>>The Cube presents UI Path Forward five. Brought to you by UI Path. >>Hi everybody. We're winding down. Day two, a forward five UI Path customer conference. This is the fourth time the Cube has been at a forward. Dave Nicholson, Dave Ante. Maureen Fleming is here. This is a program Vice President idc. She's got the data fresh survey data. We'd love to have the analyst on. And Kevin CRO is back on the cube. He's a partner for intelligent automation and digital. Upscaling is the operative word. Kevin, good to see you again, pwc. Good to see you. Thanks for coming on you guys. Yep. All right. We, we love idc. We love the data. You guys are all about it. So you've just completed a recent study. Tell us all about it. Who'd you survey? What was the objective? What'd you learn? >>Yeah, what we wanted to do was try to learn more about people who are adopting robotic process automation. So mainly large, you know, larger to midsize, enter midsize, large enterprises. And we wanted to figure out how many of them had a citizen developer program. And then we wanted to compare the difference between people who do not have that program and people who do, and what the difference is in terms of how, what kind of reach they have inside the enterprise, and also the different ways that, that they valued it. So the difference, so we asked the same questions of the, of these people without them knowing that we were actually looking for a citizen developer. And then we compared the results of that to see is it more valuable to have citizen developer and enterprise, or is it more valuable to have enterprise only? So what was the impact >>Global survey? >>It was North America. >>North America. Was it, was it we any kind of slice and dice in terms of industry or targets or you, >>We, we kept it across industry, cross industry. We're finding that RPA is adopting cross >>Industry way. Was it, was it UI path specific or more Any tech, Any automation, >>Any rpa. >>Okay. And top two or three findings. >>So one thing was, first off, the rapid growth rate in citizen, citizen developer programs grew 47% over a two year period. And so now for people who've adopted rpa, it's the majority there. They're, you know, it's a pervasive trend to >>See you're taking over, >>You know, right now the conclusion from that, and some other studies that I did that have similar conclusions is that we have to start learning to live with this idea that business users can learn how to develop. They are developing their driving value. And so now we just need to figure out how to build these sorts of programs accurately. And the other, the really key finding of it was that, that there was much more significant reach for people that were doing citizen developer plus enterprise automation, more reach, more processes touched, more employees impacted by it. And then on top of it, the, they rated the value, the people who had the combination rated the programs at a higher value across different measures. So effectively the, the combination is working out better than standalone top down automation. >>So Kevin, from what, what's your takeaway here? What does this mean to you and your customers? >>So I guess a, a couple things and just anecdotally, you know, building on what Marine found in the, in the survey, the concept of citizen development is a real concept and it's something that organizations are applying and trying to figure out how to apply at scale. The reason why they're doing it is twofold. One, early automation efforts struggled to get scale and they struggled to deliver value from a scale perspective. There were two major problems. The ability to identify the right opportunities and the ability to tackle a wide range of, from the little to the very large, often teams focus on the very large, but don't focus on the little, the little is important. The second part is thinking about how you create a better culture of innovation and actually drive identifying opportunities for the, the more, I'll call it technology professionals to focus on. And so, you know, there's been, you know, based on that big drive to say, okay, not how do we replace automation professionals with business users, you know, the random accountant, the random operations analyst. It's more around how do you actually engage them in innovation. And that in, in that engagement may involve actual hands on building of bots and technologies like UiPath or it might just involve generating ideas to get further engaged. >>So 47% growth. What's the catalyst for that kind of growth? Where's that come from? >>I scarcity? So, well there are a couple things. One is, you know, we all know about developer scarcity and it's strive to automate. You know, if you have an automation strategy in place, you wanna do this quickly and aggressively. But if you've got a shortage of, of people, you know, developers don't have enough, they're turning over. Then you go to, you go and figure out, well this is low code. And so why can't we train our business users who are the subject matter experts to do automation for themselves or their teams? So sort of think about this as the long tail, the things that that top down like enterprise, I think UiPath is calling it enterprise automation versus people automation. So, you know, so there's just different things that they work on as well. And there's also, you know, fearlessness on the part of a lot of people on the business side, they're not afraid of technology, they're not afraid of getting trained. >>And the other piece to me that made, like, I've covered this topic for a long time, and what I found originally when people started talking about citizen developers is that they, they were calling me and having inquiry about why these programs were failing. And when we would decompose the failure was because the ma their managers didn't give them any, they didn't put 'em in trading but wouldn't get, give 'em time to develop. And so they just could not, you know, they just were running into problems. And so with things that, things like PWC and what they're doing, they're sort of saying, here's the, here are the features of a program that matter, including being given time to develop and do that as part of your job. So >>Maureen, is there a minimum level size of organization that you find taking advantage of this? I mean, you know, where's the sweet spot for the value delivered from this kind of automation? >>Do you have an idea? Right. So we, we tended in some of the surveys, we tended to do like thousand employees up. So we were screening for that. But I also met with the, our, our analysts who covered smb, small midsize. She said that they've had that for a long time because they don't have these clear distinctions between IT and business. So then the question is, who are adopters of rpa, for example? And you know that that's still a little bit at, at, you know, the enterprise level, but, but citizen developer at it, it, it is SB is just a given concept. So, >>But is it, is there, is there an economy of scale that kicks in at a certain point? Have we been able to figure that out? I'm thinking of, I'm thinking of business process automation being such a competitive advantage that there becomes almost a divide because of smaller organization. Yes, they could go out and they can buy, they have access to the same software packages, but you have to build all of those processes. Yes. You have to develop those processes over time. So is there any sense for a divide possibly happening or what the, >>It's a really good question because they, you know, in a way people have to understand what a business process is, you know, and they need to understand what the technology can do. And so from that perspective, people who have thought leaders inside their organization and maybe have a chance to get out and look at broader topics might be more inclined to try this out and also identify directly as a problem. SMB also tends to try to buy package solutions. And you see larger enterprises say, well, you know, what we do is unique and so we should just sort of use horizontal technology and apply it at will where it's needed. And so for me that's kind of why we organize toward higher, you know, higher si, larger sizes. As it gets simplified, it's gonna go down into the SMB market though. >>So Kevin, when it comes to you guys, your client engagements, upscaling keeps, keep coming back to that word low code. Is it fundamental component of upscaling? Is it, is it, I don't say synonymous, but is it a prerequisite to have low code capabilities to scale? >>You know, from our perspective, I think the two biggest challenges with making this work, one is learning and development. How do you actually teach the skills in a way that allows people to apply them very quickly and give them the time to actually function right to the finding about managers not necessarily being supportive. And so you have to figure out, you know, what, you know, how do you actually create that right environment and give people the right tools? It's an area that we invested really heavily in from the PWC side with the, with the launch of our pro edge platform and really thinking about how to solve that. But then the problem that you're ultimately getting at once you solve the people equation is how do you get scale and how do you move quicker? And so the, you know, the, the, the, the biggest challenge is not should you let a, a business user build a bot. It's, you know, how do we actually build many bots, generate many ideas for the professional developers and actually create an ecosystem to move faster. Every client that we work with, it's all about, you know, how we're not moving fast enough. A COE cannot, you know, by itself automate an entire organization. And so, you know, the, you know, the, the this theme of scale really becomes, you know, the critical aspect of this >>Is the former other words, the the teaching and individual how to build a bot. Is that trivial or, or is that really not the big gate is what you're saying? It's, >>We don't think it's a big gate. I think the, you know, to the original question, I think the, the, the low code space is a ripe spot for this, you know, upskilling construct because you're not, you're not, you're, you're gauging with employees who don't have an undergraduate degree in computer science who are not IT professionals. And so giving someone, you know, a book on job and saying, go build an application's, probably not gonna be very productive. But with, with tools in the, in the low code space, be it RPA or be it other forms of lower code technology, you get people opportunity where they need to learn some technical concepts. You need to understand how the technology works and how basic programming techniques work, but you don't need to understand everything. And again, going back to the, the simple versus the complex, the goal here is not to turn people into professional developers. The goal is to get them engaged and, and create, you know, make them part of that company's digital transformation. >>But from what you just described, that's, to me it's basic logic skills. I mean you don't have to be, like I say, a assembly language programmer. Yeah. But you gotta understand and you gotta know the business process, right? I mean you have to be a domain expert. Yeah. >>But that, but that's the, that's the biggest advantage of this. You're engaging the people closest to the business process, right? You look at how most big IT projects failed was the same reason a lot of early automation efforts failed. You're creating, you know, a function that essentially lives in an ivory tower that's focused on, you know, where can I go out and find opportunities and automate. But you're not, those aren't the people that run the process day to day. Yeah, okay. You, you put it, you make those people that run the process day to day accountable, you're gonna get a different outcome >>And they'll lean in and get excited. Exactly. >>So where, where, where is that transition? I know it's easy to say, oh, you know, it's logic and people can do it, but what about having a bot whisperer in your, in your organization who's who, who literally says, you know, Maureen, I'm gonna come and sit with you on Friday and you're going to explain your frustrations to me and I'm gonna sit right next to you and I'm gonna code this bot for you and we're gonna test it and you're gonna tell me if it does what you want it to do. And Maureen doesn't need to understand how to move the widgets around and do anything. >>It's, you know, it's a great question cuz I think it's changing the nature of how you accelerate these efforts, right? I think you know, the, and if I go into early RPA days, the initial kind of thought process was let's just get a factory in here and build as many bots as possible. A lot of our client engagement today isn't always around our bot development services. It's around can you bring in coaches? Can you hold office hours? Exactly. We have an office hour construct, which I've never really had in my consulting career where we put, you know, I mean this obviously post covid when when people are in their offices, we put someone in a room and people can come by and get help. And I think having that, that coaching and mentoring construct is very helpful. What we've also seen, and I think it's a really critical success factor for clients to make this work, is thinking about how they pick a subset of their population and making them, you know, digital accelerators, digital champions, pick your word, not it professionals, peers who will actually get realtime dedicated. Right. And maybe a full time or a halftime job where that's exactly what they do. >>Maureen, we're out of time, but my last question for you is, when you do a survey like this, you know you have open ended sometimes and you analyze a survey, you take a bath in the data, write it up. There's always something that you wish you'd asked, which is great cuz then you could do it on the next one. What, was there anything in there that you wish you'd asked that you're gonna ask in the next one? Are you gonna explore in the next survey? >>Yeah. One of the things that I asked, one thing that I was glad I asked was, I, I, we, we spent time finding what were considered business side product champions or RPA champions and then we ask 'em what they did, how often they did, how much time they spent. But what I want, what I really, really wanna ask of my next survey, and I will, I've got a planned, is to find out how, how what percentage of population is involved with, with big a citizen developer and what activities are common and what are less common and you know, what their challenges are. So we'll be looking at a different kind of audience with this next >>Survey. Well, we'd love to have you back to talk about that. Just invite, Thank you very much. Come queue. Really appreciate it Kevin. Good to see you again. >>Good to see you. >>All right. And thank you for watching. Keep it right there. Dave Nicholson and Dave Ante. We're here wrapping up day two of UI path forward. Five live from the Venetian, all Las Vegas. Super right back.

(upbeat music) >> From the Bellagio Hotel in Las Vegas, It's theCUBE. Covering UiPath FORWARD IV. Brought to you by UiPath. >> Welcome back to theCUBE's coverage of UiPath FORWARD IV. Live from the Bellagio, in Las Vegas. I'm Lisa Martin with Dave Vellante. We're here all day today and tomorrow. We're going to talk about process mining next. We've got two guests here. Mike Engel is here, intelligent automation and process intelligence leader at PWC. And Ryan McMahon, the SVP of growth at UiPath. Gentlemen, welcome to the program. >> Thank you, Lisa. >> Thank you. >> So Ryan, I'm going to start with you. Talk to us about process mining. How does UiPath do it differently and what are some of the things being unveiled at this event? >> So look, I would tell you it's actually more than process mining and hopefully, not only you but others saw this this morning with Param. It's really about the full capabilities of that discovery suite. In which, obviously, process mining is part of. But it starts with task capture. So, going out and actually working with subject matter experts on a process. Accounts payable, accounts receivable, order to cash, digitally capturing that process or how they believe it should work or execute across one's environment. Right Mike? And then from there, actually validating or verifying with things or capabilities like process mining. Giving you a full digital x-ray of actually how that process is being executed in the enterprise. Showing you process bottlenecks. For things like accounts payable, showing you days outstanding, maverick buying, so you can actually pin point and do a few things. Fix your process, right? Where process should be fixed. Fix your application because it's probably not doing what you think it is, and then third, and where the value comes, is in our platform of which process mining is a capability, our PA platform. Really moving directly to automations, right? And then, having the ability with even task mining to drill into a specific bottleneck. Capturing keystrokes, clicks, and then moving to, with both of those, process mining and task mining, into Automation Hub, as part of our discovery platform as well. Being able to crowdsource, prioritize, all of those potential, if you will, just capabilities of automations, and saying, "Okay, let's go and prioritize these. These deliver to the greatest value," and executing across them. So, as much as it is about process mining, it's actually the whole entire discovery suite of capabilities that differentiates UiPath from other RPA vendors, as the only RPA vendor that delivers process mining, task mining and this discovery suite as part of our enterprise automation platform. >> Such a critical point, Ryan. I mean, it's multi-dimensional. It's not just one component. It's not just process mining or task mining, it's the combination that's really impactful. Agree with you a hundred percent. >> So, one of the things that people who watch our shows know, I'm like a broken record on this, the early days of RPA, I called it paving the cow path. And that was good because somebody knew the process, they just repeat it. But the problem was, the process wasn't necessarily the best process. As you just described. So, when you guys made the acquisition of ProcessGold, I said, "Okay, now I'm starting to connect the dots," and now a couple years on, we're starting to see that come together. This is what I think is most misunderstood about UiPath, and I wonder, from a practitioner's perspective, if you can sort of fill in some of those gaps. It's that, it's different from a point tool, it's different from a productivity tool. Like Power Automate, I'll just say it, that's running in Azure Cloud, that's cool or a vertically integrated part of some ERP Stack. This is a horizontal play that is end to end. Which is a bigger automation agenda, it's bold but it's potentially huge. $60 billion dollar TAM, I think that's understated. Maybe you could, from a practitioner's perspective, share with us the old way, >> Yeah. >> And kind of, the new way. >> Well obviously, we all made a lot of investments in this space, early on, to determine what should we be automating in the first place? We even went so far as, we have platforms that will transcribe these kind of surveys and discussions that we're having with our clients, right. But at the end of the day all we're learning is what they know about the process. What they as individuals know about the process. And that's problematic. Once we get into the next phase of actually developing something, we miss something, right? Because we're trying to do this rapidly. So, I think what we have now is really this opportunity to have data driven insights and our clients are really grabbing onto that idea, that it's good to have a sense of what they think they do but it's more important to have a sense of what they actually do. >> Are you seeing, in the last year in a half we've seen the acceleration of a lot of things, there's some silver linings but we've also seen the acceleration in automation as a mandate. Where is it? In terms of a priority, that you're seeing with customers, and are there any industries that you're seeing that are really leading the edge here? >> Well I do see it as a priority and of course, in the role that I have, obviously everybody I talk to, it's a priority for them. But I think it's kind of changing. People are understanding that it's not just a sense of, as Ryan was pointing out, it's not just a sense of getting an understanding of what we do today, it's really driving it to that next step of actually getting something impactful out the other end. Clients are starting to understand that. I like to categorize them, there's three types of clients, there's starters, there's stall-ers and those that want to scale. >> Right? So we're seeing a lot more on the other ends of this now, where clients are really getting started and they're getting a good sense that this is important for them because they know that identifying the opportunities in the first place is the most difficult part of automation. That's what's stalling the programs. Then on the other end of the spectrum, we've got these clients that are saying, "Hey, I want to do this really at scale, can you help us do that?" >> (Ryan) Right. >> And it's quite a challenge. >> How do I build a pipeline of automations? So I've had success in finance and accounting, fantastic. How do I take this to operations? How do I take this this to supply chain? How do I take this to HR? And when I do that, it all starts with, as Wendy Batchelder, Chief Data Officer at VMware, would say and as a customer, "It starts with data but more importantly, process." So focusing on process and where we can actually deliver automation. So it's not just about those insights, it's about moving from insights to actionable next steps. >> Right. >> And that is where we're seeing this convergence, if you will, take place. As we've seen it many times before. I mentioned I worked at Cisco in the past, we saw this with Voice Over IP converging on the network. We saw this at VMware, who I know you guys have spoken to multiple times. When a move from a hypervisor to including NSX with the network, to including cloud management and also VSAN for storage, and converging in software. We're seeing it too with process, really. Instead of kids and clipboards, as they used to call it, and many Six Sigma and Lean workshops, with whiteboards and sticky papers, to actually showing people within, really, days how a process is being executed within their organization. And then, suggesting here's where there's automation capabilities, go execute against them. >> So Ryan, this is why sometimes I scoff at the TAM analysis. I get you've got to do the TAM analysis, you've got to communicate to Wall Street. But basically what you do is you pull out IDC or Gartner data, which is very stovepipe, and you kind of say, "Okay we're in this market." It's the convergence of these markets. It's cloud, it's containers, it's IS, it's PaaS, it's Saas, it's blockchain, it's automation. They're all coming together to form this, it sound like a buzzword but this digital matrix, if you will. And it's how well you leverage that digital matrix, which defines your digital business. So, talk about the role that automation, generally, RPA specifically, process mining specifically, play in a digital business. >> Do you want to take that Mike or do you want me to take it? >> We can both do it? How about that? >> Yeah, perfect. >> So I'll start with it. I mean all this is about convergence at this point, right? There are a number of platform providers out there, including UiPath, that are kind of teaching us that. Often times led by the software vendors in terms of how we think of it but what we know is that there's no one solution. We went down the RPA path, lots of clients and got a lot of excitement and a lot of impact but if you really want to drive it broader, what clients are looking at now, is what is the ecosystem of tools that we need to have in place to make that happen? And from our perspective, it's got to start with really, process intelligence. >> What I would say too, if you look at digital transformation, it was usually driven from an application. Right? Really. And what I think customers found was that, "Hey," I'm going to name some folks here, "Put everything in SAP and we'll solve all your problems." Larry Ellison will tell you, "Put everything into Oracle and we'll solve all your problems." Salesforce, now, I'm a salesperson, I've never used an out of the box Salesforce dashboard in my life, to run my business because I want to run it the way I want to run it. Having said that though, they would say the same thing, "Put everything into our platform and we'll make sure that we can access it and you can use it everywhere and we'll solve all of your problems." I think what customers found is that that's not the case. So they said, "Okay, where are there other ways. Yes, I've got my application doing what it's doing, I've improved my process but hang on. There's things that are repeatable here that I can remove to actually focus on higher level orders." And that's where UiPath comes in. We've kind of had a bottom up swell but I would tell you that as we deliver ROI within days or weeks, versus potentially years and with a heavy, heavy investment up front. We're able to do it. We're able to then work with our partners like PWC, to then demonstrate with business process modeling, the ability to do it across all those, as I call, Silo's of excellence in an organization, to deliver true value, in a timeline, with integrated services from our partner, to execute and deliver on ROI. >> You mentioned some of the great software companies that have been created over the years. One you didn't mention but I want you to comment on it is Service Now. Because essentially McDermott's trying to create the platform of platforms. All about workflow and service management. They bought an RPA company, "Hey we got this too." But it's still a walled garden. It's still the same concept is put everything in here. My question is, how are you different? Yeah look, we're going to integrate with customers who want to integrate because we're an open platform and that's the right approach. We believe there will be some overlap and there'll be some choices to be made. Instead of that top down different approach, which may be a little bit heavy and a large investment up front, with varied results, as far as what that looks like, ours is really a bottoms up. I would tell you too, if you look at our community, which is a million and a half, I believe, strong now and growing, it's really about that practitioner and those people that have embraced it from the bottom up that really change how it gets implemented. And you don't have what I used to call the white blood cells, pushing back when you're trying to say, "Hey, let's take it from this finance and accounting to HR, to the supply chain, to the other sides of the organization," saying, "Hey look, be part of this," instead of, "No, you will do." >> Yeah, there's no, at least that I know of, there's no SAP or Salesforce freemium. You can't try it before you buy. And the entry price is way higher. I mean generally. I guess Salesforce not necessarily but I could taste automation for well under $100,000. I could get in for, I bet you most of your customers started at 25 of $50,000 departmental deployments. >> It's a bottoms up ground swell, that's exactly right. And it's really that approach. Which is much more like an Atlassian, I will tell you and it's really getting to the point where we obviously, and I'm saying this, I work at UiPath, we make really good software. And so, out of the box, it's getting easier and easier to use. It all integrates. Which makes it seamless. The reason people move to RPA first was because they got tired of bouncing between applications to do a task. Now we deliver this enterprise automation platform where you can go from process discovery to crowd sourcing and prioritizing your automations with your pipeline of automations, into Studio, into creating those automations, into testing them and back again, right? We give you the opportunity not to leave the platform and extract the most value out of our, what we call enterprise automation platform. Inclusive of process mining. Inclusive of testing and all those capabilities, document understanding, which is also mine, and it's fantastic. It's very differentiated from others that are out there. >> Well it's about having the right framework in place. >> That's it. From an automation perspective. I think that's a little bit different from what you would expect from the SAP's of the world. Mike, where are you seeing, in the large organizations that you work with, we think of what you describe as the automation pipeline, where are some of the key priorities that you're finding in large organizations? What's in that pipeline and in what order? >> It's interesting because every time we have a conversation whether it's internal or with our clients, we come up with another use case for this type of technology. Obviously, when we're having the initial conversations, what we're talking about is really automation. How do we stuff that pipe with automation. But you know, we have clients that are saying, "Hey listen, I'm trying to carve out of a parent company and what I need to do is document all of my processes in a meaningful way, that I can, at some point, take action on, so there's meaningful outcomes." Whether it be a shared services organization that's looking to outsource, all different types of use cases. So, prioritizing is, I think, it's about impact and the quickest way to impact seems to be automation. >> Is it fair to say, can I look at you UiPath as automation infrastructure? Is that okay or do you guys want to say, "Oh, we're an application." The reason I ask, so then you can answer, is if you look at the great infrastructure plays, they all had a role. The DBA, the CCIE from Cisco, the Cloud Architect, the VMware admin, you've been at all of them, Ryan. So, is there a role emerging here and if it's not plumbing or infrastructure, I know, okay that's cool but course correct me on the infrastructure comment and then, is there a role emerging? >> You know, I think the difference between UiPath and some of the infrastructure companies is, it used to take, Dave, years to give an ROI, really. You'd invest in infrastructure and it's like, if we build it they will come. In fact, we've seen this with Cloud, where we kind of started doing some of that on prem, right? We can do this but then you had Amazon, Azure and others kind of take it and say, "Look, we can do it better, faster and cheaper." It's that simple. So, I would say that we are an application and that we reference it as an enterprise automation platform. It's more than infrastructure. Now, are we going to, as I mentioned, integrate to an open platform, to other capabilities? Absolutely. I think, as you see with our investments and as we continue to build this out, starting in core RPA, buying ProcessGold and getting into our discovery suite of capabilities I covered, getting into, what I see next is, as you start launching many bots into your organization, you're touching multiple applications, so you got to test it. Any time you would launch an application you're going to test it before you go live, right? We see another convergence with testing and I know you had Garrett on and Matt, earlier, with testing, application testing, which has been a legacy, kind of dinosaur market, converging with RPA, where you can deliver automations to do it better, faster and cheaper. >> Thank you for that clarification but now Mike, is that role, I know roles are emerging in RPA and automation but is there, I mean, we're seeing centers of excellence pop up, is there an analogy there or sort of a similar- >> Yeah, I think the new role, if you will, it's not super new but it's really that sense of an automation solution architect. It's a whole different thing. We're talking about now more about recombinant innovation. >> Mike: Yeah. >> Than we are about build it from scratch. Because of the convergence of these low-code, no-code types of solutions. It's a different skill set. >> And we see it at PWC. You have somebody who is potentially a process expert but then also somebody who understands automations. It's the convergences of those two, as well, that's a different skill set. It really is. And it's actually bringing those together to get the most value. And we see this across multiple organizations. It starts with a COE. We've done great with our community, so we have that upswell going and then people are saying, "Hang on, I understand process but I also understand automations. let me put the two together," and that's where we get our true value. >> Bringing in the education and training. >> No question. >> That's a huge thing. >> The traditional components of it still need to exist but I think there are new roles that are emerging, for sure. >> It's a big cultural shift. >> Oh absolutely, yeah. >> How do you guys, how does PWC and UiPath, and maybe you each can answer this in the last minute or so, how do you help facilitate that cultural shift in a business that's growing at warp speed, in a market that is very tumultuous? How do you do that? >> Want to go first or I can go? >> I'll go ahead and go first. It's working with great partners like Mike because they see it and they're converging two different practices within their organization to actually bring this value to customers and also that executive relevance. But even on our side, when we're meeting with customers, just in general, we're actually talking about, how do we deal with, there's what? 13 and a half million job openings, I guess, right now and there's 8500 people that are unemployed, is the last number that I heard. We couldn't even fill all of those jobs if we wanted to. So it's like, okay, what is it that we could potentially automate so maybe we don't need all those jobs. And that's not a negative, it's just saying, we couldn't fill them anyway. So let's focus on where we can and where, there again, can extract the most value in working with our partners but create this new domain that's not networking or virtualization but it's actually, potentially, process and automation. It's testing and automation. It might even be security and automation. Which, I will tell you, is probably coming next, having come out of the security space. You know, I sit there and listen to all these threats and I see these people chasing, really, automated threats. It's like, guys a threat hunter that's really good goes through the same 15 steps that they would when they're chasing a false positive, as if a bot would do that for them. >> I mean, I've written about the productivity declines over the past several decades in western countries, it's not universal around the world and maybe we have a productivity boost because of Covid but it's like this perpetual workday now. That's not sustainable. So we're not going to be able to solve the worlds great problems. Whether it's climate change, diversity, massive deaths, on and on and on, unless we deal with that labor gap. >> That's right. >> And the only way to do that is automation. It's so clear to me that that's the answer. Part of the answer. >> It is part of the answer and I think, to your point Lisa, it's a cultural shift that's going to happen whether we want it to or not. When you think about people that are coming into the work force, it's an expectation now. So if you want to retain or you know, attract and retain the right people, you'd better be prepared for it as an organization. >> Yeah, remember the old, proficient in Word and Excel. Makes it almost trivial. It's trivial compared to that. I think if you don't have automation chops, going forward, it's going to be an issue. Hey, we have whatever, 5000 bots running at our company, how could you help? Huh? What's a bot? >> That's right. You're right. We see this too. I'll give you an example at Cisco. One of their financial analysts, junior starter, he says, "Part of our training program, is creating automations. Why? Because it's not just about finance anymore. It's about what can I automate in my role to actually focus on higher level orders and this for me, is just amazing." And you know, it's Rajiv Ramaswamy's son who's over there at Cisco now as a financial analyst. I was sitting on my couch on a Saturday, no kidding, right Dave? And I get a text from Rajiv, who's now CEO at Nutanix, and he says, "I can't believe I just created a bot." And I said, "I'm at the right place." Really. >> That's cool, I mean hey, you're right too. You want to work for Amazon, you got to know how to provision a EC2 instance or you don't get the job. >> Yeah. >> You got to train for that. And these are the types of skills that are expected- >> That's right. >> For the future. >> Awesome. Guys- >> I'm glad I'm older. >> Are you no longer proficient in Word is the question. >> Guys, thanks for joining us, talking about what you guys are doing together, how you're really facilitating this massive growth trajectory. It's great to be back in person and we look forward to hearing from some of your customers later today. >> Terrific. >> Great. >> Thank you for the opportunity. >> Thank you for having us. >> Thank you guys. >> Our pleasure. For Dave Vellante, I'm Lisa Martin, you're watching theCUBE live from the Bellagio in Las Vegas, at UiPath FORWARD IV. Stick around. We'll be back after a short break. (upbeat music)

