>> (Announcer) From the Bellagio hotel in Las Vegas. It's theCube covering UiPath FORWARD IV, brought to you by UiPath. >> Good afternoon. Welcome back to theCube's live coverage of UiPath FORWARD IV. Lisa Martin here with Dave Vellante. We're on day two of our coverage. We've been talking a lot about automation, all of the opportunities that it's uncovering across industries. We're now going to be talking about a big company undergoing its own automation-led digital transformation. Joining us next, Mariesa Coughanour, head of Automation Advisory Services at Cognizant. Mariesa, welcome to the program. >> Thank you for having me. I'm excited to be here today. >> So let's talk. So Cognizant is a part, both a partner and a customer of UiPath. >> Yes. >> We're going to talk about you in the customer realm today. Cognizant is undergoing its own automation-led digital transformation. Let's talk about that. Talk to me about some of the business outcomes that are, that you're expecting, how it's going to transform the employee experience, the customer experience. >> (Mariesa) Sure, absolutely. We actually started working with automation ourselves back in 2018, where we just put in a CoE, we said we want to drive it into our business operations. But about a year ago, we said, let's go further. I really wanted to play with all of our employees. We wanted to empower them. We talk about citizen development, of robot for every person. And we know that that's really the future. That's where we're going. We're digitally transforming our organizations. And so what we did is we sat down and we worked really closely with UiPath on how do we do this? What kind of training do we need? We're going to need some process, some governance in there. And so we put that in place and, you know, we said, let's get this going this year. So we went out, we did, our first Hackathon, went really well. It was Bring Your Own Bots. So BYOB, so, fun themes. And we got some good savings. We actually drove over 10,000, close to 20,000 hours back into the organization. And we said after that, let's go a bit bigger though. And we did what's called Game of Bots. So obviously we know where that came from, right? And we said, we're going to go a little bit longer and we want to go bigger. So we went and had 2,500 people participate over eight weeks. We built over a thousand bots. And guess what? We drove over 200,000 hours back into the organization in just eight weeks. So super big success story. People loved it. Our teams were excited. We recognized over 200 people out of that with team awards, who submitted the most ideas. And even our top leadership said, let's do a presentation. So the guys and gals who had the top, biggest impact automations got to meet with our top senior leaders and present out to them. It's been awesome. And now we're starting to move that force. We're scaling bigger. We're actually going pretty big in Cognizant. We have some big goals right now. >> That's a gob of hours. Game of Bots, get it? GOB. >> (laughs) >> Come on, with me. >> It is a gob of hours. >> How do you measure the hours? Is it a back of napkin kind of thing? We ask people, Hey, how much, how what, how do you actually measure it? >> No, we actually track it. We could see how many hours people were doing a certain tasks and things that they do every day, whether they're running reports, submitting claims for a customer. And so we're able to see that that time is actually going down. We're faster. We get better quality. People were also able to get hours back in their day so they could do more value added work in the organization. So we actually do track it. And we're able to really measure those tangible outcomes for the teams. >> Sounds like you guys have been moving pretty quickly on this. >> We are. >> So the appetite at Cognizant was there, the culture was there to embrace it. Those are probably, I imagine, two big facilitators of being able to move at the speed and the scale, >> Yeah >> that, with what you're doing. >> Culture was there. We're really digitally savvy. I would say we're digital at heart in Cognizant. We are, we're really a tech company and we really focus on how to be at the forefront of all things when it comes to technology. But we said, we also want to transform how we work. So starting to shift the conversation from, you know, do you want to automate, to why not? How do we actually start talking about, you know, I have this to do list, but you know what, actually, we can improve if we did some of this other stuff instead. So let's free up that time, but use automation there and we can actually grow things. We can add more value. We do all that stuff on your to-do list that I think everybody has and they want to get to, but you get caught up in your day-to-day job all the time. So we're actually getting people to be more excited about and have a real voice. And I actually think that's important. Is that, it's not just about giving people the tool, it's about shifting our culture to really embrace digital, embrace this technology, because we're trying to transform how we all work. And we want to lead by example. >> So we talk about BPO. Business Process Optimization, right? It was kind of the buzz word of the '90s and early 2000s. A lot of times it meant putting in SAP. (chuckles) >> (Mariesa) (laughs) Yeah. >> So that's evolved. And there's some companies that would say, "Hey, we specialize in that," technology companies, obviously, >> (Mariesa) Yep. >> you know, SI's as well. How do you think about the difference between end-to-end enterprise automation and, and sort of traditional BPO? >> I think it has to come together a bit, is one thing. So when you do the BPO, or you do shared services, or you outsource some of the work. We actually put into those contracts, because we do a lot of that for our customers. And we put in automation. The step we took further was we actually started to empower people to actually build the automations themselves, which meant we actually had to work with customers too. So they knew we were doing this. We wanted to make sure they understood, they were comfortable. We put any controls in place that they also needed, to make sure that, you know, we didn't impact any of their services. We want to make it better. We want them to feel nothing but bigger, better results in outcomes. And then as you think about the enterprise side, we have to compliment, because a lot of those processes do feed back into how you run a business. And so we focus on how do you bring both of those stories together so that you're driving synergies across the board. And actually some good lessons learned along the way because some of this stuff becomes reusable. You have best practices you could share across the board. And we want to make sure that we are connecting the dots from the shared services BPO work, back into the enterprise because really a process is end to end, an organization. And we want to help people think that way and also get the results that way too. >> Is that end to end automation, at enterprise automation, more tech heavy, or, or maybe it's tech light in a way, whereas BPO is maybe a lot more, sort of, lean thinking, a lot more chalkboard. Are we deep into the, so I, sometimes, you're saying they have to come together. >> They do yeah. >> But from, from where I guess is, is what I'm trying to better understand. >> So I would think about it this way. When you think about a process, right, from when you even placed an order, the whole way through when you fulfill it for a customer. There's work that we, we do outsource all the time, right? So maybe it's the, the PO process, some of the order transactions from the payment, but you also have the pieces is actually touching the customer, too. You have the pieces that are fulfilling the order. So we say end to end, that is really thinking about that beginning, from a conversation with the customer, the whole way to when we're delivering. And I do think there's a lot of technology. That is something I think everyone gravitates to because there is a lot. Especially if you're going to go end to end, you have to be able to take in documents. You have automation. You're not going to know all the rules, no matter how many times you ask, you're going to need machine learning to be able to help figure it out and get smarter as what, as you go along the way. But as you're putting this into place, what's important is: as you're thinking about, kind of, transforming that business so that they're feeling the results the whole way through, because if you just focus on one, you might create a bottleneck, right? You might've got super fast, but the guy who's going to get the work from you, they're going to feel like, oh my goodness, there's all this work on my plate. So we really want to make sure that we create that seamless experience for everyone across the board, as we put it in. >> And how does UiPath, help facilitate that? >> Across the board, I mean, we were sitting down, we were laying out our program. 'Cause we're actually trying to get to 60,000 strong. So we have 7,000 trained today. We're going to get to 60,000. That's our plan. So we're working very closely with UiPath on what does that training that you need to have in place? What's that model? How do we get people comfortable? Because one thing you'll find is not everyone's in the same spot. Some are going to jump in, dive right in, give me the tool. I want to build. I love this. Others might need a little bit more confidence boost. They might need more handholding. And I think that's really important. And it's probably the one thing I would add too, as you do talk a lot about the technologies, we put it in, but it's the people at the end of the day, it's how you help them adopt, feel comfortable with this technology and really embrace it. That's really going to be the difference on whether, how fast you get down that line for transformation. >> Is it a classic bell curve? You got your 10% early adopters, you got a big fat middle, and then you've got some laggards who come along. >> It kind of is. And I think what's important is that middle is all up in how you do it because 10% are always going to love it. You're always going to have a few people, they're a little extra nervous maybe. But in the middle, if you really think about it, and you're able to put in that culture, you're able to put in your leadership is engaged. You're putting us in gamification, make it fun. That's what we found is, if we got people really having fun up front with it, it gives people a reason to be a part of it. And also, why don't we let people partner up? We can give them the technology, but if someone's not as comfortable, let us do teams. Let's meet people where they're at and then move them along this journey. And let's try to accelerate the best we can. >> How did you gamify it? Crypto. No. (chuckles) >> (laughs) >> (laughs) No, no crypto. But I will say we have some really cool prizes and people were super excited to get to do the presentations because they got to show their, their bots live, their creations, to the team. And I think that was important. Not everyone always is able to capture all the results, but we wanted to actually talk about like, what were the ideas, share it across the board. Cause it also generated ideas. because what you'll find is, when you hear something like, you know what, that's kind of what I do. Wonder if I could do some automation too. At least submit an idea, and then, maybe they're moving down the line, they're getting their hands on the technology. And I think that's how we all push the needle forward and move this along faster. >> One of the most important things about automation is letting people be able to move away from the mundane, the repetitive tasks, that they probably don't enjoy. And being able to focus more on their core competencies or more strategic initiatives that really make them more relevant to themselves and to their company. And it sounds like you guys have achieved that pretty quickly and, and you have an aggressive plan >> (chuckles) We do. >> to go from 7,000 to 60,000. >> Yes. And that's really the power of automation, if you think about it. We all have things in our job we don't like to do. I don't know about you guys, but there's things that I'm like, oh man, like, can we please automate this? Expense reports, for example. All about automated expense reports. (laughs) But it's really about freeing people up. Think about it. These people went to school, they often have degrees and things, and they do get caught in a lot of the manual things, downloading reports, consolidating data, you know, submitting spreadsheets and forms. Imagine if we're able to make that easier for people, we give them what they need to do their job. So that all that stuff you would like to do, that you know would improve things. You know would make the company better. The culture better. Heck, maybe it's a new product that people know would be really awesome to go build, but everyone feels like they're so busy. They don't have the time to do it. I mean, that's one of the big values of automation. Is this value creation conversation that you get to have with people. And you get to start asking 'why not' a little bit more. >> You've mentioned a couple of times the IDC presentation this morning. And we were talking about earlier, and the pie chart of, of, of value benefits was cost savings, which was very large, new revenue, which was very large. And then I think 15% was quality improvements. And that, I think that's an underappreciated slice of the pie. Somebody, I think years ago, of the UiPath FORWARD said to me, I can very inexpensively apply Six Sigma to business process. >> (Mariesa) Yeah. >> And I could never afford to do that before RPA. And, and so I wonder if you could talk to the quality impacts that you're seeing. >> Absolutely. I actually spent a lot of time in Lean Six Sigma in my early career days. And one of the things about it too, is when you're doing automation, we actually asked that question upfront, can we just simplify, can we just stop doing this? Because you don't want to automate a bad process either. So you want to ask some of those questions. >> (Dave) Yeah. >> But you're spot on. There's a ton of quality benefits that you get from automation. And one of the things I've actually seen is if you focus on some of the quality upfront, process gets better. Get better impact, as when you get faster. If you have better quality, and get faster, you also get your cost out targets. And I, that really matters because quality also, beyond being able to drive the cost out, it also helps a lot with the experience that people face. Customers are frustrated if they have poor quality, something doesn't work the way it's supposed to, a site's not working the way it should. And also even employees, they go, how many times, if you try to do something and you try to follow a process and something's hung up or who knows what happened, right. It's frustrating. So if you're able to improve the quality in the process, not only do you get the cost savings, but you get these, it's softer tan, there's still tangible experiences that get better and actually motivates people to want to do more. >> And those motivated people are probably dealing with customers much, much better. >> Yes, yeah. >> I mean, it's, I always think the employee experience is so, is, is a critical component. >> It is. >> But the customer experience. So how has the customer experience improved at Cognizant as a result of building in automation and enabling all these people? >> Yeah, they're loving the results because we're giving them back efficiencies in their process immediately by putting this automation in. These are quick impacts they're feeling and we're able to do more for them as well. So we're actually having conversations now on how do we drive more efficiencies for you and also, you know, how can we do more? Is there more volume of work? Is there more we could be doing to add value back to your organization? And that's what you want to talk about with customers is we're able to give you this value. And by the way, we actually did X for you now as well, because we knew you needed it. And we have the capacity to do this for you. So it's a really positive conversation, but we did have to upfront talk to them about it, to make sure that we, everyone was on board. They're comfortable. And we're continuing to have those conversations because you know, sometimes you're in a regulated business and we did put a little extra control in. Absolutely okay. But we want to be able to drive these efficiencies back for them. So they feel it in their own operations internally too. And it hits their bottom line and oftentimes helps their employees too, because we interact with them. So those downstream benefits and sometimes even upstream get some nice returns there as well. >> We've heard from, well, we're going to have Daniel on soon. He's the CEO. We've of course heard from CFOs. We've, that's kind of one of the main springs of RPA in the early days. We've heard a lot more CIOs at this event and we have a CTO coming on later. Are these C suite executives totally aligned in their objectives? Do they have they have different agendas? What are you seeing in terms of serving the C suite? >> Yeah. They're all going to have a little bit different agendas, right? Cause that's, their roles have different objectives, but they all align back to the strategy, obviously, for their company. But they're going to have portions of it that they're trying to drive and deliver. What we do see is that there's still some merging that needs to happen between the operations, the more business focused side and the more technical side. But we do, we're starting to see that convergence happen. Because what happens is, is that, you have these technologists, who really are going to have to help move you forward. We're, you know, we're applying AI, ML. Very technical technologies, and we want to make sure we do it right, that we put the right governance in. And we think about the security that we have to have in place for this too. And but we also have the business outcomes and coming together is where you really see the results. If you look at all of those that have reached true maturity, it's where you see these agendas aligning a bit more because you also have to shift the culture too. And it's a collaboration point. You need to be able to have the tech savvy folks. It helps bring them along this journey, but you also have to have the business depth as because you're looking at a process and you're going really deep into it to apply the technology. So it's when people partner is when we really see the results become more exponential. >> So digital transformation, you know, we hear that term a lot. And automation-led digital transformation. >> Yep. >> I hear a lot of data led digital transformations are those parallel tracks, or they can talk a lot about convergence. >> Yeah. >> Are they? I mean, they're not competing. They're obviously very much related. How do you see the data agenda and the automation agenda coming together. >> They have to. Because you really need good quality data to be able to enable your automation at the end of the day. And, but they actually play nicely together. You can actually use automation to help go back and improve your master data management too, which is the core of your information because that's actually where a lot of the struggle sometimes comes, is in the quality of the data that everyone has to work with. So you see the data agenda working on, "How do I clean this? How do I get more insightful, predictful information?" And then from an automation standpoint, how do I then use that to go take action? So all we see is you bring it together, to be able to identify where do you need to get in the process? How do I get the right information? So the automation also is proven data behind it, that we drove the outcomes, because that's where you take it to the bank at the end of the day. Is that you see it in the data itself. But I think one of the things I've seen with automation that helps drive the digital transformation conversation is, the business and IT teams are coming together and having a joint conversation now. People are excited. They're understanding it. I think that's why people jumped on with RPA so quickly, was because they're like, I get this, this is rule-based, this is my business process. I just tell it what to do. I'll take that. I want to do that. And so people got excited about that. And then they said, let's do more. How do I make it more intelligent? How do I help it do things in my process that it's harder for me to explain because there's just so much information here. There's so many nuances. Well, we have the technology can help make it more intelligent, smarter, and learn, so that we're able to drive that back into the business itself to transform. >> You mentioned Master Data Management is, is the data agenda as it relates to automation, primarily reporting, is it moving? Is it transcending reporting into the building of data products, for example, data services that can be monetized either within Cognizant or in your customer base? >> So it's really evolving. I would say some start with reports. That's easy. That's where we'll start, but I'll just kind of give you maybe a little example. So we have a customer and we work with them. So they have customers where they need to, when they call in, the sales folks and the contact centers, they have to upsell. So they work with a lot of different restaurants and different, maybe, bars and, you know, different companies that have different type of like beverages and things like that. So we worked with them to show, how are they performing today with all their sales reps? And then we started to use some automation to be able to get them more helpful information the moment the customer's calling in. And we also did some semantic analysis on a voice, how people were, how were they sounding? How was their tone? Were they happy? Were they upset? Were they sad during the call? And we fed that information back to those teams, back to those managers, and went back even to their training programs. What they actually saw was a ton of top line growth. They saw all of their metrics starting to get better, and they also start to get more predictive on ways that they can use more data to drive the support for those teams and their customers. Like for example, if you know holidays are coming up or a certain time of year with weather, we're able to actually put that type of information in and helps those sales reps better serve their customers. >> Last question, some of the announcements that came out yesterday and some of the news today about UiPath, what excites you about the technology and how it's going to continue to enable you to, to foster this new culture that you've shifted? >> I think, so one thing about UiPath that we've always loved to be able to partner with them as we're still customer centric. And you see that in every announcement that they're doing, and also they're focused on this true process transformation, intelligent end to end thinking, because I think a lot of times when we've had conversations most get stuck in kind of point solutions. And that's just because people are trying to solve today's problems. But with where UiPath is moving and where we want to move to, is how do we help you to really transform how people work? We know automation is a part of our future. We know it's going to be how we work in the future. And we love about UiPath is to really think about how do we integrate it? How do we make those connections? So we can drive the bigger results, we can make it easier for people to adopt and really embrace it because we need to bring the people along this journey and we need to be able to actually impact our processes too, so we can transform them. So I think that's one thing that's been really exciting is just watching them in general. Involved with the announcements the last couple of days, we really see them continue to push that needle. >> Excellent. Well, Mariesa, thanks for joining us. Talking to us about the automation-led digital transformation at Cognizant. Good luck raising your trained individuals from 7K to 60K. It sounds like the momentum is there. The culture's there. We can't wait to hear what happens next! >> Awesome. Thanks again for having me today. >> Our pleasure. >> Good to see you. >> Thank you. >> For Dave Vellante, I'm Lisa Martin live in Las Vegas at the Bellagio. UiPath FORWARD IV is the event we're covering. We'll be right back with our next guest. >> (bubbly outro 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 Las Vegas. Live the cube. Yes, it's live in Las Vegas at the Bellagio. Lisa Martin, with Dave Alante, we are covering UI path forward for very excited to be here, talking with customers, UI path, employees, partners, lots of great conversations going on about automation and the acceleration that we're seeing, especially in the last 18 months. We've got two guests here with me today to talk about emerging technologies, specifically continuous process discovery. Please welcome Paula Katikia VP of product management at UI path and Layla Deleage CIO and digital officer at Coca Cola. Ladies, welcome to >>The program. Thank you. It's great to be here. So let's >>Talk about public. Let's start with you. Continuous process discovery. Define that for us. What does that mean? >>So process discovery has been, um, a concept that's been around for awhile, right? It's enterprises have a bunch of processes that are deployed and people are following them. Um, the concept of discovery has existed. What we're trying to do with continuous process discovery is enable you to identify the processes, figure out how to optimize them and then automate them