>>The cube presents HPE discover 2022 brought to you by HPE. >>Hi buddy. We're back. This is the Cube's coverage of H P's discover a big discover event this year, 2022 in Las Vegas. We're at the, what used to be called the sands convention center. Now the Venetian Dave Lotte for John furrier per deep Kumar is here. He is the senior vice president and general manager of HPE E's point next services where the rubber meets the road services is where it's at. That's that's where the value is. <laugh> right. >>It's absolutely >>Great to see you again, man. Thanks for coming on. Okay. >>Welcome John. Hopefully y'all are having a good time. >>Yeah, it's very nice to be. It was always great to be face to face. Right? It's nothing like it. Yeah, yeah, yeah. You know, we, we slog through two years of virtual and >>It was packed in keynote. Antonio's keynote was jam packed overflow rooms. Yeah. Um, and it was a big room. It wasn't a small room. It was huge. So that's a sign. Yeah. >>People are here good times. Yeah. People love to be here. Yeah. So >>What's the update with, with point next >>It's, uh, lot's happening. Lot's happening, right? Uh, the transformation is underpinned by point next doing the right thing and just, uh, transforming and helping customers to transform themselves as well with the pandemic it just caught on. Right. Everybody wants to do things faster, digitize things faster. And uh, we really bring the technology and the expertise. I think that's this pretty crucial, >>You know, what, what are the, how do you think about success rates with transformations on the one hand? It, it kept the industry going all industries going on the other hand, I feel like a lot of the transformations were rushed. I call it the forced March to digital. Yeah. Yeah. What failures did you see in that? Forced March and, and how are companies course correcting? Yeah, >>Really good question. <laugh> Dave, um, more than half of the transformations fail, right? So there was a BCG study done over 3000 customers over three years around the world. And, um, 57% of the transformations failed. Right. In the sense when somebody start to transform, they, they set it out a set of goals, scope it. This is what it is. They either didn't meet the goal or they spent more money than they should have, or they overshot the timing. Right. Or all of this about, so it's a staggering number, uh, a large piece of them fail. Yeah. Right. So, um, to answer your second question, Dave, so what are we finding out? Why are they failing and what are they, how are they course-correcting I think there's sort of, you know, we speak to customers all the time. So we get an idea of, you know, what's working and what's not working and there's sort of three things that keep on coming up. >>Right. One is, uh, senior management, CEO, CIO, commitment to the north star. Yeah. Right. Hey, are we tied in, are we doing this? The second thing is the, um, the alignment between it and the business and the functions. Right. If you don't agree on the goal set, if you don't agree on the timeline, uh, then it just, you know, don't work. <laugh> the third is expertise. The people underestimate the expertise. You need the discipline, you need to get stuff done. Right. And so these are the three and none of them are technology related. Yeah. I mean, you're heard they're all people related stuff. >>Right. But di I want to get your thoughts on this is a really important point. I love that commentary because what we're seeing as well is that with COVID now we're kind of third year post COVID, if you will. Yeah. I was just getting out of COVID. It caught a lot of people flatfooted. So people who were on a digital transformation either got stuck and fell down or failed, or they had a tailwind going into it and had momentum. They had alignment and they were filling gaps. They kind of crossed over at the right point and could succeed during the pandemic. But many people failed. Yeah. Because they didn't prepare, they didn't have the technology. They had too many gaps. They had antiquated old stuff. What have you learned? Because this is now ignited the services business because no one wants to have that happen again. Yeah. Can you share your experiences with that? With the customers that are going through that learning pain? What are their core issues? Some projects got doubled down on some got killed. Hey, we don't need that anymore. So what, what are the learnings? Well, tell, share us your perspective, cuz this is important. >>Yeah. So people want to do transformation, right? Absolutely. Because it's a must with COVID faster, quickly you want to get, but they also have to run the business because otherwise you don't have the EPS to support the transformation. Right. So it's, it's transform and perform. So we call it within HP perform while you transform and people who got that balance right. Created