>>From the Bellagio hotel in Las Vegas, it's the cube covering UI path forward for brought to you by UI path. >>Welcome back to the queue. We are live at the Bellagio in Las Vegas, Lisa Martin, with Dave Volante UI path forward for it is so great to be sitting in an anchor desk next to Dave and with guests in person, we're going to be talking about automation workforce of the future. I've got two guests here with Dave and me. Kevin crone is here intelligent automation and digital upskilling leader from PWC. Kevin. Welcome. Thank you. Can't wait to talk about upskilling and Bettina Koblick is here the chief people officer at UiPath. Welcome to the program. Thanks for having me. So, as I understand that PWC has embedded UI path into a couple of product offerings. One of them we're going to talk about today, Kevin that's pro pro edge. Talk to me about that. What is that? >>So, um, as we look at, uh, challenges that C-suite leaders are facing, I think one of the biggest emerging challenges right now is around the topic of upscaling. There's the number of jobs that are being displaced, um, is growing by automation. But on the flip side, the number of jobs that are emerging is actually greater and there is a consistent challenge that gets cited there. All of our research through our CEO survey, their work we've done with the world economic forum and other sources around the need to fill that gap. And most leaders feel like they're not doing a good job to, to fill that. So, um, we at PWC have invested in developing a, a new software product called pro edge, which is really focused on, um, identifying the skills needed for the future, teaching those skills and helping to scale the usage of the skills and the organization. And one of the key skills as we look at the digital space is UI path. And we really think that, you know, teaching non technologists around the use of tools like robotic process automation is going to be one of those critical kind of must have skills in the future. >>And patina, you guys are using pro edge. Why, why, why? I mean, you're like the automation pros, what do you need? >>We need it because we have the same, um, challenges that every other company has that introduced us automation, right? People, um, people's time, their tasks that they have been doing are basically displaced. Um, and we're trying to figure out how do we up-skill re-skill how do we position people who now no longer are work working on maybe 50% of what they've done in the past for their next role? Um, so it's incredibly important for us, >>You know, you know this well, Tina and Kevin, you as well, when, when the automation trend RPA first hit, it was like, oh yeah, the trade press, come on. It's going to take away jobs, blah, blah, blah. Now we're working perpetual workdays, right? We all weekend all night, you never stopped working. You're always on. So I think people will brace automation, but as the chief people officer, first of all, how, how was it getting through the pandemic? And have you seen, I presume that UI path folks embrace automation, of course it's in your DNA, but have you seen others sort of, is that narrative done in, is COVID effected that >>I think COVID has affected it, um, for a number of reasons, because so many things shifted in how we do work. Number one, and I can talk about that a little more, but I yesterday I was in a customer advisory board meeting actually with Kevin. And the biggest conversation was not about the technology. It was around what happens when automation is introduced to a company and what happens with people, um, as to whether they want, they're willing to adopt, embrace, have an automation mindset. So that conversation isn't done at all. And it's probably one of the biggest conversations after, you know, adopting the technology, trying to introduce it as how do you drive adoption. And a lot of that is people's people's ability to understand how it will make their life easier, but then not be afraid about what's next. Uh, so I think it's absolutely still a conversation. I don't know if you feel the same. Yeah, >>Yeah. It it's been interesting. I think during the pandemic cause peoples, you know, day to day work lives have gone up ended and he start to think about, um, you know, the, the mixture between what I'll call kind of transaction oriented type work versus analytical type work. And if it just, you know, historically everyone's always said we should do less transaction work and more analytic work. But I think the pandemic was almost like forced that conversation on steroids and people's lot. You I've had to figure out that, like, I don't want to do this type of work and I'm being, I have more demands on me and I'm being asked to do other things, how can I do this more effectively? And so part of this becomes learning these skills to automate the things in front of you right now, the part of this becomes, I need to be able to, to actually have that analytical skill set in the future. And I think that is almost a precursor for what we see happening. And that was, that was the fun part of the conversation yesterday is thinking about, okay, well, what is the, you know, what is the, uh, the accounting analyst role five years from now and what someone does today versus what someone does in five years and how do you actually plan for that, >>The patina, where in your organization, like who's using it and talk to me about the adoption and their willingness to embrace it. >>Yeah. So we are, we've introduced it to our finance organization. One of the reasons we did that is because our finance organization is also a big user of automation, right? So, um, what's been really interesting is that because the technology or because pro edge kind of takes biases out of mapping, what a person can do, um, what learning paths there are for them and what their job will look like in the future, in which job do they go to or could be a potential path. I think it actually motivates people much beyond having work shifting because of automation. Because in addition, you also get to see a path, right. And everywhere you turn, just want to know what's the possibility for the future. So, um, while I'd like to say it was genius for us to envision that it's, it's a pleasant surprise and something, we should talk about more, >>I'm sensing a journey. It's always the case where I know I call it the force March to digital. We were thrown into this. And so, so much was unknown. And I know our team, I mean our producers and it's death by a thousand paper cuts in any one individual thing is not that bad, but yeah, the Moffitt, it's just, that's what kills your work day, your work week and your mental health. And so maybe it's, that's kind of the starting point is, are pigs a band-aid for, for, for, for that fundamental, but then it's wow. I can see the light bulb goes off. I can see the potential, that's where the digital upskilling comes in. I mean, maybe that's oversimplifying it, but how do you see that journey? Yeah. >>Yeah. I think there's a couple of different pieces with this cause, you know, and it goes back to the divide between the things you need to do now. And how do you think about making your life easier, but then it really goes to what you need to do in the future. And that journey to actually get there is tough because it's not just a question of, Hey, I need to pick up a textbook or pick up an online training module. And I'm just going to become an expert. It's really thinking about what are the, what's the combination of different skills. I need to learn. Some of that's going to be hands on technical skills. It's going to be platforms like UI path. It may be other complimentary platforms in the analytics space and other things. Um, some of this may also be on the kind of softer side. >>How do I learn how to work in a more agile way and have a design thinking mindset, have a product mindset, but then it's really how's that going to change my role in the future. And how do I actually, for lack of a better word, start to embed these practices in my job in a way that I'm actually learning these skills and it will stick. And how do you actually manage that co culture change? Um, for lack of better word over time. That was probably the biggest thing I picked up from yesterday was just some of this talk around change management and culture, uh, which is, you know, we, we have a lot of, for lack of better word techie. Cause if this conference would like to think about all the cool stuff that technology doing, but the big lesson learned is really, you know, you actually have to make the stick inside an organization. >>And in the last year, Kevin, I'm curious about the adoption because you know, everything we've seen so much acceleration in the last year that digital acceleration, the acceleration in automation, we've also seen tremendous, uh, people and from a cultural perspective, I'd love to, for you to shed some light on what you've seen since you've rolled this product out, how is the pandemic, has it been an enabler of that change management and that cultural change, which historically is very hard to do. >>It's very hard. And I think this, if, if I want to CFO or COO two years ago and talked about the skills gap in what was happening, the organization, I would probably get someone that would be on and say, okay, yeah, that, that, that is happening. We need to think about this, but I got 50 other things I need to worry about. You know, I think over the past year a while, things like, you know, TA TA, well, time is a big, uh, luxury or having excess time is a big luxury that most people don't have. I think there's a recognition that, um, it's a challenging work environment right now. We're trying to get more done. People are not in person. Um, people have, you know, there's issues with, with mental health and other challenges and there's, uh, almost like a renewed focus on how do we make employees lives better and better can mean different things. >>But when I think about it, it's, it's giving people a hope that they have a future career path, that their job is not going to be eliminated, that they're developing the right skills and they're being given the capacity to actually do that now. And so a lot of the discussions have really been are around that fact. And I would say probably more so than the traditional just cost saving discussion than most automation, um, threads in with RPA begin with this really, you know, became, um, we need to do this and we need to, you know, send a message to our employees that we really care about you. And this is something that is really going to be us investing in you as a perk in the future. >>What's the role of the head of human capital management in the context of automation? Is she the champion? Is she the therapist? Is she the change agent? Well, how do you see that? >>Well, clearly he should have been talking to the head of people, um, two years ago. We even, because, uh, the way I think about it, and I think a lot of people in my role think about it is, you know, a CFO really looks after the financial health of the company. Um, the focus for us is looking after the people, health of the company, right? And so I think, um, in my career, what I've learned is that change is constant. We all know this and, um, change for people is difficult. So the way I think about introducing new technology, introducing automation, introducing anything that changes or being forced to change because of something like a pandemic, um, what I really ended up thinking a lot about is how does that impact people and how do we, how do we help them through it? Um, so that's my lens. And I think that's a chief people officer lens to all of this, but makes a perfect partnership with platforms that make this easy for us. Because if you can imagine, uh, a C-suite person comes to, uh, comes to an HR department and says, tell me what we should do here. How do we develop all our people? And it's, it's an overwhelming task. What pro edge does is just beautifully delivers this on a platter, um, in a way that we could never do manually. So it's >>Talk to me a little bit Bettina about the last year and a half. And obviously as being the chief people, officer, you came in, you said about five months ago, but obviously during a very, very challenging time, I always think that the employee experience is directly related to the customer experience. I see them as inextricably linked, how have you been able to foster a good employee experience in your time here in a very strange world so that the customer experience, I mean, you guys are a fast moving company, 8,000 plus customers. So that, that customer experience is a stellar as UI path has always had to be. >>Yeah, I think for us, it came down to just some simple things. Um, one is just being flexible. Uh, there was not a one size fits all. We had to recognize that we have to meet people in a place that works for them, everybody, uh, dealt with a different reality and the same for our customers. Um, and I agree with you. I think employees that feel enabled that feel safe, that feel they have a future, um, have a much different relationship with their customers, um, then employees that are worried about their safety and security and whatnot. So we really took an approach of flexibility, safety, um, meeting people where they are jumping in when there were big crises in India and whatnot to really, really take care of our people and help them understand that we're here for >>Big impact on mental health. Did you see that, um, there was an insert in the wall street journal. I think it was last week, uh, women at work. Um, and it was a stat in there. I don't know if you're a working mom, but it said that, uh, 30, it was Qualtrics was the source. 30% of working moms said their mental health had declined since the pandemic. Interestingly only 15. I said only 15% of working dads. Um, so that was sort of interesting, uh, and notable, uh, but you know, to your point, CFO, financial health of the company, the chief people officer, the, the human capital health. Yeah. >>Um, very much so. And by the way, I'm not surprised by that stat as a woman. >>I thought it was, I thought it was low. I was talking to my wife about it the other day. She's not a working mom, but she's like my mental health, even though I'm not a working mom, I have my mental health. I'm a working dad, but, but I got it easier than she does, but, but, and I'm not surprised at the disparity. I'm surprised that the only 30% and 50%, I think it's a lot higher than that. And people may be just like, I don't know if that's actually, maybe some people like working at home and that's, I could see that both sides of that equation. Yeah. >>There's also a stigma around mental health that we've, that's been addressed in. So even during the Olympic coverage this last summer, but having your team be really focused and enabled and knowing that they took to your point, Kevin, from an upscale perspective, that they have a path where they can go, they can increase their own value to the company. >>I completely agree. And I think, uh, other studies show that what people really want is a future at work. And, and this is what I think privilege dresses. Beautiful. >>Yeah. It's interesting. Right. Cause I think when you talk about some of the mental health challenges, I think it can get down very quickly to a cab just on this crazy schedule or I'm on zoom for 14 hours a day. And I, I don't have the time to breathe in my time commuting where I may have had time to decompress. It's just been replaced with more meetings. And I think that that may be the, like the surface issue, but I actually think if you go below the surface, not being in the office, not having some of the in-person networking, not having some of that creates anxiety about the future. And you're not really sure around, okay, what does my career path look like? I may not be getting the amount of career counseling that I used to get just by impromptu conversations or, you know, just by more traditional ways. Um, but I think the reality is when we look at the way most companies are thinking about their future work models. It's not going to go back to the way the world operated two years ago, it's, we're going to be in some sort of hybrid model. And so it really becomes more important to actually dig below where maybe some of the challenges were in the passengers, not surfaced. And I think upskilling and thinking about, um, kind of role skills and roles, it just becomes a much more important conversation. >>Absolutely. Last question, Bettina for you, we're almost out of time, but you started this in the, in financial, in the finance organization. What do you see over the next couple of years in terms of being very much UI path land and expand with your customers? Where do you see it rolling out across two iPads. >>We're already talking to our sales enablement group. Um, for a couple of reasons we want them to experience it. We want them to have also, we want them to have the conversations with our customers much like what we learned yesterday, right? It's a multi-dimensional conversation. It's not just a financial ROI, it's a people journey, change management. So we'll, we're taking it to our sales enablement group. We're absolutely gonna use it in HR, uh, obviously. Um, and I, I would just think we'll use it in two years. It'll be enterprise wide >>Different is pro edge in the marketplace. And just in, particularly in terms of its business impact. >>Yeah. I take a stab. So when we think about the challenge in a topic like digital upskilling, I think in traditional approaches to learning, it would be okay, we're going to enroll someone in a learning program. You know, you're going to go through, do certain amount of self study. Maybe there's a class, the some classroom based training. And that's it. I think for us, we saw two different challenges on both sides of that. One was trying to identify who needs to learn, what, and what part of the organization, why is that important? What an executive may need to learn is going to be different from what someone who does the transaction processing, uh, for their, their full-time job needs to learn and learning kind of from basic digital acumen through kind of hands-on skills. What are the different, um, pieces? I think probably the more interesting part is the back end of that. >>And thinking about, you know, how do you actually put these skills into practice and how do you put scale? One of the buzzwords that's thrown around at this conference a lot is the concept of citizen led automation as a topic. And really how, how do you have your, does this users building bots or creating data dashboards or doing other things that is, um, that's challenging. So as we design the product, what we really wanted to think about was that end to end journey from kind of the point of identifying skills through the point of scaling a citizen led effort. It's one of the things we're really excited to be working with UI path on is one of the core technologies that we, that we view in this ecosystem is really thinking about how do you make that happen? And if the outcome is not just people are new things, but the outcome are, people are actually creating solutions that are, that are having an impact on their job on a day to day basis. We think that's a really powerful concept. >>It's really important work, what you guys are doing. Thank you both for joining David me on the program today, talking about this very interesting symbiotic relationship partners, PWC UI path customers. Really interesting, great work that you're doing. Thanks for joining us. Thank you so much for having us for Dave Volante. I'm Lisa Martin. You're watching the cube live from Las Vegas at the Bellagio UI path forward for it. We'll be right back, stick around.

>>Live from Las Vegas. It's the cube covering UI path forward Americas 2019 brought to you by UI path. >>Welcome back to UI path forward three. This is UI pass. Third North American conference. We're here at the Bellagio hotel. You are watching the cube, the leader in live tech coverage. We go out to the events, we extract the signal from the noise, we pick the brains of experts. Kevin crone is here. He's a financial services intelligent automation leader at PWC. Kevin, thanks for coming on the cube Bexar Avenue. You're very welcome. So financial services has always been kind of a leading indicator of technology adoption. I presume that automation is, is no difference, but you know, you're in the New York area, you're belly to belly with the financial services companies, the big whales, what's going on in Fs these days? Sure. >>So as we look across the financial services industry, they were one of the leaders with automation more because the overarching business environment really forced them. As we looked at, um, the regulatory burden that a lot of our banking clients we're under over the past decade kind of post crash that really, um, has kind of forced two things. One, it's limited the amount of um, discretionary spend that they have to spend on really big technology transformation projects. It's also forced a lot of margin pressure and having to think about, uh, differently how they could run their business at a much lower and more effective price points. And so that's, um, driven automation to the top. And we've seen tools like U I path and kind of the broader RPA ecosystem becoming kind of, you know, the right technology at the right time of being able to, um, really kind of embrace that, that, that, that rightsizing agenda and financial services sector. >>Yeah. And furniture at the macro level, they're a little bit out of favor right now you've had this, what we thought was this rising interest rate environment and that's reversed. And so that's not necessarily good for them. So they got to look for other ways to sort of drive the bottom line. So maybe you could talk a little bit about, you know, gen generally where you're seeing automation, um, back office, front office. Think about the maturity curve. What are the leaders doing? What, >>what's the sort of best practice right now for intelligent automation RPA? Sure. So as we looked at intelligent automation right now, I think one of the interesting things, vital services was an early adopter. So a lot of, a lot of the big banks and asset managers and insurance companies really start investing in this, this class of technology four, five, six, seven years ago. And so we're actually seeing the, the early returns from, from those, which is informing how this, you know, this topic goes to other industries. But I think as we look at those returns, we see a couple of major challenges. Um, there's challenges with getting the scaling technology, there's challenges with, so that's interesting. Okay. So the, the ladder changing, the nature of work is, as you're saying, largely automating existing mundane processes, kind of paving the cow path as I sometimes say. >>However, if, if it's a, if it's not the most efficient processy to begin read process to begin with, they need to sort of re look at that and that may be falls into the, to the, to the former category of enterprise life. And so where people investing in boat or they are they just hitting the low hanging fruit where we're seeing an investment in both. And then PWC is used that a while fucks your mission program should have both channels and each channel should be informing the other. So if citizens are coming up with ideas of things that they can automate themselves, that's great, but those should also be contributed into the kind of broader ecosystem. And there may be, um, what's called grander ways to, to, to solve that problem, both from a technology perspective and from a process reengineering perspective. Is there a, is there an automation ex-officio is there a chief who's sort of looking at all this stuff or is it more organic? >>It's, you know, one of the, I think interesting things we've seen and learned from our clients over the past couple of years is the con, you know, we thought there'd be an emergence of a chief automation officer or something like that. But really the automation agenda's owned in so many different places within our clients. And it's not consistent client decline in some cases. It's really a CIO own topic. A lot of cases it's more of a chief operating officer, chief digital officer, chief transformation officer. We're also seeing a push at the chief HR officer level because this is really, you know, there's a, there's a big question straight in terms of thinking about kind of skills and how you equip your workforce with the right digital skills for the future, which is now putting HR at the table for this, which is the place where I think traditionally with big technology transformations, they've never really sat. >>So, in thinking about, um, ROI, you know, you've laid out this sort of bifurcated, you know, paths to vectors the hard sort of end-to-end problems and then the sort of low hanging fruit changing the way to work. I would presume the second one gives you the quick hit, you know, faster break even, but probably lower net present value. Um, and, and so maybe you could talk a little bit about the ROI equation and how people are looking at that. Yeah. It's interesting cause I think yeah, to your point, I think an enterprise led initiative, you're going to want to define a business case and say this is why we're doing it and what we're looking to achieve going down to SIS and let channel, that's a harder thing to do because you don't want to stifle innovation. The organization, one of our views is that the people that sit closest to the business process are the ones that should be coming up the right ideas, if they're given the right upscaling and the right tools at their disposal. >>Um, but you know, it's bottoms up exercise. And so again, going back to the concept of having a kind of an ecosystem with both an enterprise channel and a citizen channel is important because you're at the enterprise level, you're going to need to understand what type of benefits are actually being created at the, you know, at the micro level and figure out two things. One, are there things that, you know, do, have we built enough that we can start to release capacity from organization? Um, or is there something else that if I put in, will allow us to really think about transforming our business? So it's a, it's a lover. It's not that the end solution, right? When I tell people about you that don't know what RPA is, I say it's a lot of back office stuff and it is. Um, but we heard today that from one of the keynotes that, you know, we gotta move from the back office to the, to the front office. >>How much is that happening in financial services and how much of a sort of a holistic end to end strategy are you seeing? I'm sure you guys are promoting that are fans of that because you're going to get a much bigger business impact. It's transformational. But where are we at in the maturity of that? Yeah, it's interesting, right? So we, you know, staying on this theme of the enterprise and citizen light innovation levers, you know, the enterprise. Um, and you know, innovation levers tend to be focused more in the back office, high transaction volume type processes. I think when we look at the citizen led channel and a lot of the ideas that have been coming out in our cotton with our clients are starting to embrace this. They tend to be more front office oriented processes. There's lots of things, especially client servicing or that are tasks that are done are somewhat mundane. >>And um, you know, it's the business case and LOC isn't necessarily back capacity. It's about client experience and customer service. So, you know, you can take the, um, you know, the, the, the wealth advisor that has to log into five different systems to answer a simple client question. That's a, you know, that's a process that being able to actually have an automated way to generate that same thing at their fingertips, um, you know, could be really powerful. And so there's a big push there. I think the interesting part on the, um, going back to your bet, your business case question from before is that, um, you know, the, the business case for a lot of those types of automations, um, it's not just a factor of um, you know, have we built enough that we think that there's benefit, it's also about adoption. So if I build a robot to automate that wealth advisor process that I just noted, if 50 wealth advisors can adopt that rather than one wealth advisor, it's going to be a much greater business case. And that's a much, that's a different way of thinking about business case in the RPA sense. Because most people tend to think, here's a process, this process, I have five people that run this on a day to day basis. Um, and here's, here's my business case. In this case it's, I built something really innovative. If I can get a a hundred people to use this because it's, it takes 10 minutes out of their day, there's real, there's, there's real time there, but it is causing a lot of our clients to think differently. >>So you talk about three things as challenges scaled the business case, which you just talked about and change management. Is that part of the, and they're interrelated? Is that part of the challenge with scale? It is far as the channel. >>I mean just building on the last point around adoption, you know, that what we're doing, what we're talking about here with RPA, I think people that live in the RPA space day to day, this does this almost become second nature. And like, yeah, the technology is not that complicated. This is very basic, but you start going out to the entire organization and especially outside of technology. Um, it's, it's new. And so the change management's really important. Um, and it's important we, we view from two lenses. One is really thinking about how do you, um, upskill your workforce at a minimum so they know what technology is actually out there. It doesn't necessarily mean you're gonna make everyone a bot builder in your organization. But knowing what RPA is and knowing that, Hey, I have some tools to go help solve a given business problem is really important. But, uh, you know, the, the uh, the second point that we think is really important in here is the ability to, um, really think, sorry, really think about the, um, you know, what the longterm impact of kind of, um, you know, the overall organizational model and how that actually adopts to using automation over time. >>And that ties into change management, which is the other thing and people don't like change. Um, the other thing we heard this morning, um, Craig LeClaire Forrester analyst talked about how a lot of robots are idle sitting around ill, you know, then though at the orchestrator. And so I was, I was thinking, well, we're seeing sass models emerge, you know, UI path announced their cloud product and I would expect you're going to see new pricing models as well, kind of usage base pricing, which is kind of generally not how things are priced today. But is that something that customers are pushing for >>or definitely. I mean I think there's, um, there's two, two things we hear from customers in this space. I think as RPA, as a product is developed and you know, I think there was a push, uh, with most, with all the vendors towards kind of what's priced for bot. But the concept of a bot is a somewhat ambiguous concept to a lot of our clients. And what our clients really want is to price and value, right? And understand, um, if I'm building bots that are, you know, covering this part of the organization, I'm appropriately paying for this, um, rather than worry about how much workload did I put onto one bod versus another. I think with, uh, with the mass adoption of cloud and the fact that the RP ecosystems quickly moving from an on prem solution to a cloud based solution, I think a lot of this is just gonna happen naturally. Um, over time. I think the other, I think the other really important part in there is not to just make this a technology question about the kind of the pricing. It's also a question on value delivered and realize the benefits case and can you actually tie what those realized benefits are to what the actual price that's actually going to pay for the software is >>all right. You ready for some curve balls? Sure. Okay. So you're, you know, thought leader you worked for one of the largest consultancies on the planet global scale. You guys do some really great work disruption. We talk about digital transformation, automation obviously plays in there, blockchain, AI, RPA, et cetera. Do you, do you think that banks will lose control of payment systems? >>I'm not sure. I would say the pro, the biggest problems that banks are facing, um, with regards to that isn't necessarily whether they control the payment system or not. I actually think it's how effective they can run the system internally. I mean, I'm a, I'm an automation guy, right? And my goal is to make clients run as efficiently and as effectively as possible. And I look at a lot of the legacy debt that sits within a lot of our clients infrastructure. I think that's the biggest problem to tackle. I think if they don't tackle that and are not successful topics like RPA and automation, it, it's going to create the forces of nature that allow some of the broader disruption to happen. So it's, you know, to me, at least in my mind, it's one of these things that you, you have your agenda in what'd you can control. These are the things that you actually shouldn't be focusing on. So you're set up to compete with some of the big disruptors in the future. >>Yeah, interesting. I mean that's one industry, there's a disruption all around us, but that's one industry along with healthcare and defense that it hasn't been highly disrupted yet because it's very high risk. Not only that they're, you know, they've got very strong relationship with the government. So this, and they're big and they're well funded, but, but it seems like that disruption scenario is coming to financial services. When you talk to people in the industry, they certainly see it, but there's also a lot of complacency. It's like, Hey, we're a big, big Fs. We're doing really well. Um, dots on that. >>Um, you know, there is, you know, when we looked across and I'll just say kind of technology investment in the banking sector, big banks and asset managers, insurance companies are some of the biggest spenders on technology out there. And in your view, look at a lot of the commentary that comes out of analyst calls. There's pretty consistent, um, push a to talk about, um, you know, Becky organization as a technology company or some form of that. And there's also a big push to talk about how much money they're spending. That's great. But we've also, yeah, I think when you, you kind of look under the covers, there's been a lot of historical challenges with um, with implementing big technology projects and things. There's a lot of legacy debt that's been built over the past 25 years and complexity really thinking about this from a front to back perspective. >>Like from the point, you know, taking a, the trading side of a bank, looking at the point of trade entry through post-trade processing through finance processing through kind of every step in the life cycle. It's still run from a technology perspective, probably not as efficient as possible. And I think especially when you get outside the front office area and some of the training areas and look at that. So there's a ton of opportunity for improvement and, and you know, kind of building on the last theme, I think to the extent that technologies like RPA and automation are embraced, it helps think about that problem a little bit differently and gives us a chance to tackle some of these big meaty legacy problems that had been around for a while. If we're successful at this and we can force the ROI to be proved, we can force the change management exercise to happen. I think it sets our clients up for, again, for success to avoid some of these disruptive factors. >>Yeah. So huge opportunity then for a UI path than some of its competitors, you know, penetration wise, adoption wise, what inning are we in? >>Uh, adding to we're, we're in early days. I mean, I think we've seen a ton of interest. It's under the excitement from our clients. But you know, our surveys of, of, of the financial services industry, um, most clients will acknowledge their past the pilot and proof of concept phase and there may be even past the first 10 bought phase, but they're not at scale. Right. And I think until three things happen, I think until we can prove that the technology is being used, um, you know, from an organizational coverage across a much wider swath than it is today. I think when we can prove that there's actually a real demonstrable benefit happening from a, from an organizational operating model perspective, and to the extent that the workforce is actually embracing this and I'm posing it, I think we'll, you know, >>be in a much better position to say, Hey, we're working now getting to ending five or six and, and this, this picture's becoming more complete. But it's still early. A lot of opportunities. Kevin, thanks very much to come into the Q was great to have you. Thank you for having me. Hi, and thank you for watching. We're right back with our next guest right after this short break. You're watching the cube live from UI path forward 2019 at the Bellagio right back.

