd call it kind of wasted money or inefficiencies on the marketing side. So, if I maybe I spin that a different way, I think given kind of analytics and those companies that do have best practices, and I write things on the marketing side, you know, they're going to continue to go and grow, you know, on cert with the right sales team. So I think that you bring up a great point and that area is going to continue to evolve a lot. >> Does that principle apply to product marketing? In other words do you feel like product marketing should be more aligned with engineering or sales and maybe sales and finance, where do you land on that? >> Yeah, I mean, I'm kind of old school, so I go back to Dick and Jack and Roger and Mike Rutgers, and you all in terms of, hey, you have those silos, but you get everybody at the table, kind of what we're working well together. It is interesting though in today's world, the PLG, Product-Led Growth models, where a lot of companies now are trying to get in maybe almost like a VMware, maybe BMC did in the early days where you're kind of getting into the low level developers and then kind of things bubble up so that you think Product-Led Growth model, having a lower cost insight sales model, works when I'll say the kind of the product sells itself. But I would argue, that I think some of those PLG led companies really miss out on leveraging the high end enterprise relationships, to kind of turbocharge and supersize and expedite larger sales deals, larger (indistinct). >> Well, and you mentioned earlier a channel you said a lot of times that's overlooked and I couldn't agree more, channel increasingly important. That's where a lot of the relationships live, it gives you scale, it just gives you a lot of leverage, maybe you talk about the importance of channel and how it relates to Sales Community. >> Yeah, I mean, it's interesting they're really unto themselves, there's some things that are channel channel, but if you think about, you know, go to market tech sales, pick the company on average is probably half of the business goes through the channel. And it used to be way back when just kind of fulfillment, but now the best companies really are those that have the right relationships, that are adding value, that can help on the pre sales, that can help on the post sales, that can help kind of cross sale. You know, if I'm a customer, I don't want to deal with whatever five or 10 different vendors if I can have a one stop shop with one bar solution provider, partner, SI, or whatever you want to call them, you know, that certainly makes life a lot easier. And I think a lot of companies almost been kind of a second class citizen, but I think those companies that really bring them into the fold as really partners at the table, whether it be an account planning sessions, whether you're doing sales calls, but kind of leveraging that I call it a variable cost kind of off balance sheet, sales force really is where the future is going to continue to go. >> So you've been a successful individual sales contributor. You've been a CEO, you've run large sales organizations. I mean, you basically ran sales at HP for Donna Telly, and so you've seen it all, and you've been helping startups. When you look at hiring sales people, what are the attributes that you look for? Is it intelligence, is it hard work, is it coach ability? What are some of the things that are most important to you, and do you apply different attributes in different situations? What are your thoughts on that? >> Great question in a little plug, maybe for a recruiting business, top talent recruiting, (laughing) but one of the key things that we do, which I think is different from others in the recruiting side is the relationships. So a lot of people don't dig in, when we're talking to candidates, they say, well, nobody really asked me this before. And I would argue a key differentiator, and this is way before COVID, but especially now with COVID is okay, who do you have relationships with? So I could be talking to a candidate that maybe somebody is hiring, wants to cover financial services in New York. And then I'll say, okay, well, who do you know what City JPB Bay and I'll know more people than they know. And I'll probably say, just so you know, that's weird me up in Boston. I know more than the council you probably know the best. So really trying to unearth, really kind of who has the right relationships and then separate from that in terms of a reference check, being able to reference checks sooner in the process with somebody that know well firsthand, as opposed to second hand. And a lot of times I've seen even some of the larger, more expensive recruiting firms, you're kind of wait until somebody is the final say, when do an offer, then they do a reference check and they do the reference check with somebody that they don't know. And to me, I mean, that's totally useless which quite with LinkedIn today, I could be say if we're looking at you for candidate, maybe a bad example, but I don't know, we probably have a 1000 in common, and from those, we probably have 200 that we both know, well, that I could check. And when you