once they're automated, we want to monitor them and then keep doing that cycle over and over again, using technology rather than having fill in, having people fill in paperwork and then having those processes go out of, um, out of, um, status, like right away, because they're just becoming stale with continuous process discovery. They don't become stale. You're getting that real time feedback loop and you're getting the processes to work and to end continuously. >>So I wonder if I could follow up on that because I remember when you guys made the acquisition of process gold. And so as somebody who's heavily involved in product management, how did you go about, I mean, it's been, sounds like it's seamless, but it never is. Right. But how did you go about integrating and making it appear as though it's just kind of part of the platform? >>I mean, there's a lot goes into that right. Process gold was a great technology to begin with. So it wasn't a huge stretch for us to take it and integrate it and make it part of the platform. Um, typically when we acquire companies, we look for product market fit. We look for a technology fit. We look for people fit and we had that with process gold. The other thing to add there is a process discovery, um, specifically with Parsis gold and automation go hand in hand, you can't having one without the other is kind of leaving half of your solution on the table and just focusing on understanding and not focusing on implementation. And so it was very easy to take that technology and make it part of the hyper automation platform. >>Well, the reason why I asked that question is because it sort of coincides with a customer's journey where you go from sort of a individual department. And then now you're saying, I always say pave the cow path. And I kind of take a process that I know I'll just implement that even might not be the best I'm going to repeat and takes you to a new realm. And so this is, to me, this is all about how incumbent companies, a hundred plus year old companies can actually be digital disruptors as opposed to being disrupted themselves. Right? A lot of smart people running these big companies. So last time we talked, you were relatively new inside of a year. So how's the journey going. And, and how does it tie in to some of the advancements that UI path has made? Yeah, >>Absolutely. So the journey is going great. I like to work to use accelerate. So I'm here to accelerate and transform and why we have to do it is so that we don't become obsolete and we continue to be relevant for our customers, for our employees. They're important and for our community. So the are doing a lot of finished running a lot of initiatives. When you look at being relevant for the customer, that means we have to transform the way we operate and our business models. We have to generate new revenue streams now that are enabled and based on data and technology, while you do that, you have to create efficiency internally. You cannot create great experiences with customers and you work with very monolithic and very old school, traditional processes or based off working and systems. So you have to make sure that you adapt and change and transform the way you work internally to meet the customer's needs and demand and generate these new business models. >>So our starting position was automation. We have to automate at an extreme speed, but we also wanted to go really far without automation, not just fast and hit with task automation and just automate these traditional 50, 60 year old processes, but have Doobie identify what else is there? There's a wealth of opportunity when you look at an end to end process. So that's where process mining as Polak described, comes into play. And actually we started affiliating with process mining during process gold. So your question around how the integration went, we actually went through that. I think the UI pads, one key value that they have, and they should never use is listening to the customer. So the got to get her with iPads. And we said, there's more to what we can do with automation. And we implemented process mining for one end to end process, amazing results, just one country, one end to end process, amazing results. But it's because of the partnership. We know what we need to achieve, but we have to do, and they know how to help us to get the technology up and running or adapt to technology and improve the technology. So that's where we are achieving outcomes. We are generating new business model, new revenue stream, automating internally re-skilling and up-skilling our people, which is extremely important that comes along with automation that redesign exciters sorry, but that redesign a work is >>Very important in the CEO's role is very important in that as well. I wanted to talk though about something that you just said with respect to the listening piece that you have is so good at this morning in the keynote. Mary said too, you know, all that, which was standing room only, which was amazing to see, um, in this day and age, but that they wanted to hear from customers. What are we doing? Right? What are we not doing that you want to see more of? What do you want to see less of? Talk to me about the direction and advice that you, as the CIO of Coca-Cola is able to provide to flock and the team about where you I've had this going, right. It's really on a very fast cadence. >>Absolutely. So as Coca-Cola TJ, we started the journey with two iPad, three years of work. Exactly. I was on the job and the second big technology decision I made was the iPad. And since then it was fear consistently think. But during our cab meeting, Daniel said something, he said, I'm not welcoming the request. He said, we welcome. He said, no, no, sorry. I am not welcoming. I'm requesting you to give us insight. And I think that's very critical. That's what we want to hear. At the end of the day, we are technologists. We are total leaders, but the are better taught leaders with our technology partners. So we want technology partners to show us the way sometimes. And with low code, no code type of approaches. And the evolution of the technology that UI path is, has been running since the past three years is helping us remove so many barriers. >>When it comes to people, they are listening to us in terms of the roadmap and what should be implemented and what should be prioritized VR, providing with them, our roadmap, our vision on where we want to go in automation and hugged battle. We want to integrate with other ecosystem and environments that we have. They are listening to us in terms of, for the existing products, what can be improved, what can work better? And we don't need a cab actually for you iPad to listen to us. We work hand in hand with two iPad team continuously be coil, you know, eight sometimes. So, and that's what we want them to continue to do. They are great technologists, as long as they continue to listen to us, they're going to be greater technology. >>Yeah. And I'll share my perspective on this, this, this, you know, these partnerships actually make us build better products, right? We get to, this is how we stay ahead of the curve by listening to our customers, because they're the ones who are doing the implementations. They understand how our product works. We can design it, we can test it. But that's the extent to which we can go once they implement it is when we know what's working, what's not working. And how do we take that feedback and make better products. So it's a two-way street. We love hearing from them constantly. >>You have to decode what the customer is saying sometimes, right? Like Steve jobs said, yeah, if you just ask the customer what they want, you'll never build, you know, something that's game changing the world changing. And so, so you have to talk to Layla, you get the input from COVID, Coca-Cola maybe many and then other customers to figure out, okay, how can I apply this? So that actually can scale and meet the needs of many customers. Not just so, because otherwise you end up being, you know, a custom development shop, which ironically is what you guys were 20 years ago. Right? So it's kind of some art involved in the science of listening. Isn't it? >>There is definitely, I mean, most of our job as product managers is to design the product, right? It's very much art and the feedback that we get from Layla and others, it really just helps us focus on a vision. But, you know, keeping up with new technology trends, figuring out how to figuring out how to, um, bring AI into our product vision and looking beyond what we're being told and asked for and looking forward at what the next trends are going to be in technology is what helps us continue to innovate. So it's both, it's the balance of what we're hearing, but also technologies. And what's possible with what's available >>Question for you. You said three years ago, you guys brought in UI path, right after you joined the company as it's CIO, why U I path, clearly you looked at some of the other folks, you mentioned that company that they acquired, but what in your mind differentiates what they're able to deliver on the partnership side and the technology side? >>Yeah. Very important question. We have a definition for a technology partner for us, the technology partner needs to meet criteria of innovating. So how much do you invest in innovation? And Daniel says, I don't even know the number, right? So because we want them to be on the forefront. Sometimes they have to pull us and sometimes we have to pull them. The second one is very important for a company to be successful in automation or in any advanced technology, you have to build intellectual property within your enterprise. And we did not want to art source technology. We wanted to insource technology and we asked you, I pad, if they would be reeling to co-innovate, co-develop collaborate with us. They were the only ones who allowed us to build the intellectual property within my enterprise, because that's the way I'm going to innovate. And that's the way I'm going to help product leaders like Pollock to create better products. Right? So, and the third one is just building expertise. Low-code no-code the technology company needs to, you know, wait where they remove some of the barriers for me to find the skills or develop talent, how easy it is to find the talent and skills to develop this technology. Right. And what, what does the technology company do to develop skills? So these are a few criteria that we have, and then when the company takes all of those, they are in, >>I'm interested in, um, to kind of shift the conversation. If I may, in your, your role, it's not uncommon to see a CIO and a chief digital officer together, but it's quite uncommon at a, at a large firm like Coca-Cola. And, and I'm wondering, is that how the company, cause your group sees information in digital? Is that how the company's organized? You know, that you plug into somebody who has that to a role. Can you talk about, >>Yeah, absolutely. So cocoli too. Jake is within the Coca-Cola system. We are one of the leading butlers within the Coca-Cola system. The reason I merged the two roles is to be successful in the digital era. When you have the digital and it separated. If it goes a little slower, you can not be successful in digital and you cannot be successful in generating new revenue streams or new business models. So you have to orchestrate that evolution and transformation of it and the rest of the business together. And that's why I merged the two roles. We are unique as Coca-Cola >>Merged them. You say you merged those roles, like, did you come at it from the, where you digital first and then CIO first >>Digital first. Okay. Great point. I built from scratch and started with the digital strategy. And then we went into defining what roles, what skills do we need? And then we redefined, what are the improvements we need on the it side? But it was all digital product based >>Because I think, uh, I think it would be much harder for a CIO, let alone a woman CIO, no offense, but I don't think there's any offense there, but oh, she's trying to do a land grab. I could see that happening, but the digital officer title, because that's the hot title and it's the visionary. Right. And it's a lot of times it's undefined. Yeah. So that's that and that, and that that's the structure of the organization. So you roll up into it. >>Uh, so yeah, because I came into the ex-con role. I had the privilege to kind of shape it from scratch. >>Exactly. And >>Like Shankar was talking about hidden brain and all the change this morning, it was a change in terms of how are we going to approach digital? It was a change in terms of all the people who are part of the company and people who have been in technology or it before right now, the expectations are very different. You have to be product organization, you have to be outcome centric. You have to generate the revenue streams. So it's very different from the world of it. I think any it or any technology leader can do this, if they are willing to transform themselves first and then their organization, and then they can transform the rest of the company, >>Chief digital officer data is a big part of your role. You're not the chief data officer, >>The organization, that's >>Part of your, okay, so the CDL reports into, okay, and that individual sure is responsible for governance and compliance. >>Well look, the data management, data governance, the foundation, and all the database solutions, I think >>You got it right. I think this idea of creating stovepipes, it just it's, it's not as productive and it's harder to make decisions that are aligned with the organization's goals, >>Boulder. So we're going to disrupt further. Our goal now is to create platforms and then democratize the platforms. So our operating partners can learn the new skills and they can develop their own use cases on the platforms. And that way they'll go much, further and much faster in terms of the generational new revenue, streams, changing, operating models, data and technology. I call it the new operating system of any business and everybody must learn >>Well. And that's what I want to ask you about, because if you think about, uh, uh, a company and incumbent, like Coca-Cola your processes over the years have in your data, maybe they were organized around the bottlers or the distribution channel, et cetera. And that might not be the best process. So you have to take a look at that and then use process mining to say, actually, what is the best process, reinvent yourself? Okay. >>Absolutely VRD and re-engineering and reinventing in a lot of places. Process mining helped us in short order to cash cycle. Everybody, every company has ordered to cash process. We took an order to cash process, which we recently standardized, by the way we thought we did. And every process mining told us that very few times you go through the happy path. Most of the times you go out of the happy path. So gave us a lot of tangible outcomes where we improve the cycle time. And it's an interesting process because you touch the customer it's impacts your delivery and your commitments to the customer. And it makes life easier for the employees. When you improve the process, this is only one piece VR also transforming the way we are interacting with our customers using digital means and digital channel. But one thing is very valuable with us while we do all of this staying hybrid is very important. Like with everything else, they do that human touch and personal relationship with our customers and consumers is invaluable. So we going to keep that doesn't matter how digital we go or how much technology we implement. They're going to keep the customer and consumer connect the most valuable asset that we have. >>Absolutely. It is. I'll go ahead. >>I was going to say, this is the one thing that, that we think about when we're designing our products, right? It's how can process my mining help you optimize your workflows, such that you can spend more time with the customer such that you can spend more time and get back to them faster. >>Yeah, that's critical. They, I always say the employee experience is inextricably linked to the customer experience. And so what you just talked about, you talked about so much stuff that I'd love to unpack. We probably don't have time, but coming in as with a transformation mindset, one being, you mentioned, you know, leaders need to be willing to embrace that. Obviously you were, but as a CIO, >>Working with UI path, you're really helping to redefine work. And also that customer experience, to an extent, how's your iPod helped facilitate that. So because they are listening and they are willing to partner with, and I think the most importantly, they're going to be part of our outcomes. They care about our outcomes. And going back to your question, how do we select a technology partner? That was one of the critical items. Outcomes are very critical. If there's no outcome, there's no point in it are not doing technology for the sake of doing it. We are, yes. We are all excited with what technology can bring and removing barriers very important, which is a huge, another huge topic. But if you don't generate an outcome it's meaningless and you AIPAC is willing to understand the outcome we are generating. So it's less of a commercial discussion, more of a technology and outcome conversation. >>So whether it's an customer outcome or an employee outcome or a cash outcome, financial outcome, I think that's why we have been successful. And they have been on the journey with you, iPad process mining. I think they are one of the very few clients, right? Customers of UI path who are using it. And because we are very progressive organization, you AIPAC is listening to our feedback and implementing back to your earlier question, you have so many customers who do you listen, right? So when you are progressive and when you really know what you are doing, you're also pulling your iPad, a big technology company into a direction that is more meaningful. So they listen to us in terms of what to improve with process mining. And that's why we were able to achieve the outcomes. And now they are listening to us further on further improvements on process mining so that we can capitalize on further outcomes and benefits of process mining >>In order to cash is common use cases. So what, what, uh, were there any diamonds in the rough, or do you suspect there are with, >>We already realized, yes. We realized multiple tangible outcomes. We discussed this with Polak earlier today. One of them is some very interesting, I'm not able to share, but the most critical one is be focused on improving cash cycle. It's scent. You can imagine extremely full flow business, even within FMCG, right? We as Coca-Cola system, we are an extremely flow business. It's an instant consumption business. Hence your delivery and cash cycles are very different compared to other industries. So we said, we want to improving cash. We discovered that the improved, the invoice due date change, which impacts the payment terms by 20%, we improved credit limits approvals by 5% by removing unnecessary approval steps. We realized there were unnecessary approvals. These two are directly impacting our customers as well because it's waiting in somebody's queue to handle those approvals. And the customer is not getting to delay delivery because it's payment, payment and delivery go hand in hand. >>And the third one is, and I'm not able to articulate it exact outcome, but it's a very critical day, every day gain on getting cash. So it's a cash game. The next big outcome is the cycle time improvements. So we significantly improve the cycle time of the process. And this means efficiency for our employees. We are making life easier for them. The last one is again, a tangible one 30,000 hours back in terms of productivity, one process, one country, 30,000 hours. And that translates into exactly that translates into benefit for the customer. You increase customer satisfaction, you increase employee satisfaction. 'cause you remove all the non-available for it. So going back to Pollock's point around continuous discovery, that's why we love it. It's like good old lean six Sigma lean six Sigma is exactly that you continuously, you want to continuously improve the process. You don't do it once with process mining. We don't want to do it once. We want to do it continuously, but this time with automation, >>But before we go, I'm the lone male on the panel. So I have to ask. So, so you CIO seat, chief digital role, very uncommon, let alone uncommon for a woman. Big time product management person. Okay. That's cool check. Right? You've been in the industry for a while now, a celebrity on the, on the cube and elsewhere. So has the pandemic, how has the pandemic affected the whole women in tech trend? Has it slowed it down? Has it accelerated? We were talking earlier about the working moms feeling like way stressed out more than the working dads, double 30% versus 15%. Has the pandemic in your minds altered in any way, was women in tech meme? How so positive. Negative. >>So we are trying to turn the negative into a positive. It is negative. Absolutely. I think it's impacted everybody, all, all women in all industries and in all areas of operation and workforce women in technology is already a very slim, right? It's a very tiny layer within any company and out there in the society. And unfortunately the challenges that came with COVID impacted and some of them had to leave and they couldn't stick around. Right. So we are trying to turn that into positive. As a digital function, we have a big give back initiative. It's a priority of the digital team. I'll be talking about that very in, in, and our technology removes barriers. So we have to turn this into a positive, yes, COVID has impacted everybody personally and directly or indirectly. But now with technology, we can remove barriers. We have now flexible working and hybrid working models, being ramped up across all geographies and all industries and all companies, technology removes barriers. >>We can teach technology to a lot of people and our communities and they can join because we have huge skill gaps in technology that would sat is we have huge scarcity of skills in technology. And we have very few people, but we are talking about women dropping out or any type of minor to dropping out, right? So we can leverage and improve and turn it around. I hope we'll accomplish to do that. We started doing that in our company and in Turkey. And we are trying to expand that across multiple other countries with NGO partnerships, helping women to gain certain skills so that they can join the economy again from wherever they are. >>And from my point of view, I think there are two aspects to it. As Layla said, it has affected women a little bit more, but I've also seen, in some cases it has leveled the playing field a little bit because there's, you know, everybody's on zoom. The kids show up on zoom cameras for men, just as much as they do for women. So it helps shine a light on things that we would normally go through that nobody would know about. And I thought that was a really cool outcome to some degree of this. You know, my manager prom has little kids and they'd be in his background all the time, just as my little kids would be by background. And I'm like, oh wow. So you know how it feels to be the caregiver at home. And I thought, I thought that was a positive outcome of the whole being a female in technology. I liked that >>That's something that I hadn't thought about in terms of leveling the playing field like that there's in this situation, there are both positives and negatives. I like how you're seeing the playing field level a bit more and how you're at. Coca-Cola looking to, how can we turn this negative into a positive lots of opportunities there we uncovered a lot in the last, I'm going to guess 20 minutes talking about continuous process discovery, all the way to women in technology, how you're each doing that and what your perspectives are. I wish we had more time. We could keep going, but ladies, thank you for joining David. >>It's been a pleasure >>For Dave Volante. I'm Lisa Martin live in Las Vegas at the Bellagio UI path forward for it. We'll be 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 around the globe. It's the Cube presenting Cuban cloud brought to you by Silicon Angle. Hi, this is David Linton. You're watching the Cubes coverage of the Cube on Cloud, our own virtual event where we're trying to understand the future of cloud, where we've come from and where we're going. And we're bringing in visionaries to really have that detailed conversation. Daniel Jones is here. He's the CEO of automation specialist. You. I path Daniel. Thanks for coming on and sharing your insights here. >>Thank you so much for inviting me. They've appreciated. >>That's always a pleasure to get together with folks that have started companies with a seed of a vision and have exploded in tow. You know, great success. And when I wanna go back to the the the founding days of you, I path 2005. It was a pre cloud. There's certainly pre cloud as we know it today. A w s came out in 2006. Aw, and then we saw the clouds Ascendancy. But but your original founding premise there was no cloud, you know, it wasn't like a startup could just spend up stuff in the cloud. But what you've seen that evolution. So when you first started to see cloud evolved, What did you think? Did you think Oh, well, we'll see what happens. Or did you? Did you know at the time that this was gonna be a bigas? It actually has become. What were your thoughts back then? >>Well, I honestly, I thought that we are kind of agent. And maybe it's stupid to not to pie foot in tow, The new trends in technology like Cloud Mobile social and I we kept, you know, working on