>> Live from the MIT campus in Cambridge, Massachusetts, it's The Cube, covering the 12th annual MIT Chief Data Officer and Information Quality Symposium. Brought to you by Silicon Angle Media. >> Welcome back to The Cube's coverage of MIT CDOIQ, here in Cambridge, Massachusetts. I'm your host, Rebecca Knight, along with my cohost Peter Burris. We're joined by Ilana Golbin. She is the manager of artificial intelligence accelerator PWC... >> Hi. >> Based out of Los Angeles. Thanks so much for coming on the show! >> Thank you for having me. >> So I know you were on the main stage, giving a presentation, really talking about fears, unfounded or not, about how artificial intelligence will change the way companies do business. Lay out the problem for us. Tell our viewers a little bit about how you see the landscape right now. >> Yeah, so I think... We've really all experienced this, that we're generating more data than we ever have in the past. So there's all this data coming in. A few years ago that was the hot topic: big data. That big data's coming and how are we going to harness big data. And big data coupled with this increase in computing power has really enabled us to build stronger models that can provide more predictive power for a variety of use cases. So this is a good thing. The problem is that we're seeing these really cool models come out that are black box. Very difficult to understand how they're making decisions. And it's not just for us as end users, but also developers. We don't really know 100% why some models are making the decisions that they are. And that can be a problem for auditing. It can be a problem for regulation if that comes into play. And as end users for us to trust the model. Comes down to the use case, so why we're building these models. But ultimately we want to ensure that we're building models responsibly so the models are in line with our mission as business, and they also don't do any unintended harm. And so because of that, we need some additional layers to protect ourself. We need to build explainability into models and really understand what they're doing. >> You said two really interesting things. Let's take one and then the other. >> Of course. >> We need to better understand how we build models and we need to do a better job of articulating what those models are. Let's start with the building of models. What does it mean to do a better job of building models? Where are we in the adoption of better? >> So I think right now we're at the point where we just have a lot of data and we're very excited about it and we just want to throw it into whatever models we can and see what we can get that has the best performance. But we need to take a step back and look at the data that we're using. Is the data biased? Does the data match what we see in the real world? Do we have a variety of opinions in both the data collection process and also the model design process? Diversity is not just important for opinions in a room but it's also important for models. So we need to take a step back and make sure that we have that covered. Once we're sure that we have data that's sufficient for our use case and the bias isn't there or the bias is there to the extent that we want it to be, then we can go forward and build these better models. So I think we're at the point where we're really excited, and we're seeing what we can do, but businesses are starting to take a step back and see how they can do that better. >> Now the one B and the tooling, where is the tooling? >> The tooling... If you follow any of the literature, you'll see new publications come out sometimes every minute of the different applications for these really advanced models. Some of the hottest models on the market today are deep learning models and reinforcement learning models. They may not have an application for some businesses yet, but they definitely are building those types of applications, so the techniques themselves are continuing to advance, and I expect them to continue to do so. Mostly because the data is there and the processing power is there and there's so much investment coming in from various government institutions and governments in these types of models. >> And the way typically that these things work is the techniques and the knowledge of techniques advance and then we turn them into tools. So the tools are lagging a little bit still behind the techniques, but it's catching up. Would you agree? >> I would agree with that. Just because commercial tools can't keep up with the pace of academic environment, we wouldn't really expect them to, but once you've invested in a tool you want to try and improve that tool rather than reformat that tool with the best technique that came out yesterday. So there is some kind of iteration that will continue to happen to make sure that our commercially available tools match what we see in the academic space. >> So a second question is, now we've got the model, how do we declare the model? What is the state of the art in articulating metadata, what the model does, what its issues are? How are we doing a better job and what can we do better to characterize these models so they can be more applicable while at the same time maintaining fidelity that was originally intended and embedded? >> I think the first step is identifying your use case. The extent to which we want to explain a model really is dependent on this use case. For instance, if you have a model that is going to be navigating a self-driving car, you probably want to have a lot more rigor around how that model is developed than with a model that targets mailers. There's a lot of middle ground there, and most of the business applications fall into that middle ground, but there're still business risks that need to be considered. So to the extent to which we can clearly articulate and define the use case for an AI application, that will help inform what level of explainability or interpretability we need out of our tool. >> So are you thinking in terms of what it means, how do we successfully define use cases? Do you have templates that you're using at PWC? Or other approaches to ensure that you get the rigor in the definition or the characterization of the model that then can be applied both to a lesser, you know, who are you mailing, versus a life and death situation like, is the car behaving the way it's expected to? >> And yet the mailing, we have the example, the very famous Target example that outed a young teenage girl who was pregnant before. So these can have real life implications. >> And they can, but that's a very rare instance, right? And you could also argue that that's not the same as missing a stop sign and potentially injuring someone in a car. So there are always going to be extremes, but usually when we think about use cases we think about criticality, which is the extent to which someone could be harmed. And vulnerability, which is the willingness for an end user to accept a model and the decision that it makes. A high vulnerability use case could be... Like a few years ago or a year ago I was talking to a professor at UCSC, University of California San Diego, and he was talking to a medical devices company that manufactures devices for monitoring your blood sugar levels. So this could be a high vulnerability case. If you have an incorrect reading, someone's life could be in danger. This medical device was intended to read the blood sugar levels by noninvasive means, just by scanning your skin. But the metric that was used to calculate this blood sugar was correct, it just wasn't the same that an end user was expecting. Because that didn't match, these end users did not accept this device, even though it did operate very well. >> They abandoned it? >> They abandoned it. It didn't sell. And what this comes down to is this is a high vulnerability case. People want to make sure that their lives, the lives of their kids, whoever's using this devices is in good hands, and if they feel like they can't trust it, they're not going to use it. So the use case I do believe is very important, and when we think about use cases, we think of them on those two metrics: vulnerability and criticality. >> Vulnerability and criticality. >> And we're always evolving our thinking on this, but this is our current thinking, yeah. >> Where are we, in terms of the way in which... From your perspective, the way in which corporations are viewing this, do you believe that they have the right amount of trepidation? Or are they too trepidatious when it comes to this? What is the mindset? Speaking in general terms. >> I think everybody's still trying to figure it out. What I've been seeing, personally, is businesses taking a step back and saying, "You know we've been building all these proof of concepts, "or deploying these pilots, "but we haven't done anything enterprise-wide yet." Generally speaking. So what we're seeing are business coming back and saying, "Before we go any further, we need "a comprehensive AI strategy. "We need something central within our organization "that tells us, that defines how we're going to move forward "and build these future tools, so that we're not then "moving backwards and making sure everything aligns." So I think this is really the stage that businesses are in. Once they have a central AI strategy, I think it becomes much easier to evaluate regulatory risks or anything like that. Just because it all reports to a central entity. >> But I want to build on that notion. 'Cause generally we agree. But I want to build on that notion, though. We're doing a good job in the technology world of talking about how we're distributing processing power. We're doing a good job of describing how we're distributing data. And we're even doing a good job of just describing how we're distributing known process. We're not doing a particularly good job of what we call systems of agency. How we're distributing agency. In other words, the degree to which a model is made responsible for acting on behalf of the brand. Now in some domains, medical devices, there is a very clear relationship between what the device says it's going to do, and who ultimately is decided to be, who's culpable. But in the software world, we use copyright law. And copyright law is a speech act. How do we ensure that this notion of agency, we're distributing agency appropriately so that when something is being done on behalf of the brand, that there is a lineage of culpability, a lineage of obligations associated with that? Where are we? >> I think right now we're still... And I can't speak for most organizations, just my personal experience. I think that the companies or the instances I've seen, we're still really early on in that. Because AI is different from traditional software, but it still needs to be audited. So we're at the stage where we're taking a step back and we're saying, "We know we need a mechanism "to monitor and audit our AI." We need controls around this. We need to accurately provide auditing and assurance around our AI applications. But we recognize it's different from traditional software. For a variety of reasons. AI is adaptive. It's not static like traditional software. >> It's probabilistic and not categorical. >> Exactly. So there are a lot of other externalities that need to be considered. And so this is something that a lot of businesses are thinking about. One of the reasons why having a central AI strategy is really important, is that you can also define a central controls framework, some type of centralized assurance and auditing process that's mandated from a high level of the organization that everybody will follow. And that's really the best way to get AI widely adopted. Because otherwise, I think we'll be seeing a lot of challenges. >> So I've got one more question. And one question I have is, if you look out in the next three years, as someone who is working with customers, working with academics, trying to match the need to the expertise, what is the next conversation that's going to pop to the top of the stack in this world, in, say, within the next two years? >> Yeah what we'll we be talking about next year or five years from now, too, at the next CDOIQ? >> I think this topic of explainability will persist. Because I don't think we will necessarily tick all the boxes in the next year. I think we'll uncover new challenges and we'll have to think about new ways to explain how models are operating. Other than that, I think customers will want to see more transparency in the process itself. So not just the model and how it's making its decisions, but what data is feeding into that. How are you using my data to impact how a model is making decisions on my behalf? What is feeding into my credit score? And what can I do to improve it? Those are the types of conversations I think we'll be having in the next two years, for sure. >> Great, well Ilana, thanks so much for coming on The Cube. It was great having you. >> Thank you for having me. >> I'm Rebecca Knight for Peter Burris. We will have more from MIT Chief Data Officer Symposium 2018 just after this. (upbeat electronic music)

>> From Times Square, in the heart of New York City, it's theCUBE. Covering Imagine 2018. Brought to you by Automation Anywhere. >> Welcome back everybody, Jeff Frick here with theCUBE, we are at Automation Anywhere in midtown Manhattan, 2018, excited to have our next guest, he's Kevin Kroen, he's partner of financial services, intelligent automation leader at PWC, Kevin, great to see you. >> Thank you. >> So financial services seems to be a theme, we're here in Manhattan, why is financial services an early adopter or maybe a frequent adopter or an advanced adopter of the RPA technology? >> Sure, so I think as we see our financial services clients and their agendas, there's been a huge focus on productivity and simplifying their overall operating model over the past couple of years. Banks in particular have gone through several years of having to focus their spending on non discretionary manners like regulatory compliance and risk management. And what that's generated is a need, as they started looking towards the next generation to really start thinking about what they're gonna look like in a post regulatory environment. And automation has quickly risen to the top of the agenda. >> What they're gonna look like in a post regulatory environment. >> Yes. >> Why a post regulate? >> Well I mean if you look through, you know what banks have had to deal with in term of Dodd-Frank, in terms of CCAR, you know, the regulation from federal reserve, these are things that took a lot of spending both on implementing operational processes and on implementing technology. A lot of that work is starting to you know, the banks are putting that behind themselves and so as they look forward and look at how they're going to gain more profitability in the future, the challenge becomes, there's not necessarily a new set of product innovation coming in, and so you have to really look at the expense line. >> Right. >> And so because of that automation has risen to the top of that agenda and so this continues to be one of the top areas of interest that we're getting from our clients. >> Right, so when you say post regulatory, you mean like a new regulation that they have to respond to, not that they're suddenly not gonna be regulated. >> There's not a lot of new regulations coming in right now, especially- >> That pesky one last week, GDRP. >> Yeah but in the US we're in an environment right now, there was just, you know, the revisions to the Dodd-Frank bill that were passed a lot of regulatory rules were actually being loosened so you don't necessarily have an increase in dollars that are going to be going into that. >> Right right, so it just always fascinates me, right, I thought ERP was supposed to wring out all the efficiency in our systems but that was not the case, not even by a long shot and now we continue to find these new avenues for more efficiency and clearly this is a big one that we've stumbled upon. >> Yeah, you know I think it's interesting, when you look at big technology investment over the last decade or two, you could argue a lot of efforts been focused at what I call the kind of core infrastructure and core plumbing so you know, how do I consolidate data into a single location? How do I make sure that data reconciles into different parts of my organization but that like kind of last mile of what someone does as part of their day to day business process was never really addressed, you know or is only addressed in pieces, and so I think as you start looking at the productivity term and how you actually start getting efficiency, we have very few clients that are saying, I want to take on that next big ERP type of limitation or I'm ready to spend 300 million dollars on a new project, they're looking to try to get the most value out of what they already have and they're actually looking to look at that last mile and how can they actually gain some benefit off it so the RPA technologies I think we're one of the catalysts of just being the perfect technology in the right place at the right time from a current business environment, a current technology spend perspective. >> Yeah it's pretty interesting Mihir was talking about, you know one of the big benefits is that you can take advantage of your existing infrastructure, you know, it's not a big giant rip and replace project but it's, again, it's this marginal incremental automation that you just get little benefit, little benefit, little benefit, end of the day, turns into a big benefit. >> Yeah, and I think that's, you know, it's quick, it's fast, it's, you know it can be implemented in an agile manner and you know, our clients are continuously telling us over and over again, they're willing to invest, but they wanna invest where they're gonna see a tangible payback immediately. >> Right. >> And I think when you start to talk the concept of digital transformation, it can mean a lot of different things to a lot of different people but there are big picture changes that could be made, those may be longer term trends but they're more immediate things and more immediate benefits that could be gained and I think that's really the sweet spot of where RPA and Automation Anywhere fall into. >> I was just looking up Jeff Immelt in his key note said this is the easy fountain money of any digital transformation project, I think that was the quote, that you'll ever do. That's a pretty nice endorsement. >> Yeah and it's, as we go out, we talk to CFOs, COOs, CIOs, you know, it's, the value proposition is really attractive because, you know, there have been, there's a track record of failed, technology projects failed big transformation projects and, you know, no one wants to necessarily risk their career on creating the next big failure and so I think using technology like RPA almost as an entry point or kind of like a gateway drug into the digital world, see the benefits, start to understand what are some of the business problems and historical kind of, you know, things you're trying to untangle in your infrastructure, attack that and then, you know, start to layer on additional things on top of that, once you get good with RPA and then you can start figuring out, okay, that's they gateway to artificial intelligence, okay how do I start to apply AI across my organization? As you get beyond AI, okay, how do I get into, more advanced state infrastructure and you can start thinking about this world where you can, you know, rather than do the big, five year project where you're gonna try to solve world hunger, it gives you a chance to kind of incrementally go digital over time and I think that's definitely the direction we see a lot of our clients wanting to go in. >> Right, Kevin I want to get your feedback on another topic that came up again in the keynote, was just security, you know it was like the last thing that was mentioned, you know, like A B C D E F G and security, financial services, obviously security is number one, it's baked into everything that everyone's trying to do now, it's no longer this big moat and wall, but it's got to be everywhere so I'm just curious, from the customer adoption point of view, where does security come up in the conversation, has it been a big deal, is it just assumed, is there a lot of good stuff that you can demonstrate to clients, how does security fit within this whole RPA world? >> You know with security and I would just say the broader kind of risk management pieces to the operator infrastructure are one of the first questions we get asked and a highly regulated environment like financial services, you know, the technology is easy and powerful with RPA but you also have to take a step back and say okay, I can program a bot to go do anything in my infrastructure, and that could mean running a reconciliation or it could mean going to our wire system and trying to send money out the door. And so there's a lot of concern around, not only understanding the technical aspects to you know, how the tools work with different types of security technologies, but more looking at your approach to entitlements and your approach to how you actually manage who has access to code bots, deployed bots in production, the overtime, understand what happens, you know we did a presentation to a board of directors a couple months ago on kind of automation more broadly and you know this is, you know, senior level executives the first question we got was, you know, okay, how do I prevent the 22 year old kid that just came off of campus from building a bot that no one knows about, setting it loose in our infrastructure and it going rogue, right? And so I mean this group was pretty savvy, they caught onto it very quickly and you know, the CIO of this client was sitting next to me and she kind of didn't have an immediate answer to that and I think that was kind of the a-ha moment, this is something we really need to put some thought into around you know, who are we gonna let build bots, what policies are gonna be set around how bots get deployed into our production environment, how are we gonna monitor what happens? You know how are we gonna get our auditors, our operational risk folks, our regulators, how are we gonna get all our different stakeholder groups comfortable that we have a well controlled, well functioning bot infrastructure that exists? >> Right, cause the bots actually act like people, they're entitled as like a role right, within the organization? >> We have clients that have literally had to set bots up as new employees, like they get onboarded, they have a, you go to the corporate directory and you can see a picture of R2D2, right like and it's the way they get around how they get a bot intel to a system but it's still, it's not a human right, so you still have to have a policy for how you actually will get code that uses that bot entitlement to function right and so that has to be done in a well disciplined, well controlled manner. >> Right, because to give them the ability to provide information to help a person make a decision is very different then basically enabling them to make that decision and take proactive action. >> Exactly. >> Yeah, it's funny we talked to Dr. Robert Gates at a show a little while ago and he said the only place in the US military where a machine can actually shoot a gun is on the Korean border, but every place else they can make suggestions but ultimately it's gotta be a person that makes the decision to push the button. >> And we're seeing, you know, trying to equate that to financial services, you see a similar pattern where there are certain areas where people are very comfortable playing this technology, you know you get into accounting and reporting and you know more back office type processes, you got other areas that people are a little less comfortable, you know anything that touches kind of wire systems or touches things that, you know, going out the door, touches kind of core trading processes, things like that there's a different risk profile associated with it. I think the other challenge is too is RPA is getting the gateway drug into this going back to my previous point, as you start to layer additional technologies into this, you might have less transparency over understanding clearly what's happening, especially as artificial intelligence takes a much broader role in this and so there's gonna be a lot of scrutiny I think over the next couple years put into like how do I understand the models that are created by artificial intelligence technologies and those decisions that are being made because you, if your regulator says, okay, why did you make this decision, you have to be able to explain it as the supervisor of that intelligent bot, you can't just say, oh it's cause what the machine told me to do, as so, that'll be one of the interesting challenges that's ahead of us. >> Yeah it's good, I mean it's part of the whole scale of conversation, I had interesting conversation with a guy, talking about really opening up those AI boxes so that you have an auditable process, right, you can actually point to why it made the decision even if you're not the one that made it in real time and it's doing it really really quickly so. >> Exactly. >> Really important piece. >> Yeah and as PWC, it's one of our challenges, as a consultant I'm helping clients implement this, my colleagues in our audit practice are now grappling with that same question because we're increasingly being asked to audit that type of infrastructure and have to prove that something did what it was suppose to have done. >> Right, right, alright Kevin, well nothing but opportunities for you ahead and thanks for taking a few minutes to stop by. >> Okay, thank you for having me. >> Alright, he's Kevin, I'm Jeff, you're watching theCUBE from Automation Anywhere, Imagine 2018 in Manhattan, thanks for watching. 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lie from las vegas it's the cube covering discover 2016 las vegas brought to you by Hewlett Packard Enterprise now here's your host Jeff Frick hey Jeff Rick here with the cube we're in Las Vegas at the hpe discovered 2016 the first year that HP Enterprises has discovered in Vegas they flipped the switch before they went to a London last year so we're excited to be back a lot of changes a lot more green squares all over the place green frames so it's pretty exciting but you know obviously what's at the forefront of all this is data in big data what's happening with data so we're excited to get somebody from the trenches who's out working with customers first off crystal and obviously VP biz dev cube alumni been on all the time we'll see him in Boston how long Krista that show the end of August a little further and then ken Chris the director of data analytics for pwc welcome thank you nice to be here absolutely so welcome so data a lot of talk about data in kind of this this this change in data as it's kind of a liability back in the day like what am I going to do with all this stuff i'm going to sample to now I've got the data but that's not really enough you need to get the data to information you got to get the information to incite then you got to get the insight into actionable information so what are you seeing out in the real world with some of the customers that you work with so I think that a lot of what we're seeing with customers out there I mean I was walking through the floor earlier today and to see all the things that HP is doing with various technologies the people are partnering with very impressive but fundamentally at the end of the day a lot of those technologies are producing data and like you said clients and customers are trying to figure out how do i generate value from this how do I get it in the right hands of the people that can make decisions what am I seeing out in the industry today a lot of stuff particularly around customers personalization better service client experience we have the whole concept of CX which is that customer experience end-to-end don't just worry about you know how am I going to retain customers and prevent churn but also go up the the lifecycle and figure out how to attract more customers using data personalizing my service offerings improving my digital products things of that nature I'd love to get your perspective there's a lot of talk of you know there's never enough data scientists right how we're going to get enough data scientist but it takes me back to the day when there's never going to be enough chauffeur's this car thing is never going to take off I mean are you seeing the you know this kind of this vision of getting the data into the decision-makers hands getting it out of the hallowed halls of just the data science are you seeing that happening in the real world and what are some of the ways that that happened definitely I mean we've talked a long time about the concept of the data scientists being that individual that is like the unicorn it doesn't exist right so what we talk more about now is like pulling together those SWAT teams where you have someone that understands the data someone that understands the business problem someone that understands deep analytics spin teams like that up go out and find the answers yeah that's funny that you said that because we hear that a lot that data science is not an individual's it's a team sport you know you really have to bring a lot of people to bear and it's it's not just this this hallowed thing down a mahogany row at the very end it's actually getting that in you know and getting dirty with a lot of folks yeah that and I would also say another thing that's going to help with regards to the whole data scientist crunch is machine learning robotics things of that nature artificial intelligence I definitely think that that's something that people kid about as something that's far down the future but I think it's coming very quickly and something that customer sorry excuse me company should pay attention today so Chris you've been playing in the space forever you've seen a lot of transformation wonder if you could speak specifically to how the cloud has really impacted this whole kind of big data meme in this big data discussion because now suddenly it's a lot of people that have a lot of access to a lot of stuff that aren't necessarily connected to the VPN you know back at corporate headquarters that enable that to go out well it's allowed a lot of customers to iterate faster to try new things more quickly set them up take them down it's gotten business people involved one of the things can and I talked about in the session we just gave together was about how this is becoming more of a business discussion so our partnership with solution partners like PwC become more and more important because it's not always just IT people these days driving the data lakes it's now you're starting to see other sea level execs you know CFO the CMO starting to drive some of these initiatives and cloud-based solutions make those things more accessible so we're definitely seeing both quicker iteration and more business involvement the other thing we hear Kendall a lot about was back in the day right you had to sample you know you couldn't store all the data you couldn't process all the data yeah there was a lot of sampling going on right now that's that's changing you know you can store the data you can grab a lot more than you even think that you might need today but what you might need tomorrow and you can run big processes against big data sets that you couldn't do before you seen that kind of manifest itself in the market oh yeah all over the place i mean my specialty is within the entertainment media and communications business so when you talk about the cable companies and phone companies out there digesting set-top box data data coming off of phones if you go into the world where you know people Internet of Things sensor data just that you know we call it data to lose where where where it's just coming in Fast and Furious and the folks that are responsible for maintaining protecting and serving that data up are challenged more and more today and there's a lot of business pressure because people that use you know apps on their phone don't understand why can't I do the same thing with data that I know that we have to makes it make it insightful and actionable and allow me to do my job right but then kind of the dark side of that is if you have too much data you know our argues are you swimming in data that's not necessarily an indication of the change that you're trying to impact or you know it's not an indicator of something that you can take action so how are people kind of filtering through to get the right data to the right people at the right time yeah I mean Chris mentioned this and one of his previous answers but the attack that we take and that we stress with our clients is to take a business capabilities driven approach so when you think about the guy in the field that's responsible for sales or the person in the call center that's responsible for customer service taking the viewpoint of how what data do they need how do they need it served up how do they need it parsed and when do they need it that is the key to the approach to figuring out how do i find the signals through the noise what data is really worthwhile and do i really need to protect and make sure it gets served up versus this stuff i can keep versus this stuff i really don't need right and of course the other big trend is is an actual word spark summit we had another crew up there is this whole move to real time right and streaming data and not not you know grabbing capturing reviewing and looking back but watching it in real time and taking action while it's dreaming totally changing the business yeah fascinating and big data are used you know you use that car analogy before and if you heard Meg in the keynote say I think every driverless car is going to create three library of congress's worth of in fourth of data so and obviously it's very important right so you want to aggregate the data about what's going on with if you're running a fleet of cars but obviously you also have to know what's going on in the car and that's that's about as real time as it gets so and so these things are complementary big data and fascinator highly complementary and we're seeing a lot more activity out at the edge and obviously we made some announcements here both in terms of partners and some of our initiatives at HB around that here so Ken last question video we hear over and over and over the videos and increasing proportion of the total traffic on the Internet nobody ever thought that people would hang out on their phones and watch Game of Thrones or an NFL game or go warriors and you're in the media comes or the cube that's right well we knew they would watch a cute Chris um they're only 18 minutes but that's a huge huge stressor on resources a huge stress Iran on capacity storage networking and yet the customers want it right the expectation is going to be there it's going to look good so how is that impacting the guys on the back end that are responsible for delivering a good experience but they also have pricing pressure and they've got a ton of demands on their resources yeah yeah it's funny that you bring that up I walked into my house last week and hell-bent on having some good family time with my wife and kids and the TV was on and all of them had multiple devices actually iPads and iPhones that they were and everything was sucking off the internet which was kind of amusing to me but that's exactly your point and a lot of the companies that we're working with in the communications industry specifically their main goal and focuses to make sure that the pipes are big enough that they're utilized properly to make sure people have the best experience possible so utilizing the technology not only capture the data but really deep analytics to pinpoint where are my peaks and troughs and utilization and usage going to be how do i divert and make sure the right resources are available again also that can provide the best customer experience just can't over provision it like bananas oh yeah but it's expensive so you don't want those pipes of the empty either that's the thing you want to have enough capacity but you don't want / build that so it's it's an analytics challenge this analytics challenge and it's I always think of the old AT&T ma belle you know problem on Mother's Day everybody calls mom on mother's day back in the day you had to build the pipe to support mother's day even though most people aren't calling or not on Mother's Day well can Chris thanks for stopping by can give you last word we're looking forward to in the next six months as you know see some of the exciting things your customers are working on yeah i mean the technological advances are really great i will say that customers especially business consumers of the data getting very much more smarter much more savvy er so the demands on the folks serving up that data storing that data and protecting that data are going to be you know more and more crucial but it's it's just great business to be a part of it's great to see it's great to see the technology and some of the stuff that you guys are doing so we're proud to be part of it and happy to be here thanks for stopping by Ken Chris crystal and I'm Jeff Rick you're watching the cube we'll see you next time