that flywheel, John >>Don't run outta gas in other words, translation. >><laugh> exactly. So second thing is, so you have a set of people, you have expertise and COVID you started losing people. Great resignation. You heard everything. Then you are trying to balance your people between, do you put them on transformation or do you put them on operating this stuff? This is where companies then now are realizing, Hey, if I put my best guys on transformation, I need to make sure this operations work well. So people are coming to us and saying, Hey, could you operate this one? Well, right. I mean, today we had somebody on stage, in low medical. Right. They, um, they got a ransomware hit and they had been using us, um, to do all the operations. And when hit hit, we were like switched on. They're like, I mean, on stage they're like you guys were golden, took care of the situation. So if you didn't have any extra help of some expertise, then you are really suffering. Right? >>Yeah. We heard this too. From partners we heard during the pandemic, a lot of the partners stepped up the channel and ISV partners. Yeah. Because they could. Yeah. And that was another key point. Yeah. It all comes together. I love to perform and transform Dave, cuz this is about running the business. Cuz you have cyber security as a serious problem right now. Yeah. That's also part of the transformation. Yeah. Where's the overlap. What are the areas that you're seeing, where you gotta operate and transform? Where's the hot zone. So to speak with customers, is it cyber? Is it, is it, uh, data, data? >>I would say clearly data is number one, right? In anything. Now data, data modernization is the key. Otherwise you are not changing your company the way you do things. So we just announced four real big stuff, addressing, uh, data migration. Right. Um, one of the problems so people have is quality of data. Quality of data is not good. They exist in silos. Mm-hmm <affirmative>, it's not in a platform form where you can really take the data, get the insights and use it for your future. Right. I mean that's a key problem, right? Yeah. So you, you hire a few data scientists. They come in, they're doing, they're spending the time on housekeeping data rather than actually doing data science, >>Data engineering, not just wrangling, it's a lot of engineering going on. >>Absolutely. Okay. >>Absolutely. So that's a well known problem. Uh, but as you said before that it's not really a technology problem. I think it's an organizational issue and part of the problem. And I wonder if you're seeing this within your customer base, is this idea that we're gonna try to put everything into some kind of central repository. Yeah. And then we're gonna create a hyper specialized team. That is the goal between the data that you need <laugh> and the insights, right? Yeah. To get the insights. And we're seeing this dispersion of the expertise, which put, putting more responsibility into the line of business, a new data architecture, new organizational thinking. Are you seeing that? Are there particular industries where that's happening more, more quickly where the context which LA is lacking in the centralized team is actually going out to the lines of business where the data quality will be inherently improved. >>Yeah. I think it's like implementing ERP systems. I mean, people who try to create massive data lakes, I don't think it's going to work. Right. Because it's like, nobody has the time to wait for three years until you have structured data in a particular way. The other thing is some of the data companies were take people like that who came in are no more because things are changing at a rapid pace. So anything if you're doing, that's taking too long to get your act together, the market has moved on. You may not be even in that business. So what people are doing Dave is sort of microservices, they're cutting it into pieces and saying, let me get the best, vast, quick, and make it work. And then creating the fly wheel of changing other things that are priority for their. >>So they're getting tactical with their absolutely >>Getting >>Quick wins. Absolutely >>Inviting >>Off smaller. >>Well that's the data. The data thing is, is a cyber problem too. Cuz data is helping cyber, but machine learning feeds off data. Yes. So if you have gaps or blind spots, machine learning isn't as good. So machine learning is only as good in the eye is only as good as the data. Yeah. It can see. Yeah. >>Yeah. >>So that's means it's gotta be fast available, not siloed. So, but you, so this is a balance. What do I silo and protect for compliance. Yeah. And what can I address quickly? Low latency. >>Yeah. If I may add John, the other thing is because there's so many passwords used in the industry. Right. Um, and AIML is one of those, right? So everybody then businesses pick up an area for AI and ML. They do a