this computer vision technology that 15 years ago, war was not really hot. But with the evolution of self driving cars and the latest development in AI, we we've been able to capture our investments in the domain that was not hot. But suddenly, you know, became the word the of the greatest minds in I t. And we definitely we specialize Our computer vision toe a narrow use case, but still, it's the It's the key of what we've done in, uh, in the end, the robots are powered by computer vision technology. This kind of a robot emulate how human user work. So obviously we use vision a lot in our day by day work and having the best technology that allows our robots to interact with the computer screen more like human user is quintessential and, uh, making our business reliable and easy to use. So we were lucky. But I always felt that maybe I should change it. And we were feeling I remember you know, many discussions with my, you know, initial developers because we like what you're doing. What we felt a bit left outside my door. What way? Got lucky in the end. >>So So I have a premise here and that when you go back to the early days of cloud, what they got right was they were attacking the human labor problem and they automate it was storage. It was it was networking. It was compute. But really the automation that they brought toe i t. And the quality that that drove and the flexibility was, you know, a game changer. Of course, we know that now. And you know, many of us at the time were very excited about Cloud. I'm not sure we predicted the impact that it had, but my premise is that there's a parallel in your business with the automation that you're driving into the business. We've talked toe people, for instance, that some of your customers have said, You know I can't do Six Sigma. I can't afford to do six Sigma before things like R P. A. For business process. I do that for Mission critical things, but now I can apply six Sigma thinking across my entire business that drives quality. It takes costs out of my business. So what do you think about that premise? That there's a parallel between the early days of cloud taking human labor out of the equation and driving quality and flexibility, cost saving speed and revenue, etcetera and what you're doing on the business side, >>it is clearly a parallel. I can tell that the cloud was built by looking at ICTY Automation use cases first of all, because this is all software engineers understand the most software engineers. Let's be you little on this. They don't understand the business work. They don't understand all how the rial work is performing a big enterprise and they don't care. Sometimes when in my own discussions with our CFO, he is surprised that I don't know all the use cases in the world. Yes, of course. I don't know exactly how an insurance company work All the processes in a health care, all the banking processes. I have intellectual curiosity how they were. But what interests me the most is our computer vision technology that works uniformly well across different. That was the same from the cloud. So initially they built and they build a cow cloud one toe, help them when what they know the best. And now, for we were put in the face of having great technology, this computer region technology, but without having a great use case in the I t world that we understood. And when we when I'm speaking about our early days like 12, 13, 14, I believe this technology has a lot less applicable bility in the real world. Because again, we were thinking of some sorts of small I T automation gigs that were not possible just doing the AP ice. But when I discovered the messy world of business processes and how important is to emulate people when you think automation, that was a big ah ha moment. So I believe that we can do for business processes what the cloud has done for I t processes on. We are really patient now about this business processes on helping people toe eliminate all the repetitive work that is their delegate. This work two robots and have the people that are required to do this work do do better. A smaller number of tasks every day. Everyone has own, as on her or him played today like, let's say, 10, 20 different activities. Some of them can be completely delegated to rob to robots, and they are the low value type of activities, while they can focus on the high value activities like interaction with people, creativity, decision making and this type of human like things that we as humans really love. >>I love that you shared that story, but you thought it was a very narrow, sort of set of use cases when you first started and then, you know, that's that's just an awesome founders, you know, really ization. I love it when we've often said in the Cube that, you know, for decades we've marched to the tune of Moore's Law. That was the innovation engine. No longer is that case. It's a combination of of data, applied machine intelligence and cloud for scale. And I guess the computer vision pieces How you in just the data you've you've made some investments in a I and there's many more to come the industry in general and the cloud is sort of the piece of that equation that we see for scale. So I wonder how you see those pieces fitting to your business. Uh, and how important is the cloud for your scale? At last? Uh, at last year, I path forward. There was a lot of talk amongst your customers about scaling. Is the cloud critical for that scale? >>Yeah, I believe so. And we are thinking of clouds in tow. Distinct ways number one. We're offering Onda manage automation service in our own close, using where we host everything by ourselves, including our orchestrator, and then be next to have the plans to include our the robots that execute the automation And people simply can't connect to our cloud building automation and just scheduled to run without any maintainers. And they will have access to oh, great analytics, Everything integrated. So this is a major force to us, and the way we launching G a. This cloud offering in April this year, and I can tell you that until now, 20% of our customers already are in a shape or another in this type of offering, not 20% dollar amount, but 20% of our customers. And it's clear that at this point this has mawr applicability into the long tail, a smaller customers than in the on our biggest customers. But the second, this thing type of cloud offering that we focus on is toe have best in class support and best in class multi cloud support for the cloud of choice of our customers. For instance, if you go in if you go in a w, g, c, p usher and you buy a subscription there, you wear buildings. Specialized editions were with one click. You will be able to install our technology in those clouds and you'll be ableto scale up and down your robots. You can connect your robots to our many service were within your tenant, but basically the angle is toe lesson. Ah lot the administration, the maintainers footprint of your installation, either on our own cloud, even on your cloud of choice. I'm a strong believer that we will see an accelerated transition from the completely on Prem Workloads into these two source of cloud workloads. >>I wanna ask you, is a a technologist if you see. So you mentioned that you're gonna take your products and your support. Multiple clouds will run on any cloud in A lot of companies are talking about that, you know, for their respective whether it's a database or, you know, whatever storage device, etcetera. Do you see the day where you'll actually start? You're collaborating across clouds. Where the user, uh, maybe maybe the user today doesn't know, but maybe a developer does know which cloud it's running on. But do you see any value in actual, you know, connecting across clouds where the data and one cloud is relevant for the data? Another cloud is I know there are latent see issues. Is that you know, technically feasible. And is it it? Will it drive business value? What do you think about that cross cloud connection? >>I believe it is already happening. There is a mesh between between various services and who knows in which cloud they are awful. Already. I feel the Leighton see is less and less of a problem as much as the biggest cloud provider have have a very distributed geographically president. So as long as I can playing AWS in East Coast, on on Asia in East Coast, it's not such a big Leighton see issue. Uh huh. Frankly, in the past, our customers at least start telling us they seen how it is to be completely looking toe one technology on people would like Toa have optionality. It's not necessarily that I will use three clothes, but I would like to use the vendor that gives me optionally even. And this is what we're trying to offer. >>Do you, when you think about the future of work? I mean, e said before the cloud one dato was infrastructure storage, networking, computing Uh, it seems like to Dato we're bringing in more ai new workloads. We're seeing, you know, analytics and machine intelligence applied to the data and then, you know, distributed at scale self serve to the business. How do you see the future of work specifically as it relates toe automation affecting that, uh on you know what role does cloud play there? What's your vision? >>So as the workloads will move to cloud. It's absolutely critical that the processes will move to cloud, so there is no way back. I think, that moving in tow, moving from home for and software into cloud will make even easier toe automate this type of workloads into the cloud. It's gonna be less maintain us. You will deal less with legacy applications that require some special care. It's kind of a bit more easier to automate modern Onley, Web based type of application so that Z we'll see an acceleration on the moving to cloud. But again, there will be different sorts of cloud from a completely manage automation service from us toe managing yourself the automation in your cloud tenant, but not on prayer. I'm not a big believer that we will accept unless very few critical sectors I don't think that we will see home Primor roads in the past five years. >>I mean, I agree in this case, the business case for on Prem just gets, you know, less and less. I mean, it'll be a certain applications for sure. My last question is, when thinking about from a software developer standpoint, you obviously you're gonna wanna run in a W S and G, C P and Azure. Uh, perhaps Alibaba, Uh, do you look at other clouds? Whether their regional clouds, of course. You got your own cloud. Maybe Oracle. IBM. How do you think about those? Do you just sort of evaluated on a case by case basis? You let customers, you know, tell you where you need to be. >>Yeah, way focus on the on the three big clouds today, but we're building on the top off Q Burnett is most of our way. We have a big shift in tow building que Burnett is micro services. And my guess is that all mother clouds would offer fantastic support for kubernetes. So what What it takes when you create a new edition for another cloud is toe is toe have the underlying services. Like if we plan to use snowflake, for instance in our analytics offering, you better have snowflake in another cloud. Otherwise, probably the the analytics will will have toe be delayed or use a less of one part technology. So it's not only about what we are building, but it's also, you know, the vast availability of other set of technologies that we try toe use when you choose a technology. Now, first of all, we are looking. We need to choose something that is multi cloud. There's who's dedicated from one cloud vendor. That's that's our first priority. This is why I've mentioned snowflake and then when when we moved into a cloud. We are limited by the offerings that are there, but I my belief is in the main clouds, probably in the US I don't know one of the region's what's gonna happen, but in the main crowds in the U. S. In I believe that they will. In the end, they will catch up in terms off offering and convincing of other defenders toe have kind of kind of similar offering on their own. I don't know if, besides, the Big Three, or you'll see someone and that is able to compete could be too much fragmented. Maybe they will be dedicated clouds for certain services. But for General Cloud, I think three is more than enough. >>Yeah, and so, you know, in the early days of cloud, people talked about dial tone, and essentially, that's what's becoming. It's the it's the value that's running on top of the cloud from software companies like ey Path and others that is really driving. So the cloud to Dato the next generation Daniel Dennett is thanks so much for sharing your vision on participating in the Cuban cloud. Really appreciate it. >>My pleasure, Dave. Thank you so much for inviting. >>You're welcome. You always great to talk to you. And thank you for watching everybody keep it right there. We'll be back with our next guest right into this short break. This is Dave Volonte for the Cube. Yeah.

okay here we go hi everybody this is dave vellante and you're watching thecube's coverage of the cube on cloud our own virtual event where we're trying to understand the future of cloud where we've come from and where we're going and we're bringing in visionaries to really have that that detailed conversation daniel dines is here he's the ceo of automation specialist uipath daniel thanks for coming on and sharing your insights here thank you so much for inviting me dave appreciate it that's always a pleasure to get together with with folks that have started companies with a seed of a vision and have exploded into you know great success and and but i want to go back to the the founding days of uipath 2005. it was pre-cloud there's certainly pre-cloud as we know it today aws came out in 2006 and then we we saw the clouds ascendancy but but your original founding premise there was no cloud you know it wasn't like a startup that could just spin up stuff in the cloud but you've seen that evolution so when you first started to see cloud evolve what did you think did you think oh well we'll see what happens or did you did you know at the time that this was going to be as big as it actually has become what were your thoughts back then well i honestly i i thought that we are kind of ancient and maybe it's stupid to not to private into the new trends in technology like cloud mobile social but i we kept you know working on this computer vision technology that uh 15 years ago was not really hot but with the evolution of self-driving cars and the latest development in ai we we've been able to capture our investments in a domain that was not hot but suddenly you know became the word of the greatest minds in i.t and we definitely we we specialize our computer vision to a narrow use case but still it's the it's the key of what we've done in uh in the end the robots are powered by computer vision technology this kind of a robot emulate how human user work so obviously we use vision a lot in our day by day work and having the best technology that allows our robots to interact with the computer screen more like a human user is quintessential in uh in making our business reliable and easy to use so we were lucky but i always felt that maybe i should change it and we we were feeling i i remember you know many discussions with my you know initial developers because we like what we were doing but we felt a bit left outside by the world but we got lucky in the end so so i have a premise here and that when you go back to the early days of cloud what they got right was they were attacking the the human labor problem and they automated it was storage it was it was networking it was compute but really the automation that they brought to it and the quality that that drove and the flexibility uh was you know a game changer of course we we know that now and you know many of us at the time were very excited about cloud i'm not sure we predicted the impact that it had but my premise is that there's a parallel in your business with the automation that you're driving into the business we've talked to people for instance some of your customers have said you know i can't do six sigma i can't afford to do six sigma before things like rpa for business process i do that for mission critical things but now i can apply six sigma thinking across my entire business that drives quality it takes cost out of my business so what do you think about that premise that there's a parallel between the early days of cloud taking human labor out of the equation and driving quality and flexibility cost saving speed and revenue etc and what you're doing on the business side it is clearly a parallel i can tell that the cloud was built by looking at it automation use cases first of all because this is what software engineers understand the most software engineers let's be you know honest they don't understand the business work they they don't understand all how the real work is performed in a big enterprise and they don't care sometimes when in my own discussions with our cfo he is surprised that i don't know all the use cases in the world yes of course i don't know exactly how an insurance company work all the processes in healthcare all the banking processes i have intellectual curiosity how they work but what interests me the most is our computer vision technology that works uniformly well across different that was the same from the cloud so initially they built in the they built the cloud to help them when what they know the best and now for we were put in the face of having great technology this computer vision technology but without having a great use case in the iit world that we understood and when we when i'm speaking about our early days like 12 13 14 i believe this technology has a lot less applicability in the real world because again we were thinking of some sorts of small it automation gigs that were not possible just doing the apis but when i discovered the messy world of business processes and how important is to emulate people when you think automation that was the big aha moment so i believe that we can do for business processes what the cloud has done for i.t processes and we are really patient now about these business processes and helping people to eliminate all the repetitive work that is there delegate this work to robots and have the people that are required to do this work do do better a smaller number of tasks every day everyone has one as on her or him played today like let's say 10 20 different activities some of them can be completely delegated to rock to robots and they are the low value type of activities while they can focus on the high value activities like interaction with people creativity decision making and this type of human-like things that we as humans really love i love that uh you shared that story but you you thought it was a very narrow sort of set of use cases when you first started and then you know that's that's just an awesome founders you know realization i i love it when we've often said in the cube that you know for decades we've marched to the the tune of moore's law that was the innovation engine no longer is the case it's a combination of of data applied machine intelligence and cloud for scale and i guess the computer vision piece is how you ingest the data uh you you've you've made some investments in in ai and there's many more to come the industry in general and the cloud is is sort of the piece of that equation that we see for scale so i wonder how you see those pieces fitting to your business and how important is the cloud for your scale at last uh at last ui path forward there was a lot of talk amongst our customers about scaling is the cloud critical for that scale yeah i believe so and we are thinking of cloud in two distinct ways number one we are offering and manage automation service in our own cloud using uh where we host everything by ourselves including our orchestrator and then next we have the plans to include our the robots that execute the automation and people simply can connect to our cloud build an automation and just schedule it to run without any maintenance and they will have have access to great analytics everything integrated so this is a major focus to us and the way we launching ga this cloud offering in april this year and i can tell you that until now 20 percent of our customers already are in a shape or another in this type of offering not 20 dollar amount but 20 of our customers and it's clear that at this point this has more applicability into the long tail a smaller customers than in the on our biggest customers but the second distinct type of cloud offering that we focus on is to have best-in-class support in best-in-class multi-cloud support for the cloud of choice of our customers for instance if you go in if you go in aws gcp azure and you buy a subscription there you we we are building specialized editions where with one click you will be able to install our technology in those clouds and you will be able to to scale up and down your robots you can connect your robots to our many services were within your tenant but basically the end goal is to lessen a lot the administration the maintenance footprint of your installation either on our own cloud even on your cloud of choice i'm a strong believer that we will see an accelerated transition from the completely on prem workloads into these two source cloud workloads i want to ask you as a as a technologist if you see so you mentioned that you're going to take your products and you support multiple clouds it'll run on any cloud and a lot of companies are talking about that you know for their respective whether it's a database or you know whatever storage device etc do you see the the day where you'll actually start you're collaborating across clouds where the user uh maybe maybe the user today doesn't know but but maybe a developer does know which cloud it's running on but do you see any value in actual you know connecting across clouds where the data in one cloud is relevant for the data another cloud is i know there are latency issues is is that you know technically feasible and is it will it drive business value what do you think about that cross-cloud connection i believe it is already happening there is a mesh between between various services and who knows in which cloud they are offered already i feel the latency is less and less of a problem as much as the biggest cloud provider have have a very distributed geographically present so as long as i can play in aws in east coast on azure in east coast it's not such a big latency issue and frankly in the past our customers at least are telling us they seen how it is to be completely locked into one technology and people would like to have optionality it's not necessarily that i will use three clouds but i would like to use a vendor that gives me optionality even the and this is what we are trying to offer do you when you think about the future of work i mean as i said before the cloud 1.0 is infrastructure storage networking compute and it seems like 2.0 we're bringing in more ai new workloads uh we're seeing you know analytics and and machine intelligence applied to the data and then you know distributed at scale self-serve to the business how do you see the future of work specifically as it relates to automation affecting that uh and you know what role does cloud play there what's your vision so as the workloads will move to cloud it's absolutely critical that the processes will move to cloud so there is no way back and i i think that uh moving into moving from opera and software into cloud will make even easier to automate this type of workloads into the cloud it's gonna be less maintenance you will deal less with legacy applications that require some special care it's kind of a bit more easier to automate modern only web-based type of application so that's uh we will see an acceleration on the on the moving to cloud but again there will be different sorts of cloud from a completely managed automation service from us to managing yourself the automation in your cloud tenant but not on-prem i'm not a big believer that we will ex unless very few critical sectors i don't think that we will see on-prem workloads in the past five years i mean i agree in the business the business case for on-prem just gets you know less and less i mean it'll there's certain applications for sure my last question is when thinking about from a software developer standpoint you obviously you're going to want to run in aws and gcp and azure uh perhaps alibaba do you look at other clouds whether they're regional clouds of course you've got your own cloud maybe oracle ibm how do you think about those do you just sort of evaluate them on a case-by-case basis you let customers you know tell you where where you need to be yeah we we we focus on the on the three big clouds today but we are building on the top of kubernetes most of our we we have a big shift into building kubernetes microservices and my guess is that all modern clouds will offer fantastic support for kubernetes so what what it takes when you create an edition for another cloud is to is to have the underlying services like if we plan to use snowflake for instance in our analytics offering you better have snowflake in another cloud otherwise probably the the analytics will will have to be delayed or use less of one part technology so it's not only about what we are building but it's also you know the vast availability of other set of technologies that we try to use when you choose a technology now first of all we are looking we need to choose something that is multi-cloud versus dedicated from one cloud vendor that's that's our first priority this is why i've mentioned snowflake and then when you when we move into a cloud we are limited by the offerings that are there but i my belief is in the in the main clouds probably in the us i don't know on other regions what's going to happen but in the main clouds in the us and i believe that they will in the end they will catch up in terms of offering and convincing other other vendors to to have kind of similar offering on their own i don't know if besides the big three we will see someone and that is able to compete could be too much fragmented maybe they will be dedicated clouds for certain services but for general cloud i think three is more than enough yeah and so you know in the early days of cloud people talked about dial tone and essentially that's what's becoming it's the it's the value that's running on top of the cloud from software companies like uipath and others that is really driving sort of the cloud 2.0 the next generation daniel dines thanks so much for sharing your your vision uh and participating in the cube on cloud really appreciate it my pleasure dave thank you so much for inviting you're welcome always great to talk to you and thank you for watching everybody keep it right there we'll be back with our next guest ready for this short break this is dave vellante for the cube