do reference checking, it's not a maybe it's either, hey, the person is a yes, or the person's a no. So trying to do that early in the process, I think is a big differentiator. And then last and probably third piece I'd highlight is, if it's a startup company, you can't get somebody that's just from a big company. If it's a big company role, you can't get somebody that just from a small company, you got to really make sure you kind of peel back the onions and see where they're from. And you could have somebody from a big company, but they were kind of wearing a smaller division. So again, you have to kind of, you can't judge a book by the cover. You got to kind of peel back the onion. >> So Randy, how do people learn more about Sales Community? Where do they go to engage, sign up, et cetera? >> Absolutely, it's salescommunity.com. So it should be pretty straight forward. A lot of great information there. You can go subscribe, and if you like it spread the word and a lot of great content and you can ping me there. And if not I'm randy@salescommunity.com. So love to get any feedback, help out in any way we can. >> Well, I think it's critical that you're putting this network together and you are probably the best networker that I know I've seen you in action at gatherings and you really have been a great inspiration and a friend. So, Randy, thanks so much for doing the Sales Community and coming on theCUBE and sharing your experience with us. >> Great, thanks Dave, appreciate it. >> All right you're very welcome and thank you for watching everybody. This is Dave Vellante for theCUBE, and we'll see you next time. (upbeat music)

>>Hi buddy, we're back. This is Dave Volante with the cube goes out to the shows. We extract the signal from the noise. Nate Silver's here. Nate, we've been saying that since 2010, rip you off. Hey Marcus feeder. Oh, you have that trademarks. Okay. So anyway, welcome to the cube. You man who needs no introduction, but in case you don't know Nate, uh, he's a very famous author, five 30 eight.com. Statistician influence, influential individual predictor of a lot of things including presidential elections. And uh, great to have you here. Great to be here. So we listened to your keynote this morning. We asked earlier if some of our audience, can you tweet it and you know, what would you ask Nate silver? So of course we got the predictable, how the red Sox going to do this year? Who's going to be in the world series? Are we going to attack Syria? >>Uh, will the fed E's or tightened? Of course we're down here. Who'd you vote for? Or they, you know, they all want to know. And of course, a lot of these questions you can't answer because it's too far out. But, uh, but anyway, again, welcome, welcome to the cube. Um, so I want to start by, uh, picking up on some of the themes in your keynote. Uh, you're here at the Tableau conference. Obviously it's all about about data. Uh, and you, your basic, one of your basic premises was that, um, people will misinterpret data, they'll just use data for their own own biases. You have been a controversial figure, right? A lot of people have accused you of, of bias. Um, how, what do you F how do you feel about that as a person who's, uh, you know, statistician, somebody who loves data? >>I think everyone has bias in the sense that we all have one relatively narrow perspective as compared to a big set of problems that we all are trying to analyze or solve or understand together. Um, you know, but I do think some of this actually comes down to, uh, not just bias, but kind of personal morality and ethics really. It seems weird to talk about it that way, but there are a lot of people involved in the political world who are operating to manipulate public opinion, um, and that don't really place a lot of value on the truth. Right. And I consider that kind of immoral. Um, but people like that I think don't really understand that someone else might act morally by actually just trying to discover the way the objective world is and trying to use science and research to, to uncover things. >>And so I think it's hard people to, because if they were in your shoes, they would try and manipulate the forecast and they would cheat and put their finger on their scale. They assume that anyone else would do the same thing cause they, they don't own any. Yeah. So will you, you've made some incredibly accurate predictions, uh, in the face of, of, of others that clearly had bias that, that, that, you know mispredicted um, so how did you feel when you got those, those attacks? Were you flabbergasted? Were you pissed? Were you hurt? I mean, all of the above having you move houses for, for you? I mean you get used to them with a lot of bullshit, right? You're not too surprised. Um, I guess it surprised me how, but how much the people who you know are pretty intelligent are willing to, to fool themselves and how specious arguments where meet and by the way, people are always constructing arguments for, for outcomes they happen to be rooting for. >>Right? It'd be one thing if you said, well I'm a Republican, but boy I think Obama's going to crush Romney electoral college or vice