from Houston Texas extracting the signal from the noise it's the cute coverage Grace Hopper celebration of women in computing now your host John furrier and Jeff fridge okay welcome back everyone we are here live in Houston Texas for the Grace Hopper celebration of women in computing this is SiliconANGLE media's the cube our flagship program we go out to the events and extract the simla noise i'm john ferry the founder of SiliconANGLE join with Jeff Frick general manager of the cube our next guest is Lisa Dougal who's the chief diversity officer pwc consulting welcome to the cube thank you very much great to see you great to chat with you before we came on we talked about you were at Carnegie Mellon back in the 80s and we just had Eileen big enough for it to it another 80s throwback like me in sheb back to the 80s hot tub time machine whatever you want to call it it's a lot of fun so thanks for spending some time with us oh my pleasure so first what are you working on so that's the first point we've learned that's a good question to ask what are you working on what am i working on so for me personally I do a number of different things right as my role is chief diversity officer I am creating and evolving and implementing programs that help all kinds of diversity in the workplace which ranges from women to minorities to men as well which is one of our big focus areas right as a partner in the practice i'm also a retail consumer partner so I work with retail and consumer clients on transforming their businesses from strategy to execution digital transformations hot right now Adam everything is being automated I mean everything's addressable now Internet of Things creates absolutely % data acquisition it does but I think at the same time it's created such a wealth of I will call it information old school or data its recent project right I think companies are struggling with how do you parse through how do you tell the story how do you figure out a what the data is telling you if you take the consumer industry for one right they've got huge amounts of consumer data now the question is how do you use it how you turn it into innovation one of the things you were mentioning before you came on was that you did a thesis at Carnegie Mellon back in the eighties where you ready to say a computer science major but everyone had the code which great paid back in the 80s and maybe we should reinstitute that across the university I agree I think everything went should coach likes math and sciences to me I think a requisite skill for everybody but you say that these are supposed decision-making using computers now fast forward to today where we were just chatting about for the first time in modern in business history you can actually measure everything so no more excuses if you could actually measure everything right so the question becomes what do you want to measure right yeah so what does that do with a business how does that change and I think it's a combination of measurement which just looks historical and that's important right with predictive and right where the world is going it's predictive analytics behavioral analytics right because that enables us to figure out how we want to change we're only ever looking backwards we had a static point in time yeah and that's informative and you need that and as we talked before you need to be able to parse through the data and decide which is relevant and which is really the lever you want to pull but I think more and more we're seeing companies doing data modeling and data predictive analytics on just about everything right right and Merv Adrian loves to talk about data in motion from gartner and you know it's no longer good enough to have it look at it then decide what you're going to do now really was spark and some of the new technologies you actually have an opportunity to look at the data in motion in a transaction in a retail environment and change change the transaction midstream to hopefully get to a better out absolutely so what you seeing kind of out in the in the world of some of these more advanced retailers and some of the things I think that's happening i think the ability to drop coupons as people walk by the aisle is more and more prevalent right not just any coupon but we know you buy a lot of milk right i think you're going to see more and more price changing based on the consumer i know you you've been into my store you're a loyal customer I'll pop you the milk at this price where somebody else might pay a higher price I think the world is open in terms of how these companies are using not just the data they collect on the product and the technologies but also on you as the individual least I want to get your thoughts on a concept that we've been kind of gleaming out of the data here at Grace Hopper and other events we've been to around women in computing but more importantly also computer science and that there's a lot of different semantics people argue about women versus ladies this versus that there's so many different you know biases mean I'm biased whatever all that stuff's happening but one constant in all this is that these two debt variables transparency and always learning and that seems to be a driver of a lot of change here and you mentioned digital transformation what are you seeing out there that's really driving the opportunities around transparency you can save data access you have data then things are transparent always be learning this new opportunities so those seems to be a big pivot points here at this event here where there's a lot of opportunities there's a subtle conversation of not just the pay thing and the gender equality on pay but opportunities is the big theme we're seeing here absolutely I am really energized by being here right first of all to see so many young women all passionate about technology and computing and really being inserted in the right ways you know I've had women come up to me even on the escalator shake my hand as a hello you're from pricewaterhousecoopers let me ask you what you do during your day right I think in my day a there was no place to go and even if you did you were trying to navigate a very different world and you were trying to perhaps not be you but be somebody else right how do you fit into the man's world I used to watch all sports all weekend so I can make sure I could participate in office conversation when I got in on Monday mornings right I think to hear the conversations that the women are having that are very technology driven but also very much authentic to who they are is where we're going see if you were a young lady in tech now you actually program the fantasy games so that you'd win the game everywhere that's right you could write the code this is but there's a lot of coding a lot of developers here phenomenal growth in develops we just had a young girl just graduated she's phenomenal Natalia and she got into it she started in journalism major and second year in she switched into computer science because she was tinkering with wearables which is terrific right one of the conversations I like to have with our young women about PwC in particular but a lot of parts of the industry the ability to combine industry or sector knowledge with the technology right so I was talking to one women who said well you know I just switched out of pre-med I really like medicine but I got into coding and I simply have you thought about you know the whole arena of the health care industry is dramatically changing right we're moving to the point where we have you know patient information hospital information drug trial information we can integrate all that you could stay with healthcare and still do technology and coding and she's looking at me like she'd never thought about the revelation you said early undulation the old days you try to be someone else try to fit into a man's world but now you're saying you know just the app just follow your passion and this technology behind it interesting enough is also an effect on the men like I had a Facebook post on my flight down here at the Wi-Fi on the plane and i typed in my facebook friends hey real question is a politically incorrect to say I love women in tech I kind of put that out there is kind of a link bait but all sudden the arguments were weighed politically correct love is for versions of love's like argument and wedding Gary deep hey very deep but the one comment was just be yourself and I think I tell our women that all the time and all our people right but i think this the shift to the workplace openness where you can be authentic and i find often are young women in particular get guidance from mentors who are men and they try to emulate that and some of that is good but you have to emulate that while being authentic to who you are otherwise you run that risk of perhaps being perceived in authentic or you know it comes off a little bit too can write what's your best advice to men because one of the things that we seeing is a trend now and certainly is that men inclusion is also into the conversation absolutely big thing we are doing that as a firm both in the US and globally we're a ten-by-ten impact sponsor for he for she which is the UN's initiative with companies governments and not-for-profits to engage men in a conversation about raising awareness around women and for us it's women in the workplace right so there really a couple of things I think men can do one is listen and actively engage with the women and not just women at your level women who are Millennials as well if you can't of not comfortable having that conversation which I know many with women and men both aren't it's hard to put yourself in their shoes right the second is to really be an advocate right think about when you walk into meetings who's not in the room are the people looking all like you what do you do about that right and i think that the third is make it personal you know be involved and know what's going on and know how you could help it seems so simple right when you just lay it out there right those are not complicated concepts but but to put them in practices is you know it takes an active you know kind of thinking about it right to really make it happen to impact change it does and i think more it is natural for people to gravitate to people who are like them particularly in the workspace we get very comfortable in our own let's call them echo chambers and then you move with your echo chamber and your echo chamber might have a little diversity but likely it doesn't have a lot of generational diversity it may or may not have all kinds of racial ethnic gender diversity and so you might meet somebody on the outside who's a little different but you go back to your go tues who are still in your echo chamber so I think the goal is to get into multiple a few echo chambers right also I also comfort zone right i mean people like what's familiar to them and pushing the comfort zone barrier is one issue right now happy young come to be uncomfortable be comfortable and the uncomfortable how is that right what people should look for I mean and everyone has their own struggles and journeys what how did people cope it so I often to have this conversation with methanol how do I talk to women about being women I said well that's probably not the first conversation you should be having right talk to them about who they are and what's important to you and then the relationship you have to build what we call familiarity comfort and trust and once you've built that you can have a conversation perhaps about what a woman's plans are if she's pregnant but you can't just walk in and taught me the for that yeah you can't blurt it out right thank you thanks off at not a walk not a good icebreaker yeah yeah so Lisa you know there's a lot of talk about what's the right thing to do what is right meaning it's the right thing to do in terms of morally and as a human being to include people but really there's there's a bottom line positive impact to there's a better outcome impact and pwc you guys do a lot of analysis you work a lot of companies so there's some studies you can share some some facts or figures that you guys have discovered about how there's really great bottom line better decisions better products better profitability when you have a diverse point of view that you bring to a problem set absolutely there are number of different ways to look at that I think you're right it is the right thing to do the moral thing to do people want to feel good about it but at the end of the day we know that diversity is good for business performance right and there are a number of studies out there that talk about board composition and how you know now bored women on boards has been legislated in enough countries around the world for long enough now you can correlate long-term 10-15 year performance with the performance of those companies and we see that those companies perform better right you can look at just the diversity I mean another angle of looking at it is we do a lot of work with Millennials in the millennial studies right and people coming off a campus are more Geographic gender ethnic minority diverse than any generations we've seen at a very long time right there more women coming off of campus in general than men right now and they're doing very well right so there's also the zero-sum game that says if we don't figure out how to accommodate a track promote retain women then we're not going to be able to get the best of the best of the workforce and you become at a competitive disadvantage well it's quality that's the competitive advantage is the quality that you get with the diversity absolutely how do you manage that process because some would say diversity slows things down because you have different perspectives but the outputs higher quality high equality and more innovation right and one of the things we like to do is talk about diversity and a number of different angles so there's race gender sexual orientation there's also in our business diversity of degrees so we have coders working with mba is working with lawyers doctors strategist and part of that is the way you get the thinking and the most innovative solutions to your problems and I think when you begin to develop and to find it that way there are places for more people to get on the wheel so to speak right everybody is thinking about diversity not just you look different or you experience but you bring a different perspective to the problem because you have a different background where you grow up and what you studied it's just it's just funny that you know in being diverse you're actually leveraging people's biases to get to a better solution absolutely perfect all the way around that's right and i think that there's a movement now and we're really moving from thinking about being equal to thinking about being equitable right equal would say if you have three kids peering over a fence ones four foot ones five-foot 16 foot give them all in one foot box well that's not going to get the forefoot guy over the fence right what you really have to do is give them each a size box that they need right so the six-foot kid probably doesn't need a box at all if it's a five-foot fence right the 5-foot kid might need a little stepstool and the forfeit kid probably needs a large cube right right that's being equitable it's not necessary to me out well based on the outcome based on the album about the objective right versus some statistical equitable correct so I think in business we're moving more to looking at that outcome based heck with biddle equity being equitable across outcomes equitable thank you not just being equal because I think for a long term it was treat everybody the same and that's diversity it's really appreciate everybody for their just as differences and let them play to their strengths right and use the data science tools available Go Daddy put out the survey results of their salaries to you seeing the University of Virginia Professor Brian gave a keynote today about the software that they're building an open source for tooling but the date is going to be key but at the end of the day management drives the outcome objective so I'm Celeste someone at a senior level who's had a good journey from the 80 Eileen big and talk about the same thing you're now at the top of the pyramid the flywheels developing there's some good on in migration with women coming into the field house the balance how's that flywheel working for the mentoring the pipeline in the operational I'd say I give you one example right so we have a women in technology what started as a program it's now a part of our business right we started about two and a half years ago with 30 women who are trying to figure out in technology you give you a long term implementation projects for you know six months a year two years and only operate in the same echo chamber right so how do you network with other women how do you meet them it's now 1400 people strong and one of the pillars of it is a mentorship program we had and it doesn't sound like a lot but see from where you start right increase if we started with needing having about 50 50 women mentored right we're up to hundreds of women being mentored and last time we opened the program we had 150 leaders not just we had other people but leaders sign up within the first few days to mentor the women so in my mind that's success that success reason I didn't need to promise my job good job on your older thank you taking you for that network effect there's an app for that now the network effectors are dynamic now so coming back to the theory of socialization and social theory as you get a network effect going on there's a good social vibe going on talk about that dynamic it's kind of qualitative and then be might be some numbers so save it but talk about that the the network effect of that viral growth if you will I think you sort of have it's now a important and good and rewarded thing to do right but I also think there's a millennial factor there yeah right so what we've been able to see is as our tech women come in off a campus they're beginning to get opportunities that change the game around women in the community right so we brought a number of two-year three-year out women with us and have them help us in the planning of being here all the way from designing our website to putting together the booth to submitting and speaking at so they got speaker slots which gives them amazing exposure with then sentenced that social dynamic in a number of ways right you have them wanting to other people wanting to emulate it you have leaders reaching out to me and say wow we didn't know Emily you know Emily did that that is great right she spoke to 900 people yesterday and so that changes the social landscape acceptable it certainly does it's great amplification so as we wrap here at Lisa I think that's a great segue talk about the Grace Hopper celebration of women in computing it's a very different kind of conference it's a very different kind of feel why is it important to pwc why do you guys invest in this show and you know the example you caves just a great lead into it I think it's for a number of reasons it's a great source of recruits right so so we want to be here we want to meet the young people coming off of campus so maybe we might not meet in our structured campus environment right I think the second is it's a great opportunity for our young women to promote and develop themselves and gain skills that we would never gain I think the third is just to empower our women just like being here and even the emails i'm getting from our women who are not here and our men who are not here the fact that we are here has sort of had a little bit of a viral offensive foam oh you're missing out you're missing out it's an amazing experience it's really helped put in some ways women in technology in a little different league right a lot of the alliances and a lot of the conference's we do are we do 15 major conferences now and we support leadership for women events at all of them but this is one of the few that's not alliance space it's not being at SI p with us AP or being an owl with Oracle which are great things for us to do but this is for the women about the women and the development of the women it's an exciting time and we're excited to document and thanks for spending the time sharing your insights and data and perspective here on the cube well thank you so much John and jeff bennett me having me whereas our pleasure was so inspired so really awesome and if you want to be part of the cube we are hiring looking for women digital scientists data analyst on-air host and we've been shamed a little bit for having an all-male team here I was just gonna ask ya we are looking for powerful strong smart women who want to join the cube we're hiring so contact us offline thanks for watching me right back with more live coverage here in Houston Texas at the Grace Hopper celebration be right back

>> Narrator: "theCUBE's" live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (intro music) >> Good afternoon, everyone. Welcome back to "theCUBE's" day three coverage of MWC23. Lisa Martin here in Spain, Barcelona, Spain with Dave Nicholson. We're going to have a really interesting conversation next. We're going to really dig into MWC, it's history, where it's going, some of the controversy here. Please welcome our guests. We have Jim Harris, International Best Selling Author of "Blindsided." And Carolina Milanese is here, President and Principle Analyst of creative strategies. Welcome to "theCUBE" guys. Thank you. >> Thanks. So great to be here. >> So this is day three. 80,000 people or so. You guys have a a lot of history up at this event. Caroline, I want to start with you. Talk a little bit about that. This obviously the biggest one in, in quite a few years. People are ready to be back, but there's been some, a lot of news here, but some controversy going on. Give us the history, and your perspective on some of the news that's coming out from this week's event. >> It feels like a very different show. I don't know if I would say growing up show, because we are still talking about networks and mobility, but there's so much more now around what the networks actually empower, versus the network themselves. And a little bit of maybe that's where some of the controversy is coming from, carriers still trying to find their identity, right, of, of what their role is in all there is to do with a connected world. I go back a long way. I go back to when Mobile World Congress was called, was actually called GSM, and it was in Khan. So, you know, we went from France to Spain. But just looking at the last full Mobile World Congress here in Barcelona, in pre-pandemic to now, very different show. We went from a show that was very much focused on mobility and smartphones, to a show that was all about cars. You know, we had cars everywhere, 'cause we were talking about smart cities and connected cars, to now a show this year that is very much focused on B2B. And so a lot of companies that are here to either work with the carriers, or also talk about sustainability for instance, or enable what is the next future evolution of computing with XR and VR. >> So Jim, talk to us a little bit about your background. You, I was doing a little sleuthing on you. You're really focusing on disruptive innovation. We talk about disruption a lot in different industries. We're seeing a lot of disruption in telco. We're seeing a lot of frenemies going on. Give us your thoughts about what you're seeing at this year's event. >> Well, there's some really exciting things. I listened to the keynote from Orange's CEO, and she was complaining that 55% of the traffic on her network is from five companies. And then the CEO of Deutsche Telecom got up, and he was complaining that 60% of the traffic on his network is from six entities. So do you think they coordinated pre, pre-show? But really what they're saying is, these OTT, you know, Netflix and YouTube, they should be paying us for access. Now, this is killer funny. The front page today of the show, "Daily," the CO-CEO of Netflix says, "Hey, we make less profit than the telcos, "so you should be paying us, "not the other way around." You know, we spend half of the money we make just on developing content. So, this is really interesting. The orange CEO said, "We're not challenging net neutrality. "We don't want more taxes." But boom. So this is disruptive. Huge pressure. 67% of all mobile traffic is video, right? So it's a big hog bandwidth wise. So how are they going to do this? Now, I look at it, and the business model for the, the telcos, is really selling sim cards and smartphones. But for every dollar of revenue there, there's five plus dollars in apps, and consulting and everything else. So really, but look at how they're structured. They can't, you know, take somebody who talks to the public and sells sim cards, and turn 'em in, turn 'em in to an app developer. So how are they going to square this circle? So I see some, they're being disrupted because they're sticking to what they've historically done. >> But it's interesting because at the end of the day, the conversation that we are having right now is the conversation that we had 10 years ago, where carriers don't want to just be a dumb pipe, right? And that's what they are now returning to. They tried to be media as well, but that didn't work out for most carriers, right? It is a little bit better in the US. We've seen, you know, some success there. But, but here has been more difficult. And I think that's the, the concern, that even for the next, you know, evolution, that's the, their role. >> So how do they, how do they balance this dumb pipe idea, with the fact that if you make the toll high enough, being a dumb pipe is actually a pretty good job. You know, sit back, collect check, go to the beach, right? So where, where, where, where does this end up? >> Well, I think what's going to happen is, if you see five to 15 X the revenue on top of a pipe, you know, the hyperscalers are going to start going after the business. The consulting companies like PWC, McKinsey, the app developers, they're... So how do you engage those communities as a telco to get more revenue? I think this is a question that they really need to look at. But we tend to stick within our existing business model. I'll just give you one stat that blows me away. Uber is worth more than every taxi cab company in North America added together. And so the taxi industry owns billions in assets in cars and limousines. Uber doesn't own a single vehicle. So having a widely distributed app, is a huge multiplier on valuation. And I look to a company like Safari in Kenya, which developed M-Pesa, which Pesa means mo, it's mobile money in Swahili. And 25% of the country's GDP is facilitated by M-Pesa. And that's not even on smartphones. They're feature phones, Nokia phones. I call them dumb phones, but Nokia would call them "feature phones." >> Yeah. >> So think about that. Like 25, now transactions are very small, and the cut is tiny. But when you're facilitating 25% of a country's GDP, >> Yeah. >> Tiny, over billions of transactions is huge. But that's not the way telcos have historically thought or worked. And so M-Pesa and Safari shows the way forward. What do you think on that? >> I, I think that the experience, and what they can layer on top from a services perspective, especially in the private sector, is also important. I don't, I never believe that a carrier, given how they operate, is the best media company in the world, right? It is a very different world. But I do think that there's opportunity, first of all, to, to actually tell their story in a different way. If you're thinking about everything that a network actually empowers, there's a, there's a lot there. There's a lot that is good for us as, as society. There's a lot that is good for business. What can they do to start talking about differently about their services, and then layer on top of what they offer? A better way to actually bring together private and public network. It's not all about cellular, wifi and cellular coming together. We're talking a lot about satellite here as well. So, there's definitely more there about quality of service. Is, is there though, almost a biological inevitability that prevents companies from being able to navigate that divide? >> Hmm. >> Look at, look at when, when, when we went from high definition 720P, very exciting, 1080P, 4K. Everybody ran out and got a 4K TV. Well where was the, where was the best 4K content coming from? It wasn't, it wasn't the networks, it wasn't your cable operator, it was YouTube. It was YouTube. If you had suggested that 10 years before, that that would happen, people would think that you were crazy. Is it possible for folks who are now leading their companies, getting up on stage, and daring to say, "This content's coming over, "and I want to charge you more "for using my pipes." It's like, "Really? Is that your vision? "That's the vision that you want to share with us here?" I hear the sound of dead people walking- (laughing) when I hear comments like that. And so, you know, my students at Wharton in the CTO program, who are constantly looking at this concept of disruption, would hear that and go, "Ooh, gee, did the board hear what that person said?" I, you know, am I being too critical of people who could crush me like a bug? (laughing) >> I mean, it's better that they ask the people with money than not consumers to pay, right? 'Cause we've been through a phase where the carriers were actually asking for more money depending on critical things. Like for instance, if you're doing business email, then were going to charge you more than if you were a consumer. Or if you were watching video, they would charge you more for that. Then they understood that a consumer would walk away and go somewhere else. So they stopped doing that. But to your point, I think, and, and very much to what you focus from a disruption perspective, look at what Chat GTP and what Microsoft has been doing. Not much talk about this here at the show, which is interesting, but the idea that now as a consumer, I can ask new Bing to get me the 10 best restaurants in Barcelona, and I no longer go to Yelp, or all the other businesses where I was going to before, to get their recommendation, what happens to them? You're, you're moving away, and you're taking eyeballs away from those websites. And, and I think that, that you know, your point is exactly right. That it's, it's about how, from a revenue perspective, you are spending a lot of money to facilitate somebody else, and what's in it for you? >> Yeah. And to be clear, consumers pay for everything. >> Always. Always. (laughs) >> Taxpayers and consumers always pay for everything. So there is no, "Well, we're going to make them pay, so you don't have to pay." >> And if you are not paying, you are the product. Exactly. >> Yes. (laughing) >> Carolina, talk a little bit about what you're seeing at the event from some of the infrastructure players, the hyperscalers, obviously a lot of enterprise focus here at this event. What are some of the things that you're seeing? Are you impressed with, with their focus in telco, their focus to partner, build an ecosystem? What are you seeing? >> I'm seeing also talk about sustainability, and enabling telco to be more sustainable. You know, there, there's a couple of things that are a little bit different from the US where I live, which is that telcos in Europe, have put money into sustainability through bonds. And so they use the money that they then get from the bonds that they create, to, to supply or to fuel their innovation in sustainability. And so there's a dollar amount on sustainability. There's also an opportunity obviously from a growth perspective. And there's a risk mitigation, right? Especially in Europe, more and more you're going to be evaluated based on how sustainable you are. So there are a lot of companies here, if you're thinking about the Ciscos of the world. Dell, IBM all talking about sustainability and how to help carriers measure, and then obviously be more sustainable with their consumption and, and power. >> Going to be interesting to see where that goes over the years, as we talk to, every company we talk to at whatever show, has an ESG sustainability initiative, and only, well, many of them only want to work with other companies who have the same types of initiative. So a lot of, great that there's focus on sustainability, but hopefully we'll see more action down the road. Wanted to ask you about your book, "Blind," the name is interesting, "Blindsided." >> Well, I just want to tag on to this. >> Sure. >> One of the most exciting things for me is fast charging technology. And Shalmie, cell phone, or a smartphone maker from China, just announced yesterday, a smartphone that charges from 0 to 100% in five minutes. Now this is using GAN FEST technology. And the leader in the market is a company called Navitas. And this has profound implications. You know, it starts with the smartphone, right? But then it moves to the laptops. And then it'll move to EV's. So, as we electrify the $10 trillion a year transportation industry, there's a huge opportunity. People want charging faster. There's also a sustainability story that, to Carolina's point, that it uses less electricity. So, if we electrify the grid in order to support transportation, like the Tesla Semi's coming out, there are huge demands over a period. We need energy efficiency technologies, like this GAN FEST technology. So to me, this is humongous. And it, we only see it here in the show, in Shalmie, saying, "Five minutes." And everybody, the consumers go, "Oh, that's cool." But let's look at the bigger story, which is electrifying transportation globally. And this is going to be big. >> Yeah. And, and to, and to double click on that a little bit, to be clear, when we talk about fast charging today, typically it's taking the battery from a, not a zero state of charge, but a relatively low state of charge to 80%. >> Yep. >> Then it tapers off dramatically. And that translates into less range in an EV, less usable time on any other device, and there's that whole linkage between the power in, and the battery's ability to be charged, and how much is usable. And from a sustainability perspective, we are going to have an avalanche of batteries going into secondary use cases over time. >> They don't get tossed into landfills contrary to what people might think. >> Yep. >> In fact, they are used in a variety of ways after their primary lifespan. But that, that is, that in and of itself is a revolutionary thing. I'm interested in each of your thoughts on the China factor. Glaringly absent here, from my perspective, as sort of an Apple fanboy, where are they? Why aren't they talking about their... They must, they must feel like, "Well we just don't need to." >> We don't need to. We just don't need to. >> Absolutely. >> And then you walk around and you see these, these company names that are often anglicized, and you don't necessarily immediately associate them with China, but it's like, "Wait a minute, "that looks better than what I have, "and I'm not allowed to have access to that thing." What happens in the future there geopolitically? >> It's a pretty big question for- >> Its is. >> For a short little tech show. (Caroline laughs) But what happens as we move forward? When is the entire world going to be able to leverage in a secure way, some of the stuff that's coming out of, if they're not the largest economy in the world yet, they shortly will be. >> What's the story there? >> Well, it's interesting that you mentioned First Apple that has never had a presence at Mobile World Congress. And fun enough, I'm part of the GSMA judges for the GLOMO Awards, and last night I gave out Best Mobile Phone for last year, and it was to the iPhone4 Team Pro. and best disruptive technology, which was for the satellite function feature on, on the new iPhone. So, Apple might not be here, but they are. >> Okay. >> And, and so that's the first thing. And they are as far as being top of mind to every competitor in the smartphone market still. So a lot of the things that, even from a design perspective that you see on some of the Chinese brands, really remind you of, of Apple. What is interesting for me, is how there wouldn't be, with the exception of Samsung and Motorola, there's no one else here that is non-Chinese from a smartphone point of view. So that's in itself, is something that changed dramatically over the years, especially for somebody like me that still remember Nokia being the number one in the market. >> Huh. >> So. >> Guys, we could continue this conversation. We are unfortunately out of time. But thank you so much for joining Dave and me, talking about your perspectives on the event, the industry, the disruptive forces. It's going to be really interesting to see where it goes. 