>> Narrator: From around the globe, it's theCUBE. With digital coverage of smart data marketplaces. Brought to you by Io-Tahoe. >> Digital transformation has really gone from a buzzword to a mandate, but digital business is a data business. And for the last several months we've been working with Io-Tahoe on an ongoing content series, focused on smart data and automation to drive better insights and outcomes, essentially putting data to work. And today we're going to do a deeper dive on automating data discovery. And one of the thought leaders in this space is Ajay Vohora, who's the CEO of Io-Tahoe. Once again, joining me, Ajay good to see you. Thanks for coming on. >> Great to be here, David, thank you. >> So let's, let's start by talking about some of the business realities and what are the economics that are driving automated data discovery? Why is that so important? >> Yeah, on this one, David it's a number of competing factors. We've got the reality of data which may be sensitive. So there's control. Three other elements wanting to drive value from that data to innovation. You can't really drive a lot of value without exchanging data. So the ability to exchange data and to manage those cost overheads and data discovery is at the root of managing that in an automated way to classify that data and set some policies to put that automation in place. >> Yeah, look, we have a picture of this. If we could bring it up guys, cause I want to, Ajay, help the audience understand kind of where data discovery fits in here. This is, as we talked about, this is a complicated situation for a lot of customers. They've got variety of different tools and you've really laid it out nicely here in this diagram. So, take us through sort of where that piece fits. >> Yeah, I mean, we're at the right hand side of this exchange, you know. We're really now in a data driven economy that is everything's connected through APIs that we consume online through mobile apps. And what's not apparent is the chain of activities and tasks that have to go into serving that data to an API at the outset. They may be many legacy systems, technologies, platforms On-premise, in cloud, hybrid, you name it and across those silos, getting to a unified view is the heavy lifting. I think we've seen some, some great impacts that BI tools, such as Power BI, Tableau, Looker, and so on, and Qlik have had, and they're in our ecosystem on visualizing Data and, you know, CEOs, managers, people that are working in companies day-to-day get a lot of value from saying, "What's the real time activity? "What was the trend over this month versus last month?" The tools to enable that, you know, we hear a lot of good things that we're doing with Snowflake, MongoDB on the public Cloud platforms, GCP Azure about enabling building those pipelines to feed into those analytics. But what often gets hidden is how do you source that data that could be locked into a mainframe, a data warehouse, IOT data, and pull over all of that together. And that is the reality of that is it's a lot of heavy lifting. It's hands on work that can be time consuming. And the issue there is that data may have value. It might have potential to have an impact on the top line for a business, on outcomes for consumers, but you're never really sure unless you've done the investigation, discovered it, unified that, and be able to serve that through to other technologies. >> Guys, if you would bring that picture back up again, because Ajay you made a point and I want to land on that for a second. There's a lot of manual curating. An example would be the data catalog. You know, data scientists complain all the time that they're manually wrangling data. And so you're trying to inject automation into the cycle. And then the other piece that I want you to address is the importance of APIs. You really can't do this without an architecture that allows you to connect things together that sort of enables some of the automation. >> Yep, I mean, I'll take that in two parts, David, the APIs, so virtual machines connected by APIs, business rules, and business logic driven by APIs, applications, so everything across the stack from infrastructure down to the network, hardware is all connected through APIs and the work of serving data through to an API, building those pipelines, is often miscalculated, just how much manual effort that takes and that manual effort, we've got a nice list here of what we automate down at the bottom, those tasks of indexing, labeling, mapping across different legacy systems, all of that takes away from the job of a data scientist or data engineer, looking to produce value, monetize data, and to help that business convey to consumers. >> Yeah, it's that top layer that the business sees, of course, there's a lot of work that has to go into achieving that. I want to talk about some of the key tech trends that you're seeing. And one of the things that we talk about a lot is metadata. The importance of metadata, you know, can't be understated. What are some of the big trends that you're seeing metadata and others? >> Yeah, I'll summarize it as five. There's a trend now look at metadata more holistically across the enterprise. And that really makes sense from trying to look across different data silos and apply a policy to manage that data. So that's the control piece. That's that lever. The other side, sometimes competing with that control around sensitive data around managing the cost of data is innovation. Innovation being able to speculate and experiment and try things out where you don't really know what the outcome is if you're a data scientist and engineer, you've got a hypothesis and therefore you've got that tension between control over data and innovation and driving value from it. So enterprise wide metadata management is really helping to unlock where might that latent value be across that sets of data. The other piece is adaptive data governance. Those controls that stick from the data policemen, data stewards, where they're trying to protect the organization, protect the brand, protect consumers data necessary, but in different use cases, you might want to nuance and apply a different policy to govern that data relevant to the context where you might have data that is less sensitive, that can be used for innovation and adapting the style of governance to fit the context is another trend that we're seeing coming up here. A few others is where we're sitting quite extensively in working with automating data discovery. We're now breaking that down into what can we direct? What do we know is a business outcome is a known upfront objective and direct that data discovery to towards that. And that means applying our algorithms around technology and our tools towards solving a known problem. The other one is autonomous data discovery. And that means, you know, trying to allow background processes to understand what changes are happening with data over time, flagging those anomalies. And the reason that's important is when you look over a length of time to see different spikes, different trends and activity, that's really giving a data ops team the ability to manage and calibrate how they're applying policies and controls the data. And the last two, David, that we're seeing is this huge drive towards self-service. So re-imagining how to apply policy data governance into the hands of a data consumer inside a business, or indeed the consumer themselves, to self-service if they're a banking customer or healthcare customer and the policies and the controls and rules, making sure that those are all in place to adaptively serve those data marketplaces that when are involved in creating. >> I want to ask you about the autonomous data discovering, the adaptive data governance, is the problem we're addressing there one of quality, in other words, machines are better than humans are at doing this? Is it one of scale? That humans just don't don't scale that well? Is it both? Can you add some color to that? >> Yeah, honestly, it's the same equation that existed 10 years ago, 20 years ago, it's being exacerbated, but it's that equation of how do I control all the things that I need to protect? How do I enable innovation where it is going to deliver business value? How do I exchange data between a customer, somebody in my supply chain safely, and do all of that whilst managing the fourth leg, which is cost overheads. There's not an open checkbook here. I've got to figure out if I'm the CIO and CDO, how I do all of this within a fixed budget. So those aspects have always been there, now with more choices, infrastructure in the Cloud, API driven applications, On-premises, and that is expanding the choices that a business has and how they put their data to work. It's also then creating a layer of management and data governance that really has to now manage those four aspects, control, innovation, exchange of data, and the cost overhead. >> That top layer of the first slide that we showed was all about the business value. So, I wonder if we could drill into the business impact a little bit. What are your customers seeing specifically in terms of the impact of all this automation on their business? >> Yeah, so we've had some great results. I think a few of the biggest have been helping customers move away from manually curating their data and their metadata. It used to be a time where if data initiatives or data governance initiatives, there'd be teams of people manually feeding a data catalog. And it's great to have that inventory of classified data to be able to understand single version of the truth, but having 10, 15 people manually process that, keep it up to date, when it's moving feet, the reality of it is what's true about data today, add another few sources and a few months time to your business, start collaborating with new partners, suddenly the landscape has changed. The amount of work has gone up, but what we're finding is through automating, creating that data discovery, feeding our data catalog, that's releasing a lot more time for our customers to spend on innovating and managing their data. A couple of others is around self service data analytics, moving the choices of what data might have business value into the hands of business users and data consumers to have faster cycle times around generating insights. And we're really helping them by automating the creation of those data sets that are needed for that. And the last piece, I'd have to say where we're seeing impacts more recently is in the exchange of data. There are a number of marketplaces out there who are now being compelled to become more digital, to rewire their business processes and everything from an RPA initiative to automation involving digital transformation is having CIOs, chief data officers and enterprise architects rethink how do they, how do they rewire the pipelines for their data to feed that digital transformation? >> Yeah, to me, it comes down to monetization. Now, of course, that's for a for-profit industry. For non-profits, for sure, the cost cutting or in the case of healthcare, which we'll talk about in a moment, I mean, it's patient outcomes, but the job of a Chief Data Officer has gone from data quality and governance and compliance to really figuring out how data can be monetized, not necessarily selling the data, but how it contributes to the monetization of the company. And then really understanding specifically for that organization, how to apply that. And that is a big challenge. We sort of chatted about 10 years ago, the early days of a dupe. And then 1% of the companies had enough engineers to figure it out, but now the tooling is available. The technology is there and the practices are there. And that really, to me is the bottom line, Ajay, is it's show me the money. >> Absolutely. It's definitely is focusing in on the single view of that customer and where we're helping there is to pull together those disparate, siloed sources of data to understand what are the needs of the patient, of the broker of the, if it's insurance? What are the needs of the supply chain manager, if it's manufacturing? And providing that 360 view of data is helping to see, helping that individual unlock the value for the business. So data's providing the lens provided, you know which data it is that can assist in doing that. >> And, you know, you mentioned RPA before, I had an RPA customer tell me she was a Six Sigma expert and she told me, "We would never try to apply Six Sigma "to a business process, "but with RPA we can do so very cheaply." Well, what that means is lower costs. It means better employee satisfaction and really importantly, better customer satisfaction and better customer outcomes. Let's talk about healthcare for a minute because it's a really important industry. It's one that is ripe for disruption and has really been, up until recently, pretty slow to adopt a lot of the major technologies that have been made available. But what are you seeing in terms of this theme we're using a putting data to work in healthcare specifically? >> Yeah, I mean, health care's has had a lot thrown at it. There's been a lot of change in terms of legislation recently, particularly in the U.S. market, in other economies, healthcare is on a path to becoming more digital. And part of that is around transparency of price. So, to be operating effectively as a healthcare marketplace, being able to have that price transparency around what an elective procedure is going to cost before taking that step forward. It's super important to have an informed decision around that. So if we look at the U.S., for example, we've seen that healthcare costs annually have risen to $4 trillion, but even with all of that cost, we have healthcare consumers who are reluctant sometimes to take up healthcare even if they have symptoms. And a lot of that is driven through not knowing what they're opening themselves up to. And, you know, I think David, if you or I were to book travel a holiday, maybe, or trip, we'd want to know what we're in for, what we're paying for upfront. But sometimes in healthcare that choice, the option might be the plan, but the cost that comes with it isn't. So recent legislation in the U.S. is certainly helpful to bring forward that price transparency. The underlying issue there though is the disparate different format types of data that are being used from payers, patients, employers, different healthcare departments to try and make that work. And where we're helping on that aspect in particular related to price transparency is to help make that data machine readable. So, sometimes with data, the beneficiary might be a person, but in a lot of cases, now we're seeing the ability to have different systems interact and exchange data in order to process the workflow to generate online lists of pricing from a provider that's been negotiated with a payer is really an enabling factor. >> So guys, I wonder if you could bring up the next slide, which is kind of the nirvana. So, if you saw the previous slide that the middle there was all different shapes and presumably to disparate data, this is the outcome that you want to get, where everything fits together nicely. And you've got this open exchange. It's not opaque as it is today. It's not bubble gum, band-aids and duct tape, but describe this sort of outcome that you're trying to achieve and maybe a little bit about what it's going to take to get there. >> Ajay: Yeah, that that's the culmination of a number of things. It's making sure that the data is machine readable, making it available to APIs, that could be RPA tools. We're working with technology companies that employ RPA for healthcare, and specifically to manage that patient and payer data to bring that together. In our data discovery, what we're able to do is to classify that data and have it made available to a downstream tool technology or person to apply that, that workflow to the data. So this looks like nirvana, it looks like utopia, but it's, you know, the end objective of a journey that we can see in different economies, that are at different stages of maturity in turning healthcare into a digital service even so that you can consume it from where you live, from home with telemedicine and tele care. >> Yeah, so, and this is not just for healthcare, but you know, you want to achieve that self-service data marketplace in virtually any industry. You're working with TCS, Tata Consulting Services to achieve this. You know, a company like Io-Tahoe has to have partnerships with organizations that have deep industry expertise. Talk about your relationship with TCS and what you guys are doing specifically in this regard. >> Yeah, we've been working with TCS now for a long while and we'll be announcing some of those initiatives here where we're now working together to reach their customers where they've got a brilliant framework of business, 4.0, where they're re-imagining with the clients, how their business can operate with AI, with automation and become more agile and digital. Our technology, now, the reams of patients that we have in our portfolio, being able to apply that at scale, on a global scale across industries, such as banking, insurance and healthcare is really allowing us to see a bigger impact on consumer outcomes, patient outcomes. And the feedback from TCS is that we're really helping in those initiatives remove that friction. They talk a lot about data friction. I think that's a polite term for the image that we just saw with the disparate technologies that the legacy that has built up. So if we want to create a transformation, having that partnership with TCS across industries is giving us that reach and that impact on many different people's day-to-day jobs and lives. >> Let's talk a little bit about the Cloud. It's a topic that we've hit on quite a bit here in this content series. But, but you know, the Cloud companies, the big hyper-scalers, they've put everything into the Cloud, right? But customers are more circumspect than that. But at the same time, machine intelligence, ML, AI, the Cloud is a place to do a lot of that. That's where a lot of the innovation occurs. And so what are your thoughts on getting to the Cloud, putting data to work, if you will, with machine learning, stuff that you're doing with AWS, what's your fit there? >> Yeah, we, David, we work with all of the Cloud platforms, Microsoft Azure, GCP, IBM, but we're expanding our partnership now with AWS. And we're really opening up the ability to work with their Greenfield accounts, where a lot of that data, that technology is in their own data centers at the customer. And that's across banking, healthcare, manufacturing, and insurance. And for good reason, a lot of companies that have taken the time to see what works well for them with the technologies that the Cloud providers are offering, and a lot of cases, testing services or analytics using the Cloud to move workloads to the Cloud to drive data analytics is a real game changer. So there's good reason to maintain a lot of systems On-premise. If that makes sense from a cost, from a liability point of view and the number of clients that we work with that do have, and will keep their mainframe systems when in Cobra is no surprise to us, but equally they want to tap into technologies that AWS has such as SageMaker. The issue is as a Chief Data Officer, I didn't have the budget to move everything to the Cloud they want, I might want to show some results first upfront to my business users and work closely with my Chief Marketing Officer to look at what's happening in terms of customer trends and customer behavior> What are the customer outcomes, patient outcomes and partner outcomes that you can achieve through analytics, data science? So, working with AWS and with clients to manage that hybrid topology of some of that data being in the Cloud, being put to work with AWS SageMaker and Io-Tahoe being used to identify where is the data that needs to be amalgamated and curated to provide the dataset for machine learning, advanced analytics to have an impact for the business. >> So what are the critical attributes of what you're looking at to help customers decide what to move and what the keep if you will? >> Well, one of the quickest outcomes that we help customers achieve is to buy that business glossary, you know, that the items of data, that means something to them across those different silos and pull all of that together into a unified view. Once they've got that data engineer working with a business manager to think through, how do we want to create this application? Now, what is the churn model, the loyalty or the propensity model that we want to put in place here? How do we use predictive analytics to understand what needs for a patient that sort of innovation is what we're unlocking, applying a tools such as SageMaker on AWS to then do the computation and to build those models to deliver that outcome is across that value chain. And it goes back to the first picture that we put up, David, you know, the outcome is that API on the back of it, you've got a machine learning model that's been developed in a tool such as Databricks or Jupiter notebook. That data has to be sourced from somewhere. Somebody has to say that, "Yep, "You've got permission to do what you're trying to do without falling foul "of any compliance around data." And it all goes back to discovering that data, classifying it, indexing it in an automated way to cut those timelines down to hours and days. >> Yeah, it's the innovation part of your data portfolio, if you will, that you're going to put into the Cloud, apply tools like SageMaker and others, your tool Azure. I mean, whatever your favorite tool is, you don't care. The customer's going to choose that. And you know, the Cloud vendors, maybe they want you to use their tool, but they're making their marketplaces available to everybody, but it's that innovation piece, the ones that you, where you want to apply that self-service data marketplace to, and really drive, as I said before, monetization, All right, give us your final thoughts. Ajay, bring us home. >> So final thoughts on this, David, is at the moment, we're seeing a lot of value in helping customers discover their data using automation, automatically curating a data catalog. And that unified view is then being put to work through our API is having an open architecture to plug in whatever tool technology our clients have decided to use. And that open architecture is really feeding into the reality of what CIOs and Chief Data Officers are managing, which is a hybrid On-premise Cloud approach to use best of breed. But business users wanting to use a particular technology to get their business outcome, having the flexibility to do that no matter where your data is sitting On-premise, on Cloud is where self-service comes in so that sales service view of what data I can plug together, jive exchange, monetizing that data is where we're starting to see some real traction with customers. Now accelerating, becoming more digital to serve their own customers. >> Yeah, we really have seen a cultural mind shift going from sort of complacency, and obviously COVID has accelerated this, but the combination of that cultural shift, the Cloud machine intelligence tools give me a lot of hope that the promises of big data will ultimately be lived up to in this next 10 years. So Ajay Vohora, thanks so much for coming back on theCUBE. You're a great guest and appreciate your insights. >> Appreciate it, David. See you next time. >> All right, keep it right there, everybody, right back after this short break. 