versa. But you should have an extra layer of scrutiny when you have a view that diverges from the consensus or what kind of the markets are saying. And by the way, you can go and they're betting Margaret's, you can go and you could have bet on the outcome of election bookies in the UK, other countries. Right. And they kind of had forecast similar to ours. We were actually putting their money where their mouth was. Agree that Obama was a. Not a lot, but a pretty heavy favorite route. Most of the last two months in the election. I wanted to ask you about prediction markets cause as you probably know, I mean the betting public are actually very efficient. Handicappers right over. >>So I'll throw a two to one shot is going to be to three to one is going to be a four to one, you know, more often than not. But what are your thoughts on, on prediction markets? I mean you just sort of betting markets, you'd just alluded it to them just recently or is that a, is that a good, well there a lot there then then I think the punditry right. I mean, you know, so with, with prediction markets you have a couple of issues. Number one is do you have enough, uh, liquidity, um, and my volume in the markets for them to be, uh, uh, optimal. Right. And I think the answer right now is maybe not exactly. And like these in trade type markets, knowing trade has been, has been shut down. In fact, it was pretty light trading volumes. It might've had people who stood to gain or lose, um, you know, thousands of dollars. >>Whereas in quote, unquote real markets, uh, the stakes are, are several orders of magnitude higher. If you look at what happened to, for example, just prices of common stocks a day after the election last year, um, oil and gas stocks lost billions of dollars of market capitalization after Romney lost. Uh, conversely, some, you know, green tech stocks or certain types of healthcare socks at benefit from Obamacare going into play gain hundreds of millions, billions of dollars in market capitalization. So real investors have to price in these political risks. Um, anyway, I would love to have see fully legal, uh, trading markets in the U S people can get bet kind of proper sums of money where you have, um, a lot of real capital going in and people can kind of hedge their economic risk a little bit more. But you know, they're, they're bigger and it's very hard to beat markets. They're not flawless. And there's a whole chapter in the book about how, you know, the minute you assume that markets are, are clairvoyant and perfect, then that's when they start to fail. >>Ironically enough. But they're very good. They're very tough to beat and they certainly provide a reality check in terms of providing people with, with real incentives to actually, you know, make a bet on, on their beliefs and people when they have financial incentives, uh, uh, to be accurate then a lot of bullshit. There's a tax on bullshit is one way. That's okay. I've got to ask him for anyway that you're still a baseball fan, right? Is that an in Detroit fan? Right. I'm a tiger. There's my bias. You remember the bird? It's too young to remember a little too. I, so I grew up, I was born in 78, so 84, the Kirk Gibson, Alan Trammell teams are kind of my, my earliest. So you definitely don't remember Mickey Lola cha. I used to be a big guy. That's right fan as well. But so, but Sony, right when Moneyball came out, we just were at the Vertica conference. >>We saw Billy being there and, and uh, when, when, when, when, when that book came out, I said Billy Bean's out of his mind for releasing all these secrets. And you alluded to in your talk today that other teams like the rays and like the red Sox have sort of started to adopt those techniques. At the same time, I feel like culturally when another one of your V and your Venn diagram, I don't want you vectors, uh, that, that Oakland's done a better job of that, that others may S they still culturally so pushing back, even the red Sox themselves, it can be argued, you know, went out and sort of violated the, the principles were of course Oakland A's can't cause they don't have a, have a, have a budget to do. So what's your take on Moneyball? Is the, is the strategy that he put forth sustainable or is it all going to be sort of level playing field eventually? >>I mean, you know, the strategy in terms of Oh fine guys that take a lot of walks, right? Um, I mean everyone realizes that now it's a fairly basic conclusion and it was kind of the sign of, of how far behind how many biases there were in the market for that, you know, use LBP instead of day. And I actually like, but that, that was arbitrage, you know, five or 10 years ago now, um, put butts in the seat, right? Man, if they win, I guess it does, but even the red Sox are winning and nobody goes to the games anymore. The red Sox, tons of empty seats, even for Yankees games. Well, it's, I mean they're also charging 200 bucks a ticket or something. you can get a ticket for 20, 30 bucks. But, but you know, but I, you know, I, I, I mean, first of all, the most emotional connection to baseball is that if your team is in pennant races, wins world series, right then