 TheCube presents HPE Discover 2022 brought to you by HPE. Welcome back to theCUBE's day one coverage of HPE Discover 2022 live from Las Vegas. Lisa Martin here with Dave Vellante. We've got a couple of guests here with us next. Going to be talking about industry transformation. Please welcome Brad Schleggenhoff, Director of Global Industry and Sustainability Marketing and Andy Hulkhalter, Senior Director of Worldwide Industry Sales Programs, guys from HPE. Thanks for joining us. Thank you for having me here. Industry transformation, that's a big term. It's not a new concept, but we see so much going on. Andy, talk to you about industry transformation from your perspective. Where are customers? How are they capitalizing to really make data a true currency? Right. Well, underlying all this is the data that is becoming so complex. But at the same time, there's specialization required in each industry with the different applications that the industries are running and our ability to bring that forward and connect all those things is a big trend going on. And as we see that developing over time, we're getting more, connecting those different applications that are running is becoming more every day. We're doing more of that. One more. So where do you want to start? What's your favorite industry to transform? I mean, financial services has got the whole blockchain thing going on. Industry 4.0 and manufacturing, retail, everybody has an Amazon war room, energy now with EVs and solar and everything else and the price of oil. And now you throw in inflation and supply chain. I mean, it's just every industry is getting disrupted. I want to make an observation. You guys tell me what you think. Think about the incumbent industries. They generally have data at the outskirts. It's all siloed. And they're trying to put it at the core and that's a big challenge for them. What are you guys seeing in terms of who's having success with that? Do you have examples? What role do you play? We have so much to talk about. Yeah, yeah, I'll jump in here. I mean, I think one of the unique ideas is all those industries you mentioned there are all trying to learn from each other, right? If you're a financial institution, you want to understand what retail is doing because you want to serve your customers better, right? You want to look at some of these technologies, how they're being applied. You look about like sustainability. The industries are trying to learn how to do that better from each other. So this notion of industry transformation is kind of twofold. It's one, how are these industries almost like entering new markets? I mean, you look at all the tech companies out there, they're all getting into payments, for example, right? You know, Google Pay, Apple Pay, yeah. So that's just like one example of where you're seeing that blurring of lines between industries happening. Content, Amazon getting into grocery. And so in the premises, the data is the enabler. I mean, right for decades, we've seen a stack, a vertical stack within an industry where whether it's research and development, manufacturing, sales, and distribution, marketing, you were in that industry stuck for life and now all of a sudden, data allows you to traverse industries. This dual disruption agenda that you mentioned. Yeah, it's really, at its core is because these companies have the ability to take advantage of that data even more and they're trying to serve their customers even better that that's kind of opening up these new doors for them to do that because that's, you know, and again, there's so many good examples out there. Automobile manufacturers are looking towards the gaming industry, how do they design controls? That kind of stuff is an example. So you see all kinds of that. You mentioned also that everybody's trying to bring the data to the core. I don't think that's necessarily true. I think you heard earlier today in the keynote that companies want to be able to take advantage of the data wherever it is. It's the edge and a factory floor. It's patient data sitting somewhere. You want to handle it where it is and there's a cost to doing that to bring it all together. Yeah, so by the way, I want to clarify because you're absolutely right. The data by its very nature is distributed. Sure. When I say core, I mean, put it at the core of their business. Sure. That's what I mean by data first, but your point is really, we're going to talk about that because it brings so many other challenges with how you deal with that, but please jump in Lisa. I was going to ask you, Brad, talk about the blurred lines between industries and talk to us about how is HPE, a facilitator of those industries learning from each other? You have such breadth in so many different industries, as Dave mentioned, but how are you that enabler, if you will, of allowing them to be able to have data be that key? Yeah. I think it just comes through the experience of working with these customers in these various industries, and then there's so many times where customers come to us, they want us brief, and again, they want to learn for these other industries. We're an aggregator of that technology. We obviously understand the technology with cloud or Edge or anything we're doing with data, so we're using those lessons and just applying those out there to those industries. I think it's just us as an aggregator. How's the customer experience changing? We heard from Home Depot this morning, they were focused on the customer experience and their associate experience bringing those together. Well, what we also heard this morning is the different personas that are out there and that are looking to transform their business, and each of those personas is still linked together by the data, but they want to use it in different ways with different applications, and the ability to connect all those things, again, they're learning from each industry, so what Home Depot learns about their mobile apps may be something that we can deploy in manufacturing as far as locating things on the floor and connecting the Edge data in, and then use that to analyze, use AI models to do predictive behavior, preventative maintenance. All these things are similar uses of connecting the data but then applying to the specific industry use case, and that pivot of that horizontal use of the data into those specific demands by the personas within the different industries is what we're focused on. And the technology is like an accelerant here, so you're thinking about something like 5G, right? 