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>>from around the globe. It's the Cube with digital coverage of smart data. Marketplace is brought to You by Io Tahoe Digital transformation is really gone from buzzword to a mandate. Additional businesses, a data business. And for the last several months, we've been working with Iot Tahoe on an ongoing content. Serious, serious, focused on smart data and automation to drive better insights and outcomes, essentially putting data to work. And today we're gonna do a deeper dive on automating data Discovery. And one of the thought leaders in this space is a J ahora who is the CEO of Iot. Tahoe's once again joining Me A J Good to see you. Thanks for coming on. >>A great to be here, David. Thank you. >>So let's start by talking about some of the business realities. And what are the economics that air? That air driving, automated data Discovery? Why is that so important? >>Yeah, and on this one, David, it's It's a number of competing factors we've got. The reality is data which may be sensitive, so this control on three other elements are wanting to drive value from that data. So innovation, you can't really drive a lot of value without exchanging data. So the ability to exchange data and to manage those costs, overheads and data discovery is at the roots of managing that in an automated way to classify that data in sets and policies to put that automation in place. >>Yeah. Okay, look, we have a picture of this. We could bring it up, guys, because I want oh, A j help the audience. Understand? Unaware data Discovery fits in here. This is as we talked about this, a complicated situation for a lot of customers. They got a variety of different tools, and you really laid it out nicely here in this diagram. So take us through. Sort of where that he spits. >>Yeah. I mean, where at the right hand side, This exchange. You know, we're really now in a data driven economy that is, everything's connected through AP, eyes that we consume on mine free mobile relapse. And what's not a parent is the chain of activities and tasks that have to go into serving that data two and eight p. I. At the outset, there may be many legacy systems, technologies, platforms on premise and cloud hybrids. You name it. Andi across those silos. Getting to a unified view is the heavy lifting. I think we've seen Cem some great impacts that be I titles such as Power Bi I tableau looker on DSO on in Clear. Who had Andi there in our ecosystem on visualising Data and CEO's managers, people that are working in companies day to day get a lot of value from saying What's the was the real time activity? What was the trend over this month? First his last month. The tools to enable that you know, we here, Um, a lot of good things are work that we're doing with snowflake mongo db on the public cloud platforms gcpd as your, um, about enabling building those pay planes to feed into those analytics. But what often gets hidden is have you sauce that data that could be locked into a mainframe, a data warehouse? I ot data on DPA, though, that all of that together that is the reality of that is it's it's, um, it's a lot of heavy lifting It z hands on what that, um, can be time consuming on the issue There is that data may have value. It might have potential to have an impact on the on the top line for a business on outcomes for consumers. But you never any sure unless you you've done the investigation discovered it unified that Onda and be able to serve that through to other technologies. >>Guys have. You would bring that picture back up again because A. J, you made a point, and I wanna land on that for a second. There's a lot of manual curating. Ah, an example would be the data catalogue if they decide to complain all the time that they're manually wrangling data. So you're trying to inject automation in the cycle, and then the other piece that I want you to addresses the importance of AP eyes. You really can't do this without an architecture that allows you to connect things together. That sort of enables some of the automation. >>Yeah, I mean, I don't take that in two parts. They would be the AP eyes so virtual machines connected by AP eyes, um, business rules and business logic driven by AP eyes applications. So everything across the stack from infrastructure down to the network um, hardware is all connected through AP eyes and the work of serving data three to an MP I Building these pipelines is is often, um, miscalculated. Just how much manual effort that takes and that manual ever. We've got a nice list here of what we automate down at the bottom. Those tasks of indexing, labeling, mapping across different legacy systems. Um, all of that takes away from the job of a data scientist today to engineer it, looking to produce value monetize data on day two to help their business day to conceive us. >>Yes. So it's that top layer that the business sees, of course, is a lot of work that has to go went into achieving that. I want to talk about some of the key tech trends that you're seeing and one of the things that we talked about a lot of metadata at the importance of metadata. It can't be understated. What are some of the big trends that you're seeing metadata and others? >>Yeah, I'll summarize. It is five. There's trains now, look, a metadata more holistically across the enterprise, and that really makes sense from trying. Teoh look across different data silos on apply, um, a policy to manage that data. So that's the control piece. That's that lever the other side's on. Sometimes competing with that control around sense of data around managing the costs of data is innovation innovation, being able to speculate on experiment and trying things out where you don't really know what the outcome is. If you're a data scientist and engineer, you've got a hypothesis. And now, before you got that tension between control over data on innovation and driving value from it. So enterprise wide manage data management is really helping to enough. Where might that latent value be across that sets of data? The other piece is adaptive data governance. Those controls that that that stick from the data policemen on day to steer its where they're trying to protect the organization, protect the brand, protect consumers data is necessary. But in different use cases, you might want to nuance and apply a different policy to govern that data run of into the context where you may have data that is less sensitive. Um, that can me used for innovation. Andi. Adapting the style of governance to fit the context is another trend that we're seeing coming up here. A few others is where we're sitting quite extensively and working with automating data discovery. We're now breaking that down into what can we direct? What do we know is a business outcome is a known up front objective on direct that data discovery to towards that. And that means applying around with Dems run technology and our tools towards solving a known problem. The other one is autonomous data discovery. And that means, you know, trying to allow background processes do winds down what changes are happening with data over time flagging those anomalies. And the reason that's important is when you look over a length of time to see different spikes, different trends and activity that's really giving a day drops team the ability to to manage and calibrate how they're applying policies and controls today. There, in the last two David that we're seeing is this huge drive towards self service so reimagining how to play policy data governance into the hands off, um, a day to consumer inside a business or indeed, the consumer themselves. The South service, um, if their banking customer or healthcare customer and the policies and the controls and rules, making sure that those are all in place to adaptive Lee, um, serve those data marketplaces that, um when they're involved in creating, >>I want to ask you about the autonomous data discovering the adaptive data. Governance is the is the problem where addressing their one of quality. In other words, machines air better than humans are doing this. Is that one of scale that humans just don't don't scale that well, is it? Is it both? Can you add some color to that >>yet? Honestly, it's the same equation that existed 10 years ago, 20 years ago. It's It's being exacerbated, but it's that equation is how do I control both things that I need to protect? How do we enable innovation where it is going to deliver business value? Had to exchange data between a customer, somebody in my supply chains safely. And all of that was managing the fourth that leg, which is cost overheads. You know, there's no no can checkbook here. I've got a figure out. If only see io and CDO how I do all of this within a fixed budget so that those aspects have always been there. Now, with more choices. Infrastructure in the cloud, um, NPR driven applications own promise. And that is expanding the choices that a a business has and how they put mandated what it's also then creating a layer off management and data governance that really has to now, uh, manage those full wrath space control, innovation, exchange of data on the cost overhead. >>That that top layer of the first slide that we showed was all about business value. So I wonder if we could drill into the business impact a little bit. What do your customers seeing you know, specifically in terms of the impact of all this automation on their business? >>Yeah, so we've had some great results. I think view the biggest Have Bean helping customers move away from manually curating their data in their metadata. It used to be a time where for data quality initiatives or data governance initiative that be teams of people manually feeding a data Cavallo. And it's great to have the inventory of classified data to be out to understand single version of the trees. But in a having 10 15 people manually process that keep it up to date when it's moving feet. The reality of it is what's what's true about data today? and another few sources in a few months. Time to your business on start collaborating with new partners. Suddenly the landscape has changed. The amount of work is gonna But the, um, what we're finding is through automating creating that data discovery feeding a dent convoke that's releasing a lot more time for our CAS. Mr Spend on innovating and managing their data. A couple of others is around cell service data and medics moving the the choices of what data might have business value into the hands of business users and and data consumers to They're faster cycle times around generating insights. Um, we really helping that by automating the creation of those those data sets that are needed for that. And in the last piece, I'd have to say where we're seeing impacts. A more recently is in the exchange of data. There are a number of marketplaces out there who are now being compelled to become more digital to rewire their business processes. Andi. Everything from an r p a initiative. Teoh automation involving digital transformation is having, um, see iose Chief data officers Andi Enterprise architects rethink how do they how they re worthy pipelines? But they dated to feed that additional transformation. >>Yeah, to me, it comes down to monetization. Of course, that's for for profit in industry, from if nonprofits, for sure, the cost cutting or, in the case of healthcare, which we'll talk about in a moment. I mean, it's patient outcomes. But you know, the the job of ah, chief data officer has gone from your data quality and governance and compliance to really figuring out how data and be monetized, not necessarily selling the data, but how it contributes for the monetization of the company and then really understanding specifically for that organization how to apply that. And that is a big challenge. We chatted about it 10 years ago in the early days of a Duke. And then, you know, 1% of the companies had enough engineers to figure it out. But now the tooling is available, the technology is there and the the practices air there, and that really to me, is the bottom line. A. J is it says to show me the money. >>Absolutely. It's is definitely then six sing links is focusing in on the saying over here, that customer Onda, where we're helping there is dio go together. Those disparities siloed source of data to understand what are the needs of the patient of the broker of the if it's insurance? Ah, one of the needs of the supply chain manager If its manufacturing onda providing that 3 60 view of data, um is helping to see helping that individual unlock the value for the business. Eso data is providing the lens, provided you know which data it is that can God assist in doing that? >>And you know, you mentioned r p A. Before an r p A customer tell me she was a six Sigma expert and she told me we would never try to apply six segment to a business process. But with our P A. We can do so very cheaply. Well, what that means is lower costs means better employee satisfaction and, really importantly, better customer satisfaction and better customer outcomes. Let's talk about health care for a minute because it's a really important industry. It's one that is ripe for disruption on has really been up until recently, pretty slow. Teoh adopt ah, lot of the major technologies that have been made available, but come, what are you seeing in terms of this theme, we're using a putting data to work in health care. Specific. >>Yeah, I mean, healthcare's Havlat thrown at it. There's been a lot of change in terms of legislation recently. Um, particularly in the U. S. Market on in other economies, um, healthcare ease on a path to becoming more digital on. Part of that is around transparency of price, saying to be operating effectively as a health care marketplace, being out to have that price transparency, um, around what an elective procedure is going to cost before taking that that's that forward. It's super important to have an informed decision around there. So we look at the US, for example. We've seen that health care costs annually have risen to $4 trillion. But even with all of that on cost, we have health care consumers who are reluctant sometimes to take up health care if they even if they have symptoms on a lot of that is driven through, not knowing what they're opening themselves up to. Andi and I think David, if you are, I want to book, travel, holiday, maybe, or trip. We want to know what what we're in for what we're paying for outfront, but sometimes in how okay, that choice, the option might be their plan, but the cost that comes with it isn't so recent legislation in the US Is it certainly helpful to bring for that tryst price, transparency, the underlying issue there? There is the disparity. Different formats, types of data that being used from payers, patients, employers, different healthcare departments try and make that make that work. And when we're helping on that aspect in particular related to track price transparency is to help make that date of machine readable. So sometimes with with data, the beneficiary might be on a person. I've been a lot of cases now we're seeing the ability to have different systems, interact and exchange data in order to process the workflow. To generate online at lists of pricing from a provider that's been negotiated with a payer is, um, is really a neighboring factor. >>So, guys, I wonder if you bring up the next slide, which is kind of the Nirvana. So if you if you saw the previous slide that the middle there was all different shapes and presumably to disparage data, this is that this is the outcome that you want to get. Everything fits together nicely and you've got this open exchange. It's not opaque as it is today. It's not bubble gum band aids and duct tape, but but but described this sort of outcome the trying to achieve and maybe a little bit about what gonna take to get there. >>Yeah, that's a combination of a number of things. It's making sure that the data is machine readable. Um, making it available to AP eyes that could be our ph toes. We're working with technology companies that employ R P. A full health care. I'm specifically to manage that patient and pay a data. Teoh, bring that together in our data Discovery. What we're able to do is to classify that data on having made available to eight downstream tour technology or person to imply that that workflow to to the data. So this looks like nirvana. It looks like utopia. But it's, you know, the end objective of a journey that we can see in different economies there at different stages of maturity, in turning healthcare into a digital service, even so that you could consume it from when you live from home when telling medicine. Intellicast >>Yes, so And this is not just health care but you wanna achieve that self service doing data marketplace in virtually any industry you working with TCS, Tata Consultancy Services Toe Achieve this You know, if you are a company like Iota has toe have partnerships with organizations that have deep industry expertise Talk about your relationship with TCS and what you guys are doing specifically in this regard. >>Yeah, we've been working with TCS now for room for a long while. Andi will be announcing some of those initiatives here where we're now working together to reach their customers where they've got a a brilliant framework of business for that zero when there re imagining with their clients. Um, how their business cause can operate with ai with automation on, become more agile in digital. Um, our technology, the dreams of patients that we have in our portfolio being out to apply that at scale on the global scale across industries such as banking, insurance and health care is is really allowing us to see a bigger impact on consumer outcomes. Patient outcomes And the feedback from TCS is that we're really helping in those initiatives remove that friction. They talk a lot about data. Friction. Um, I think that's a polite term for the the image that we just saw with the disparity technologies that the legacy that has built up. So if we want to create a transformation, Um, having a partnership with TCS across Industries is giving us that that reach and that impacts on many different people's day to day jobs and knives. >>Let's talk a little bit about the cloud. It's It's a topic that we've hit on quite a bit here in this in this content Siri's. But But you know, the cloud companies, the big hyper scale should put everything into the cloud, right? But but customers are more circumspect than that. But at the same time, machine intelligence M. L. A. The cloud is a place to do a lot of that. That's where a lot of the innovation occurs. And so what are your thoughts on getting to the cloud? Ah, putting dated to work, if you will, with machine learning stuff you're doing with aws. What? You're fit there? >>Yeah, we we and David. We work with all of the cloud platforms. Mike stuffed as your G, c p IBM. Um, but we're expanding our partnership now with AWS Onda we really opening up the ability to work with their Greenfield accounts, where a lot of that data that technology is in their own data centers at the customer, and that's across banking, health care, manufacturing and insurance. And for good reason. A lot of companies have taken the time to see what works well for them, with the technologies that the cloud providers ah, are offered a offering in a lot of cases testing services or analytics using the cloud to move workloads to the cloud to drive Data Analytics is is a real game changer. So there's good reason to maintain a lot of systems on premise. If that makes sense from a cost from a liability point of view on the number of clients that we work with, that do have and we will keep their mainframe systems within kobo is is no surprise to us, but equally they want to tap into technologies that AWS have such a sage maker. The issue is as a chief data officer, I don't have the budget to me, everything to the cloud day one, I might want to show some results. First upfront to my business users Um, Onda worked closely with my chief marketing officer to look at what's happening in terms of customer trains and customer behavior. What are the customer outcomes? Patient outcomes and partner at comes I can achieve through analytics data signs. So I, working with AWS and with clients to manage that hybrid topology of some of that data being, uh, in the cloud being put to work with AWS age maker on night, I hope being used to identify where is the data that needs to bay amalgamated and curated to provide the data set for machine learning advanced and medics to have an impact for the business. >>So what are the critical attributes of what you're looking at to help customers decide what what to move and what to keep, if you will. >>Well, what one of the quickest outcomes that we help custom achieve is to buy that business blustery. You know that the items of data that means something to them across those different silos and pour all of that together into a unified view once they've got that for a data engineer working with a a business manager to think through how we want to create this application. There was the turn model, the loyalty or the propensity model that we want to put in place here. Um, how do we use predictive and medics to understand what needs are for a patient, that sort of innovation is what we're looking applying the tools such a sagemaker, uh, night to be west. So they do the the computation and to build those models to deliver the outcome is is across that value chain, and it goes back to the first picture that we put up. David, you know the outcome Is that a P I On the back of it, you've got the machine learning model that's been developed in That's always such as data breaks. But with Jupiter notebook, that data has to be sourced from somewhere. Somebody has to say that yet you've got permission to do what you're trying to do without falling foul of any compliance around data. Um, it'll goes back to discovering that data, classifying it, indexing it in an automated way to cut those timelines down two hours and days. >>Yeah, it's the it's the innovation part of your data portfolio, if you will, that you're gonna put into the cloud. Apply tools like sage maker and others. You told the jury. Whatever your favorite tool is, you don't care. The customer's gonna choose that and hear the cloud vendors. Maybe they want you to use their tool, but they're making their marketplaces available to everybody. But it's it's that innovation piece, the ones that you where you want to apply that self service data marketplace to and really drive. As I said before monetization. All right, give us your final thoughts. A. J bring us home. >>So final thoughts on this David is that at the moment we're seeing, um, a lot of value in helping customers discover that day the using automation automatically curating a data catalogue, and that unified view is then being put to work through our A B. I's having an open architecture to plug in whatever tool technology our clients have decided to use, and that open architecture is really feeding into the reality of what see Iose in Chief Data Officers of Managing, which is a hybrid on premise cloud approach. Do you suppose to breed Andi but business users wanting to use a particular technology to get their business outcome having the flexibility to do that no matter where you're dating. Sitting on Premise on Cloud is where self service comes in that self service. You of what data I can plug together, Dr Exchange. Monetizing that data is where we're starting to see some real traction. Um, with customers now accelerating becoming more digital, uh, to serve their own customers, >>we really have seen a cultural mind shift going from sort of complacency. And obviously, cove, it has accelerated this. But the combination of that cultural shift the cloud machine intelligence tools give give me a lot of hope that the promises of big data will ultimately be lived up to ah, in this next next 10 years. So a J ahora thanks so much for coming back on the Cube. You're you're a great guest. And ah, appreciate your insights. >>Appreciate, David. See you next time. >>All right? And keep it right there. Very right back. Right after this short break