that produces multimillion dollar increases in ticket sales and, and TV contracts down the road. >>So, um, in fact, you know, I think one thing is, is looking at the financial side, like modeling the martial impact of a win, but also kind of modeling. If you do kind of sign a free agent, then, uh, that signaling effect, how much does that matter for season ticket sales? So you could do some more kind of high finance stuff in baseball. But, but some of the low hanging fruit, I mean, you know, almost every team now has a Cisco analyst on their payroll or increasingly the distinctions aren't even as relevant anymore. Right? Where someone who's first in analytics is also listening to what the Scouts say. And you have organizations that you know, aren't making these kind of distinctions between stat heads and Scouts at all. They all kind of get along and it's all, you know, finding better ways, more responsible ways to, to analyze data. >>And basically you have the advantage of a very clear way of measure, measure success where, you know, do you win? That's the bottom line. Or do you make money or, or both. You can isolate guys Marshall contribution. I mean, you know, I am in the process now of hiring a bunch of uh, writers and editors and developers for five 38 right? So someone has a column and they do really well. How much of that is on the, the writer versus the ed or versus the brand of the site versus the guy at ESPN who promoted it or whatever else. Right. That's hard to say. But in baseball, everyone kind of takes their turn. It's very easy to measure each player's kind of marginal contribution to sort of balance and equilibrium and, and, and it's potentially achieved. But, and again, from your talk this morning modeling or volume of data doesn't Trump modeling, right? >>You need both. And you need culture. You need, you need, you know, you need volume of data, you need high quality data. You need, uh, a culture that actually has the right incentives align where you really do want to find a way to build a better product to make more money. Right? And again, they'll seem like, Oh, you know, how difficult should it be for a company to want to make more money and build better products. But, um, when you have large organizations, you have a lot of people who are, uh, who are thinking very short term or only about only about their P and L and not how the whole company as a whole is doing or have, you know, hangups or personality conflicts or, or whatever else. So, you know, a lot of success I think in business. Um, and certainly when it comes to use of analytics, it's just stripping away the things that, that get in the way from understanding and distract you. >>It's not some wave a magic wand and have some formula where you uncover all the secrets in the world. It's more like if you can strip away the noise there and you're going to have a much clearer understanding of, of what's really there. Uh, Nate, again, thanks so much for joining us. So kind of wanna expand on that a little bit. So when people think of Nate silver, sometimes they, you know, they think Nate silver analytics big data, but you're actually a S some of your positions are kind of, you take issue with some of the core notions of big data really around the, the, the importance of causality versus correlation. So, um, so we had Kenneth kookier on from, uh, the economist who wrote a book about big data a while back, the strata conference. And you know, he, in that book, they talk a lot about it really doesn't matter how valid anymore, if you know that your customers are gonna buy more products based on this dataset or this correlation that it doesn't really matter why. >>You just try to try to try to exploit that. Uh, but in your book you talk about, well and in the keynote today you talked about, well actually hypothesis testing coming in with some questions and actually looking for that causality is also important. Um, so, so what is your, what is your opinion of kind of, you know, all this hype around big data? Um, you know, you mentioned volume is important, but it's not the only thing. I mean, like, I mean, I'll tell you I'm, I'm kind of an empiricist about anything, right? So, you know, if it's true that merely finding a lot of correlations and kind of very high volume data sets will improve productivity. And how come we've had, you know, kind of such slow economic growth over the past 10 years, where is the tangible increase in patent growth or, or different measures of progress. >>And obviously there's a lot of noise in that data set as well. But you know, partly why both in the presentation today and in the book I kind of opened up with the, with the history is saying, you know, let's really look at the history of technology. It's a kind of fascinating, an understudied feel, the link between technology and progress and growth. But, um, it doesn't always go as planned. And I certainly don't think we've seen any kind of paradigm shift as far as, you know, technological, economic productivity in the world today. I mean, the thing to remember too is that, uh, uh, technology is always growing in and developing and that if you have