5G is going to accelerate a lot of transformation in various industries throughout that. I mean, the technology alone is not really what the customer cares about, they care about what do I do with that, what kind of outcome can I get? I want to ask you, Andy, about the customer conversations. You talked about the personas, we've been talking about data democratization for a very long time, obviously it's a challenging thing to do, but how are you seeing customer conversations change and evolve, especially over the last couple of years where every LOB has to have access to data and be a driver of its value? Well, the customer, you know, historically HPE's background is in infrastructure and we've served industries in the data center for a legacy, right? But now they're saying it's more, I've got to talk to more people in my business as a data center owner, I've got to serve these folks, understand their business, and as a supplier to me, you need to understand them as well and sometimes help me with that conversation and help me see the things to make those connections that I may not know as a data, as an IT professional. And how do we challenge the business to think about different ways of doing things in the industry? So how do we think about, bringing those connections from other industries in and uncovering opportunities or problems, anticipating problems in those deployments that they may not have seen by their staying in their swim lane? You know, I'm torn on this topic because on the one hand, I think about the big data era and I know a lot of failures to return the expectations and it wasn't a fail fast, took a decade to get there and part of the failure domain was, to your earlier point Brad, everything was sort of shoved into this centralized location, you have this hyper-specialized data team and everybody has to go through them but organizations I think are now realizing like your thoughts on this, that data has to go out to the lines of business, it has to be contextualized, people are now talking about building data products and monetizing data and that's really to me what digital transformation is about. So, but generally speaking, most companies are not great at data, they have a lot of data, a lot of data line around insights, I think we heard in the morning keynote are scarce, so what's your vision for how this evolves? Yeah, I think from the data perspective, again, at the core is how do I serve my customer better, right? So, whether that is actual customer data that you want to sort of personalize offers for or make decisions of medical decisions for their better patient outcomes, so if they keep that in mind, then as far as how it's used by the different lines of business there, that's where we can help facilitate in many ways and that's where cloud becomes a really key technology, having that flexibility to move it around as needed, create, deliver the workload where the customer needs it, that sort of idea is where we're going with this, I think. I'd like to give you an example. Please. In the FSI industry, out here on the floor, we've got a demo on payment systems, right? And we've been doing that with our nonstop product and supporting that in the banking industry for 10 years or more and it's evolved over time to be one of the, it's a ubiquitous across the, in the support. But now we're talking about new regulations with all the global events that are going on, crazy stuff that had more pressure on the banks to comply with that, worries about money laundering and fraud prevention. Well, connecting the data from those payment systems into the AI modeling that is now being deployed to do more sophisticated fraud detection and money laundering detection and all of those kinds of things, how you connect those together as an example of what we're seeing, how we get more insights by the combination that we can bring together. And the insights is critical, right? I mean, without it, the data isn't very useful. Right, right. And I think even these concepts like swarm learning, right? Where you're actually trying to aggregate a lot of those, a lot of that data and provide even a broader data set to learn from is even more beneficial. I think that when you think about the principles of this decentralized world, that it starts with an organization saying, look, we recognize that we can't shove it all into a data warehouse or a data hub or a single data lake. We're going to have all of those. And those are just kind of nodes in the mesh, if I could steal a Jamak, the Ghani term. And increasingly, data as product that can be monetized, we're hearing a lot more about this. And those are organizational considerations. I mean, HPE can maybe facilitate that through whiteboard sessions, but that leads to, in order to democratize data, I need self-service infrastructure and I need data that can be shared and governed. I don't know about the last one, but you definitely are number three. Self-service