 We're back. This is Dave Vellante of theCUBE and we're here with Ray Wong who just wrote a book reminiscent of the famous Tears for Fear song. Everybody wants to rule the world surviving and thriving in a world of digital giants. Great. Great to see you again, man. It's going on, man. How are you? Oh, great. Thanks for coming on. You know, it's crazy. You've been crazy, but it's good to see you face to face. This is. We're in the flesh. It's live. We're having conversations and the information that we're getting is cut right. Yeah. So why did you write this book and how did you find the time? Hey, we're in the middle of a pandemic. No. I wrote the book because what was happening was digital transformation efforts. They're starting to pop up, but companies weren't always succeeding and something was happening with digital giants that was very different. They were winning in the marketplace and never in the form of if you think about extreme capitalism, if we think about capitalism in general, never in the history of capitalism have we seen growth of large companies. They get large. They fall apart. They don't have anything to build. They can't scale. The organizations are in shambles. But what happened? If you look at 2017, the combined market cap of the fangs and Microsoft was two trillion. Today, it is almost 10.2 trillion. It's quintippled. That's never happened. And there's something behind that business model that they put into place that others have copied from the Airbnb's to the robloxes to what's going to happen with like a Starlink and of course, the Robin Hoods and, you know, Robinson and Coinbases of the world. And the fundamental premise is all around data. Putting data at the core, if you don't do that, you're going to fly blind. It is. And the secret behind it is these long-term platforms called data-driven digital networks. These platforms take the ability to large memberships or large devices. They look at that effect. Then they look at figuring out how to actually win on data supremacy. And then, of course, they monetize off that data. And that's really the secret behind that is you've got to build that capability. And what they do really well is they disintermediate customer account control. They take the relationships, aggregate them together. So, food delivery app companies are a great example of that. You know, small businesses were out there that hundreds and thousands of customers. Today, what happens? Well, they've been aggregated. Millions of customers together into a food delivery app. Well, I think, you know, this is really interesting what you're saying because if you think about how we deal with Netflix, we don't call the Netflix sales department or the marketing department of the service. Just one interface to Netflix. So, they've been able to put data at their core. Can incumbents do that? How can they do that? Incumbents can definitely do that. And it's really about figuring out how to automate that capture. What you really want to do is you start in the cloud, you bring the data together, and you start putting the three A's. Analytics, automation, and AI are what you have to be able to put into place. And when you do do that, you now have the ability to go out and figure out how to create that flywheel effect inside those data-driven digital networks. These DDDNs are important. So, in Netflix, what are they capturing? They're looking at sentiment. They're looking at context. Like, why did you interact with, you know, one title versus another? Did you watch Ted Lasso? Did you switch out of Apple TV to Netflix? Well, I want to know why. Right? Did you actually jump into another category? You switched into genres? After 10 p.m., what are you watching? Maybe something very different than what you're watching at 2 p.m. How many members are in the home? Right? All these questions are being answered, and that's the business graph behind all this. How much of this is kind of related to the way organizations or companies are organized? In other words, you think about historically, they would maybe put the process at the core or the, you know, bottling plant and the manufacturing facility at the core, and the data is all dispersed. It talks about silos. So, will AI be the answer to that? Will some new database? Snowflake? Is that the answer? What's the answer to sort of bringing that data together, and how do you deal with the organizational inertia? Well, the trick to it is really to have a single-plane deal of access to that data. I don't care where the data sits. Whether it's on-premise, whether it's in the cloud, whether it's in the edge, it makes no difference. That's really what you want to be able to do is bring that information together. But the glue is the context. What time was it? What's the weather outside? What location are you in? What's your heart rate? Are you smiling? All those factors come into play, and what we're trying to do is take a user, so it could be a customer, a supplier, a partner, or an employee, and how do they interact with an order dock, an invoice, an incident, and then apply the context, and what we're doing is mining that context and information. Now, the more, back to your other point on self-service and automation, the more you can actually collect those data points, the more you can capture that context, the more you're able to get to refine that information. Context, that's interesting, because if you think about our operational systems, we've contextualized most of them, whether it's sales, marketing, logistics, but we haven't really contextualized our data systems, our data architecture. It's generally run by a technical group. They don't necessarily have the line of business context. You see what HPE's doing today. It's trying to be inclusive of data on-prem. I mentioned Snowflake. They're saying, no way. Frank Slutman says, we're not going on-prem, so that's kind of interesting. So how do you see sort of context evolving with actually the business line, who has the context actually can, I hate to use the word, but I'm going to own the data. You have to have a data to decisions pathway. That data decisions pathway is you start with all types of data, structured, unstructured, semi-structured. You align it to a business process, issue to resolution, order to cash, procure to pay, hire to retire. You