roughly 3% economic growth per year exponential, that's a lot of growth, right? It's not even a straight line growth. It's like exponential growth. And to have 3% exponential growth compounding over how many years is a lot. >>So you're always going to have new technologies developing. Um, but what I, I'm suspicious that as people will say this one technology is, is a game changer relative to the whole history of civilization up until now. Um, and also, you know, again, a lot of technologies you look at kind of economic models where you have different factors or productivity. It's not usually an additive relationship. It's more a multiplicative relationships. So if you have a lot of data, but people who aren't very good at analyzing it, you have a lot of data but it's unstructured and unscrutinised you know, you're not going to get particularly good results by and large. Um, so I just want to talk a little bit about the, the kind of the, the cultural issue of adopting kind of analytics and, and becoming a data driven organization. And you talk a lot about, um, you know, really what you do is, is setting, um, you know, try to predict the probabilities of something happening, not really predicting what's going to happen necessarily. >>And you talked to New York, you know, today about, you know, knowledging where, you know, you're not, you're not 100% sure acknowledging that this is, you know, this is our best estimate based on the data. Um, but of course in business, you know, a lot of people, a lot of, um, importance is put on kind of, you know, putting on that front that you're, you know, what you're talking about. It's, you know, you be confident, you go in, this is gonna happen. And, and sometimes that can actually move markets and move decision-making. Um, how do you balance that in a, in a business environment where, you know, you want to keep, be realistic, but you want to, you know, put forth a confident, uh, persona. Well, you know, I mean, first of all, everyone, I think the answer is that you have to, uh, uh, kind of take a long time to build the narrative correctly and kind of get back to the first principles. >>And so at five 38, it's kind of a case where you have a dialogue with the readers of the site every day, right? But it's not that you can solve in one conversation. If you come in to a boss who you never talked to you before, you have to present some PowerPoint and you're like, actually this initiative has a, you know, 57% chance of succeeding and the baseline is 50% and it's really good cause the upside's high, right? Like you know, that's going to be tricky if you don't have a good and open dialogue. And it's another barrier by the way to success is that uh, you know, none of this big data stuff is going to be a solution for companies that have poor corporate cultures where you have trouble communicating ideas where you don't everyone on the same page. Um, you know, you need buy in from, from all throughout the organization, which means both you need senior level people who, uh, who understand the value of analytics. >>You also need analysts or junior level people who understand what business problems the company is trying to solve, what organizational goals are. Um, so I mean, how do you communicate? It's tricky, you know, maybe if you can't communicate it, then you find another firm or go, uh, go trade stocks and, and uh, and short that company if you're not violating like insider trading rules of, of various kinds. Um, you know, I mean, the one thing that seems to work better is if you can, uh, depict things visually. People intuitively grasp uncertainty. If you kind of portray it to them in a graphic environment, especially with interactive graphics, uh, more than they might've just kind of put numbers on a page. You know, one thing we're thinking about doing with the new 580 ESPN, we're hiring a lot of designers and developers is in case where there is uncertainty, then you can press a button, kind of like a slot, Michigan and simulate and outcome many times, then it'll make sense to people. Right? And they do that already for, you know, NCAA tournament stuff or NFL playoffs. Um, but that can help. >>So Nate, I asked you my, my partner John furry, who's often or normally the cohost of this show, uh, just just tweeted me asking about crowd spotting. So he's got this notion that there's all this exhaust out there, the social exhaustive social data. How do you, or do you, or do you see the potential to use that exhaust that's thrown off from the connected consumer to actually make predictions? Um, so I'm >>a, I guess probably mildly pessimistic about this for the reason being that, uh, a lot of this data is very new and so we don't really have a way to kind of calibrate a model based on it. So you can look and say, well, you know, let's say Twitter during the Republican primaries in 2016 that, Oh, Paul Ryan is getting five times as much favorable Twitter sentiment as Rick Santorum or whatever among Republicans. But, but what's that mean? You know, to put something into a model, you have to have enough history generally, um, where you can translate X into Y by means of some function