little pilot, they do a POC and it works well and they're extremely happy <laugh> and then they try to scale it across the whole enterprise. Yeah. And it's a complete failure because most of the time it doesn't work. Right. >>But your data lake comment actually translates over your point there because you can spend, I had a quote on the last event I went to, the quote was we spend all of our time trying to figure out what the latest open source machine learning is. That's a full-time job. So the data lake is heavy lift. Just understand what's going on there. Tracking machine learning yeah. Is a full time job even and changes. >>Absolutely. So >>The change, what does that mean to the customer? That managed services are gonna be part of it? How do the customers tame that moving train that's happening around these really important areas? >>Yeah. So, um, I think, um, customers do need help. So I think they need to be open to ideas of, okay, what is the expertise we need for where we want to get to? And some may be available inside some, they need to go for help outside. I mean, that's a reality, right? So you need to open your eyes and say, I've got, let me put my best people, maybe on transformation. Let me take the people with some expertise, knowledge on different things, right. Mm-hmm <affirmative> and shortsighted companies. What they do is John, they just automate what's their current. And that's not a transformation in the end, you look back and say, >>That's incremental. >>You didn't achieve anything. Right. Because you haven't transformed your processes. You haven't chained the theme, you just automated what the garbage and garbage out. It's the, the same crap that comes out. So >>How much of the work that point next does is, um, I'll, I'll say, you know, consultative in terms of be being that change agent. Right? Cause again, we back think about data. Yeah. A lot of it is, is thinking about the organization. Yeah. Decentralizing, you know, making that decision, uh, thinking in different terms, around data products, um, having the lines of business, maybe take more responsibility for, and, and those are internal decisions. Yeah. And they have customers have, certainly have a lot of expertise around, but they sometimes need a change agent. Do you play that role? Is that a, a GSI that plays that role? >>Yeah. So, uh, it's a mixed bag. Uh, we play the role in some places and then, uh, some SIS would also play, play that role. Okay. Um, more of the point next is if, if you take a customer engagement advisory, professional services, then actually maintaining their landscape and then manage services, which again, sort of you monitor, but you also provide some info on how to manage it. Right. In those three pieces, Dave, the top piece and the bottom piece are the big pieces. Customers want expertise on the middle piece is getting automated because systems are getting smarter. They are self-healing. And in the middle piece, what people want is knowledge. So say for example, you have an enterprise it's not working well. They want it knowledge up front, tell me where it's broken or what do we need to do? And that's it. Right. Um, and they want to fix it themselves. It's just like consumer. Right. So, um, that's the way it's working. >>So the reason I ask that is we we're having a data discussion here. Yeah. And, and I think that a big role that you can play in the data transformation is to provide self-service infrastructure. Yes. Uh, right where the, the technical pieces or an operational detail. Absolutely. Okay. And then the, the second is that you just touched on it is, is, is automated, automated governance and security. So that when I share data, I know that it's going to the right place. That individual has the proper access to it. So those are two sort of white spaces I think. And a lot of organizations where they need help big >>Wide spaces >>Actually. Absolutely. Absolutely. Yeah. And that, that middle please is a complete cloud experience. Mm-hmm <affirmative> right. Everything is going to be digitalized. Everything's going to be automated. And um, so you know, people can use it any way they want, >>Do you see hybrid as a steady state? I mean, know, we gotta wrap up. We don't a lot of time left. Yeah. The real quick hybrid we've been saying here in the cube, it's it's gonna be a steady state for a long, long >>Time. Absolutely. Absolutely. And it would be, you know, OnPrem off Preem multi-cloud but it's going to be hybrid world >><laugh> all right. Hybrid world. >>Thank you so much. Hybrid >>Cube cube hybrid cube >>Was great to have you on you're so articulate and, and it's just wonderful to see you. Thanks. Thanks. >>Thank you. Thanks Dave. >>Thank you, John. And thank you for watching John furry, Dave Valante, we'll be back with the cubes coverage of HPE. Discover 2022 in Las Vegas. Right after this short break we're live.