'Cause at the end of the day, it's the consumers that just want to make sure I can connect wherever I am 24 by seven, and it just needs to work. Thank you so much for your insights. >> Thank you. >> Lisa, it's been great. Dave, great. It's a pleasure. >> Our pleasure. For our guests, and for Dave Nicholson, I'm Lisa Martin. You're watching, "theCUBE," the leader in live and emerging tech coverage coming to you day three of our coverage of MWC 23. Stick around. Our next guest joins us momentarily. (outro music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is "Breaking Analysis" with Dave Vellante. >> A decade of big data investments combined with cloud scale, the rise of much more cost effective processing power. And the introduction of advanced tooling has catapulted machine intelligence to the forefront of technology investments. No matter what job you have, your operation will be AI powered within five years and machines may actually even be doing your job. Artificial intelligence is being infused into applications, infrastructure, equipment, and virtually every aspect of our lives. AI is proving to be extremely helpful at things like controlling vehicles, speeding up medical diagnoses, processing language, advancing science, and generally raising the stakes on what it means to apply technology for business advantage. But business value realization has been a challenge for most organizations due to lack of skills, complexity of programming models, immature technology integration, sizable upfront investments, ethical concerns, and lack of business alignment. Mastering AI technology will not be a requirement for success in our view. However, figuring out how and where to apply AI to your business will be crucial. That means understanding the business case, picking the right technology partner, experimenting in bite-sized chunks, and quickly identifying winners to double down on from an investment standpoint. Hello and welcome to this week's Wiki-bond CUBE Insights powered by ETR. In this breaking analysis, we update you on the state of AI and what it means for the competition. And to do so, we invite into our studios Andy Thurai of Constellation Research. Andy covers AI deeply. He knows the players, he knows the pitfalls of AI investment, and he's a collaborator. Andy, great to have you on the program. Thanks for coming into our CUBE studios. >> Thanks for having me on. >> You're very welcome. Okay, let's set the table with a premise and a series of assertions we want to test with Andy. I'm going to lay 'em out. And then Andy, I'd love for you to comment. So, first of all, according to McKinsey, AI adoption has more than doubled since 2017, but only 10% of organizations report seeing significant ROI. That's a BCG and MIT study. And part of that challenge of AI is it requires data, is requires good data, data proficiency, which is not trivial, as you know. Firms that can master both data and AI, we believe are going to have a competitive advantage this decade. Hyperscalers, as we show you dominate AI and ML. We'll show you some data on that. And having said that, there's plenty of room for specialists. They need to partner with the cloud vendors for go to market productivity. And finally, organizations increasingly have to put data and AI at the center of their enterprises. And to do that, most are going to rely on vendor R&D to leverage AI and ML. In other words, Andy, they're going to buy it and apply it as opposed to build it. What are your thoughts on that setup and that premise? >> Yeah, I see that a lot happening in the field, right? So first of all, the only 10% of realizing a return on investment. That's so true because we talked about this earlier, the most companies are still in the innovation cycle. So they're trying to innovate and see what they can do to apply. A lot of these times when you look at the solutions, what they come up with or the models they create, the experimentation they do, most times they don't even have a good business case to solve, right? So they just experiment and then they figure it out, "Oh my God, this model is working. Can we do something to solve it?" So it's like you found a hammer and then you're trying to find the needle kind of thing, right? That never works. >> 'Cause it's cool or whatever it is. >> It is, right? So that's why, I always advise, when they come to me and ask me things like, "Hey, what's the right way to do it? What is the secret sauce?" And, we talked about this. The first thing I tell them is, "Find out what is the business case that's having the most amount of problems, that that can be solved using some of the AI use cases," right? Not all of them can be solved. Even after you experiment, do the whole nine yards, spend millions of dollars on that, right? And later on you make it efficient only by saving maybe $50,000 for the company or a $100,000 for the company, is it really even worth the experiment, right? So you got to start with the saying that, you know, where's the base for this happening? Where's the need? What's a business use case? It doesn't have to be about cost efficient and saving money in the existing processes. It could be a new thing. You want to bring in a new revenue stream, but figure out what is a business use case, how much money potentially I can make off of that. The same way that start-ups go after. Right? >> Yeah. Pretty straightforward. All right, let's take a look at where ML and AI fit relative to the other hot sectors of the ETR dataset. This XY graph shows net score spending velocity in the vertical axis and presence in the survey, they call it sector perversion for the October survey, the January survey's in the field. Then that squiggly line on ML/AI represents the progression. Since the January 21 survey, you can see the downward trajectory. And we position ML and AI relative to the other big four hot sectors or big three, including, ML/AI is four. Containers, cloud and RPA. These have consistently performed above that magic 40% red dotted line for most of the past two years. Anything above 40%, we think is highly elevated. And we've just included analytics and big data for context and relevant adjacentness, if you will. Now note that green arrow moving toward, you know, the 40% mark on ML/AI. I got a glimpse of the January survey, which is in the field. It's got more than a thousand responses already, and it's trending up for the current survey. So Andy, what do you make of this downward trajectory over the past seven quarters and the presumed uptick in the coming months? >> So one of the things you have to keep in mind is when the pandemic happened, it's about survival mode, right? So when somebody's in a survival mode, what happens, the luxury and the innovations get cut. That's what happens. And this is exactly what happened in the situation. So as you can see in the last seven quarters, which is almost dating back close to pandemic, everybody was trying to keep their operations alive, especially digital operations. How do I keep the lights on? That's the most important thing for them. So while the numbers spent on AI, ML is less overall, I still think the AI ML to spend to sort of like a employee experience or the IT ops, AI ops, ML ops, as we talked about, some of those areas actually went up. There are companies, we talked about it, Atlassian had a lot of platform issues till the amount of money people are spending on that is exorbitant and simply because they are offering the solution that was not available other way. So there are companies out there, you can take AoPS or incident management for that matter, right? A lot of companies have a digital insurance, they don't know how to properly manage it. How do you find an intern solve it immediately? That's all using AI ML and some of those areas actually growing unbelievable, the companies in that area. >> So this is a really good point. If you can you bring up that chart again, what Andy's saying is a lot of the companies in the ETR taxonomy that are doing things with AI might not necessarily show up in a granular fashion. And I think the other point I would make is, these are still highly elevated numbers. If you put on like storage and servers, they would read way, way down the list. And, look in the pandemic, we had to deal with work from home, we had to re-architect the network, we had to worry about security. So those are really good points that you made there. Let's, unpack this a little bit and look at the ML AI sector and the ETR data and specifically at the players and get Andy to comment on this. This chart here shows the same x y dimensions, and it just notes some of the players that are specifically have services and products that people spend money on, that CIOs and IT buyers can comment on. So the table insert shows how the companies are plotted, it's net score, and then the ends in the survey. And Andy, the hyperscalers are dominant, as you can see. You see Databricks there showing strong as a specialist, and then you got to pack a six or seven in there. And then Oracle and IBM, kind of the big whales of yester year are in the mix. And to your point, companies like Salesforce that you mentioned to me offline aren't in that mix, but they do a lot in AI. But what are your takeaways from that data? >> If you could put the slide back on please. I want to make quick comments on a couple of those. So the first one is, it's surprising other hyperscalers, right? As you and I talked about this earlier, AWS is more about logo blocks. We discussed that, right? >> Like what? Like a SageMaker as an example. >> We'll give you all the components what do you need. Whether it's MLOps component or whether it's, CodeWhisperer that we talked about, or a oral platform or data or data, whatever you want. They'll give you the blocks and then you'll build things on top of it, right? But Google took a different way. Matter of fact, if we did those numbers a few years ago, Google would've been number one because they did a lot of work with their acquisition of DeepMind and other things. They're way ahead of the pack when it comes to AI for longest time. Now, I think Microsoft's move of partnering and taking a huge competitor out would open the eyes is unbelievable. You saw that everybody is talking about chat GPI, right? And the open AI tool and ChatGPT rather. Remember as Warren Buffet is saying that, when my laundry lady comes and talk to me about stock market, it's heated up. So that's how it's heated up. Everybody's using ChatGPT. What that means is at the end of the day is they're creating, it's still in beta, keep in mind. It's not fully... >> Can you play with it a little bit? >> I have a little bit. >> I have, but it's good and it's not good. You know what I mean? >> Look, so at the end of the day, you take the massive text of all the available text in the world today, mass them all together. And then you ask a question, it's going to basically search through that and figure it out and answer that back. Yes, it's good. But again, as we discussed, if there's no business use case of what problem you're going to solve. This is building hype. But then eventually they'll figure out, for example, all your chats, online chats, could be aided by your AI chat bots, which is already there, which is not there at that level. This could build help that, right? Or the other thing we talked about is one of the areas where I'm more concerned about is that it is able to produce equal enough original text at the level that humans can produce, for example, ChatGPT or the equal enough, the large language transformer can help you write stories as of Shakespeare wrote it. Pretty close to it. It'll learn from that. So when it comes down to it, talk about creating messages, articles, blogs, especially during political seasons, not necessarily just in US, but anywhere for that matter. If people are able to produce at the emission speed and throw it at the consumers and confuse them, the elections can be won, the governments can be toppled. >> Because to your point about chatbots is chatbots have obviously, reduced the number of bodies that you need to support chat. But they haven't solved the problem of serving consumers. Most of the chat bots are conditioned response, which of the following best describes your problem? >> The current chatbot. >> Yeah. Hey, did we solve your problem? No. Is the answer. So that has some real potential. But if you could bring up that slide again, Ken, I mean you've got the hyperscalers that are dominant. You talked about Google and Microsoft is ubiquitous, they seem to be dominant in every ETR category. But then you have these other specialists. How do those guys compete? And maybe you could even, cite some of the guys that you know, how do they compete with the hyperscalers? What's the key there for like a C3 ai or some of the others that are on there? >> So I've spoken with at least two of the CEOs of the smaller companies that you have on the list. One of the things they're worried about is that if they continue to operate independently without being part of hyperscaler, either the hyperscalers will develop something to compete against them full scale, or they'll become irrelevant. Because at the end of the day, look, cloud is dominant. Not many companies are going to do like AI modeling and training and deployment the whole nine yards by independent by themselves. They're going to depend on one of the clouds, right? So if they're already going to be in the cloud, by taking them out to come to you, it's going to be extremely difficult issue to solve. So all these companies are going and saying, "You know what? We need to be in hyperscalers." For example, you could have looked at DataRobot recently, they made announcements, Google and AWS, and they are all over the place. So you need to go where the customers are. Right? >> All right, before we go on, I want to share some other data from ETR and why people adopt AI and get your feedback. So the data historically shows that feature breadth and technical capabilities were the main decision points for AI adoption, historically. What says to me that it's too much focus on technology. In your view, is that changing? Does it have to change? Will it change? >> Yes. Simple answer is yes. So here's the thing. The data you're speaking from is from previous years. >> Yes >> I can guarantee you, if you look at the latest data that's coming in now, those two will be a secondary and tertiary points. The number one would be about ROI. And how do I achieve? I've spent ton of money on all of my experiments. This is the same thing theme I'm seeing across when talking to everybody who's spending money on AI. I've spent so much money on it. When can I get it live in production? How much, how can I quickly get it? Because you know, the board is breathing down their neck. You already spend this much money. Show me something that's valuable. So the ROI is going to become, take it from me, I'm predicting this for 2023, that's going to become number one. >> Yeah, and if people focus on it, they'll figure it out. Okay. Let's take a look at some of the top players that won, some of the names we just looked at and double click on that and break down their spending profile. So the chart here shows the net score, how net score is calculated. So pay attention to the second set of bars that Databricks, who was pretty prominent on the previous chart. And we've annotated the colors. The lime green is, we're bringing the platform in new. The forest green is, we're going to spend 6% or more relative to last year. And the gray is flat spending. The pinkish is our spending's going to be down on AI and ML, 6% or worse. And the red is churn. So you don't want big red. You subtract the reds from the greens and you get net score, which is shown by those blue dots that you see there. So AWS has the highest net score and very little churn. I mean, single low single digit churn. But notably, you see Databricks and DataRobot are next in line within Microsoft and Google also, they've got very low churn. Andy, what are your thoughts on this data? >> So a couple of things that stands out to me. Most of them are in line with my conversation with customers. Couple of them stood out to me on how bad IBM Watson is doing. >> Yeah, bring that back up if you would. Let's take a look at that. IBM Watson is the far right and the red, that bright red is churning and again, you want low red here. Why do you think that is? >> Well, so look, IBM has been in the forefront of innovating things for many, many years now, right? And over the course of years we talked about this, they moved from a product innovation centric company into more of a services company. And over the years they were making, as at one point, you know that they were making about majority of that money from services. Now things have changed Arvind has taken over, he came from research. So he's doing a great job of trying to reinvent themselves as a company. But it's going to have a long way to catch up. IBM Watson, if you think about it, that played what, jeopardy and chess years ago, like 15 years ago? >> It was jaw dropping when you first saw it. And then they weren't able to commercialize that. >> Yeah. >> And you're making a good point. When Gerstner took over IBM at the time, John Akers wanted to split the company up. He wanted to have a database company, he wanted to have a storage company. Because that's where the industry trend was, Gerstner said no, he came from AMEX, right? He came from American Express. He said, "No, we're going to have a single throat to choke for the customer." They bought PWC for relatively short money. I think it was $15 billion, completely transformed and I would argue saved IBM. But the trade off was, it sort of took them out of product leadership. And so from Gerstner to Palmisano to Remedi, it was really a services led company. And I think Arvind is really bringing it back to a product company with strong consulting. I mean, that's one of the pillars. And so I think that's, they've got a strong story in data and AI. They just got to sort of bring it together and better. Bring that chart up one more time. I want to, the other point is Oracle, Oracle sort of has the dominant lock-in for mission critical database and they're sort of applying AI there. But to your point, they're really not an AI company in the sense that they're taking unstructured data and doing sort of new things. It's really about how to make Oracle better, right? >> Well, you got to remember, Oracle is about database for the structure data. So in yesterday's world, they were dominant database. But you know, if you are to start storing like videos and texts and audio and other things, and then start doing search of vector search and all that, Oracle is not necessarily the database company of choice. And they're strongest thing being apps and building AI into the apps? They are kind of surviving in that area. But again, I wouldn't name them as an AI company, right? But the other thing that that surprised me in that list, what you showed me is yes, AWS is number one. >> Bring that back up if you would, Ken. >> AWS is number one as you, it should be. But what what actually caught me by surprise is how DataRobot is holding, you know? I mean, look at that. The either net new addition and or expansion, DataRobot seem to be doing equally well, even better than Microsoft and Google. That surprises me. >> DataRobot's, and again, this is a function of spending momentum. So remember from the previous chart that Microsoft and Google, much, much larger than DataRobot. DataRobot more niche. But with spending velocity and has always had strong spending velocity, despite some of the recent challenges, organizational challenges. And then you see these other specialists, H2O.ai, Anaconda, dataiku, little bit of red showing there C3.ai. But these again, to stress are the sort of specialists other than obviously the hyperscalers. These are the specialists in AI. All right, so we hit the bigger names in the sector. Now let's take a look at the emerging technology companies. And one of the gems of the ETR dataset is the emerging technology survey. It's called ETS. They used to just do it like twice a year. It's now run four times a year. I just discovered it kind of mid-2022. And it's exclusively focused on private companies that are potential disruptors, they might be M&A candidates and if they've raised enough money, they could be acquirers of companies as well. So Databricks would be an example. They've made a number of investments in companies. SNEAK would be another good example. Companies that are private, but they're buyers, they hope to go IPO at some point in time. So this chart here, shows the emerging companies in the ML AI sector of the ETR dataset. So the dimensions of this are similar, they're net sentiment on the Y axis and mind share on the X axis. Basically, the ETS study measures awareness on the x axis and intent to do something with, evaluate or implement or not, on that vertical axis. So it's like net score on the vertical where negatives are subtracted from the positives. And again, mind share is vendor awareness. That's the horizontal axis. Now that inserted table shows net sentiment and the ends in the survey, which informs the position of the dots. And you'll notice we're plotting TensorFlow as well. We know that's not a company, but it's there for reference as open source tooling is an option for customers. And ETR sometimes like to show that as a reference point. Now we've also drawn a line for Databricks to show how relatively dominant they've become in the past 10 ETS surveys and sort of mind share going back to late 2018. And you can see a dozen or so other emerging tech vendors. So Andy, I want you to share your thoughts on these players, who were the ones to watch, name some names. We'll bring that data back up as you as you comment. >> So Databricks, as you said, remember we talked about how Oracle is not necessarily the database of the choice, you know? So Databricks is kind of trying to solve some of the issue for AI/ML workloads, right? And the problem is also there is no one company that could solve all of the problems. For example, if you look at the names in here, some of them are database names, some of them are platform names, some of them are like MLOps companies like, DataRobot (indistinct) and others. And some of them are like future based companies like, you know, the Techton and stuff. >> So it's a mix of those sub sectors? >> It's a mix of those companies. >> We'll talk to ETR about that. They'd be interested in your input on how to make this more granular and these sub-sectors. You got Hugging Face in here, >> Which is NLP, yeah. >> Okay. So your take, are these companies going to get acquired? Are they going to go IPO? Are they going to merge? >> Well, most of them going to get acquired. My prediction would be most of them will get acquired because look, at the end of the day, hyperscalers need these capabilities, right? So they're going to either create their own, AWS is very good at doing that. They have done a lot of those things. But the other ones, like for particularly Azure, they're going to look at it and saying that, "You know what, it's going to take time for me to build this. Why don't I just go and buy you?" Right? Or or even the smaller players like Oracle or IBM Cloud, this will exist. They might even take a look at them, right? So at the end of the day, a lot of these companies are going to get acquired or merged with others. >> Yeah. All right, let's wrap with some final thoughts. I'm going to make some comments Andy, and then ask you to dig in here. Look, despite the challenge of leveraging AI, you know, Ken, if you could bring up the next chart. We're not repeating, we're not predicting the AI winter of the 1990s. Machine intelligence. It's a superpower that's going to permeate every aspect of the technology industry. AI and data strategies have to be connected. Leveraging first party data is going to increase AI competitiveness and shorten time to value. Andy, I'd love your thoughts on that. I know you've got some thoughts on governance and AI ethics. You know, we talked about ChatGBT, Deepfakes, help us unpack all these trends. >> So there's so much information packed up there, right? The AI and data strategy, that's very, very, very important. If you don't have a proper data, people don't realize that AI is, your AI is the morals that you built on, it's predominantly based on the data what you have. It's not, AI cannot predict something that's going to happen without knowing what it is. It need to be trained, it need to understand what is it you're talking about. So 99% of the time you got to have a good data for you to train. So this where I mentioned to you, the problem is a lot of these companies can't afford to collect the real world data because it takes too long, it's too expensive. So a lot of these companies are trying to do the synthetic data way. It has its own set of issues because you can't use all... >> What's that synthetic data? Explain that. >> Synthetic data is basically not a real world data, but it's a created or simulated data equal and based on real data. It looks, feels, smells, taste like a real data, but it's not exactly real data, right? This is particularly useful in the financial and healthcare industry for world. So you don't have to, at the end of the day, if you have real data about your and my medical history data, if you redact it, you can still reverse this. It's fairly easy, right? >> Yeah, yeah. >> So by creating a synthetic data, there is no correlation between the real data and the synthetic data. >> So that's part of AI ethics and privacy and, okay. >> So the synthetic data, the issue with that is that when you're trying to commingle that with that, you can't create models based on just on synthetic data because synthetic data, as I said is artificial data. So basically you're creating artificial models, so you got to blend in properly that that blend is the problem. And you know how much of real data, how much of synthetic data you could use. You got to use judgment between efficiency cost and the time duration stuff. So that's one-- >> And risk >> And the risk involved with that. And the secondary issues which we talked about is that when you're creating, okay, you take a business use case, okay, you think about investing things, you build the whole thing out and you're trying to put it out into the market. Most companies that I talk to don't have a proper governance in place. They don't have ethics standards in place. They don't worry about the biases in data, they just go on trying to solve a business case >> It's wild west. >> 'Cause that's what they start. It's a wild west! And then at the end of the day when they are close to some legal litigation action or something or something else happens and that's when the Oh Shit! moments happens, right? And then they come in and say, "You know what, how do I fix this?" The governance, security and all of those things, ethics bias, data bias, de-biasing, none of them can be an afterthought. It got to start with the, from the get-go. So you got to start at the beginning saying that, "You know what, I'm going to do all of those AI programs, but before we get into this, we got to set some framework for doing all these things properly." Right? And then the-- >> Yeah. So let's go back to the key points. I want to bring up the cloud again. Because you got to get cloud right. Getting that right matters in AI to the points that you were making earlier. You can't just be out on an island and hyperscalers, they're going to obviously continue to do well. They get more and more data's going into the cloud and they have the native tools. To your point, in the case of AWS, Microsoft's obviously ubiquitous. Google's got great capabilities here. They've got integrated ecosystems partners that are going to continue to strengthen through the decade. What are your thoughts here? >> So a couple of things. One is the last mile ML or last mile AI that nobody's talking about. So that need to be attended to. There are lot of players in the market that coming up, when I talk about last mile, I'm talking about after you're done with the experimentation of the model, how fast and quickly and efficiently can you get it to production? So that's production being-- >> Compressing that time is going to put dollars in your pocket. >> Exactly. Right. >> So once, >> If you got it right. >> If you get it right, of course. So there are, there are a couple of issues with that. Once you figure out that model is working, that's perfect. People don't realize, the moment you decide that moment when the decision is made, it's like a new car. After you purchase the value decreases on a minute basis. Same thing with the models. Once the model is created, you need to be in production right away because it starts losing it value on a seconds minute basis. So issue number one, how fast can I get it over there? So your deployment, you are inferencing efficiently at the edge locations, your optimization, your security, all of this is at issue. But you know what is more important than that in the last mile? You keep the model up, you continue to work on, again, going back to the car analogy, at one point you got to figure out your car is costing more than to operate. So you got to get a new car, right? And that's the same thing with the models as well. If your model has reached a stage, it is actually a potential risk for your operation. To give you an idea, if Uber has a model, the first time when you get a car from going from point A to B cost you $60. If the model decayed the next time I might give you a $40 rate, I would take it definitely. But it's lost for the company. The business risk associated with operating on a bad model, you should realize it immediately, pull the model out, retrain it, redeploy it. That's is key. >> And that's got to be huge in security model recency and security to the extent that you can get real time is big. I mean you, you see Palo Alto, CrowdStrike, a lot of other security companies are injecting AI. Again, they won't show up in the ETR ML/AI taxonomy per se as a pure play. But ServiceNow is another company that you have have mentioned to me, offline. AI is just getting embedded everywhere. >> Yep. >> And then I'm glad you brought up, kind of real-time inferencing 'cause a lot of the modeling, if we can go back to the last point that we're going to make, a lot of the AI today is modeling done in the cloud. The last point we wanted to make here, I'd love to get your thoughts on this, is real-time AI inferencing for instance at the edge is going to become increasingly important for us. It's going to usher in new economics, new types of silicon, particularly arm-based. We've covered that a lot on "Breaking Analysis", new tooling, new companies and that could disrupt the sort of cloud model if new economics emerge. 'Cause cloud obviously very centralized, they're trying to decentralize it. But over the course of this decade we could see some real disruption there. Andy, give us your final thoughts on that. >> Yes and no. I mean at the end of the day, cloud is kind of centralized now, but a lot of this companies including, AWS is kind of trying to decentralize that by putting their own sub-centers and edge locations. >> Local zones, outposts. >> Yeah, exactly. Particularly the outpost concept. And if it can even become like a micro center and stuff, it won't go to the localized level of, I go to a single IOT level. But again, the cloud extends itself to that level. So if there is an opportunity need for it, the hyperscalers will figure out a way to fit that model. So I wouldn't too much worry about that, about deployment and where to have it and what to do with that. But you know, figure out the right business use case, get the right data, get the ethics and governance place and make sure they get it to production and make sure you pull the model out when it's not operating well. >> Excellent advice. Andy, I got to thank you for coming into the studio today, helping us with this "Breaking Analysis" segment. Outstanding collaboration and insights and input in today's episode. Hope we can do more. >> Thank you. Thanks for having me. I appreciate it. >> You're very welcome. All right. I want to thank Alex Marson who's on production and manages the podcast. Ken Schiffman as well. Kristen Martin and Cheryl Knight helped get the word out on social media and our newsletters. And Rob Hoof is our editor-in-chief over at Silicon Angle. He does some great editing for us. Thank you all. Remember all these episodes are available as podcast. Wherever you listen, all you got to do is search "Breaking Analysis" podcast. I publish each week on wikibon.com and silicon angle.com or you can email me at david.vellante@siliconangle.com to get in touch, or DM me at dvellante or comment on our LinkedIn posts. Please check out ETR.AI for the best survey data and the enterprise tech business, Constellation Research. Andy publishes there some awesome information on AI and data. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching everybody and we'll see you next time on "Breaking Analysis". (gentle closing tune plays)

(upbeat music) >> Hello, beautiful cloud community, and welcome back to AWS reInvent. It is day four here in fabulous Las Vegas, Nevada. My voice can feel it, clearly. I'm Savannah Peterson with my co-host Paul Gillin. Paul, how you doing? >> Doing fine, Savannah. >> Are your feet about where my voice is? >> Well, getting little rest here as we have back to back segments. >> Yeah, yeah, we'll keep you off those. Very excited about this next segment. We get to have a chat with one of our very favorite analysts, Keith Townsend. Welcome back to theCUBE. >> Savannah Page. I'm going to use your south names, Savannah Page. Thank you for having me, Paul. Good to see you again. It's been been too long since CubeCon Valencia. >> Valencia. >> Valencia. >> Well at that beautiful lisp, love that. Keith, how's the show been for you so far? >> It has been great. I tweeted it a couple of days ago. Amazon reInvent is back. >> Savannah: Whoo! Love that. >> 50, 60 thousand people, you know? After 40 thousand, I stop countin'. It has been an amazing show. I don't know if it's just the assignment of returning, but easily the best reInvent of the four that I've attended. >> Savannah: Love that. >> Paul: I love that we have you here because, you know, we tend to get anchored to these desks, and we don't really get a sense of what's going on out there. You've been spending the last four days traversing the floor and talking to people. What are you hearing? Are there any mega themes that are emerging? >> Keith: So, a couple of mega themes is... We were in the Allen session with Adam, and Adam bought up the idea of hybrid cloud. At the 2019 show, that would be unheard of. There's only one cloud, and that's the AWS cloud, when you're at the Amazon show. Booths, folks, I was at the VMware booth and there's a hybrid cloud sign session. People are talking about multicloud. Yes, we're at the AWS show, but the reality that most customers' environments are complex. Adam mentioned that it's hybrid today and more than likely to be hybrid in the future in Amazon, and the ecosystem has adjusted to that reality. >> Paul: Now, is that because they want sell more outposts? >> You know, outpost is definitely a part of the story, but it's a tactile realization that outposts alone won't get it. So, you know, from Todd Consulting, to Capgemini, to PWC, to many of the integrations on the show floor... I even saw company that's doing HP-UX in the cloud or on-prem. The reality is these, well, we've deemed these legacy systems aren't going anywhere. AWS announced the mainframe service last year for converting mainframe code into cloud workloads, and it's just not taking on the, I think, the way that the Amazon would like, and that's a reality that is too complex for all of it to run in the cloud. >> Paul: So it sounds like the strategy is to envelop and consume then if you have mainframe conversion services and HP-UX in the cloud, I mean, you're talking about serious legacy stuff there. >> Keith: You're talking about serious legacy stuff. They haven't de-emphasized their relationship with VMware. You know, hybrid is not a place, it is a operating model. So VMware cloud on AWS allows you to do both models concurrently if you have those applications that need layer two. You have these workloads that just don't... SAP just doesn't... Sorry, AWS, SAP in the cloud and EC2 just doesn't make financial sense. It's a reality. It's accepting of that and meeting customers where they're at. >> And all the collaboration, I mean, you've mentioned so many companies in that answer, and I think it's very interesting to see how much we're all going to have to work together to make the cloud its own operating system. Cloud as an OS came up on our last conversation here and I think it's absolutely fascinating. >> Keith: Yeah, cloud is the OS I think is a thing. This idea that I'm going to use the cloud as my base layer of abstraction. I've talked to a really interesting startup... Well actually it's a open source project cross plane of where they're taking that cloud model and now I can put my VMware vsphere, my AWS, GCP, et cetera, behind that and use that operating model to manage my overall infrastructure. So, the maturity of the market has fascinated me over the past year, year and a half. >> It really feels like we're at a new inflection point. I totally agree. I want to talk about something completely different. >> Keith: Okay. >> Because I know that we both did this challenge. So one of the things that's really inspiring quite frankly about being here at AWS reInvent, and I know you all at home don't have an opportunity to walk the floor and get the experience and get as many steps as Paul gets in, but there's a real emphasis on giving back. This community cares about giving back and AWS is doing a variety of different activations to donate to a variety of different charities. And there's a DJ booth. I've been joking. It kind of feels like you're arriving at a rave when you get to reInvent. And right next to that, there is a hydrate and help station with these reusable water bottles. This is actually firm. It's not one of those plastic ones that's going to end up in the recycled bin or the landfill. And every single time that you fill up your water bottle, AWS will donate $3 to help women in Kenya get access to water. One of the things that I found really fascinating about the activation is women in sub-Saharan Africa spend 16 million hours carrying water a day, which is a wild concept to think about, and water is heavy. Keith, my man, I know that you did the activation. They had you carrying two 20 pound jugs of water. >> Keith: For about 15 feet. It's not the... >> (laughs) >> 20 pound jugs of water, 20 gallons, whatever the amount is. It was extremely heavy. I'm a fairly sizeable guy. Six four, six five. >> You're in good shape, yeah. >> Keith: Couple of a hundred pounds. >> Yeah. >> Keith: And I could not imagine spending that many hours simply getting fresh water. We take it for granted. Every time I run the water in the sink, my family gets on me because I get on them when they leave the sink water. It's like my dad's left the light on. If you leave the water on in my house, you are going to hear it from me because, you know, things like this tickle in my mind like, wow, people walk that far. >> Savannah: That's your whole day. >> Just water, and that's probably not even enough water for the day. >> Paul: Yeah. We think of that as being, like, an 18th century phenomenon, but it's very much today in parts of Sub-Saharan Africa. >> I know, and we're so privileged. For me, it was just, we work in technology. Everyone here is pretty blessed, and to do that activation really got my head in the right space to think, wow I'm so lucky. The team here, the fabulous production team, can go refill my water bottle. I mean, so simple. They've also got a fitness activation going on. You can jump on a bike, a treadmill, and if you work out for five minutes, they donate $5 to Fred Hutch up in Seattle. And that was nice. I did a little cross-training in between segments yesterday and I just, I really love seeing that emphasis. None of this matters if we're not taking care of community. >> Yeah, I'm going to go out and google Fred Hutch, and just donate the five bucks. 'Cause I'm not, I'm not. >> (laughs) >> I'll run forever, but I'm not getting on a bike. >> This from a guy who did 100 5Ks in a row last year. >> Yeah. I did 100 5Ks in a row, and I'm not doing five minutes on a bike. That's it. That's crazy, right? >> I mean there is a treadmill And they have the little hands workout thing too if you want. >> About five minutes though. >> Savannah: I know. >> Like five minutes is way longer than what you think it is. >> I mean, it's true. I was up there in a dress in sequence. Hopefully, I didn't scar any anyone on the show floor yesterday. It's still toss up. >> I'm going to take us back to back. >> Take us back Paul. >> Back to what we were talking about. I want to know what you're hearing. So we've had a lot of people on this show, a lot of vendors on the show who have said AWS is our most important cloud partner, which would imply that AWS's lead is solidifying its lead and pulling away from the pack as the number one. Do you hear that as well? Or is that lip service? >> Keith: So I always think about AWS reInvent as the Amazon victory lap. This is where they come and just thumb their noses at all the other cloud providers and just show how far ahead they're are. Werner Vogels, CTO at Amazon's keynotes, so I hadn't watched it yet, but at that keynote, this is where they literally take the victory lap and say that we're going to expose what we did four or five years ago on stage, and what we did four or five years ago is ahead of every cloud provider with maybe the exception of GCP and they're maybe three years behind. So customers are overwhelmingly choosing Amazon for these reasons. Don't get me wrong, Corey Quinn, Gardner folks, really went at Adam yesterday about Amazon had three majors outages in December last year. AWS has way too many services that are disconnected, but from the pure capability, I talked to a born in the cloud data protection company who could repatriate their data protection and storage on-prem private data center, save money. Instead, they double down on Amazon. They're using, they modernize their application and they're reduced their cost by 60 to 70%. >> Massive. >> This is massive. AWS is keeping up with customers no matter where they're at on the spectrum. >> Savannah: I love that you use the term victory lap. We've had a lot of folks from AWS here up on the show this week, and a couple of them have said they live for this. I mean, and it's got to be pretty cool. You've got 70 thousand plus people obsessed with your product and so many different partners doing so many different things from the edge to hospital to the largest companies on earth to the Israeli Ministry of Defense we were just talking about earlier, so everybody needs the cloud. I feel like that's where we're at. >> Keith: Yeah, and the next step, I think the next level opportunity for AWS is to get to that analyst or that citizen developer, being able to enable the end user to use a lambda, use these data services to create new applications, and the meanwhile, there's folks on the show floor filling that gap that enable develop... the piece of owner, the piece of parlor owner, to create a web portal that compares his prices and solutions to other vendors in his area and adjust dynamically. You go into a restaurant now and there is no price menu. There's a QR code that Amazon is powering much of that dynamic relationship between the restaurateur, the customer, and even the menu and availability. It's just a wonderful time. >> I always ask for the print menu. I'm sorry. >> Yeah. You want the printed menu. >> Look down, my phone doesn't work. >> Gimme something I could shine my light on. >> I know you didn't have have a chance to look at Vogel's keynote yet, but I mean you mentioned citizen developer. One of the things they announced this morning was essentially a low code lambda interface. So you can plug, take your lamb dysfunctions and do drag and drop a connection between them. So they are going after that market. >> Keith: So I guess I'll take my victory lap because that was my prediction. That's where Amazon's next... >> Well done, Keith. >> Because Lambda is that thing when you look at what server list was and the name of the concept of being, not having to have to worry about servers in your application development, the logical next step, I won't take too much of a leap. That logical first step is, well, code less code. This is something that Kelsey Hightower has talked about a lot. Low code, no code, the ability to empower people without having these artificial barriers, learning how to code in a different language. This is the time where I can go to Valencia, it's pronounced, where I can go to Valencia and not speak Spanish and just have my phone. Why can't we do, at business value, for people who have amazing ideas and enable those amazing ideas before I have to stick a developer in between them and the system. >> Paul: Low-code market is growing 35% a year. It's not surprising, given the potential that's out there. >> And as a non-technical person, who works in technology, I've been waiting for this moment. So keep predicting this kind of thing, Keith. 'Cause hopefully it'll keep happening. Keith, I'm going to give you the challenge we've been giving all of our guests this week. >> Keith: Okay. >> And I know you're going to absolutely crush this. So we are looking for your 32nd Instagram real, sizzle hot take, biggest takeaway from this year's show. >> So 32nd Instagram, I'll even put it on TikTok. >> Savannah: Heck yeah. >> Hybrid cloud, hybrid infrastructure. This is way bigger than Amazon. Whether we're talking about Amazon, AWS, I mean AWS's solutions, Google Cloud, Azure, OCI, on-prem. Customers want it all. They want a way to manage it all, and they need the skill and tools to enable their not-so-growing work force to do it. That is, that's AWS reInvent 2019 to 2022. >> Absolutely nailed it. Keith Townsend, it is always such a joy to have you here on theCUBE. Thank you for joining us >> Savannah Page. Great to have you. Paul, you too. You're always a great co-host. >> (laughs) We co-hosted for three days. >> We've got a lot of love for each other here. And we have even more love for all of you tuning into our fabulous livestream from AWS reInvent Las Vegas, Nevada, with Paul Gillin. I'm Savannah Peterson. You're watching theCUBE, the leader in high tech coverage. (upbeat music)