bring that together, and then you start mining and figuring out what patterns exist. Once you have the patterns, you can then figure out the next best action, and when you get the next best action, you can compete on decisions, and that becomes a very important part. That decision piece, that's going to be automated, and when we think about that, you and I make a decision, one per second. How long does it get out of management committee? Could it be a week, two weeks, a quarter, a year? It takes forever to get anything out of management committee, but these new systems, if you think about machines, can make decisions a hundred times per second, a thousand times per second, and that's what we're competing against. That asymmetry is the decision velocity. How quickly you can make decisions will be a competitive weapon. Is there a dissonance between the fact that you just mentioned speed, compressing that sort of time to decision, and the flip side of that coin, quality, security, governance, how do you see squaring that circle? Well, that's really why we're going to have to make that. That's the automated, that's the AI piece. Just like we got all types of data, we got to spew up automated ontologies. We got to spin them up, we got to be using, we got to put them back into play, and then we got to be able to take back into action. And so you want enterprise class capabilities. That's your data quality, that's your security, that's the data governance, that's ability to actually take that data, understand time series, and actually make sure that the integrity of that data is there. What do you think about this sort of notion that increasingly people are going to be building data products and services that can be monetized, and that kind of goes back to context, the business lines kind of being responsible for their own data, not having to get permission to add another data source. Do you see that trend, do you see that decentralization trend? Two-part question, and where do you see HPE fitting into that? I see one that that trend is definitely going to exist. I'll give you an example. I can actually destroy the top two television manufacturers in the world in less than five years. I could take them out of the business, and I'll show you how to do it. So I'm going to make you an offer, $15 per month for the next five years. I'm going to give you a 72-inch, is it 74? 75-inch, 75-inch smart TV, 4K, big TV, and it comes with a warranty. And if anything breaks, I'm going to return it to you in 48 hours or less with a brand new one. I don't want your personal information, I'm only going to monitor performance data, I want to know the operations, I want to know which supplier lied to me, which components are working, what features you use, I don't need to know your personal viewing habits. Okay, would you take that deal? TV is a service, sure, of course I would. $15, and I'm going to make it a better deal. For $25 a month, you get to make an upgrade anytime during that five-year period. What would happen to the two largest TV manufacturers if I did that? Yeah, they'd be disrupted. Now, you obviously have a pile of VC money that you're going to do that. Will you ever make money at that model? Well, here's why I'll get there, and I'll explain. What's going to happen is, I locked them out on the market for four to five years. I'm going to take 50-60% of the market, yes, I got to raise $10 billion to figure out how to do that. But that's not really what happens at the end. I become a data company because I have warranty data. I'm going to buy a company that does insurance like an Asurion. I'm going to get break-fixed data from a Best Buyer company like that. I'm going to get it safety data for Underwriters Lab. It's a competition for data. And suddenly, I know those habits better than anyone else. I'm going to go do other things more than the TV. I'm not done with the TV. I'm going to do your entire kitchen. For $100 a month, I'll do mid-range. For $500 a month, I'm going to take your dishwasher, your dryer, your refrigerator, your range, and I'll do like mealy, gagging out. If you want to go down Viking Wolf, I'll do it for $450 a month for the next 10 years. By year five, I have better insurance information than the insurance companies from warranty. And I can even make that deal portable. You see where we're going? Yes, so each of those, I see them as data products. So you've got your TV service products, you've got your kitchen products, you've got your maintenance data products. All those can be monetized. And I went from TV manufacturer to Underwriter overnight. I'm competing on data on insurance and underwriting. And more importantly, here's the green initiative. Here's why someone would give me $10 billion to do it. I now control 50% of all power consumption in North America, because I'm also going to do HVAC units. And I can actually engineer the green capabilities in there to actually do better power purchase consumption, better monitoring, and also smart capabilities in those appliances. And that's how you actually build a model like that. And that's how you can win on a data model. Now, where does HPE fit into that? Their job is to bring that data together at the edge. They bring that together in the middle. Then they have the ability to manage that on a remote basis and actually deliver those services in the cloud so that someone else can consume it. All right. So if you're hitting on something that some people have talked about, but I don't think it's widely sort of discussed. And that is historically, if you're in an industry, you're in that industry's vertical stack, the sales, the marketing, the manufacturing, the R&D, you become an expert in insurance or financial services or whatever, automobile manufacturing or radio and television, etc. Obviously, you're seeing the big internet giants, those 10 trillion, some of the market caps, they're using data to traverse industries. We've never seen this before. Yes, we know. Amazon and content. You're seeing Apple and finance. Others are going into healthcare. So they're technology companies that are able to traverse industries. Never seen this before. And it's because of data. And it's the collapsing value chains. Their data value chains are collapsing. Coms, media, entertainment, tech, same business. Whether