>> Narrator: From around the globe, it's theCUBE, covering HPE Discover Virtual Experience, brought to you by HPE. >> Hello and welcome to theCUBE's coverage of HPE Discover 2020, The Virtual Experience. I'm Lisa Martin and I've got a couple of guests joining me, Stephen Laaper principal at Deloitte consulting and Brenna Sniderman the Executive Director for the Center of Integrated Research at Deloitte Services, Stephen and Brenna, nice to have you on the program today. >> Thank you, >> (mumbles) >> So we're going to be talking about The Smart Factory. I'd love for you to start Brenna, we'll start with you. Give our audience an overview of Deloitte's definition of The Smart Factory then we can dig into some of the very interesting research that Deloitte has been doing the last few years. >> Sure, absolutely. So the way we think about The Smart Factory is it is a system that's quite flexible that uses data and information from throughout, physical assets to optimized performance, to enable the facility to be more agile, to be proactive, to optimize its assets and to react and change as quickly as possible to shifts going on. It overall enables organizations to just be more intelligent about the way they use their assets to use data, to make more informed decisions and to drive a more optimized process. >> And Stephen for you, one of the things that I found interesting looking at some of Deloitte's research is that the last few years or so, there's been net zero growth in manufacturing labor productivity and labor productivity being an indicator of economic impact. Why in Deloitte's perspective, has that manufacturing labor productivity growth been flat? >> Yeah, it's a really interesting observation. And what we've seen is really decades and decades of management principles, companies using things like Lean, like Six Sigma, taking advantage of labor arbitrage in many cases. And the reality is that a lot of that low hanging fruit is gone. Those projects have been executed well and we're now seeing what we would consider to be diminishing returns as it relates to the investments in those same types of tools. And that is really what's leading many organizations now towards things like the capabilities that you'd find in a Smart Factory. Adding additional technologies to the capability set to really bring companies to that new productivity frontier. >> One of the things that I saw too, is that Smart Factory adoption in one of your studies, can result in a threefold productivity increase. So talk to me about in the last few years, some of the early adopters, Brenna we'll start with you, what are some of the trends that you've seen with those early adopters? any industries in particular that are leading in that respect? >> Well, that's a good question. I think when we recently published a study on lessons from early adopters in the Smart Factory and what we found was that a lot of the organizations that have adopted the Smart Factory have learned lessons that are not necessarily new but some that are new as well. Really I think the biggest challenge has been to figure out how to gather data from a lot of assets that maybe haven't had to produce data before to find out where all the information is from throughout the facility to bring together different groups and different cultures within the organization, whether it's IT and OT and have them figure out how to share information and data and really just to figure out what to do with that information once we've gotten it. Some of the organizations that we spoke with for our research really ran the gamut from aerospace to automotive, to consumer products, to industrial manufacturing. It really has been an interesting spread that we've looked at. >> Stephen walk us through the last three years or so of research that Deloitte has been doing into the Smart Factory from the 2017 study to the 2019 study, to the one that was just released, what's some of the progress that you've seen over the last three years? Is it what you anticipated it would be? >> Yeah, it's interesting. I mean, three years ago, I think a lot of people were talking about Industry 4.0, they were talking about the industrial internet of things, they were talking about The Smart Factory, but we saw relatively few very concentrated efforts to advance those. Now as we fast forward three years, we're seeing that the specific capabilities that each one of those topic areas can enable for organizations, has become much clearer. So correspondingly companies have been planning for these types of investments and they're taking action on much of the capability build and quite frankly, starting to see the value. One of the underlying kind of architectural elements that I think are critical as part of the modern Smart Factory is exactly what Brenna touched on. And that was as it relates to the data. Many assets out there even if they're several decades old likely have a wealth of data associated with them. The challenge is that data is either not readily accessible or it's not well understood. And much of the effort that organizations have now undertaken is not only how do they connect, extract and use that information many times on a real time or near real time basis, but now also combining that information with other assets, other parts of the manufacturing facility, or even their manufacturing network to generate that value. >> So Stephen follow on question, how does an organization, a company start that process, if as you said, there's myriad assets of varying age, some really advanced, some really old as well as even from, I guess, a generational perspective in the workforce, you've got multiple generations, for organizations that know we've got data that's hidden, where do they start? >> Yeah, absolutely. And I think a really important element of your question is how do you determine where to start? And the reality is that not all of these solutions are created equal. Not all of the assets have data that's interesting enough to be equal. And so really going through a very concerted effort to understand what are the capabilities we're trying to build And what value does it create for our organization? Aligning that to the objectives and the goals of the organization is critical right from the outset. And we see companies that are being most successful in their implementation of the Smart Factory, following that value orientation. And that might not mean that that value comes tomorrow, It might not come next month, but there's a very clear guidance in terms of how the particular capabilities that are being built will lead to value. Organizations that are not doing that, we tend to see random X visual. We see a lot of different efforts underway with very little tied value and correspondingly many of those efforts don't continue because the executive team, the shareholders aren't going to continue those investments in that space without showing them (mumbles). >> So Brenna walk us through, along what Stephen was just saying. I was reading in your 2020 study that positioning a Smart Factory initiative for value starts with human-centered design and I thought this was really interesting that Deloitte research demonstrated successful teams generally focus on the user first, not the technology. >> Well, yeah. And I think to follow on a little bit to what Stephen said about understanding the value and the goal of what you're trying to do before thinking about the technology you need to rush out and implement goes along with this as well. You want to think about what the user is actually going to be using that data for, what is their job, what information are they going to need and think about from their perspective, what is going to be most helpful and effective for them. And I think the value of this is twofold. One is if talent within your organization and folks on the shop floor, see the value of this data and information, they're going to be more inclined to adopt it because it makes their job easier. But also if you have a tremendous amount of data and information from all the different assets and parts of your facility, if an individual has to sift through all of that, to find what's going to be valuable to them, it's not really going to make their job easier. So human-centered design is really thinking about what that individual needs to do their role, and in a lot of the work that we've done, we've almost thought about it as personas where this particular persona or job needs this information, needs to go through these steps and here's the data information we need to show them to enable them to do that. It's just a way for people to leverage information, to make smarter decisions more quickly. >> How does a manufacturing company do that, Brenna, excuse me, without being siloed, like in business units, so I'm thinking, getting cross-functional support all the way up to the top level. >> Mhhh, that's something that we saw quite a bit in our research that many of the groups or organizations that have successfully enacted a Smart Factory have done so because it's not just coming down from the top, it's also coming up from the bottom. You know, although that may sound like a pejorative term, but coming from all angles of the organization. So we see from the strategic level, this is what we need to do to change the way our organization operates in a more effective way. But from the line of business individuals that are using this information and data every day, we need to think about sort of having a groundswell of support work there as well, so that our team members are using this information. So I think it has to be something that comes from throughout the organization. What we've also found your point about silos is bringing in diverse teams and individuals from throughout the organization who have different types of expertise, different perspectives, different things that they're looking at in different ways that they need to use this technology to do their job, will enable us to make sure that, what we're producing is something that's going to be of value to them. >> And along those lines, Stephen question for you, this must need to be looked at, not as what can we do today or the next six months, but over the long-term. So that ongoing enablement and education is going to be critical. >> Yeah, absolutely. Right. And you know, the reality is that some of these investments that organizations are making into Smart Factory, do take quite a bit of thought, research and assessment and those aren't investments that they're making for the short-term, many of them are long-term. The important part about those investments that organizations are making is that they're creating platforms by which teams can continue to evolve the persona-based type solutions that Brenna referred to, so critical. And so, the flexibility, the adaptability, the agility of those platforms and the investments that are being made, really is one of their critical factors. I did want to just revisit the user adoption of these types of solutions. And, I'm a engineer by education. And I could look up back to early in my career and say, "Hey, look, I built solutions, "using data for manufacturing shop floor equipment. "And I created those solutions for others." But the reality was that I created it in a way that an engineer would you consume that data. And the reality is the persona-based approach really lets us focus on how is a particular individual in their job going to consume that data in a way that enables them to make the best next decision which ultimately has a positive outcome for the company. And in some cases that might mean not exposing them to all the complexities that happen underneath the surface. The modern smartphone, for example, enormously complex device, yet intuitive to use, easy to pick up, easy to interact with. The modern Smart Factory is also very similar in that frame. >> Along those lines of agility, but also designing with certain mindset, culturally IT and OT are different. Brenna, one of the things that I found interesting in the research was the marriage of IT and OT, how do you advise or let's go to clients that were part of that 2020 study, what lessons can the next wave of adopters learn where it comes to bridging those two IT OT mentalities and different cultures? >> Yeah, that's a good question. And I think the different cultures is sort of, key insight that is helpful. With respect to IT, they work on different timeframes, they think about investments in a different way, they think about technology in a different way than individuals who are in OT, who are on the shop floor, who are using these tools every day. and what we found was that bridging that divide and bringing them together, is a challenge that many overlook and something that really the importance of it, can't be overstated. I think to get back to Stephen's point about adoption, if those within the OT space have an understanding of what IT is doing and why, they're just likelier to adopt and to use. And conversely, if those in IT have a deeper understanding of what those in OT are doing and what types of tools they need, they're likelier to come up with solutions that are going to be effective. I think the cultural divide is something that's practically important to understand, to address and not to overlook because I think the last thing that anyone implementing any sort of Smart Factory solution wants is to roll out a solution that was sort of baked in one area, but not taking into account the other as well. >> Great point. Stephen, I want to go back to you for a second. Just understanding along the lines of the cultural differences and the design principles that need to be factored in. When the COVID-19 pandemic hit in March of 2020, for clients that you were talking to that were in whatever stage process of rolling out Smart Factory initiatives, where are they now? And what are some of the advantages that you see that organizations that aren't yet adopting Smart Factory initiatives should be doing to prepare to thrive in this new normal? >> Yeah, absolutely. Let me start with some of those advantages right at the outset. So many organizations now have been looking at advanced solutions, perhaps, to enforce social distancing within the manufacturing environment or perhaps contact tracing within the manufacturing environment and the advantages organizations are seeing that are already on that Smart Factory journey is they're finding they have largely a lot of the infrastructure required to be able to do that already in place. So that has been an enormous accelerant for companies that are already on the journey. The reality is that many organizations, are unable to have their experts, their engineers, their vendors, many of the people that are supporting the equipment and the people in their manufacturing plants around the world, they're not able to get them there. And companies that have been on the Smart Factory journey, specifically as it relates to creating what we would call the digital twin of many of their assets, where they can now see not only visual representations of those assets, but can also see that the data flowing off those assets and in the most advanced solutions, being able to see those together, they'd be able to unlock remote support, in a way that organizations that have not been on this journey simply can't. And we're starting to see some very distinct results, as it relates to those who are able to continue running at scale, and those who are struggling in the COVID environment. >> And Stephen, last question for you. I know you've got a session or a demo on Smart Factory an AI that you're doing at Discover 2020. Tell us a little bit about that and what the participants can anticipate. >> Yeah. So we're really excited to be able to bring Factory AI as we call it, in a live virtualized session. That session is going to cover what we have built around we'll call it a mini manufacturing line. And usually we'd have that with you at the conference, or we take that around the country, to many of our manufacturing clients to really show them, the power of adopting many of these different types of capabilities in the manufacturing environment. So what we're going to be showing and what viewers can expect to see is a demonstration of edge capabilities, of computer vision, of advanced internet of things, all wrapped into several high-impact use cases. So we're looking forward to you're doing that. >> Excellent. Well, Stephen, Brenna, thank you so much for your time discussing The Smart Factor. This is such an interesting provocative topic. I wish we had more time, but appreciate you speaking with me today. >> Thanks for having us. >> Thank you. >> You're watching the cube, Lisa Martin for HPE Discover 2020, The Virtual Experience. Thanks for watching. (upbeat music)

>> Live, from Las Vegas, it's theCUBE covering UiPath Forward Americas 2019. Brought to you by UiPath. >> Welcome back to the Bellagio in Las Vegas, everybody. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante. Day one of UiPath Forward III, hashtag UiPathForward. Elena Christopher is here. She's the senior vice president at HFS Research, and Elena, I'm going to recruit you to be my co-host here. >> Co-host! >> On this power panel. Jean Youngers here, CUBE alum, VP, a Six Sigma Leader at Security Benefit. Great to see you again. >> Thank you. >> Dave: And Amy Chandler, who is the Assistant Vice President and Director of Internal Controls, also from Security Benefit. >> Hello. >> Dave: Thanks for coming on theCUBE. >> Thank you. >> Alright Elena, let's start off with you. You follow this market, you have for some time, you know HFS is sort of anointed as formulating this market place, right? >> Elena: We like to think of ourselves as the voice-- >> You guys were early on. >> The voice of the automation industry. >> So, what are you seeing? I mean, process automation has been around forever, RPA is a hot recent trend, but what are you seeing the last year or two? What are the big trends and rip currents that you see in the market place? >> I mean, I think one of the big trends that's out there, I mean, RPA's come on to the scene. I like how you phrase it Dave, because you refer to it as, rightly so, automation is not new, and so we sort of say the big question out there is, "Is RPA just flavor of the month?" RPA is definitely not, and I come from a firm, we put out a blog earlier this year called "RPA is dead. Long live automation." And that's because, when we look at RPA, and when we think about what it's impact is in the market place, to us the whole point of automation in any form, regardless of whether it's RPA, whether it be good old old school BPM, whatever it may be, it's mission is to drive transformation, and so the HFS perspective, and what all of our research shows and sort of justifies that the goal is, what everyone is striving towards, is to get to that transformation. And so, the reason we put out that piece, the "RPA is dead. Long live integrated automation platforms" is to make the point that if you're not- 'cause what does RPA allow? It affords an opportunity for change to drive transformation so, if you're not actually looking at your processes within your company and taking this opportunity to say, "What can I change, what processes are just bad, "and we've been doing them, I'm not even sure why, "for so long. What can we transform, "what can we optimize, what can we invent?" If you're not taking that opportunity as an enterprise to truly embrace the change and move towards transformation, that's a missed opportunity. So I always say, RPA, you can kind of couch it as one of many technologies, but what RPA has really done for the market place today, it's given business users and business leaders the realization that they can have a role in their own transformation. And that's one of the reasons why it's actually become very important, but a single tool in it's own right will never be the holistic answer. >> So Jean, Elena's bringing up a point about transformation. We, Stew Bennett and I interviewed you last year and we've played those clips a number of times, where you sort of were explaining to us that it didn't make sense before RPA to try to drive Six Sigma into business processes; you couldn't get the return. >> Jean: Right. >> Now you can do it very cheaply. And for Six Sigma or better, is what you use for airplane engines, right? >> Right. >> So, now you're bringing up the business process. So, you're a year in, how's it going? What kind of results are you seeing? Is it meeting your expectations? >> It's been wonderful. It has been the best, it's been probably the most fun I've had in the last fifteen years of work. I have enjoyed, partly because I get to work with this great person here, and she's my COE, and helps stand up the whole RPA solution, but you know, we have gone from finance into investment operations, into operations, you know we've got one sitting right now that we're going to be looking at statements that it's going to be fourteen thousand hours out of both time out as well as staff hours saved, and it's going to touch our customer directly, that they're not going to get a bad statement anymore. And so, you know, it has just been an incredible journey for us over the past year, it really has. >> And so okay Amy, your role is, you're the hardcore practitioner here right? >> Amy: That's right. >> You run the COE. Tell us more about your role, and I'm really interested in how you're bringing it out, RPA to the organization. Is that led by your team, or is it kind of this top-down approach? >> Yeah, this last year, we spent a lot of time trying to educate the lower levels and go from a bottom-up perspective. Pretty much, we implemented our infrastructure, we had a nice solid change management process, we built in logical access, we built in good processes around that so that we'd be able to scale easily over this last year, which kind of sets us up for next year, and everything that we want to accomplish then. >> So Elena, we were talking earlier on theCUBE about you know, RPA, in many ways, I called it cleaning up the crime scene, where stuff is kind of really sort of a mass and huge opportunities to improve. So, my question to you is, it seems like RPA is, in some regards, successful because you can drop it into existing processes, you're not changing things, but in a way, this concerns that, oh well, I'm just kind of paving the cow path. So how much process reinvention should have to occur in order to take advantage of RPA? >> I love that you use that phrase, "paving the cow path." As a New Englander, as you know the roads in Boston are in fact paved cow paths, so we know that can lead to some dodgy roads, and that's part of, and I say it because that's part of what the answer is, because the reinvention, and honestly the optimization has to be part of what the answer is. I said it just a little bit earlier in my comments, you're missing an opportunity with RPA and broader automation if you don't take that step to actually look at your processes and figure out if there's just essentially deadwood that you need to get rid of, things that need to be improved. One of the sort of guidelines, because not all processes are created equal, because you don't want to spend the time and effort, and you guys should chime in on this, you don't want to spend the time and effort to optimize a process if it's not critical to your business, if you're not going to get lift from it, or from some ROI. It's a bit of a continuum, so one of the things that I always encourage enterprises to think about, is this idea of, well what's the, obviously, what business problem are you trying to solve? But as you're going through the process optimization, what kind of user experience do you want out of this? And your users, by the way, you tend to think of your user as, it could be your end customer, it could be your employee, it could even be your partner, but trying to figure out what the experience is that you actually want to have, and then you can actually then look at the process and figure out, do we need to do something different? Do we need to do something completely new to actually optimize that? And then again, line it with what you're trying to solve and what kind of lift you want to get from it. But I'd love to, I mean, hopping over to you guys, you live and breathe this, right? And so I think you have a slightly different opinion than me, but-- >> We do live and breathe it, and every process we look at, we take into consideration. But you've also got to, you have a continuum right? If it's a simple process and we can put it up very quickly, we do, but we've also got ones where one process'll come into us, and a perfect example is our rate changes. >> Amy: Rate changes. >> It came in and there was one process at the very end and they ended up, we did a wing to wing of the whole thing, followed the data all the way back through the process, and I think it hit, what, seven or eight-- >> Yeah. >> Different areas-- >> Areas. >> Of the business, and once we got done with that whole wing to wing to see what we could optimize, it turned into what, sixty? >> Amy: Yeah, sixty plus. Yeah. >> Dave: Sixty plus what? >> Bot processes from one entry. >> Yeah. >> And so, right now, we've got 189 to 200 processes in the back log. And so if you take that, and exponentially increase it, we know that there's probably actually 1,000 to 2,000 more processes, at minimum, that we can hit for the company, and we need to look at those. >> Yeah, and I will say, the wing to wing approach is very important because you're following the data as it's moving along. So if you don't do that, if you only focus on a small little piece of it, you don't what's happening to the data before it gets to you and you don't know what's going to happen to it when it leaves you, so you really do have to take that wing to wing approach. >> So, internal controls is in your title, so talking about scale, it's a big theme here at UiPath, and these days, things scale really fast, and boo-boos can happen really fast. So how are you ensuring, you know that the edicts of the organization are met, whether it's security, compliance, governance? Is that part of your role? >> Yeah, we've actually kept internal audit and internal controls, and in fact, our external auditors, EY. We've kept them all at the table when we've gone through processes, when we've built out our change management process, our logical access. When we built our whole process from beginning to end they kind of sat at the table with us and kind of went over everything to make sure that we were hitting all the controls that we needed to do. >> And actually, I'd like to piggyback on that comment, because just that inclusion of the various roles, that's what we found as an emerging best practice, and in all of our research and all of the qualitative conversations that we have with enterprises and service providers, is because if you do things, I mean it applies on multiple levels, because if you do things in a silo, you'll have siloed impact. If you bring the appropriate constituents to the table, you're going to understand their perspective, but it's going to have broader reach. So it helps alleviate the silos but it also supports the point that you just made Amy, about looking at the processes end to end, because you've got the necessary constituents involved so you know the context, and then, I believe, I mean I think you guys shared this with me, that particularly when audit's involved, you're perhaps helping cultivate an understanding of how even their processes can improve as well. >> Right. >> That is true, and from an overall standpoint with controls, I think a lot of people don't realize that a huge benefit is your controls, cause if you're automating your controls, from an internal standpoint, you're not going to have to test as much, just from an associate process owner paying attention to their process to the internal auditors, they're not going to have to test as much either, and then your external auditors, which that's revenue. I mean, that's savings. >> You lower your auditing bill? >> Yeah. Yeah. >> Well we'll see right? >> Yeah. (laughter) >> That's always the hope. >> Don't tell EY. (laughter) So I got to ask you, so you're in a little over a year So I don't know if you golf, but you know a mulligan in golf. If you had a mulligan, a do over, what would you do over? >> The first process we put in place. At least for me, it breaks a lot, and we did it because at the time, we were going through decoupling and trying to just get something up to make sure that what we stood up was going to work and everything, and so we kind of slammed it in, and we pay for that every quarter, and so actually it's on our list to redo. >> Yeah, we automated a bad