(intro upbeat music) >> TheCUBE presents UiPath Forward5, Brought to you by UiPath. >> Welcome to day two of Forward5 UiPath Customer Conference. You're watching theCUBE. My name is Dave Vellante. My co-host is David Nicholson. Yesterday, Dave, we heard about the extension into an enterprise platform. We heard about, from the two CEOs, a new go-to-market strategy. We heard from a lot of customers how they're implementing UiPath generally and automation, specifically, scaling, hyper-automation, and all the buzzwords you hear. Todd Foley is the CDO and CSO of Lydonia Technologies and Devika Saharya is the director of ERP and RPA at MongoDB. Folks, welcome to theCUBE. Thanks for taking time out of your busy day and coming on. >> Thank you Dave. >> Thank you so much. >> So let's start with the roles. So Devika, ERP and RPA. >> Yes. >> It's like peanut butter and jelly, or how do those things relate? What's your, what's your role? >> Absolutely. So I started at Mongo as an ERP manager, and you know, as we were growing, the one thing that came out of, you know, the every year goals for the company, one big goal that came out was how we have to scale. There are so many barriers to scale. How can we become a billion dollar company? What do we need to do? And when we started drilling down into, you know, different areas, we figured it out that people do a lot of stuff manually. It's like comparing sheets, you know, copying data from one place to the other, and so on and so forth. So one thing that we realized was we definitely need some kind of automation. At that time, we didn't know about automation, but we did our own market research and here we are. >> Let's automate. Yeah, right. (Devika laughs) Sounds easy. All right, thank you. Todd, CDO, Chief Data or Chief Dig, and CSO, I'm assuming Chief Data? >> Chief Data. >> And the Chief Information Security Officer. Tell us about Lydonia and also your role. >> Sure, Lydonia, we started just over three years ago. We looked at the RPA market. We saw great opportunity, but we also saw a challenge. We saw that a lot of people had deployed RPA but weren't getting the promised, you know, immediate ROI, rapid deployment that was out there. And when we looked at it, we saw that it really wasn't a technical challenge. Sometimes it was how technology was applied, but there were a lot of things that people were doing in their process and how they were treating RPA, often as if it were traditional technology that slowed them down. So we built our practice, our company, around the idea of being able to help people scale very quickly and drive that faster. And we're finding now with the RPA being pretty ubiquitous, that it's the one thing that's in the greatest demand among our clients. >> Okay, so you're the implementation partner for Mongo, is that right? >> We are. >> Okay, so relatively new. Very new actually, but a specialist. Why'd you choose Lydonia? >> So, that's an interesting question. When we came last year to UiPath Forward, we were looking for, you know, the right kind of people who can, you know, put us on track. We had the technology, we had everything in place, we did the POC, everybody liked it, but we didn't know how to, you know, basically go in that direction. We were missing that direction. And then we, you know, we were doing our homework here, we found, we accidentally stumbled with Lydonia, and I had follow up conversations with Todd, and they were just so tapered. I knew exactly what Todd was explaining me, and we knew we are, we are in safe hands. >> So, where did you start? >> So we, the first thing that we did was a POC for the finance side of business. And right after that POC, we realized that, you know, how much time people were actually investing manually, like things that were done in three to four days was turning into a 30 minute process. And that gave us, you know, the idea that we should start drilling down into different departments and try to find where there are, you know, areas where we can improve. And we did all of that. And then we met with Todd, and Todd explained that how his Reignite process works. So we took Reignite as our first step and, you know, took it from there. We chose one department, we worked with them. We had about 10 processes highlighted, thanks to Todd, he worked with them, and he literally drilled and nailed it down that what we need to do. And as of today, all those 10 are automated. >> Wow. Okay. >> Todd, does this interaction between Lydonia and MongoDB, as a customer, apply equally in the field when you're going out and talking to clients that might be running MongoDB, they might be customers of MongoDB, they may have financial applications that are backended with MongoDB, is there a synergy there that you've been able to gain? >> I think there is. I think there's one thing that's kind of unique about RPA, and that the traditional questions around integration and applicability aren't as important when you have a platform that can work with anything that people can use. I think also, you know, when we look at what we typically do with people, some of the things we see at Mongo are very common use cases you know, across all of our clients. So I, there's definitely the ability for us to take things we've done and have clients get leverage out of them. At the same time, the platform itself is, makes it different than a traditional model where, you know if somebody has worked in a particular area or built an automation for a particular application, there's some kind of utility to do it faster for another client. What we find is that that's not really the case. And that oftentimes we'll compete with people who use different tool sets than UiPath who have that kind of value story around having done it before, we come in and we do it twice as fast as they could. >> So you've, you're a veteran of complex integrations. >> Oh yeah. (Todd laughs) >> I know that from our paths have crossed in the past. So you're saying that in this world of RPA, that this tool set like UiPath as a platform, we've been talking a lot about the difference between being a tool set and being a platform. >> Right. >> That this platform can sort of hover above things without that same layer of complexity, or level of complexity, that you've experienced in the past. Because that speaks to the idea that UiPath, as a platform, is going to work moving forward in a big way. >> Exactly, right. I think we've seen for years and years that regardless of the type of development environment you're using, a developer's value sometimes is based on what reusable libraries they've created, what they have to cut and paste from their old code to be able to do things faster. The challenge with that is it has to be maintained, when things change, they've got to update those libraries. It's a value prop that's very high touch. With UiPath, they've created the ultimate in reusability. The platform, especially since they acquired cloud elements and built all of those API integrations into their platform. The platform maintains the reusability and the libraries in such a way where they're drag and drop from a development standpoint and you don't have to maintain them. It's the ultimate expression of reusability as a platform. >> Yeah, cloud elements, API automation, obviously a key pick by UiPath. Devika, what's the scale of your operation today? Like how many bots and where do you see it going? >> Yes. So we, we started with one bot. Last year we experimented a lot that, you know, we were just trying to make our footprint in the company, trying to understand that, you know, people understand what RPA is, what UiPath is. Initially we got a lot of pushback. We got a pushback from our security team as well, because they could not understand, you know, that what UiPath is and how secure it is. And we had to explain them that how we would host it over AWS, how we will work, how we will not save passwords, et cetera. When we did all of that and they got comfort, we started picking, you know, very small processes around to show, you know, people the capability of RPA and UiPath per se. When we did that, people started just coming with bigger processes, and one specific team that I can think of came that we do, you know, fuzzy logic in Excel, and we do it twice a week, but it takes a lot of time. We automated it, they run it daily, every single day, two times now. And the exponential growth that we saw just with that one automation was mind boggling. I couldn't believe that, you know. We were tracking our insights and we were like, oh my God, what happened? It just blew out of proportion. >> Okay. So then did you need more bots? Are you still running one bot, or? >> Nope. Now at the moment we have nine. >> Okay. >> And we are still looking to grow. >> Okay. So the initial friction, you said there was some, you know, concern, it was primarily security or were there others, people afraid they're going to lose their jobs? Was there any of that? >> There was no risk of losing the job. The major, you know, pushback was, one was from security, the other one was from different system owners because a lot of people were not sure why we want UI access, or why we want API access, and why are we accessing their systems? What type of information we are trying to gather out of their systems. Are we writing into their system? Because a lot of people have issues when we start saying that we will write or override data. So most of the processes that we are working around are either writing, comparing, and reading and comparing, and if it is writing, we take special permission that this is what we are going to do. >> So what did you have to do to get through the security mottle, a AWS SOC 2 report, did you have to show them the UiPath pen test? >> Absolutely. >> Did you have to change any of your processes? What was that sort of punch list like? >> Everything. >> Yeah. >> So we had to start from pen test. We had to start, we had to explain that UiPath is in the process of, you know, acquiring SOC. We also explained that how things are hosted on AWS. We had to, you know, bring our consultants in who explained that how on, on AWS, this will be a very secured way of doing things. And when we did our first process, which was actually for the auditors, which is, you know, interesting. >> Yeah. >> What we did was we did segregation of duties, which I think is very important in every field and every sphere we work in. So for example, the the writeup that we were building for auditors, we made sure that it is approved by a physical or a human, you know, and not everything is done by the bot. The biggest piece of the puzzle was writing, you know, because it was taking a lot of time. People were going into different systems, gathering information, putting it on Excel, and then you know, comparing and submitting it to PWC. >> When you say write, you mean any update to a system of record? >> Correct. >> Required some scrutiny? >> Some scrutiny, yes, yes. >> Okay, initially by a human until there was comfort level and then it's like these bots know what they're doing. >> Correct, correct. >> Okay. And now you're a NetSuite customer, correct? >> Yes. >> That's your ERP? >> That's right. >> Now we were talking about Oracle is going to acquire OCR capabilities. Will that, and we've been talking, Dave and I, a week about, okay well ServiceNow has, you know, RPA, and Salesforce, and SAP, et cetera. How will that affect your thinking about adopting UiPath? >> I don't think it should matter because I think all these systems kind of coexist in a bigger ecosystem, you know, and I also feel that all these systems have their own plus points and minus points. Not one system in, per se, can do everything within a company. So it could be that, for example, NetSuite might be very strong for financials in the space we are in, but not extremely good around sales and marketing. So for that company chose Salesforce. So you know, you have those smaller smaller multiple systems that build into a bigger ecosystem, right. And I think the other piece of the puzzle is that UiPath helps bridge that gap between these systems. You know, it could happen that certain things can get integrated, certain things cannot because of the nature of business, the nature of work that the teams are trying to do. And I think UiPath is leveraging that gap, you know, and putting, you know, those strings together. >> As you scale - >> Mm hmm. >> How will, and Todd I presume you're going to assist in this process, but how will you decide what processes to prioritize, and is that a process driven decision? Is it data led? Both? If so, what kind of data? Can you describe how you guys are going to approach that? >> Yep. Todd, would you like to take that first before I start? >> Sure, yeah. >> Maybe some best practices and then we can maybe get specific to Mongo. >> Absolutely. Our guidance is always that it should be a business decision, right? And it should be data driven, based on a business defined metric around the business case for that particular automation. Our guidance to customers is don't automate it unless you know why you're automating it, and what the value is. We see sometimes there are challenges with people being able to articulate the business case for an automation, and it can almost always be resolved by having that business case be the first step, and qualifying and identifying an automation candidate. >> And how does that apply to Mongo? Do you, where are you thinking about scaling, in your opinion? >> It's interesting because, you know, initially we thought that we will, you know, explore one area in MongoDB. And the other thing that we did was we did road shows. So because we had to create some awareness in the company that we have UiPath there's something called bots. There's something called, you know, automation that we can do, so we created a presentation with small demos inside it and, you know, circulated it within the company. Different departments tried to explain what we can achieve. And based off of that, you know, we came up with a laundry list of all the automations that different departments needed. And out of that, you know, we started doing the business case, the value, you know, trying to come up with complexity, effort. We did a full estimation matrix and based off of that we came, okay, these are the top 20 that we should build first. And as soon as we built those top 20, we saw a skyrocket, you know, growth and - >> And you're looking for hard dollars, right? >> Yes, yes. Absolutely. >> Okay, just to be clear. >> Devika, I think Mongo also is great at taking a data driven approach to looking at their program. Do you want to share how you do that? >> Yes, absolutely. So one thing that we were very sure was we have to talk in terms of numbers because that's the only solid way to see growth. And what we did was, you know, we got insights, we started doing full metrics in terms of dollar saved, hour saved, and we are trying to track how every process is impacting, you know, in the grand scheme of things. Like say for example, for finance, are we shortening the close cycle in any shape or form by doing these two or three automations that we are doing? And I'm happy to report that we have really shortened our close cycle from where we started. >> Your quarter end or month end close. >> Correct, yes. >> Daily? You at the daily close yet, (all laugh) or the "John Chambers"? >> Drive everyone nuts. First I have to say, I could feel the audience sort of smiling as they see, as they hear from MongoDB, disruptor of legacy databases being cautious in their internal approach to change. As everyone else is. >> Exactly, yeah. >> But Todd, just sort of, double clicking on this idea of kind of stove pipes of capabilities in the RPA space. I mean OCR, being added to NetSuite, I'm not sure if that's the greatest example, but the point is Lydonia will work with all of those technologies to synthesize something. Is that correct? Or are you a UiPath only? >> Both. So we exclusively use UiPath with our customers. We don't use other RPA platforms. >> Okay. >> And we don't because, not because we can't, but because we don't believe that anything else is going to be as quick or as effective. Also, it's the only platform that is as broad and comprehensive as it needs to be to deliver outcomes to our customers. We have partnerships with other companies that have gaps where UiPath isn't currently playing, but the number of companies and the number of gaps has shrunk down to almost nothing these days. And we're well placed as UiPath continues to grow their platform to take advantage of that and leverage that to deliver outcomes to customers. >> It was a great story of starting small, being careful. >> Yes. >> And prudent, from a security standpoint, especially as a public company. And then it sounds like there's virtually unlimited opportunity. >> Yes, absolutely, absolutely. >> For you guys. Great story, thank you very much for sharing it. Appreciate it. >> Thank you. >> All right, good luck. All right, thank you for watching. Keep it right there. Dave Nicholson and Dave Vellante will be back from UiPath Forward5 from the Venetian in Las Vegas. Be right back. (upbeat music playing)

>>Hey everyone. Welcome back to the cubes. Continuous coverage of AWS reinvent 2021 live. Yes. Live in Las Vegas, Lisa Martin, with Dave Nicholson. David's great to co-host with you. How you doing >>Fantastic. Great to be here with >>You, Lisa, as always, we're going to have a great conversation. Next to Cuba actually is two lifestyles, two remote studios. We've got over a hundred guests on the program talking about the next decade and cloud innovation and Dave and I are pleased to welcome Scott Carter, the CTO of TSS to the program. Scott. Welcome. >>Thank you. It's really, really great to be here. Really >>This a little bit. Great to have you on the program. Talk to us a little bit about, about TCIs and let's talk about your kind of journey to the cloud and your relationship with AWS. >>Absolutely. Um, you know, TCIs, we've been around as a company for about 40 years. We specialize in, uh, payment products specifically on the issuing side. So card issuing, we've worked with some of the largest financial brands in the world and retailers as well. Uh, and, and a lot of, you know, what I always tell people is if you have a card in your wallet today, uh, you could probably pull it out. And at least one of those cards is something that we manage and service for our customers. And, and we, uh, do everything full lifecycle of those payment products for our customers around the globe >>On behalf of being a cardholder. Thank you. Talk to me a little bit about the AWS partnership here we are at re-invent. >>Yeah, well, we started a very special, uh, partnership with AWS about 18 months ago. We're about 18 months into the journey, uh, and really our goal and our vision is to build out a financial services cloud for all of our clients and our retailers and fintechs. Uh, we're really focused right now on migrating some of our key products to the AWS cloud environment. We built we've used us a variety of AWS technology by some on-premise and in the cloud environment to migrate our processing platforms and all of our customer servicing systems. So we're in the middle of that journey. Uh, we've had a lot of successes so far. AWS is helping us out. Our engineering team is working side by side with the AWS engineering team to produce what we believe is going to be the next generation of payments, especially on the card issuing side, >>Next gen that's, that's important as a consumers, consumer life business life. We have that expectation that we're going to be able to transact whatever we want anytime day or night, >>Absolutely choice is key, uh, virtual physical, no matter where you are, we want to be able to facilitate your payment and make sure you have everything you need to support you through the full card life cycles, the life cycle of your account. >>So you talk about those cards being in our wallets and handbags. I know there's one that's actually smoking. It's so hot from use in my co-hosts handbag, but, >>Uh, we appreciate that >>Talk, talk, talk about this journey from the perspective of someone who, um, I assume like me is not just out of college, right? You've working, you've been working in this business for a while. And so you're going through the transition from the world of what some will refer to as legacy it into the world of cloud. Uh, talk about the challenges there. How do you go after the low hanging fruit versus the high hanging fruit? How do you evaluate something from an ROI perspective? Talk about that. >>Yeah, and I, you know, uh, I get that quite a similar question a lot. I get, you know, people are, are interested in the journey and especially CTOs and CEOs who were starting journeys at their own. I get a chance to talk with a lot of banks and retailers about their individual like modernization and transformation journeys. Um, and you know, the, the basics are true about the journey. And I had somebody tell me years ago that it's, it's, it's psychology, it's not technology. Uh, you've really got to address the people's side of the equation. First, you've got to focus on training and upskilling, make sure that the team comes along on the journey. And then you've gotta be a really good recruiter. You've got to go out and get the talent, the skills you need to build a good foundation. You gotta have the right partners. >>You know, we have partners like PWC and, and, uh, AWS and others that are really helping us with the journey. So that part of it's really, really important. The key is, and I think for us, uh, we really started building our talent pool, uh, probably more than five years ago. And so we were able to bring in some skill sets in dev ops and some skill sets. And, you know, nowadays AI we'd do a lot with ML and AI skill sets. Uh, but we were able to build in a lot of cloud skills and start to build out our development environments first, very, very early on. That's what we did. And we used those development environments for our engineers to cut their teeth and really get comfortable in the cloud. Um, I remember probably about three years ago, we installed our first Kubernetes cluster. Um, and we did it with a small team. >>And then over time we really incented the team by allowing them to get more and more certifications and grow their skills. And we really built up a really large team around just our on-premise cloud first. And then later that helped us with the migration, the journey into the actual public cloud for those same services. Um, and we use that, that same team as there today, we really invest in our people. We think it's important to have a staff that's there. We insource our staff. We really believe in that. Um, that's super important, even though we have partners that we really value, we make sure that we've got a core group of people that are really passionate about the journey and about cloud. And so that >>You mentioned that, that kind of cultural aspect. Yeah. And you mentioned bringing in a team starting years ago with a specific focus. What about the transition of folks who have been it practitioners for maybe decades making that transition? How has, how has that worked out culturally? Have you adopted a policy where you're basically saying, look, if you have experience with this stuff, great, stay with it. Yeah. But we're hiring net new people for the new stuff. Is that the strategy or is it >>Look like I've seen some do that? I personally don't feel that that works because you need some subject matter experts. You need people who really know your products and your company and your solutions and your customers. You really need those people to come along the journey. So what we've done internally is we created, for example, a digital boot camps where our team members could sign up that could come in. We actually construct the boot boot camps on about a six week schedule. Uh, we do two week sprints. So we do three sprints. We, we get them sort of inculcated and agile from the very beginning, we have demos at the end of each sprint. So they're working in an agile way as they're going through their training course. And then of course we, that gives us a chance to identify people who are really high potential to move into some of our cloud teams and our dev ops teams. >>And so that's been really, really beneficial for us. And I would tell you that today we've got people that have a broad range of skills just because of that digital bootcamp. So they may have started their career doing assembler or COBOL or something like that. But now they've tacked on some dev ops and some cloud skills. Uh, we have some that know dynamo DB, and they also know DB too. And we like that. So they have a broad range and those people bring a lot of deep expertise that you're not going to necessarily get with somebody that you're bringing, you know, new, you know, sometimes straight out of college into your company. You've got to grow those people too, but you need the experience, people there to help develop them. >>No, we often talk about people, process and technology, and it's kind of a phrase that's thrown around right. At every event with every vendor. But I really admire the focus on the people, part that you're talking about there and how it's really essential to enable, to enable the people, how you started very strategically starting with the people in the focus and the training on-prem then making the decision that they've, they've got the foundation. Now we need to migrate to the cloud. I'm curious the why AWS, you have a lot of choice course here we are at reinvent. But talk to me about why AWS is that strategic partner. >>We've, we've looked at a number of different cloud platforms for our business. And in fact, uh, global payments is a large company. So TCIs is sort of the issuing part of that. And so we have really great relationships with GCP and other cloud platforms, even some Azure in certain pockets of the company for the issuing side of the business, we went through a thorough evaluation and we felt like the tools, the technology, the platforms, really the, the maturity of that platform. And then the scale, you know, scale matters in our business. And a lot of businesses, it matters, uh, you know, the locations of all of the, uh, uh, availability zones and the regions that was really important to us. We were able to align all of the different AWS regions to where our customer locations are. And that's becoming more and more important as we, you know, we try to be more flexible now about where we, uh, you know, deploy our products around the globe. We want to make sure that whoever we partner with has a point of presence in those markets and that we can do that very, very quickly. We can stand up a new environment when we need to. And so that's what that's been really beneficial that we made that choice with AWS. Um, you know, there's a lot of cloud platforms out out there there's a lot of choice, but we just felt like AWS was the best for us. >>AWS is also very, very, very customer focused, but they probably would say customer obsessed, really that customer flywheel that generates everything that we'd even heard this morning in the keynote culturally, is TCIs similar to AWS in that respect. And can you share a little bit about that? >>Very much. So our reputation as a business is based on the relationships that we built with our customers, and we're known for that in financial services, the TCIs brand and the way that we think about our customers and the way that we partner with them. Um, you know, we, when we taught with the AWS team, we, we try to explain, you know, our history is, you know, w we're kind of the cloud for our customers. So they have a number of products and services. We support those, we manage those products. We, we build on top of, of those products for them. And so we really understand that it's important, not only that you're building a platform, but that platform has got to be able to support all the different things that our customers do every day. And we want that to be broad. We don't want it to be narrow. It's not just focused in one area. If our customers come to us and they say, well, you know, I need to build a data and an analytics platform, or I need some really specific fraud capabilities. We want to be able to support that on demand with our customers. And that's really the journey that we've taken with AWS. AWS is enabling that for us. >>And on-demand is key. I think we've one of the things that's been in short supply during the last 22 months is patients, right? That's >>Right. Absolutely. >>So describe the role of a CTO in that process. What does that look like? Because this isn't, you're not making unilateral decisions here, obviously you're working with the team, but talk about the CTO's perspective as you make decisions about whether AWS is the right fit for a part of your environment or GCP or something else. >>Yeah. I think, you know, um, we, we have, uh, a long history of supporting our own solutions and supporting our systems. And we run some of the world's largest like authorizations platforms, which those are the platforms where when you go into the store and you swipe your card, you, you have to get a response back from us. Like we have to give you that and we have to give it, we have a really specific amount of time. We have to give that back to you. And so we really understand operations and support and how to scale, uh, applications and systems and, and, and how to build really, really reliable solutions. We really understand that part of the business. So whoever we partner with, and, and you asked about my decision to CTO, it was really a group decision. You know, I have to partner with our business team, I have to get their buy-in. Um, they have to support the decision, whatever we do, it's a big investment, we're making the move to the cloud. And so, um, but we have to make sure that we, we cover off the basis. They've gotta be able to at least whatever, whoever our partner is, they've got to be able to at least provide the operational support and the reliability that we're able to give our customers today. So it's just a spreadsheet that's right. Technical qualifier, >>And whoever has the most boxes checked wins. That's right. You're taking into consideration all of those cultural aspects and the goals of the business. That's right. So as a chief technology officer, it's not just about the technology, it's about the business >>That's right, right. So I have a very, very close relationship with the president of our business, Galen, Jowers, um, and, and we built a team and we have on, on the, uh, the actual modernization or transformation team, we have members that represent that from a business perspective there I report into, uh, directly into the business teams. And then we have, uh, people from my, from my side of the, of the company. And we work every single day together and we're driving this forward. So the important part of that is at some point, we, we go to our customers and we show them, Hey, for this particular product or service that we're offering, we're going to be moving that to cloud on this kind of a schedule. And we're there together as a unified front and a unified communication with our customer to explain that journey. And we think that's really important that we do it that way and not do it. You know, like I've seen some companies they'll segment it and sort of technology, or it goes off and they kind of do their own sort of cloud initiative to us that wouldn't work for our business. It's gotta be together and enjoy it with the business. >>You sound like a very much a transformational CTO to me versus a traditional CTO and working at a legacy company that's been around for 40 years. That's impressive that the company is that forward in thinking, first of all, about its people, but also about that business, it partnership. But that has to be in lock step. We talk about that all the time, but it's hard to facilitate that, but you really sound like you guys have done a phenomenal job with some key strategic foresight is not the word. Um, I liked, like Dave was saying, it's not a spreadsheet. It's a checklist of technology requirements that people element is absolutely. >>Absolutely. And you have to, you have to, you have to be all in together on it because you know that as you go on the journey, you're going to have some failure. You're going to experience some challenges. Your customers might not be happy with every decision you make. So you have to be in it together. You're going to have to make that commitment as a company. And that's what we decided early earlier on is that we were going to do that and it's worked out well for us. >>What are some of the things that are going to be happening next for TCIs as we hopefully round out the year 2021 and go into a much better 20, 22, >>We've got a, we've got some really big things on the horizon. One of the things that we're working on right now is, um, we've, since we've been at this for 18 months, we're starting to get to a point where we have certain solutions that are ready to go. We're ready. We're going to be able in 2022 to make some key announcements around some parts of our platform, they're going to be available in AWS as a, as an offering. So we're excited about that. A lot of our customer servicing and some of the things that we do outside of our core processing platform are already cloud native. We run them in a cloud environment on our premise and some of those services, we're going to be able to go ahead and launch into the AWS in 2022. So we're really excited about that. We're right now in the throws of building an onboarding team, that's going to be working with both our customers and with our internal teams to make that shift and start migrating those applications out to the environment. >>So big, big things underway there. We've got a couple of, uh, really key strategic relationships that we've built over the last 12 months or so, um, that are all in, on our cloud journey. And so we're going to be able to announce some of those, uh, pretty soon as some of our customers and prospects, uh, that really want to be on the journey with us. So we're pretty excited about that. And I don't want to spoil any surprises there, so we'll wait and let that come out with the, with the schedule. But yeah, we've got a lot of great things ahead and we're very, very excited for where we're going. >>Awesome, Scott, great stuff. I love how transformational you are, the focus that you guys have on the people, as well as the technologies and the processes. Exciting. Congratulations on your, on your 18 month journey. And we'll have to have you back on so we can hear some of those, those, uh, you know, little, uh, Easter eggs that you just dropped. >>I'd love to, I'd love to be back on. This has been great. All right. >>And how did you know I have a credit card in my wallet running a whole. >>I've been feeling bad about saying that the whole time. He's not going to go well when we're done here, >>Wherever in Vegas, we hope you've enjoyed this. Like for Dave Nicholson, I'm Lisa Martin. You're watching the cube, the global leader in a live chat coverage.