or some formula. And a lot of data is so new where you don't have enough history to do that. And the other thing too is that, um, um, the demographics of who is using social media is changing a lot. Where we are right now you come to conference like this and everyone has you know, all their different accounts but, but we're not quite there yet in terms of the broader population. >>Um, you have a lot of kind of thought leaders now a lot of, you know, kind of young, smart urban tech geeks and they're not necessarily as representative of the population as a whole. That will over time the data will become more valuable. But if you're kind of calibrating expectations based on the way that at Twitter or Facebook were used in 2013 to expect that to be reliable when you want a high degree of precision three years from now, even six months from now is, is I think a little optimistic. Some sentiment though, we would agree with that. I mean sentiment is this concept of how many people are talking about a thumbs up, thumbs down. But to the extent that you can get metadata and make it more stable, longer term, you would see potential there is, I mean, there are environments where the terrain is shifting so fast that by the time you know, the forecast that you'd be interested in, right? >>Like things have already changed enough where like it's hard to do, to make good forecast. Right? And I think one of the kind of fundamental themes here, one of my critiques is some of the, uh, of, uh, the more optimistic interpretations of big data is that fundamentally people are, are, most people want a shortcut, right? Most people are, are fairly lazy like labor. What's the hot stock? Yeah. Right. Um, and so I'm worried whenever people talk about, you know, biased interpretations of, of the data or information, right? Whenever people say, Oh, this is going to solve my problems, I don't have to work very hard. You know, not usually true. Even if you look at sports, even steroids, performance enhancing drugs, the guys who really get the benefits of the steroids, they have to work their butts off, right? And then you have a synergy which hell. >>So they are very free free meal tickets in life when they are going to be gobbled up in competitive environments. So you know, uh, bigger datasets, faster data sets are going to be very powerful for people who have the right expertise and the right partners. But, but it's not going to make, uh, you know anyone to be able to kind of quit their job and go on the beach and sip my ties. So ne what are you working on these days as it relates to data? What's exciting you? Um, so with the, with the move to ESPN, I'm thinking more about, uh, you know, working with them on sports type projects, which is something having mostly cover politics. The past four or five years I've, I've kind of a lot of pent up ideas. So you know, looking at things in basketball for example, you have a team of five players and solving the problem of, of who takes the shot, when is the guy taking a good shot? >>Cause the shot clock's running out. When does a guy stealing a better opportunity from, from one of his teammates. Question. We want to look at, um, you know, we have the world cup the summer, so soccer is an interest of mine and we worked in 2010 with ESPN on something called the soccer power index. So continuing to improve that and roll that out. Um, you know, obviously baseball is very analytics rich as well, but you know, my near term focus might be on some of these sports projects. Yeah. So that the, I have to ask you a followup on the, on the soccer question. Is that an individual level? Is that a team level of both? So what we do is kind of uh, uh, one problem you have with the national teams, the Italian national team or Brazilian or the U S team is that they shift their personnel a lot. >>So they'll use certain guys for unimportant friendly matches for training matches that weren't actually playing in Brazil next year. So the system soccer power next we developed for ESPN actually it looks at the rosters and tries to make inferences about who is the a team so to speak and how much quality improvement do you have with them versus versus, uh, guys that are playing only in the marginal and important games. Okay. So you're able to mix and match teams and sort of predict on your flow state also from club league play to make inferences about how the national teams will come together. Um, but soccer is a case where, where we're going into here where we had a lot more data than we used to. Basically you had goals and bookings, I mean, and yellow cards and red cards and now you've collected a lot more data on how guys are moving throughout the field and how many passes there are, how much territory they're covering, uh, tackles and everything else. So that's becoming a lot smarter. Excellent. All right, Nate, I know you've got to go. I really appreciate the time. Thanks for coming on. The cube was a pleasure to meet you. Great. Thank you guys. All right. Keep it right there, everybody. We'll be back with our next guest. Dave Volante and Jeff Kelly. We're live at the Tableau user conference. This is the cube.