process. >> Yeah, we automated a bad process. >> That's a really good point. >> So we pay for it in maintenance every quarter, we pay for it, cause it breaks inevitably. >> Yes. >> Okay so what has to happen? You have to reinvent the process, to Elena's? >> Yes, you know, we relied on a process that somebody else had put in place, and in looking at it, it was kind of a up and down and through the hoop and around this way to get what they needed, and you know there's much easier ways to get the data now. And that's what we're doing. In fact, we've built our own, we call it a bot mart. That's where all our data goes, they won't let us touch the other data marts and so forth so they created us a bot mart, and anything that we need data for, they dump in there for us and then that's where our bot can hit, and our bot can hit it at anytime of the day or night when we need the data, and so it's worked out really well for us, and so the bot mart kind of came out of that project of there's got to be a better way. How can we do this better instead of relying on these systems that change and upgrade and then we run the bot and its working one day and the next day, somebody has gone in and tweaked something, and when all's I really need out of that system is data, that's all I need. I don't need, you know, a report. I don't need anything like that, cause the reports change and they get messed up. I just want the raw data, and so that's what we're starting to do. >> How do you ensure that the data is synchronized with your other marts and warehouses, is that a problem? >> Not yet. >> No not yet! (laughter) >> I'm wondering cause I was thinking the exact same question Dave, because on one hand its a nice I think step from a governance standpoint. You have what you need, perhaps IT or whomever your data curators are, they're not going to have a heart attack that you're touching stuff that they don't want you to, but then there is that potential for synchronization issues, cause that whole concept of golden source implies one copy if you will. >> Well, and it is. It's all coming through, we have a central data repository that the data's going to come through, and it's all sitting there, and then it'll move over, and to me, what I most worry about, like I mentioned on the statement once, okay, I get my data in, is it the same data that got used to create those statements? And as we're doing the testing and as we're looking at going live, that's one of our huge test cases. We need to understand what time that data comes in, when will it be into our bot mart, so when can I run those bots? You know, cause they're all going to be unattended on those, so you know, the timing is critical, and so that's why I said not yet. >> Dave: (chuckle) >> But you want to know what, we can build the bot to do that compare of the data for us. >> Haha all right. I love that. >> I saw a stat the other day. I don't know where it was, on Twitter or maybe it was your data, that more money by whatever, 2023 is going to be spent on chat bots than mobile development. >> Jean: I can imagine, yes. >> What are you doing with chat bots? And how are you using them? >> Do you want to answer that one or do you want me to? >> Go ahead. >> Okay so, part of the reason I'm so enthralled by the chat bot or personal assistant or anything, is because the unattended robots that we have, we have problems making sure that people are doing what they're supposed to be doing in prep. We have some in finance, and you know, finance you have a very fine line of what you can automate and what you need the user to still understand what they're doing, right? And so we felt like we had a really good, you know, combination of that, but in some instances, they forget to do things, so things aren't there and we get the phone call the bot broke, right? So part of the thing I'd like to do is I'd like to move that back to an unattended bot, and I'm going to put a chat bot in front of it, and then all's they have to do is type in "run my bot" and it'll come up if they have more than one bot, it'll say "which one do you want to run?" They'll click it and it'll go. Instead of having to go out on their machine, figure out where to go, figure out which button to do, and in the chat I can also send them a little message, "Did you run your other reports? Did you do this?" You know, so, I can use it for the end user, to make that experience for them better. And plus, we've got a lot of IT, we've got a lot of HR stuff that can fold into that, and then RPA all in behind it, kind of the engine on a lot of it. >> I mean you've child proofed the bot. >> Exactly! There you go. There you go. >> Exactly. Exactly. And it also provides a means to be able to answer those commonly asked questions for HR for example. You know, how much vacation time do I have? When can I change my benefits? Examples of those that they answer frequently every day. So that provides another avenue for utilization of the chat bot. >> And if I may, Dave, it supports a concept that I know we were talking about yesterday. At HFS it's our "Triple-A Trifecta", but it's taking the baseline of automation, it intersects with components of AI, and then potentially with analytics. This is starting to touch on some of the opportunities to look at other technologies. You say chat bots. At HFS we don't use the term chat bot, just because we like to focus and emphasize the cognitive capability if you will. But in any case, you guys essentially are saying, well RPA is doing great for what we're using RPA for, but we need a little bit of extension of functionality, so we're layering in the chat bot or cognitive assistant. So it's a nice example of some of that extension of really seeing how it's, I always call it the power of and if you will. Are you going to layer these things in to get what you need out of it? What best solves your business problems? Just a very practical approach I think. >> So Elena, Guy has a session tomorrow on predictions. So we're going to end with some predictions. So our RPA is dead, (chuckle) will it be resuscitated? What's the future of RPA look like? Will it live up to the hype? I mean so many initiatives in our industry haven't. I always criticize enterprise data warehousing and ETL and big data is not living up to the hype. Will RPA? >> It's got a hell of a lot of hype to live up to, I'll tell you that. So, back to some of our causality about why we even said it's dead. As a discrete software category, RPA is clearly not dead at all. But unless it's helping to drive forward with transformation, and even some of the strategies that these fine ladies from Security Benefit are utilizing, which is layering in additional technology. That's part of the path there. But honestly, the biggest challenge that you have to go through to get there and cannot be underestimated, is the change that your organization has to go through. Cause think about it, if we look at the grand big vision of where RPA and broader intelligent automation takes us, the concept of creating a hybrid workforce, right? So what's a hybrid workforce? It's literally our humans complemented by digital workers. So it still sounds like science fiction. To think that any enterprise could try and achieve some version of that and that it would be A, fast or B, not take a lot of change management, is absolutely ludicrous. So it's just a very practical approach to be eyes wide open, recognize that you're solving problems but you have to want to drive change. So to me, and sort of the HFS perspective, continues to be that if RPA is not going to die a terrible death, it needs to really support that vision of transformation. And I mean honestly, we're here at a UiPath event, they had many announcements today that they're doing a couple of things. Supporting core functionality of RPA, literally adding in process discovery and mining capabilities, adding in analytics to help enterprises actually track what your benefit is. >> Jean: Yes. >> These are very practical cases that help RPA live another day. But they're also extending functionality, adding in their whole announcement around AI fabric, adding in some of the cognitive capability to extend the functionality. And so prediction-wise, RPA as we know it three years from now is not going to look like RPA at all. I'm not going to call it AI, but it's going to become a hybrid, and it's honestly going to look a lot like that Triple-A Trifecta I mentioned. >> Well, and UiPath, and I presume other suppliers as well, are expanding their markets. They're reaching, you hear about citizens developers and 100% of the workforce. Obviously you guys are excited and you see a long-run way for RPA. >> Jean: Yeah, we do. >> I'll give you the last word. >> It's been a wonderful journey thus far. After this morning's event where they showed us everything, I saw a sneak peek yesterday during the CAB, and I had a list of things I wanted to talk to her about already when I came out of there. And then she saw more of 'em today, and I've got a pocketful of notes of stuff that we're going to take back and do. I really, truly believe this is the future and we can do so much. Six Sigma has kind of gotten a rebirth. You go in and look at your processes and we can get those to perfect. I mean, that's what's so cool. It is so cool that you can actually tell somebody, I can do something perfect for you. And how many people get to do that? >> It's back to the user experience, right? We can make this wildly functional to meet the need. >> Right, right. And I don't think RPA is the end all solution, I think it's just a great tool to add to your toolkit and utilize moving forward. >> Right. All right we'll have to leave it there. Thanks ladies for coming on, it was a great segment. Really appreciate your time. >> Thanks. >> Thank you. >> Thank you for watching, everybody. This is Dave Vellante with theCUBE. We'll be right back from UiPath Forward III from Las Vegas, right after this short break. (technical music)

>> Live, from Las Vegas, it's theCUBE covering UiPath Forward Americas 2019. Brought to you by UiPath. >> Welcome back to the Bellagio in Las Vegas, everybody. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante. Day one of UiPath Forward III, hashtag UiPathForward. Elena Christopher is here. She's the senior vice president at HFS Research, and Elena, I'm going to recruit you to be my co-host here. >> Co-host! >> On this power panel. Jean Youngers here, CUBE alum, VP, a Six Sigma Leader at Security Benefit. Great to see you again. >> Thank you. >> Dave: And Amy Chandler, who is the Assistant Vice President and Director of Internal Controls, also from Security Benefit. >> Hello. >> Dave: Thanks for coming on theCUBE. >> Thank you. >> Alright Elena, let's start off with you. You follow this market, you have for some time, you know HFS is sort of anointed as formulating this market place, right? >> Elena: We like to think of ourselves as the voice-- >> You guys were early on. >> The voice of the automation industry. >> So, what are you seeing? I mean, process automation has been around forever, RPA is a hot recent trend, but what are you seeing the last year or two? What are the big trends and rip currents that you see in the market place? >> I mean, I think one of the big trends that's out there, I mean, RPA's come on to the scene. I like how you phrase it Dave, because you refer to it as, rightly so, automation is not new, and so we sort of say the big question out there is, "Is RPA just flavor of the month?" RPA is definitely not, and I come from a firm, we put out a blog earlier this year called "RPA is dead. Long live automation." And that's because, when we look at RPA, and when we think about what it's impact is in the market place, to us the whole point of automation in any form, regardless of whether it's RPA, whether it be good old old school BPM, whatever it may be, it's mission is to drive transformation, and so the HFS perspective, and what all of our research shows and sort of justifies that the goal is, what everyone is striving towards, is to get to that transformation. And so, the reason we put out that piece, the "RPA is dead. Long live integrated automation platforms" is to make the point that if you're not- 'cause what does RPA allow? It affords an opportunity for change to drive transformation so, if you're not actually looking at your processes within your company and taking this opportunity to say, "What can I change, what processes are just bad, "and we've been doing them, I'm not even sure why, "for so long. What can we transform, "what can we optimize, what can we invent?" If you're not taking that opportunity as an enterprise to truly embrace the change and move towards transformation, that's a missed opportunity. So I always say, RPA, you can kind of couch it as one of many technologies, but what RPA has really done for the market place today, it's given business users and business leaders the realization that they can have a role in their own transformation. And that's one of the reasons why it's actually become very important, but a single tool in it's own right will never be the holistic answer. >> So Jean, Elena's bringing up a point about transformation. We, Stew Bennett and I interviewed you last year and we've played those clips a number of times, where you sort of were explaining to us that it didn't make sense before RPA to try to drive Six Sigma into business processes; you couldn't get the return. >> Jean: Right. >> Now you can do it very cheaply. And for Six Sigma or better, is what you use for airplane engines, right? >> Right. >> So, now you're bringing up the business process. So, you're a year in, how's it going? What kind of results are you seeing? Is it meeting your expectations? >> It's been wonderful. It has been the best, it's been probably the most fun I've had in the last fifteen years of work. I have enjoyed, partly because I get to work with this great person here, and she's my COE, and helps stand up the whole RPA solution, but you know, we have gone from finance into investment operations, into operations, you know we've got one sitting right now that we're going to be looking at statements that it's going to be fourteen thousand hours out of both time out as well as staff hours saved, and it's going to touch our customer directly, that they're not going to get a bad statement anymore. And so, you know, it has just been an incredible journey for us over the past year, it really has. >> And so okay Amy, your role is, you're the hardcore practitioner here right? >> Amy: That's right. >> You run the COE. Tell us more about your role, and I'm really interested in how you're bringing it out, RPA to the organization. Is that led by your team, or is it kind of this top-down approach? >> Yeah, this last year, we spent a lot of time trying to educate the lower levels and go from a bottom-up perspective. Pretty much, we implemented our infrastructure, we had a nice solid change management process, we built in logical access, we built in good processes around that so that we'd be able to scale easily over this last year, which kind of sets us up for next year, and everything that we want to accomplish then. >> So Elena, we were talking earlier on theCUBE about you know, RPA, in many ways, I called it cleaning up the crime scene, where stuff is kind of really sort of a mass and huge opportunities to improve. So, my question to you is, it seems like RPA is, in some regards, successful because you can drop it into existing processes, you're not changing things, but in a way, this concerns that, oh well, I'm just kind of paving the cow path. So how much process reinvention should have to occur in order to take advantage of RPA? >> I love that you use that phrase, "paving the cow path." As a New Englander, as you know the roads in Boston are in fact paved cow paths, so we know that can lead to some dodgy roads, and that's part of, and I say it because that's part of what the answer is, because the reinvention, and honestly the optimization has to be part of what the answer is. I said it just a little bit earlier in my comments, you're missing an opportunity with RPA and broader automation if you don't take that step to actually look at your processes and figure out if there's just essentially deadwood that you need to get rid of, things that need to be improved. One of the sort of guidelines, because not all processes are created equal, because you don't want to spend the time and effort, and you guys should chime in on this, you don't want to spend the time and effort to optimize a process if it's not critical to your business, if you're not going to get lift from it, or from some ROI. It's a bit of a continuum, so one of the things that I always encourage enterprises to think about, is this idea of, well what's the, obviously, what business problem are you trying to solve? But as you're going through the process optimization, what kind of user experience do you want out of this? And your users, by the way, you tend to think of your user as, it could be your end customer, it could be your employee, it could even be your partner, but trying to figure out what the experience is that you actually want to have, and then you can actually then look at the process and figure out, do we need to do something different? Do we need to do something completely new to actually optimize that? And then again, line it with what you're trying to solve and what kind of lift you want to get from it. But I'd love to, I mean, hopping over to you guys, you live and breathe this, right? And so I think you have a slightly different opinion than me, but-- >> We do live and breathe it, and every process we look at, we take into consideration. But you've also got to, you have a continuum right? If it's a simple process and we can put it up very quickly, we do, but we've also got ones where one process'll come into us, and a perfect example is our rate changes. >> Amy: Rate changes. >> It came in and there was one process at the very end and they ended up, we did a wing to wing of the whole thing, followed the data all the way back through the process, and I think it hit, what, seven or eight-- >> Yeah. >> Different areas-- >> Areas. >> Of the business, and once we got done with that whole wing to wing to see what we could optimize, it turned into what, sixty? >> Amy: Yeah, sixty plus. Yeah. >> Dave: Sixty plus what? >> Bot processes from one entry. >> Yeah. >> And so, right now, we've got 189 to 200 processes in the back log. And so if you take that, and exponentially increase it, we know that there's probably actually 1,000 to 2,000 more processes, at minimum, that we can hit for the company, and we need to look at those. >> Yeah, and I will say, the wing to wing approach is very important because you're following the data as it's moving along. So if you don't do that, if you only focus on a small little piece of it, you don't what's happening to the data before it gets to you and you don't know what's going to happen to it when it leaves you, so you really do have to take that wing to wing approach. >> So, internal controls is in your title, so talking about scale, it's a big theme here at UiPath, and these days, things scale really fast, and boo-boos can happen really fast. So how are you ensuring, you know that the edicts of the organization are met, whether it's security, compliance, governance? Is that part of your role? >> Yeah, we've actually kept internal audit and internal controls, and in fact, our external auditors, EY. We've kept them all at the table when we've gone through processes, when we've built out our change management process, our logical access. When we built our whole process from beginning to end they kind of sat at the table with us and kind of went over everything to make sure that we were hitting all the controls that we needed to do. >> And actually, I'd like to piggyback on that comment, because just that inclusion of the various roles, that's what we found as an emerging best practice, and in all of our research and all of the qualitative conversations that we have with enterprises and service providers, is because if you do things, I mean it applies on multiple levels, because if you do things in a silo, you'll have siloed impact. If you bring the appropriate constituents to the table, you're going to understand their perspective, but it's going to have broader reach. So it helps alleviate the silos but it also supports the point that you just made Amy, about looking at the processes end to end, because you've got the necessary constituents involved so you know the context, and then, I believe, I mean I think you guys shared this with me, that particularly when audit's involved, you're perhaps helping cultivate an understanding of how even their processes can improve as well. >> Right. >> That is true, and from an overall standpoint with controls, I think a lot of people don't realize that a huge benefit is your controls, cause if you're automating your controls, from an internal standpoint, you're not going to have to test as much, just from an associate process owner paying attention to their process to the internal auditors, they're not going to have to test as much either, and then your external auditors, which that's revenue. I mean, that's savings. >> You lower your auditing bill? >> Yeah. Yeah. >> Well we'll see right? >> Yeah. (laughter) >> That's always the hope. >> Don't tell EY. (laughter) So I got to ask you, so you're in a little over a year So I don't know if you golf, but you know a mulligan in golf. If you had a mulligan, a do over, what would you do over? >> The first process we put in place. At least for me, it breaks a lot, and we did it because at the time, we were going through decoupling and trying to just get something up to make sure that what we stood up was going to work and everything, and so we kind of slammed it in, and we pay for that every quarter, and so actually it's on our list to redo. >> Yeah, we automated a bad process. >> Yeah, we automated a bad process. >> That's a really good point. >> So we pay for it in maintenance every quarter, we pay for it, cause it breaks inevitably. >> Yes. >> Okay so what has to happen? You have to reinvent the process, to Elena's? >> Yes, you know, we relied on a process that somebody else had put in place, and in looking at it, it was kind of a up and down and through the hoop and around this way to get what they needed, and you know there's much easier ways to get the data now. And that's what we're doing. In fact, we've built our own, we call it a bot mart. That's where all our data goes, they won't let us touch the other data marts and so forth so they created us a bot mart, and anything that we need data for, they dump in there for us and then that's where our bot can hit, and our bot can hit it at anytime of the day or night when we need the data, and so it's worked out really well for us, and so the bot mart kind of came out of that project of there's got to be a better way. How can we do this better instead of relying on these systems that change and upgrade and then we run the bot and its working one day and the next day, somebody has gone in and tweaked something, and when all's I really need out of that system is data, that's all I need. I don't need, you know, a report. I don't need anything like that, cause the reports change and they get messed up. I just want the raw data, and so that's what we're starting to do. >> How do you ensure that the data is synchronized with your other marts and warehouses, is that a problem? >> Not yet. >> No not yet! (laughter) >> I'm wondering cause I was thinking the exact same question Dave, because on one hand its a nice I think step from a governance standpoint. You have what you need, perhaps IT or whomever your data curators are, they're not going to have a heart attack that you're touching stuff that they don't want you to, but then there is that potential for synchronization issues, cause that whole concept of golden source implies one copy if you will. >> Well, and it is. It's all coming through, we have a central data repository that the data's going to come through, and it's all sitting there, and then it'll move over, and to me, what I most worry about, like I mentioned on the statement once, okay, I get my data in, is it the same data that got used to create those statements? And as we're doing the testing and as we're looking at going live, that's one of our huge test cases. We need to understand what time that data comes in, when will it be into our bot mart, so when can I run those bots? You know, cause they're all going to be unattended on those, so you know, the timing is critical, and so that's why I said not yet. >> Dave: (chuckle) >> But you want to know what, we can build the bot to do that compare of the data for us. >> Haha all right. I love that. >> I saw a stat the other day. I don't know where it was, on Twitter or maybe it was your data, that more money by whatever, 2023 is going to be spent on chat bots than mobile development. >> Jean: I can imagine, yes. >> What are you doing with chat bots? And how are you using them? >> Do you want to answer that one or do you want me to? >> Go ahead. >> Okay so, part of the reason I'm so enthralled by the chat bot or personal assistant or anything, is because the unattended robots that we have, we have problems making sure that people are doing what they're supposed to be doing in prep. We have some in finance, and you know, finance you have a very fine line of what you can automate and what you need the user to still understand what they're doing, right? And so we felt like we had a really good, you know, combination of that, but in some instances, they forget to do things, so things aren't there and we get the phone call the bot broke, right? So part of the thing I'd like to do is I'd like to move that back to an unattended bot, and I'm going to