(gentle music) >> Hello everyone, and welcome back to day two of AWS re:Invent 2021, theCUBE's continuous coverage. My name is Dave Vellante, I'm here with my co-host, David Nicholson. We've got two sets. We had two remote sets prior to the show. We're running all kinds of activities and we've got AWS executives, partners, ecosystem technologists, Scott Weber is here as the director and an AWS partner, ambassador from PwC. Scott, good to see you. >> Nice to meet you guys. Thanks for letting me be here. >> Well, so your expertise is around application modernization. It's a hot theme these days. If you're a company with a lot of legacy debt, you've got a big complex application portfolio. I would think, especially with the forced match to digital over the last year and a half, two years. Now is really a time when you're probably too late to really start thinking about rationalizing your portfolio. What are you seeing in this space? >> Definitely, we're seeing the customers that have reached that point. I view modernization as sort of the second wave of cloud that's coming. So you had your first wave, the early adopters that lifted and shifted into the cloud. We still have people looking at getting into the cloud, but for those that went early, now, they're saying, "How do I get more out of the cloud? How do I get closer to cloud native?" And that's what we're starting to see around this modernization move is, I want to start to utilize those higher level services from AWS and the cloud providers. I want to get a better return, I want to stop worrying about running infrastructure and hardware. >> So when you think about, I go back all the way back to Y2K, that was like a boondoggle for IT to spend a bunch of doh and do some cool stuff. And then of course the .com crashed, but today it's different. It's really about the business impact the business outcome that you can drive in transforming your digital business. So how do you as a technology agnostic consultant help a company understand what they should leave alone or sunset? What they should aggressively migrate? What's the process that you use to do that? >> In some ways we go back, we can reuse sort of those 6Rs that maybe got a customer to the cloud, or as they're on that cloud journey, right? And you really want to focus on where can you optimize ROI. And you're going to come across those things that are going to be like, look, maybe it's a vendor COTS solution. There's not a lot we can do there. You're just going to have to continue down that path. Unless we can look to move that to a SaaS service. Maybe the vendor has gone to a SaaS offering. Or we get into looking at they've done development in house, but that development is still monolithic running on virtual machines, either in the data center or in AWS, but it's a critical system to that business. It's maybe it's become fragile. How can we now modernize that? Because that's where there's going to be a great return on investment for that customer, and it's also going to allow business agility for those customers. As we can get them to microservices and Lambda and function as a service, the blast radius for changes become smaller, allows the customer to move faster than what they're doing. So it's the rationalization becomes what's driving the business forward? What's critical to the business? But what's holding them back as well? So that the customers can start to move faster. >> So it's a formula of okay, what's the business value of those applications essentially? You can kind of rank that, but then it's a formula there's a cost equation. That's pretty straightforward to figure out the s is and the 2b but then there's a speed. Like an ongoing time to value from a developer standpoint and then I guess there's risk. Have you got your core jewels? Maybe you don't want to touch those yet. Is that kind of your algorithm? >> It is and on that sort of cost and value piece, that's where we can really see some interesting things happen, where as we get customers away from licensed OSS proprietary databases, that return on investment can be huge. So we've helped customers migrate from running .net applications on top of a typical Microsoft Windows stack and SQL server stack. All the way to taking those workloads, all the way, either to Linux containers or all the way to serverless if we're going to take all the steps to rewrite, you can drive 60, 70, 80% of the cost of operating at that platform out of it, then you start this flywheel effect of reinvesting that money back into the next project to help the customer move forward. >> And it's quick follow up, but I know you want to jump in. >> Yeah, yeah. >> Why wouldn't a customer, that's a Microsoft customer just run that on Azure? Why AWS? >> I mean, that's a good question and that sort of gets into a lot of philosophical, like discussion we talk about for a long time. The fact of the matter is the majority of your Windows workloads still run on top of AWS today. I would argue AWS has some pretty superior things in their underlying architecture, they're nitro architectures and things like that. But I think it's also choice. And, the whole move of .net to Linux, Microsoft started that they put the ability to, you can run SQL server on top of Linux. Well, if I run SQL server on top of Linux, I take out 20% of my costs right there. They put the support in for .net core to be able to run on Linux or on containers, but that's to help the developers move faster, that's to help us get to microservices. So that cloud provider choice, I think is becomes a bigger discussion, but a lot of people are choosing AWS because they're not just doing Microsoft workloads . Again, we could get very deep into like, trade-offs on why one over the other, but customers are choosing AWS for a lot of these words. >> Diversity and better cloud, better infrastructure. >> Yeah, and philosophical is an interesting way to look at it when it becomes a hostage negotiation. I'm not sure there was a lot of philosophy involved when server and SQL 2008 were being end of support life. And people were told, move it to Azure and we'll take care of you. Don't move it to Azure, you're on your own. But something on the subject of ROI. ROI is typically measured over time. How do you rectify and address the sort of CIO dilemma, which is that if ROI is being delivered fantastically in four years, but the average tenure of a CIO is 2.7 years, how do you address that? What is the sweet spot for timeframes that you're seeing for people to actually implement when you consider as was mentioned today, the keynote that somewhere around 15% of IT spend is in cloud today, which leaves 85% of it on premises. So what do we do about that? >> Yeah, that's a great question. So, I think, I like to get small wins. So find a very big pain point for that customer. How can we start to get them some small wins and start that flywheel effect going of like you saved money here, now, can we reinvest and start to show some wins, but we've engaged in projects where we've completely rewritten a whole application stack that was the core service for a business in a year and a half, and we took them from a run rate of somewhere between 40 and $60,000 a month. Had they been running that in AWS, they were running it in a data center today. So that was our estimate to less than $5,000 a month to run that application on a serverless platform inside of AWS. >> So when you talk about modernizing an application environment, that's typically not thought of as low hanging fruit. So does that mean that all the low hanging fruit has been consumed? Are all the net new things that are developed in a cloud native format, have they already been done? Is this the only frontier for opportunity now? >> No, it's not the only frontier. I mean, there's a lot of customers that are still just trying to get into the cloud. >> Lots of applications out there? >> Yeah, and you look at things like mainframe as well. That's I think a coming area where customers are finally starting to say, "Enough with the mainframe, we saw it in the keynote today of a new sort of service offering around helping customers rationalize how to do, to start to do things with the mainframe." So, but sometimes you can get those easy wins. Like we find a scalability issue. And we can inject scalability and pull back costs very rapidly. 'Cause you run in that scenario, there provision for max capacity that may happen 10% of the year. Now they're vastly overpaying. So we can still get some easy wins with slight tweaks to the platform while we help them rationalize those longer built times. I think the other thing we're starting to see is a shift in CIOs that are coming more from a software background too. That aren't from the pure infrastructure background and as we see those software dBase CIO start to come in. They're starting to understand the game that can be had of making the investment in the software and those upgrades to the software. >> And their tenure is elongating 'cause, CIO career is over was the joke. Now you're losing CIO, is cause they're going onto a bigger and better. They getting more options. I mean, they're becoming rockstars again. I want to ask you just as a side about that mainframe compatible runtime that they announced 'cause it sounds like you've got some experience in converting mainframe. >> Yeah. >> 'Cause I've always been a skeptic. We've seen this movie before where people have to freeze code, they've got to freeze code for 18 months. It takes 24 months, but now it's cloud, Adam Selipsky said, we can cut migration time, which is critical here by two-thirds 'cause that's the key. If you can reduce the time of which you have to freeze the code or maybe not even freeze the code. Again, I'm a skeptic, but what are you seeing with practical experience? >> So at PwC, we're seeing a lot of customers, start down this path and the ROI is pretty amazing when once you get in and you really start to dig in of what it can be if to go down this path. And there's a lot of tools out there, there's a gentleman on our team that's a real genius with this and he's helped multiple customers go down this path. There's tools that can start to do code conversion for you. I mean, we all get a little skeptical on those things cause we never know what the machine is going to try to make the code look like, but it's the starting point. But there is more. >> Like a prewash? >> Yeah, (Dave laughs) there's more and more design patterns coming out to help us down those pathways. But it goes back to agility for the business cause a lot of these customers running mainframes today are looking at a six month release cycle if they want to make any changes to their environment. If we can get them into an agile mindset to a microservice, they can get to two weeks or less for release cycles. So it's a big win for the company overall. Yes, there's a risk, but I think you can take, you can try to de-risk it as much as you can, you don't take the core, the absolute core critical piece of that mainframe. You start to pick away around the edges and you get comfortable with what you're doing. >> And going back to the concept of ROI, specifically in the mainframe space, there have been some not so subtle nudges from the marketplace that changed the dynamics associated with staying on your mainframe. Because if I tell you that the tax to stay on your mainframe is going to triple or quadruple over the next several years, that changes the balance. So you have the old guard in the software business who will remain nameless, jacking up the prices because they feel like, you know what, "What are you going to do? What are you going to do other than write me a cheque?" And the answer is, "Well move," right?. >> Yep, it's reached a point like the companies are moving. And what I think companies start to see too is, when we talk about purpose-driven databases, Adam was talking about that in the keynote today too. And we've seen that with customers when we've done builds, what's the right database for this data? And now you can start to get things moving even faster. And you unleash new ways of thinking. And I mean, some of the vendors are doing things like that and the companies aren't happy about it. >> Well, yes, but look, you're talking about Oracle in particular. (group chattering) That's one of them, but Oracle invests in its database and it's two different theories. Adam, today's the right tool for the right job, API and primitives and Oracle takes the kind of Swiss army knife approach. But they do invest if you have hard core mission critical, recovery is everything. There's a risk factor involved there, but if you want to go fast and you're a developer, you're not going to necessarily knock on Oracle's door, you're going to go to get an AWS. But it gets to my question, having done a lot of TCO analysis, it used to be labor, was always two-thirds of the cost. Now with automation, especially in Oracle environments, software license costs are the dominant component and it's maybe less true for SQL server, certainly true for Db2. I remember the early days of the flash, we used to tell customers, install flash. You're going to be able to consolidate, reduce your Oracle licenses when they come up. So that was a preferred strategy, but what are you seeing in terms of the ability? First of all is that a correct premise that software licenses is still a big component or an increasingly large component, and how do you unshackle from that? >> Yeah, so definitely software licensing costs for the OSS and for the databases are huge. I mean, there's numbers out there that like for SQL server enterprise, if you can get somebody off the SQL server enterprise and get them to an open solution like Aurora Postgres or something like that, it's a 90% ROI, and the numbers are similar for Oracle. And I talked to a lot of customers are like, "But we don't know Postgres," but it's not really that different. It's still data modeling. And when you get to these managed services platforms like RDS and Aurora, you free up those DBS to do the higher value things. The ROI of a DBA is not managing memory and desk and babysitting the servers, it's helping the developers build better data models. And those sorts of things that are higher value. So it is a big thing and we're seeing customers saying like, "Help us reduce this licensing cost," and help us be more efficient because the open platforms now, especially in the relational database area, are on par in a lot of ways with the Oracles and the SQL servers. So then you start to say, "Well, what am I gaining by paying and being sort of held hostage to these numbers?" So we definitely see customers making this transition. >> I mean, the point about Postgres is a good one because you're going to get enterprise class recoverability but even EDB would say okay, don't start with your mission critical core, pick around the edges just what he's saying over and over time, you're going to become more cloud native and get to the point, can you get to that point where everything's cloud native, everything is a service, maybe not a 100%, but a large part of your application portfolio can get there, right? >> Yeah, you're going to find those, that goes back to doing that application tiering and evaluation and ROI. So, we have a case study that we did with Constellation Brands, where they really needed a B2B type ordering portal solution. And they looked at sort of the typical vendors in a packaged solution if you will, a cottage type solution. And we proposed doing a full custom solution, soup to nuts and building it natively in AWS. And it was built completely on top of platform services. There was no servers in that environment and we were done. We were using AWS Fargate to run their containers on top of, we were using RDS Postgres, we were using Lambda and in some places we were using DynamoDB for holding inflate orders. And so the whole environment is deployable from one cloud formation template. So it completely changed how we even went through the testing of the thing. 'Cause you ran the same cloud formation template to deploy to a different environment. And you knew you were getting the same exact thing. And so they went from, they no longer had to worry about securing underlying compute, secure the containers, run on top of Fargate, use a platform service for your databases, and it was a beautiful solution for them. >> Yeah, you got to taste of that and your eyes open up and say, "Wow, what's possible?" >> Yeah, its a game changer. >> We heard that from NASDAQ this morning. An amazing story. She said, our first Amazon bill was 20 bucks. I bet it's higher now, but first hits free kind of thing. But the point is when people talk about the AWS bill, et cetera, no question, you should try to optimize that. But at the end of the day, it's about the business value Scott, isn't it? >> Scott: Yeah, it is. >> Hey, thanks so much for coming to theCUBE. It was great perspectives, >> No, thank you guys. I appreciate having you guys on. >> Thank you very much. >> Keep it right there, Dave Nicholson and I will be right back. You're watching theCUBE's coverage of AWS re:Invent 2021. (gentle music)

>>From the Bellagio hotel in Las Vegas. It's the cube covering UI path forward for brought to you by UI path. >>Good morning. Welcome to the cubes coverage of UI path forward for day two. Live from the Bellagio in Las Vegas. I'm Lisa Martin with Dave Velante, Dave. We had a great action packed day yesterday. We're going to have another action packed day today. We've got the CEO coming on. We've got customers coming on, but there's been a lot in the news last 24 hours. Facebook, what are your thoughts? >>Yeah, so wall street journal today, headline Facebook hearing fuels call for rain in on big tech. All right, everybody's going after big tech. Uh, for those of you who missed it, 60 minutes had a, uh, an interview with the whistleblower. Her name is, uh, Francis Haugen. She's very credible, just a little background. I'll give you my take. I mean, she was hired to help set Facebook straight and protect privacy of individuals, of children. And I really feel like, again, she, she didn't come across as, as bitter or antagonistic, but, but I feel as though she feels betrayed, right, I think she was hired to do a job. They lured her in to say, Hey, this is again, just my take to say, Hey, we want your help in earnest to protect the privacy of our users, our citizens, et cetera. And I think she feels betrayed because she's now saying, listen, this is not cool. >>You hired us to do a job. We in earnest, went in and tried to solve this problem. And you guys kind of ignored it and you put profit ahead of safety. And I think that is the fundamental crux of this. Now she made a number of really good points in her hearing yesterday and I'll, and we'll try to summarize, I mean, there's a lot of putting advertising revenue ahead of children's safety and, and, and others. The examples they're using are during the 2020 election, they shut down any sort of negative conversations. They would be really proactive about that, but after the election, they turned it back on and you know, we all know what happened on January 6th. So there's sort of, you know, the senators are trying that night. Um, the second thing is she talked about Facebook as a wall garden, and she made the point yesterday at the congressional hearings that Google actually, you can data scientists, anybody can go download all the data that Google has on you. >>You and I can do that. Right? There's that website that we've gone to and you look at all the data Google has and you kind of freak out. Yeah, you can't do that with Facebook, right? It's all hidden. So it's kind of this big black box. I will say this it's interesting. The calls for breaking up big tech, Bernie Sanders tweeted something out yesterday said that, uh, mark Zuckerberg was worth, I don't know. I think 9 billion in 2007 or eight or nine, whatever it was. And he's worth 122 billion today, which of course is mostly tied up in Facebook stock, but still he's got incredible wealth. And then Bernie went on his red it's time to break up big tech. It's time to get people to pay their fair share, et cetera. I'm intrigued that the senators don't have as much vigilance around other industries, whether it's big pharma, food companies addicting children to sugar and the like, but that doesn't let Facebook. >>No, it doesn't, but, but you ha you bring up a good point. You and I were chatting about this yesterday. What the whistleblower is identifying is scary. It's dangerous. And the vast majority, I think of its users, don't understand it. They're not aware of it. Um, and why is big tech being maybe singled out and use as an example here, when, to your point, you know, the addiction to sugar and other things are, uh, have very serious implications. Why is big tech being singled out here as the poster child for what's going wrong? >>Well, and they're comparing it to big tobacco, which is the last thing you want to be compared to as big tobacco. But the, but the, but the comparison is, is valid in that her claim, the whistleblower's claim was that Facebook had data and research that it knew, it knows it's hurting, you know, you know, young people. And so what did it do? It created, you know, Instagram for kids, uh, or it had 600,000. She had another really interesting comment or maybe one of the senators did. Facebook said, look, we scan our records and you know, kids lie. And we, uh, we kicked 600,000 kids off the network recently who were underaged. And the point was made if you have 600,000 people on your network that are underage, you have to go kill. That's a problem. Right? So now the flip side of this, again, trying to be balanced is Facebook shut down Donald Trump and his nonsense, uh, and basically took him off the platform. >>They kind of thwarted all the hunter Biden stuff, right. So, you know, they did do some, they did. It's not like they didn't take any actions. Uh, and now they're up, you know, in front of the senators getting hammered. But I think the Zuckerberg brings a lot of this on himself because he put out an Instagram he's on his yacht, he's drinking, he's having fun. It's like he doesn't care. And he, you know, who knows, he probably doesn't. She also made the point that he owns an inordinate percentage and controls an inordinate percentage of the stock, I think 52% or 53%. So he can kind of do what he wants. And I guess, you know, coming back to public policy, there's a lot of narrative of, I get the billionaires and I get that, you know, the Mo I'm all for billionaires paying more taxes. >>But if you look at the tax policies that's coming out of the house of representatives, it really doesn't hit the billionaires the way billionaires can. We kind of know the way that they protect their wealth is they don't sell and they take out low interest loans that aren't taxed. And so if you look at the tax policies that are coming out, they're really not going after the billionaires. It's a lot of rhetoric. I like to deal in facts. And so I think, I think there's, there's a lot of disingenuous discourse going on right now at the same time, you know, Facebook, they gotta, they gotta figure it out. They have to really do a better job and become more transparent, or they are going to get broken up. And I think that's a big risk to the, to their franchise and maybe Zuckerberg doesn't care. Maybe he just wants to give it a, give it to the government, say, Hey, are you guys are on? It >>Happens. What do you think would happen with Amazon, Google, apple, some of the other big giants. >>That's a really good question. And I think if you look at the history of the us government, in terms of ant anti monopolistic practices, it spent decade plus going after IBM, you know, at the end of the day and at the same thing with Microsoft at the end of the day, and those are pretty big, you know, high profiles. And then you look at, at T and T the breakup of at T and T if you take IBM, IBM and Microsoft, they were slowed down by the U S government. No question I've in particular had his hands shackled, but it was ultimately their own mistakes that caused their problems. IBM misunderstood. The PC market. It gave its monopoly to Intel and Microsoft, Microsoft for its part. You know, it was hugging windows. They tried to do the windows phone to try to jam windows into everything. >>And then, you know, open source came and, you know, the world woke up and said, oh, there's this internet that's built on Linux. You know, that kind of moderated by at T and T was broken up. And then they were the baby bells, and then they all got absorbed. And now you have, you know, all this big, giant telcos and cable companies. So the history of the U S government in terms of adjudicating monopolistic behavior has not been great at the same time. You know, if companies are breaking the law, they have to be held accountable. I think in the case of Amazon and Google and apple, they, a lot of lawyers and they'll fight it. You look at what China's doing. They just cut right to the chase and they say, don't go to the, they don't litigate. They just say, this is what we're doing. >>Big tech, you can't do a, B and C. We're going to fund a bunch of small startups to go compete. So that's an interesting model. I was talking to John Chambers about this and he said, you know, he was flat out that the Western way is the right way. And I believe in, you know, democracy and so forth. But I think if, to answer your question, I think they'll, they'll slow it down in courts. And I think at some point somebody's going to figure out a way to disrupt these big companies. They always do, you know, >>You're right. They always do >>Right. I mean, you know, the other thing John Chambers points out is that he used to be at 1 28, working for Wang. There is no guarantee that the past is prologue that because you succeeded in the past, you're going to succeed in the future. So, so that's kind of the Facebook break up big tech. I'd like to see a little bit more discussion around, you know, things like food companies and the, like >>You bring up a great point about that, that they're equally harmful in different ways. And yet they're not getting the visibility that a Facebook is getting. And maybe that's because of the number of users that it has worldwide and how many people depend on it for communication, especially in the last 18 months when it was one of the few channels we had to connect and engage >>Well. And, and the whistleblower's point, Facebook puts out this marketing narrative that, Hey, look at all this good we're doing in reality. They're all about the, the, the advertising profits. But you know, I'm not sure what laws they're breaking. They're a public company. They're, they're, they have a responsibility to shareholders. So that's, you know, to be continued. The other big news is, and the headline is banks challenge, apple pay over fees for transactions, right? In 2014, when apple came up with apple pay, all the banks lined up, oh, they had FOMO. They didn't want to miss out on this. So they signed up. Now. They don't like the fact that they have to pay apple fees. They don't like the fact that apple introduced its own credit card. They don't like the fact that they have to pay fees on monthly recurring charges on your, you know, your iTunes. >>And so we talked about this and we talk about it a lot on the cube is that, that in, in, in, in his book, seeing digital David, Michelle, or the author talked about Silicon valley broadly defined. So he's including Seattle, Microsoft, but more so Amazon, et cetera, has a dual disruption agenda. They're not only trying to disrupt horizontally the technology industry, but they're also disrupting industry. We talked about this yesterday, apple and finances. The example here, Amazon, who was a bookseller got into cloud and is in grocery and is doing content. And you're seeing these a large companies, traverse industry value chains, which have historically been very insulated right from that type of competition. And it's all because of digital and data. So it's a very, pretty fascinating trends going on. >>Well, from a financial services perspective, we've been seeing the unbundling of the banks for a while. You know, the big guys with B of A's, those folks are clearly concerned about the smaller, well, I'll say the smaller FinTech disruptors for one, but, but the non FinTech folks, the apples of the world, for example, who aren't in that industry who are now to your point, disrupting horizontally and now going after individual specific industries, ultimately I think as consumers we want, whatever is going to make our lives easier. Um, do you ever, ever, I always kind of scratch my nose when somebody doesn't take apple pay, I'm like, you don't take apple pay so easy. It's so easy to make this easy for me. >>Yeah. Yeah. So it's, it's going to be really interesting to see how this plays out. I, I do think, um, you know, it begs the question when will banks or Willbanks lose control of the payment systems. They seem to be doing that already with, with alternative forms of payment, uh, whether it's PayPal or Stripe or apple pay. And then crypto is, uh, with, with, with decentralized finance is a whole nother topic of disruption and innovation, >>Right? Well, these big legacy institutions, these organizations, and we've spoke with some of them yesterday, we're going to be speaking with some of them today. They need to be able to be agile, to transform. They have to have the right culture in order to do that. That's the big one. They have to be willing. I think an open to partner with the broader ecosystem to unlock more opportunities. If they want to be competitive and retain the trust of the clients that they've had for so long. >>I think every industry has a digital disruption scenario. We used to always use the, don't get Uber prized example Uber's coming on today, right? And, and there isn't an industry, whether it's manufacturing or retail or healthcare or, or government that isn't going to get disrupted by digital. And I think the unique piece of this is it's it's data, data, putting data at the core. That's what the big internet giants have done. That's what we're hearing. All these incumbents try to do is to put data. We heard this from Coca-Cola yesterday, we're putting data at the core of our company and what we're enabling through automation and other activities, uh, digital, you know, a company. And so, you know, can these, can these giants, these hundred plus year old giants compete? I think they can because they don't have to invent AI. They can work with companies like UI path and embed AI into their business and focused on, on what they do best. Now, of course, Google and Amazon and Facebook and Microsoft there may be going to have the best AI in the world. But I think ultimately all these companies are on a giant collision course, but the market is so huge that I think there's a lot of, >>There's a tremendous amount of opportunity. I think one of the things that was exciting about talking to one, the female CIO of Coca-Cola yesterday, a hundred plus old organization, and she came in with a very transformative, very different mindset. So when you see these, I always appreciate when I say legacy institutions like Coca-Cola or Merck who was on yesterday, blue cross blue shield who's on today, embracing change, cultural change going. We can't do things the way we used to do, because there are competitors in that review mirror who are smaller, they're more nimble, they're faster. They're going to be, they're going to take our customers away from us. We have to deliver this exceptional customer and employee experience. And Coca-Cola is a great example of one that really came in with CA brought in a disruptor in order to align digital with the CEO's thoughts and processes and organization. These are >>Highly capable companies. We heard from the head of finance at, at applied materials today. He was also coming on. I was quite, I mean, this is a applied materials is really strong company. They're talking about a 20 plus billion dollar company with $120 billion market cap. They supply semiconductor equipment and they're a critical component of the semiconductor supply chain. And we all know what's going on in semiconductors today with a huge shortage. So they're a really important company, but I was impressed with, uh, their finance leaders vision on how they're transforming the company. And it was not like, you