you sell me a live stream TV, a book, a video game or enterprise software, it's the same data value stream on multi-sided networks. And once you understand that, you can see retail, distribution, manufacturing collapsed in the same kind of way. So Silicon Valley broadly defined, if I can include Microsoft and Amazon in there, they seem to have a dual disruption agenda. One is on the technology front disrupting the traditional enterprise business. The other is they're disrupting industries. How do you see that playing out? Well, the problem is they're never going to be able to get into new industries going forward because of the monopoly power that people believe they have. And that's what's going on. But they're going to invest in creating joint venture startups in other industries as they power the tools to enable other industries to jump and leave Froghorn before they are. So healthcare, for example, we're going to have AI monitoring in ways that we've never seen before. You can see devices enter healthcare, but you see joint venture partnerships between a big hyperscaler and some of the healthcare providers. So HPE, transforming into a cloud company as a service, do you see them getting into insurance as you just described in your little digital example? No, but I see them powering the folks that are in insurance. They're not going to compete with their customers, maybe the way on Amazon. No, that's actually why you would go to them as opposed to a hyperscale that might compete with you, right? So is Google going to get into the insurance business? Probably not. Would Amazon maybe? Is Tesla in the business? Yeah, they're definitely in insurance. Yeah, big time, right. So, okay, so tell me more about your book. How's it being received? What's the reaction? What's your next book? So the book is doing well. We're really excited. We did a 20-city book tour. We had chances to meet everybody across the board, clients we could see in a while, partners we didn't see in a while, and that was fun. The reaction is, if you read the book carefully, there are $3 trillion market cap opportunities, $100 billion unicorns that can be built right there. Do you have a copy for me that's signed? Sorry, I'm choking on the makeup. I can get one actually in the back. Do you want one? I do. I want one. Can someone bring my book bag? I actually have one. I can sign it right here. Yeah, you know what? If we have a book, I'd love to hold it. Do you have any here as well? So it's obviously, you know, we can repeat. Everybody wants to rule the world, surviving and thriving in a world of digital giants available, you know, wherever you buy books. I'll answer your question on the next book, yeah. So, oh, are we still, we're going? Yeah, yeah, we're going. Okay, okay. What's the next book? Next book? Well, it's about disrupting those digital giants, and it's going to happen in the metaverse economy. If we think about where the metaverse is, not just the hardware platforms, not just the engines, not just what's going on with the platforms around DeFi decentralization and the content producers, we see those as four different parts today. What we're going to actually see is a whole conf… It's a confluence of events that's going to happen where we actually bring in the metaverse economy and the stuff that Nils, Nils Stevenson was writing about ages ago, and Snow Crash is going to come out real. So, okay, so you're laying out a scenario that the big guys, the disruptors, could get disrupted. Sounds like crypto is possibly a force in that disruption. Decentralized currencies, crypto plays a role, but it's the value exchange mechanisms in Algorand, in an Ether, right, in a Cordano that actually enables that to happen, because the value exchange and the smart contracts power that capability. And what we're actually seeing is the reinvention of the internet. So, you see things like Scion pop up, which actually is creating the new set of the internet standards. And when those things come together, what we're actually going to move from is, the seller is completely transparent, the buyer is completely anonymous, and it's in a trust framework that actually allows you to do that. Well, you think about those protocols, the internet protocols that were invented about 30 years ago, maybe more TCPIP, wow. I mean, and they've been co-opted by the internet giants, it's the crypto guy, some of the guys you would mention that are actually innovating and putting down new innovation, really, and have been well-funded to do so. I mean, I'll give you another example of how this could happen. About four years ago, five years ago, I wanted by Air Canada's mileage program. $400 million, 10 million users, 40 bucks a user. What do we want in a mileage program? Well, think about it. It's funded, a penny per mile, it's redeemed at 1.6 cents a mile, it's 2 cents even by magazines, 2.5 cents if you want electronics, jewelry, or sporting equipment. You don't lose money on these, CFOs hate them. They're like, oh, liability on the books, but they mortgage the crap out of them in a middle-of-ish problem and banks pay millions of dollars a year for those mileage points. But I don't want it for the 10 million flyers in Canada. What I really want is the access to 762 million people in Star Alliance. What would happen if I turned that airline mileage program into a cryptocurrency? One, I would be the world's largest cryptocurrency on day one. What would happen on day two? I'd be the world's largest ad network. Cookie Apocalypse? Go away. We don't need that anymore. And more importantly, on day three, what would I do? My ESG here, 2.2 billion people are unbanked in the world. All you need is a mobile device and a connection. Now you have a currency without any government regulation around banking, intermediaries, a whole bunch of people like taking cuts, loan sharking, that all goes away. You still only have people that are now banked and you've banked the unbanked and that creates a whole very different environment. Not a lot of people thinking about how the big giants get disintermediated, get the book, look into it. Big ideas. Ray Wong, great to see you, man. Hey man, thanks a lot. Thank you. All right, and thank you for watching. Keep it right there for more great content from HPE's Big Green Lake announcements. Right back.