infrastructure, simplification, your version of cloud. How do you see that, your role in that little vision that I just laid out, do you buy that? You want to take that or? Well, I think that we have, we definitely, because we see the data in all these different places, and we're trying to be agnostic to where it comes from, who owns it, how do you get it together and make it useful? And you don't have to capture it, you don't have to own it, but you may own some of it, you may borrow some of it, you may rent some of it, you may buy it, and you may bring it together and they'll use it for the purpose and then move on to expand into new things that you learn from, that you may then monetize in all those different ways. So we have a role of making that platform in a way that you can see it in different ways and use it consistently and repetitively and gain more value of it and then apply your applications and all those other things that you do, but that bringing it together agnostically is a big part of our offering. And am I not correct? I mean, my thinking on HPE's value is providing that infrastructure to be able to do just that. That's your swim lane, if you will. It is, but we're being asked to move up the stack and provide not only the infrastructure, now the platform, the ability to offer that platform in our HPE GreenLake offering where we now can have cloud-like services on-prem, it doesn't really matter where the data sits, and then plug in the applications and even manage those applications for the customers. Okay, so I mean, I see you as IaaS and PaaS, which is that up the stack, the ability to, okay, I want whatever, Python or OpenShift, and I want to build applications now on that. Interesting, the management piece is something that I excluded because an organization may say, hey, we need help managing this stuff, but I see that IaaS and PaaS as infrastructure, you're not getting into applications where you're getting, you're not. Other than letting customers actually build on top of that, right? There's a lot of customers. You're an enabler. Absolutely, yeah. You look at some of the things we're doing with our Esmeralda platform and things like that, we're providing that development platform in a really streamlined way of pushing applications out. I mean, little known fact, right, is that most banks right now are hiring more developers right now than finance people. So all these industries are becoming tech companies, and that's the whole launch of the FinTech industry many years ago, and it's continued to evolve. And they want to bring AI, they want to bring data into their applications, and you, HPE, I see as an enabler of that. Absolutely, yeah, absolutely. Give us last question as we wrap up here. Give us the vision, like the next five years, what are some of the industry transformation elements you're forecasting if you have a crystal ball? Yeah, yeah, yeah, I think number one, just an increased focus on personalization and customization, you look at personalized offers, when you add location-based services, things like that, combined 5G, all these technologies, you're seeing a lot of that custom manufacturing. So those kinds of trends are going to continue, and we know those are the workloads that we've got to know is coming down the pike and address those. Secondly, I think AI, right? AI is going to be, it's going to impact every industry in a big, big way, like Andy talked about fraud detection, manufacturing robotics, those kind of things. And then I think, lastly, just this more convergence of these industries, right? Tech is just impacting everything in such a big way, and so you're going to see more of that blurring of lines between industries as they jump into, jump out of their normal swim lanes, right? Right, between machine learning and AI, we're going to see efficiencies by doing things better with less deviations and driving lower cost, and we're going to see new capabilities come to the forefront. And that's going to be consistent across all industries, and it's going to be based on the data. Both of those require the data to go in and drive their models. Do you think any industry is more ripe for disruption? I mean, timeframe-wise, you've got healthcare, like I was wondering how is AI going to help doctors make better diagnoses? Already is, will AI make the diagnoses? Retail, I mentioned before, energy, government is changing, entertainment, media and entertainment is, do you see any industry patterns where one is being disrupted more than the other? When we talk to customers, every industry thinks their industry is not going fast enough. It's like, I think everybody is just so hyper-focused on what they are involved in and their domain that depending on who you talk to, you don't, everybody needs to do it faster, more economically and more efficiently. And so I think- And they're all being disrupted now too. It's not only have to do faster, but they've got to transform to keep up with the demands of their customers. Nobody's safe. Yeah, and the technology's just going to continue to accelerate that. And that's the thing. And the market's becoming less forgiving as we go. So people have to react really, really fast in these markets, especially with all the other changes going on around us to actually make that impact. I'm liking what's in this crystal ball. I'm going to have to ask you guys for some consult after we wrap here. Thank you so much for joining Dave and me talking about industry transformation, tremendous amount of transformation so far and so much to go. It's exciting to watch. Yeah, appreciate it. Thank you for having us today. Appreciate it. For our guests and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live tech coverage. We'll be back after a short break.