know, 10 years out, these were not like aspirational goals. This is like 20, 19, 20, 22. Right. And, and really taking costs out of the business, driving new innovation. And, and it's, it was it's, it's refreshing to me Lisa, to see CFOs, you know, typically just bottom line finance focused on these industry transformations. Now, of course, at the end of the day, it's all about the bottom line, but they see technology as a way to get there. In fact, he put technology right in the middle of his stack. I want to ask him about that too. I actually want to challenge him a little bit on it because he had that big Hadoop elephant in the middle and this as an elephant in the room. And that picture, >>The strategy though, that applied materials had, it was very well thought out, but it was also to your point designed to create outcomes year upon year upon year. And I was looking at some of the notes. I took that in year one, alone, 274 automations in production. That's a lot, 150,000 in annual work hours automated 124 use cases they tackled in one year. >>So I want to, I want to poke at that a little bit too. And I, and I did yesterday with some guests. I feel like, well, let's see. So, um, I believe it was, uh, I forget what guests it was, but she said we don't put anything forward that doesn't hit the income statement. Do you remember that? Yes, it was Chevron because that was pushing her. I'm like, well, you're not firing people. Right. And we saw from IDC data today, only 13% of organizations are saying, or, or, or the organizations at 13% of the value was from reduction in force. And a lot of that was probably in plan anyway, and they just maybe accelerated it. So they're not getting rid of headcount, but they're counting hours saved. So that says to me, there's gotta be an normally or often CFOs say, well, it's that soft dollars because we're redeploying folks. But she said, no, it hits the income statement. So I don't, I want to push a little bit and see how they connect the dots, because if you're going to save hours, you're going to apply people to new work. And so either they're generating revenue or cutting costs somewhere. So, so there's another layer that I want to appeal to understand how that hits the income state. >>Let's talk about some of that IDC data. They announced a new white paper this morning sponsored by UI path. And I want to get your perspectives on some of the stats that they talked about. They were painting a positive picture, an optimistic picture. You know, we can't talk about automation without talking about the fear of job loss. They've been in a very optimistic picture for the actual gains over a few year period. What are your thoughts about that? Especially when we saw that stat 41% slowed hiring. >>Yeah. So, well, first of all, it's a sponsored study. So, you know, and of course the conferences, so it's going to be, be positive, but I will say this about IDC. IDC is a company I would put, you know, forest they're similar. They do sponsored research and they're credible. They don't, they, they have the answer to their audience, so they can't just out garbage. And so it has to be defensible. So I give them credit there that they won't just take whatever the vendor wants them to write and then write it. I've used to work there. And I, and I know the culture and there's a great deal of pride in being able to defend what you do. And if the answer doesn't come out, right, sorry, this is the answer. You know, you could pay a kill fee or I dunno how they handle it today. >>But, but, so my point is I think, and I know the people who did that study, many of them, and I think they're pretty credible. I, I thought by the way, you, to your 41% point. So the, the stat was 13% are gonna reduce head count, right? And then there were two in the middle and then 41% are gonna reduce or defer hiring in the future. And this to me, ties into the Erik Brynjolfsson and, and, and, uh, and, and McAfee work. Andy McAfee work from MIT who said, look, initially actually made back up. They said, look at machines, have always replaced humans. Historically this was in their book, the second machine age and what they said was, but for the first time in history, machines are replacing humans with cognitive functions. And this is sort of, we've never seen this before. It's okay. That's cool. >>And their, their research suggests that near term, this is going to be a negative economic impact, sorry, negative impact on jobs and salaries. And we've, we've generally seen this, the average salary, uh, up until recently has been flat in the United States for years and somewhere in the mid fifties. But longterm, their research shows that, and this is consistent. I think with IDC that it's going to help hiring, right? There's going to be a boost buddy, a net job creator. And there's a, there's a, there's a chasm you've got across, which is education training and skill skillsets, which Brynjolfsson and McAfee focused on things that humans can do that machines can't. And you have this long list and they revisited every year. Like they used to be robots. Couldn't walk upstairs. Well, you see robots upstairs all the time now, but it's empathy, it's creativity. It's things like that. >>Contact that humans are, are much better at than machines, uh, even, even negotiations. And, and so, so that's, those are skills. I don't know where you get those skills. Do you teach those and, you know, MBA class or, you know, there's these. So their point is there needs to be a new thought process around education, public policy, and the like, and, and look at it. You can't protect the past from the future, right? This is inevitable. And we've seen this in terms of economic activity around the world countries that try to protect, you know, a hundred percent employment and don't let competition, they tend to fall behind competitively. You know, the U S is, is not of that category. It's an open market. So I think this is inevitable. >>So a lot about upskilling yesterday, and the number of we talked with PWC about, for example, about what they're doing and a big focus on upscaling. And that was part of the IDC data that was shared this morning. For example, I'll share a stat. This was a survey of 518 people. 68% of upscaled workers had higher salaries than before. They also shared 57% of upskilled workers had higher roles and their enterprises then before. So some, again, two point it's a sponsored study, so it's going to be positive, but there, there was a lot of discussion of upskilling yesterday and the importance on that education, because to your point, we can't have one without the other. You can't give these people access to these tools and not educate them on how to use it and help them help themselves become more relevant to the organization. Get rid of the mundane tasks and be able to start focusing on more strategic business outcome, impacting processes. >>We talked yesterday about, um, I use the example of, of SAP. You, you couldn't have predicted SAP would have won the ERP wars in the early to mid 1990s, but if you could have figured out who was going to apply ERP to their businesses, you know what, you know, manufacturing companies and these global firms, you could have made a lot of money in the stock market by, by identifying those that were going to do that. And we used to say the same thing about big data, and the reason I'm bringing all this up is, you know, the conversations with PWC, Deloitte and others. This is a huge automation, a huge services opportunity. Now, I think the difference between this and the big data era, which is really driven by Hadoop is it was big data was so complicated and you had a lack of data scientists. >>So you had to hire these services firms to come in and fill those gaps. I think this is an enormous services opportunity with automation, but it's not because the software is hard to get to work. It's all around the organizational processes, rethinking those as people process technology, it's about the people in the process, whereas Hadoop and the big data era, it was all about the tech and they would celebrate, Hey, this stuff works great. There are very few companies really made it through that knothole to dominate as we've seen with the big internet giants. So you're seeing all these big services companies playing in this market because as I often say, they like to eat at the trough. I know it's kind of a pejorative, but it's true. So it's huge, huge market, but I'm more optimistic about the outcomes for a broader audience with automation than I was with, you know, big data slash Hadoop, because I think the software as much, as much more adoptable, easier to use, and you've got the cloud and it's just a whole different ball game. >>That's certainly what we heard yesterday from Chevron about the ease of use and that you should be able to see results and returns very quickly. And that's something too that UI path talks about. And a lot of their marketing materials, they have a 96, 90 7% retention rate. They've done a great job building their existing customers land and expand as we talked about yesterday, a great use case for that, but they've done so by making things easy, but hearing that articulated through the voice of their customers, fantastic validation. >>So, you know, the cube is like a little, it's like a interesting tip of the spirits, like a probe. And I will tell you when I, when we first started doing the cube and the early part of the last decade, there were three companies that stood out. It was Splunk service now and Tableau. And the reason they stood out is because they were able to get customers to talk about how great they were. And the light bulb went off for us. We were like, wow, these are three companies to watch. You know, I would tell all my wall street friends, Hey, watch these companies. Yeah. And now you see, you know, with Frank Slootman at snowflake, the war, the cat's out of the bag, everybody knows it's there. And they're expecting, you know, great things. The stock is so priced to perfection. You could argue, it's overpriced. >>The reason I'm bringing this up is in terms of customer loyalty and affinity and customer love. You're getting it here. Absolutely this ecosystem. And the reason I bring that up is because there's a lot of questions in the, in the event last night, it was walking around. I saw a couple of wall street guys who came up to me and said, Hey, I read your stuff. It was good. Let's, let's chat. And there's a lot of skepticism on, on wall street right now about this company. Right? And to me, that's, that's good news for you. Investors who want to do some research, because the words may be not out. You know, they, they, they gotta prove themselves here. And to me, the proof is in the customer and the lifetime value of that customer. So, you know, again, we don't give stock advice. We, we kind of give fundamental observations, but this stock, I think it's trading just about 50. >>Now. I don't think it's going to go to 30, unless the market just tanks. It could have some, you know, if that happens, okay, everything will go down. But I actually think, even though this is a richly priced stock, I think the future of this company is very bright. Obviously, if they continue to execute and we're going to hear from the CEO, right? People don't know Daniel, Denise, right? They're like, who is this guy? You know, he started this company and he's from Eastern Europe. And we know he's never have run a public company before, so they're not diving all in, you know? And so that to me is something that really pay attention to, >>And we can unpack that with him later today. And we've got some great customers on the program. You mentioned Uber's here. Spotify is here, applied materials. I feel like I'm announcing something on Saturday night. Live Uber's here. Spotify is here. All right, Dave, looking forward to a great action packed today. We're going to dig more into this and let's get going. Shall we let's do it. All right. For David Dante, I'm Lisa Martin. This is the cube live in Las Vegas. At the Bellagio. We are coming to you presenting UI path forward for come back right away. Our first guest comes up in just a second.

>> From the Bellagio Hotel in Las Vegas, it's theCUBE, covering UiPath FORWARD IV, brought to you by UiPath. >> Welcome back to theCUBE, live at the Bellagio in Las Vegas, Lisa Martin, with Dave Vellante, we are with UiPath at FORWARD IV. The next topic of conversation is going to be a good one. And that's because it's automation for good. I've got two guests here joining Dave and me. James Droskoski, strategic account exec at UiPath joins us, and Brian Klochkoff, head of automation at Dentsu. Guys, welcome to the program. >> Yeah, thank you. >> Thanks for having us. >> Yeah. Happy to be here. >> We're going to, we're going to dig into automation for good, which is going to be a really feel good conversation. We're going to get into what you're doing. But Brian, I wanted you to give the audience an overview of Dentsu as an organization. Who are you? What do you guys do? >> Sure. So Dentsu is a large network of advertising agencies. We're about 45,000 people large, $10 billion plus in revenue, going across about 125 markets. So we're a large enterprise advertising media, creative CXM type business. We're really focused on helping to elevate our clients' value when it comes to the value proposition around marketing, advertising, and media. >> So you think about that as a, as a, as a, a business that maybe, you know, it's hard to understand where automation might fit in. On the other hand, it's like a lot of moving parts, a lot of arms and legs. >> Brian: Mm-hmm. So how are you applying automation to the business? >> Sure. So when we first started doing proof of concepts level approaches, we approached things in a traditional, Hey, let's go look at the shared services groups. Why are we having invoice processing delays? Things like that. And we started being a bit more prescriptive and proactive about how we were applying the limited POC budget we had to go after these problems. And we started doing some root cause analysis to understand the interaction between the back office functions and the mid-office functions. And what we uncovered was that we could actually be really good custodians of budget and enable people at the same time by solving for problems at a root cause analysis level. So what I mean by that is maybe an invoice is coming down the pipe, and it's not getting processed because it's missing critical information that could be easily added six processes upstream. So what really helped elevate the conversation that we're having around automation for good and be a catalyst for we're going to talk about a bit later is we just started connecting people from the mid-office to the back office, helping them understand, Hey, if we actually follow a process properly, put the right controls in place with RPA to generate critical data elements on those invoices, Shaler in the back office doesn't have to work the weekends because there's not a pipeline back load of invoices for him to process. So we actually connected those mid-office people with the back office people, and it really drove that human connection to drive the change management within our automation journey. And that's kind of been the crux of what we've wanted to do over the past four years, finding ways to elevate our people's potential by integrating automation and AI into their actual day-to-day work. >> Hmm. So tech for good is a theme that you hear a lot and as a, as a media company, that, that, that kind of, we're not gotcha media, you know, we more want to tell the story of tech athletes, and I think we've done a pretty good job of that over the past decade, but so it goes to tech's under fire constantly, especially big tech. We hear the Facebook hearings today and so forth, but so automation kind of early days, oh, you're going to take away my job. I think generally speaking with the fatigue of Zoom and the perpetual workday, people begin to understand that, Hey, maybe automation is a good thing. But automation for good, what, what is that, James? >> Yeah, well, it's, it's not doing technology for the sake of technology. You know? At the end of the day, when we implement solutions with our customers like Dentsu, it's about, what's the impact, what's the change, what's the benefit? And what's unique about Dentsu is because they've grown through acquisition and there are lots of different companies come together, you have to focus on the people first because there is no one process or one system that we can look and just automate that system or process. So automation for good is about focusing on the people, and how do we take the solutions and the programs and the technologies we have and make an impact so that somebody's day is better. Their, their, their job is better. The process they're doing is easier and they can focus on more of the things that make them different. You know? Specifically as we'll uncover in the conversation, you know, we looked at a program that Dentsu is doing around working with different types of people, as far as people with autism, and what was the impact we could do there? And that's uncovered a journey that we've been together for the last two years around seeing how we can make an impact with those types of folks who might not get the same types of opportunities as everybody else. >> Brian, talk about the, the catalyst for that program at Dentsu a couple years ago. >> Sure. So it goes back to that foundational layer of elevating people's potential. So the testimonial that we had from our own employees around applying automation in meaningful ways to progress their day-to-day came from an employee in the mid-office who said, I didn't go $160,000 in student debt to copy paste stuff from Excel into this proprietary platform that we use for media. And that really resonated with us, as leaders in this space, and with our executive leadership, because there was a gap between what our peoples' skills were and what they were actually doing. They wanted to do Mad Men type stuff. They want it to be the Don Drapers and the Peggy Olsons of our industry. And they were losing that opportunity because we weren't tapping into the skills that they had to drive human centric solutions for our clients. So taking that concept, we looked at the partnerships that we have with our outsourcing providers and Autonomy Works, which we're going to doing a session later tomorrow with the CEO, Dave Friedman, we're going to spend a lot of time talking about how the unique skill sets of that company and those people can actually elevate them to do more tech enabled work, but also enabling our own team to focus on building solutions with the skills that we have by allowing them to use the skills that they have to do the machine learning training of models and things like that, which they really excel at from a detail oriented perspective. And that's not only a feel good story, but it's, it's great for our business because the resources on my immediate team are building product, they're building solutions, and we can rely on an excellent partner in them to help us with the maintenance overhead that we're creating through those solutions. And eventually through automation cloud, driving better outcomes through positive, negative reinforcement within machine learning. >> And there are specific examples with individuals with autism. Correct? >> Correct. That's right. >> Yeah. >> Add some color to that. What is that all about? >> Yeah. Let me tell you a little story. So when, when they first brought the conversation to me, I was terrified because I, the type of work that they were outsourcing was very repetitive rule-based. And I'm like, this is perfect for automate. This is exactly what we automate. I was terrified that the program we were going to work on together was going to eliminate the program. And so I was, you know, cautiously, you know, approached it. >> How ironic. >> Yeah. I was like, Hey, that sounds like a great idea. And I hung up. I was like, oh, how are we going to, how am I going to figure out this one? But through the conversation, and we just started, you know, brainstorming and putting our heads together. What was interesting is because of the way that automations work, as far as being very structured and repetitive, it lends itself well to workers with autism. It's exactly the way they think. And what we actually found after kind of coming up with the collaborative ideas, hey, wait a second. We were already doing these kind of botathon hackathon type programs with the Dentsu employees, teaching them the skills, how to build automations for themselves. What if we kind of modified it and adjusted it to cater to these types of individuals who learn differently, and we have to approach it differently. And we went through the program, we adjusted everything. And what was incredible to see was they thrived with the ability to learn how to work this way. They built things that made them more productive, that created more capacity. They could do more with less now, work with more customers, do more work for, for their, for their customers because they had this almost assistant that was kind of like them. And it was, it was just so rewarding. You know, we talk about, again, what's automation for good all about? It's about that personal reward. >> Brian: Yeah. >> I mean, for me, you know, we didn't sell any more licenses or it wasn't about the commercial transaction. It was about, you know, catering to the segment of the workforce that, first of all, it was very educate, enlightening to me to see how many folks are out there that are unemployed. And I got to meet these first 15 individuals that couldn't have been more amazing and more smart and more diligent and hardworking. And the numbers are something in the lines of between 50% and 90% unemployed because they just don't get the same opportunities as people without autism. It's kind of the world's set up for us. So to know that we could do this kind of program together to go have an impact in this community, was the reward in and of itself. And, you know, we've since been working together on how we continue to expand that, how do we, you know, take that forward and, and bring that everywhere. Cause that's, the end of the day, I think beyond, you know, revenue, this is the stuff that really matters, especially in an organization at Dentsu that this is important. >> Yeah. And I think building on the missed opportunity piece around 50% to 90% being unemployed, that's a missed opportunity for business as well. So those skills are so niche and they're so necessary for us to thrive within an environment that's moving as rapidly as we are. Because we just can't keep pace with the change of feature sets that are being released coupled with maintaining existing solutions that we've built. So it's in cross enabling people to really complement each other's unique skills and strengths based off of strong, true partnership. So it really became a beautiful three-way partnership between Dentsu, Autonomy Works and UiPath that we continue to evolve as UiPath makes additional releases with emerging tech that we're officially hearing about right now. So we have a ton of different ideas of how we can bring that into the fold. And what resonates with us the most is hearing different perspectives on how to apply that coming from that working group. So just a different way of thinking about things and the diversity of thought really resonates with, Hey, are we actually applying this thing the right way? Should we be thinking about this differently? Because you get a lot of yes people, you know, when we come and talk to people about how to apply this technology. And when you have somebody with a different perspective, it's able to help us figure out what our long-term strategy is actually going to look like, by taking advantage of the resources and partnerships that we already have in place. >> In terms of that strategic vision, how do you think this three-way partnership that you mentioned is going to influence that percentage of those, these individuals who are unemployed? What are you, any predictions on how much you can bring that down with automation? >> I think that depends on Dave's staffing plan. But, but the goal is to grow, right? So I mean this, this is a, a startup out of Chicago that has, you know, a healthy amount of staff. But finding ways to apply those skills in new ways with technology that's emerging, the horizon is your, is your end point. Right? And I think with the advent of low-code no-code machine learning coming into this type of a platform, it's, it's only opportunistic. There's only, there's only things ahead of us to do that. We just have to make sure that we train people properly and give them that opportunity because they're going to run with it with the right leadership and those skills. >> Yeah. What's exciting also is, is, you know, what started as an idea and a conversation that's now turned into a pilot program and a little bit of expansion of the stuff we're working on together, we've taken some of the excitement and spread it beyond that now. So we've got partners like ENY and PWC and Revature that are saying, and Special Eastern and Automatic, who helped in the initial program saying, how can we help? What can we do? How can we broaden this? And how can we go out to the larger community and make a bigger impact? So, you know, I think it's exciting. We know, we can see how fast RPA and these types of technologies are causing change. And we've got to make sure that people don't get left behind. Especially, you know, someone as this important part of a segment of a workforce. If we can equip them with these skills to be relevant to their current employers or future employers, I think it's, it's critical. You know, another like moment for me during this process was I took for granted, you know, what working actually means, right? It creates independence for us, right? So you get a job, you get paid and generate income. You have the independence now to go live on your own, provide for yourself. A lot of these individuals, I learned, are still living with their parents because they can't get employment. They don't have that independence that we take for granted. So I think, again, that's the essence of what automation for good is all about, is, is being able to go make an impact like that, to that community. And it's, you know, we talk about cultures and brands and you know, it's also great to work with an organization like Dentsu cause they get it, right? Their product is ideas. It's human capital is their, their main ingredient of what they generate value for their customers. And so be able to take that and help people is just, I think what it's all about. >> You're lucky both to be in a business that the incentives are aligned. >> Yeah. >> You're not in businesses that are designed to appropriate data and push ads in front of our face. >> Yeah. >> In a lot of big companies, it's almost like, okay, we got to do this. I don't mean to overstate this, but we have to do this because we're big and we're rich. >> Yeah. >> And so, and if we don't, we're going to get attacked. >> Yeah. Okay. And it's sort of more like a check, check box and to put somebody in charge of it. >> Yep. >> You know, oftentimes a woman or a person of color. And I shouldn't be negative on that. >> Yeah. >> That's fine. That's good to do. But it just seems like there's a nice alignment with automation. AI could be similar because I mean, AI could be used for really bad. Automation. Okay, it maybe takes, the perception is it takes jobs away, but it's a really nice alignment that you can point at a lot of different initiatives. >> Yeah. >> So I think that's really a fortunate dynamic. >> And that's, you know, that's what defines a partnership, right? It's that alignment of long-term interests that, you know, you make the investments now and the sacrifices now to drive that. It's not just commercial. It's not just transactional. >> Dave: Yeah. >> I mean, we were talking about the opportunities for these types of people and for us as a customer and for UiPath. It's it exists within that AI conversation that you were just talking about >> Dave: Yeah. >> Because from a technical perspective, you want to mitigate as much algorithmic bias within your training models. That's what these people are doing. It's helping to train models much more rapidly and effectively and objectively than we could have done otherwise. And that's, having that as part of our extended partnership within our network is going to accelerate the type of work that we want to do within the releases that we're seeing coming out of this conference. Because we don't have to worry about, oh, well, we've got to focus on tax forms and training the models to notice a signature. Because Autonomy Works has us covered there. They're enabling us to do more. We're enabling them to do a little more. And that's, that's the beauty of this intersection between the partners. >> Brian, I presume you talk with prospective customers of UiPath. And I presume also that you probably looked at some of their competitors. If you think about what differentiates this fast moving company, they talked this morning about the cadence of releases. Woo. Very fast. >> Brian: Yeah, it's a lot. >> Why UiPath for Dentsu? >> UiPath has been a tremendous partner for us since about 2017. And we've been able to move on that journey with UiPath. We've been able to help understand the products roadmaps and move at a similar pace as each other. So we're really lucky in that we have the flexibility as an advertising and media company that we're not beholden to internal audits, external audits, and really defined regulatory bodies. So we made a decision, I don't know what, six, seven months ago to collapse six UiPath on-prem instances and migrate to cloud with the sponsorship of our global CTO and our America CTO, just because it was the right thing to do. And because it would enable this type of partnership with external providers. So being able to move at that similar pace from a release cycle, but also from a feature adoption perspective, it's, it just makes the most sense for us. And we have that liberty to go to go do those things as we need to. >> Yeah. So the move to the cloud, you get, you're able to take advantage much faster. >> Yeah. >> Because what did we hear this morning? You release every six months. >> James: Yep. >> Yes. Which is typical for an on-prem. >> James: Yeah. >> And then, but you got to prepare for that. >> James: Yeah. >> I don't know how many N minus ones you support, but it's not infinite. >> James: Yeah. >> You got to move people along, so people have to prep. Whereas now in the cloud, there's the feature. Boom. >> Yeah. >> So being invested in automation for good topic, it's not, it's about automation for good across people in general, within internally to us and externally to us. For our clients, for our employees, and for our partners. The automation cloud enables that to happen much more seamlessly because we don't have the technical debt in place that requires people to VPN into our network and go through the bureaucracy of security, legal, and privacy. Which we've already done by the way, but those conversations bureaucratically still need to happen. With automation cloud, we're able to spin up Autonomy Works employees in real-time and give them the right set of access to go pursue the use cases that they want to, and that we need them to. So that, that technical debt release that we've experienced through the automation cloud is what's enabling us to do this type of good work. >> That makes sense. A bit more, less friction, obviously greater scale. >> Yeah. >> Easier to experiment. >> Yeah. >> Fail fast. >> We went from 12 separate programs to one program in a matter of a couple of months. >> It was wild. >> Yeah. >> And I imagine you're only really scratching the surface here with what you're doing with automation, that really, the horizon is the limit, as you said. Guys, thank you for joining us, talking about automation for good, what you're doing at Dentsu RPA with autistic adults. There's probably so many other great use cases that will come from this. Guys, we appreciate your time. >> Yeah. >> Yeah, thanks for having us. >> Yeah, thank you. >> Thanks, you guys. >> Awesome. >> For Dave Vellante, I'm Lisa Martin coming to you from Vegas UiPath FORWARD IV. (upbeat music plays)