put a chat bot in front of it, and then all's they have to do is type in "run my bot" and it'll come up if they have more than one bot, it'll say "which one do you want to run?" They'll click it and it'll go. Instead of having to go out on their machine, figure out where to go, figure out which button to do, and in the chat I can also send them a little message, "Did you run your other reports? Did you do this?" You know, so, I can use it for the end user, to make that experience for them better. And plus, we've got a lot of IT, we've got a lot of HR stuff that can fold into that, and then RPA all in behind it, kind of the engine on a lot of it. >> I mean you've child proofed the bot. >> Exactly! There you go. There you go. >> Exactly. Exactly. And it also provides a means to be able to answer those commonly asked questions for HR for example. You know, how much vacation time do I have? When can I change my benefits? Examples of those that they answer frequently every day. So that provides another avenue for utilization of the chat bot. >> And if I may, Dave, it supports a concept that I know we were talking about yesterday. At HFS it's our "Triple-A Trifecta", but it's taking the baseline of automation, it intersects with components of AI, and then potentially with analytics. This is starting to touch on some of the opportunities to look at other technologies. You say chat bots. At HFS we don't use the term chat bot, just because we like to focus and emphasize the cognitive capability if you will. But in any case, you guys essentially are saying, well RPA is doing great for what we're using RPA for, but we need a little bit of extension of functionality, so we're layering in the chat bot or cognitive assistant. So it's a nice example of some of that extension of really seeing how it's, I always call it the power of and if you will. Are you going to layer these things in to get what you need out of it? What best solves your business problems? Just a very practical approach I think. >> So Elena, Guy has a session tomorrow on predictions. So we're going to end with some predictions. So our RPA is dead, (chuckle) will it be resuscitated? What's the future of RPA look like? Will it live up to the hype? I mean so many initiatives in our industry haven't. I always criticize enterprise data warehousing and ETL and big data is not living up to the hype. Will RPA? >> It's got a hell of a lot of hype to live up to, I'll tell you that. So, back to some of our causality about why we even said it's dead. As a discrete software category, RPA is clearly not dead at all. But unless it's helping to drive forward with transformation, and even some of the strategies that these fine ladies from Security Benefit are utilizing, which is layering in additional technology. That's part of the path there. But honestly, the biggest challenge that you have to go through to get there and cannot be underestimated, is the change that your organization has to go through. Cause think about it, if we look at the grand big vision of where RPA and broader intelligent automation takes us, the concept of creating a hybrid workforce, right? So what's a hybrid workforce? It's literally our humans complemented by digital workers. So it still sounds like science fiction. To think that any enterprise could try and achieve some version of that and that it would be A, fast or B, not take a lot of change management, is absolutely ludicrous. So it's just a very practical approach to be eyes wide open, recognize that you're solving problems but you have to want to drive change. So to me, and sort of the HFS perspective, continues to be that if RPA is not going to die a terrible death, it needs to really support that vision of transformation. And I mean honestly, we're here at a UiPath event, they had many announcements today that they're doing a couple of things. Supporting core functionality of RPA, literally adding in process discovery and mining capabilities, adding in analytics to help enterprises actually track what your benefit is. >> Jean: Yes. >> These are very practical cases that help RPA live another day. But they're also extending functionality, adding in their whole announcement around AI fabric, adding in some of the cognitive capability to extend the functionality. And so prediction-wise, RPA as we know it three years from now is not going to look like RPA at all. I'm not going to call it AI, but it's going to become a hybrid, and it's honestly going to look a lot like that Triple-A Trifecta I mentioned. >> Well, and UiPath, and I presume other suppliers as well, are expanding their markets. They're reaching, you hear about citizens developers and 100% of the workforce. Obviously you guys are excited and you see a long-run way for RPA. >> Jean: Yeah, we do. >> I'll give you the last word. >> It's been a wonderful journey thus far. After this morning's event where they showed us everything, I saw a sneak peek yesterday during the CAB, and I had a list of things I wanted to talk to her about already when I came out of there. And then she saw more of 'em today, and I've got a pocketful of notes of stuff that we're going to take back and do. I really, truly believe this is the future and we can do so much. Six Sigma has kind of gotten a rebirth. You go in and look at your processes and we can get those to perfect. I mean, that's what's so cool. It is so cool that you can actually tell somebody, I can do something perfect for you. And how many people get to do that? >> It's back to the user experience, right? We can make this wildly functional to meet the need. >> Right, right. And I don't think RPA is the end all solution, I think it's just a great tool to add to your toolkit and utilize moving forward. >> Right. All right we'll have to leave it there. Thanks ladies for coming on, it was a great segment. Really appreciate your time. >> Thanks. >> Thank you. >> Thank you for watching, everybody. This is Dave Vellante with theCUBE. We'll be right back from UiPath Forward III from Las Vegas, right after this short break. (technical music)

(upbeat music) >> Announcer: Live from Las Vegas, it's theCUBE! Covering UIPath FORWARD America's 2019. Brought to you by UIPath. >> Welcome back, everyone, to theCUBE's live coverage of UIPath FORWARD, here in Sin City, Las Vegas Nevada. I'm your host, Rebecca Knight, co-hosting alongside Dave Velante. We have two guests for this segment. We have Kurt Carlson, Associate Dean for faculty and academic affairs of the Mason School of Business at the college of William and Mary. Thanks for coming on the show. >> Thanks you for having me. >> Rebecca: And we have Tom Clancy, the SVP of learning at UIPath, thank you so much. >> Great to be here. >> You're a Cube alum, so thank you for coming back. >> I've been here a few times. >> A Cube veteran, I should say. >> I think 10 years or so >> So we're talking today about a robot for every student, this was just announced in August, William and Mary is the first university in the US to provide automation software to every undergraduate student, thanks to a four million dollar investment from UIPath. Tell us a little bit about this program, Kurt, how it works and what you're trying to do here. >> Yeah, so first of all, to Tom and the people at UIPath for making this happen. This is a bold and incredible initiative, one that, frankly, when we had it initially, we thought that maybe we could get a robot for every student, we weren't sure that other people would be willing to go along with that, but UIPath was, they see the vision, and so it was really a meeting of the minds on a common purpose. The idea was pretty simple, this technology is transforming the world in a way that students, we think it's going to transform the way that students actually are students. But it's certainly transforming the world that our students are going into. And so, we want to give them exposure to it. We wanted to try and be the first business school on the planet that actually prepares students not just for the way RPA's being used today, but the way that it's going to be used when AI starts to take hold, when it becomes the gateway to AI three, four, five years down the road. So, we talked to UIPath, they thought it was a really good idea, we went all in on it. Yeah, all of our starting juniors in the business school have robots right now, they've all been trained through the academy live session putting together a course, it's very exciting. >> So, Tom, you've always been an innovator when it comes to learning, here's my question. How come we didn't learn this school stuff when we were in college? We learned Fortran. >> I don't know, I only learned BASIC, so I can't speak to that. >> So you know last year we talked about how you're scaling, learning some of the open, sort of philosophy that you have. So, give us the update on how you're pushing learning FORWARD, and why the College of William and Mary. >> Okay, so if you buy into a bot for every worker, or a bot for every desktop, that's a lot of bots, that's a lot of desktops, right? There's studies out there from the research companies that say that there's somewhere a hundred and 200 million people that need to be educated on RPA, RPA/AI. So if you buy into that, which we do, then traditional learning isn't going to do it. We're going to miss the boat. So we have a multi-pronged approach. The first thing is to democratize RPA learning. Two and a half years ago we made, we created RPA Academy, UIPath academy, and 100% free. After two and a half years, we have 451,000 people go through the academy courses, that's huge. But we think there's a lot more. Over the next next three years we think we'll train at least two million people. But the challenge still is, if we train five million people, there's still a hundred million that need to know about it. So, the second biggest thing we're doing is, we went out, last year at this event, we announced our academic alliance program. We had one university, now we're approaching 400 universities. But what we're doing with William and Mary is a lot more than just providing a course, and I'll let Kurt talk to that, but there is so much more that we could be doing to educate our students, our youth, upscaling, rescaling the existing workforce. When you break down that hundred million people, they come from a lot of different backgrounds, and we're trying to touch as many people as we can. >> You guys are really out ahead of the curve. Oftentimes, I mean, you saw this a little bit with data science, saw some colleges leaning in. So what lead you guys to the decision to actually invest and prioritize RPA? >> Yeah, I think what we're trying to accomplish requires incredibly smart students. It requires students that can sit at the interface between what we would think of today as sort of an RPA developer and a decision maker who would be stroking the check or signing the contract. There's got to be somebody that sits in that space that understands enough about how you would actually execute this implementation. What's the right buildout of that, how we're going to build a portfolio of bots, how we're going to prioritize the different processes that we might automate, How we're going to balance some processes that might have a nice ROI but be harder for the individual who's process is being automated to absorb against processes that the individual would love to have automated, but might not have as great of an ROI. How do you balance that whole set of things? So what we've done is worked with UIPath to bring together the ideas of automation with the ideas of being a strategic thinker in process automation, and we're designing a course in collaboration to help train our students to hit the ground running. >> Rebecca, it's really visionary, isn't it? I mean it's not just about using the tooling, it's about how to apply the tooling to create competitive advantage or change lives. >> I used to cover business education for the Financial Times, so I completely agree that this really is a game changer for the students to have this kind of access to technology and ability to explore this leading edge of software robotics and really be, and graduate from college. This isn't even graduate school, they're graduating from college already having these skills. So tell me, Kurt, what are they doing? What is the course, what does it look like, how are they using this in the classroom? >> The course is called a one credit. It's 14 hours but it actually turns into about 42 when you add this stuff that's going on outside of class. They're learning about these large conceptual issues around how do you prioritize which processes, what's the process you should go through to make sure that you measure in advance of implementation so that you can do an audit on the backend to have proof points on the effectiveness, so you got to measure in advance, creating a portfolio of perspective processes and then scoring them, how do you do that, so they're learning all that sort of conceptual straight business slash strategy implementation stuff, so that's on the first half, and to keep them engaged with this software, we're giving them small skills, we're calling them skillets. Small skills in every one of those sessions that add up to having a fully automated and programmed robot. Then they're going to go into a series of days where every one of those days they're going to learn a big skill. And the big skills are ones that are going to be useful for the students in their lives as people, useful in lives as students, and useful in their lives as entrepreneurs using RPA to create new ventures, or in the organizations they go to. We've worked with UIPath and with our alums who've implement this, folks at EY, Booz. In fact, we went up to DC, we had a three hour meeting with these folks. So what are the skills students need to learn, and they told us, and so we build these three big classes, each around each one of those skills so that our students are going to come out with the ability to be business translators, not necessarily the hardcore programmers. We're not going to prevent them from doing that, but to be these business translators that sit between the programming and the decision makers. >> That's huge because, you know, like, my son's a senior in college. He and his friends, they all either want to work for Amazon, Google, an investment bank, or one of the big SIs, right? So this is a perfect role for a consultant to go in and advise. Tom, I wanted to ask you, and you and I have known each other for a long time, but one of the reasons I think you were successful at your previous company is because you weren't just focused on a narrow vendor, how to make metrics work, for instance. I presume you're taking the same philosophy here. It transcends UIPath and is really more about, you know, the category if you will, the potential. Can you talk about that? >> So we listen to our customers and now we listen to the universities too, and they're going to help guide us to where we need to go. Most companies in tech, you work with marketing, and you work with engineering, and you build product courses. And you also try to sell those courses, because it's a really good PNL when you sell training. We don't think that's right for the industry, for UIPath, or for our customers, or our partners. So when we democratize learning, everything else falls into place. So, as we go forward, we have a bunch of ideas. You know, as we get more into AI, you'll see more AI type courses. We'll team with 400 universities now, by end of next year, we'll probably have a thousand universities signed up. And so, there's a lot of subject matter expertise, and if they come to us with ideas, you mentioned a 14 hour course, we have a four hour course, and we also have a 60 hour course. So we want to be as flexible as possible, because different universities want to apply it in different ways. So we also heard about Lean Six Sigma. I mean, sorry, Lean RPA, so we might build a course on Lean RPA, because that's really important. Solution architect is one of the biggest gaps in the industry right now so, so we look to where these gaps are, we listen to everybody, and then we just execute. >> Well, it's interesting you said Six Sigma, we have Jean Younger coming on, she's a Six Sigma expert. I don't know if she's a black belt, but she's pretty sure. She talks about how to apply RPA to make business processes in Six Sigma, but you would never spend the time and money, I mean, if it's an airplane engine, for sure, but now, so that's kind of transformative. Kurt, I'm curious as to how you, as a college, market this. You know, you're very competitive industry, if you will. So how do you see this attracting students and separating you guys from the pack? >> Well, it's a two separate things. How do we actively try to take advantage of this, and what effects is it having already? Enrollments to the business school, well. Students at William and Mary get admitted to William and Mary, and they're fantastic, amazingly good undergraduate students. The best students at William and Mary come to the Raymond A. Mason school of business. If you take our undergraduate GPA of students in the business school, they're top five in the country. So what we've seen since we've announced this is that our applications to the business school are up. I don't know that it's a one to one correlation. >> Tom: I think it is. >> I believe it's a strong predictor, right? And part because it's such an easy sell. And so, when we talk to those alums and friends in DC and said, tell us why this is, why our students should do this, they said, well, if for no other reason, we are hiring students that have these skills into data science lines in the mid 90s. When I said that to my students, they fell out of their chairs. So there's incredible opportunity here for them, that's the easy way to market it internally, it aligns with things that are happening at William and Mary, trying to be innovative, nimble, and entrepreneurial. We've been talking about being innovative, nimble, and entrepreneurial for longer than we've been doing it, we believe we're getting there, we believe this is the type of activity that would fit for that. As far as promoting it, we're telling everybody that will listen that this is interesting, and people are listening. You know, the standard sort of marketing strategy that goes around, and we are coordinating with UIPath on that. But internally, this sells actually pretty easy. This is something people are looking for, we're going to make it ready for the world the way that it's going to be now and in the future. >> Well, I imagine the big consultants are hovering as well. You know, you mentioned DC, Booz Allen, Hughes and DC, and Excensior, EY, Deloitte, PWC, IBM itself. I mean it's just, they all want the best and the brightest, and now you're going to have this skill set that is a sweet spot for their businesses. >> Kurt: That's the plan. >> I'm just thinking back to remembering who these people are, these are 19 and 20 year olds. They've never experienced the dreariness of work and the drudge tasks that we all know well. So, what are you, in terms of this whole business translator idea, that they're going to be the be people that sit in the middle and can sort of be these people who can speak both languages. What kind of skills are you trying to impart to them, because it is a whole different skill set. >> Our vision is that in two or three years, the nodes and the processes that are currently... That currently make implementing RPA complex and require significant programmer skills, these places where, right now, there's a human making a relatively mundane decision, but it's sill a model. There's a decision node there. We think AI is going to take over that. The simple, AI's going to simply put models into those decision nodes. We also think a lot of the programming that takes place, you're seeing it now with studio X, a lot of the programming is going to go away. And what that's going to do is it's going to elevate the business process from the mundane to the more human intelligent, what would currently be considered human intelligence process. When we get into that space, people skills are going to be really important, prioritizing is going to be really important, identifying organizations that are ripe for this, at this moment in time, which processes to automate. Those are the kind of skills we're trying to get students to develop, and what we're selling it partly as, this is going to make you ready of the world the way we think it's going to be, a bit of a guess. But we're also saying if you don't want to automate mundane processes, then come with us on a different magic carpet ride. And that magic carpet ride is, imagine all the processes that don't exist right now because nobody would ever conceive of them because they couldn't possibly be sustained, or they would be too mundane. Now think about those processes through a business lens, so take a business student and think about all the potential when you look at it that way. So this course that we're building has that, everything in the course is wrapped in that, and so, at the end of the course, they're going to be doing a project, and the project is to bring a new process to the world that doesn't currently exist. Don't program it, don't worry about whether or not you have a team that could actually execute it. Just conceive of a process that doesn't currently exist and let's imagine, with the potential of RPA, how we would make that happen. That's going to be, we think we're going to be able to bring a lot of students along through that innovative lens even though they are 19 and 20, because 19 and 20 year olds love innovation, while they've never submitted a procurement report. >> Exactly! >> A innovation presentation. >> We'll need to do a Cube follow up with that. >> What Kurt just said, is the reason why, Tom, I think this market is being way undercounted. I think it's hard for the IDCs and the forces, because they look back they say how big was it last year, how fast are these companies growing, but, to your point, there's so much unknown processes that could be attacked. The TAM on this could be enormous. >> We agree. >> Yeah, I know you do, but I think that it's a point worth mentioning because it touches so many different parts of every organization that I think people perhaps don't realize the impact that it could have. >> You know, when listening to you, Kurt, when you look at these young kids, at least compared to me, all the coding and setting up a robot, that's the easy part, they'll pick that up right away. It's really the thought process that goes into identifying new opportunities, and that's, I think, you're challenging them to do that. But learning how to do robots, I think, is going to be pretty easy for this new digital generation. >> Piece of cake. Tom and Kurt, thank you so much for coming on theCUBE with a really fascinating conversation. >> Thank you. >> Thanks, you guys >> I'm Rebecca Knight, for Dave Velante, stay tuned for more of theCUBEs live coverage of UIPath FORWARD. (upbeat music)

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape hi everybody welcome to the special edition of the cube insights powered by ETR over the past several weeks we've been running breaking analysis on various market segments and today we're gonna talk about the robotic process automation market the spending data from ETR really shows that that market is poised for for continued growth it's been rocketing these segments are independent editorial they are not sponsored in any way although two of the companies that I'll be talking about today are sponsors of the cube automation anywhere and uipath both sponsor the cube we we attend their shows but they have absolutely no input over these editorial segments it's 100% data-driven based on ETR data and cube insight opinions in my opinions so thank you for watching let's get into it so Alex if you bring up the first slide I want to share with people what the robotic process automation market is and what you need to know about it it's a small but very fast-growing market according to a combination of Forrester and and Gartner data it's around one and a half to 1.7 billion dollars this year and it's growing at over 60 percent per year Gartner calls it the fastest growing software sub segment that they tracked garden just put out a Magic Quadrant on this space which was you know is always interesting reading despite what you think about magic quadrants it's essentially software robots that are automating repetitive mundane tasks and I underline tasks in this chart because it's largely tasks simple tasks that are being automated in a big way as opposed to really big complex processes they tend to be targeted at line of business users and it very popular in environments like finance and service roles and and back office areas where they're a repetitive common tasks that people frankly hate and we're going to give you some feedback from from customers there are a number of upstarts in the space uipath automation anywhere blue prism these these companies have attracted a massive influx of venture capital particularly uipath an automation anywhere over a billion and a half dollars in the last couple of years there monster valuations take those three companies their valuations are up over ten billion dollars and growing uipath for example several months ago announced that it had more than 200 million dollars in annual recurring revenue they were just at eight million dollars two years ago so you're seeing just this this massive growth a lot of influx of capital and a lot of jockeying for position now users that we've talked to will express a great deal of business impact related to the introduction and application of RPA in their business so I want you to take a look at this video of one practitioner that we interviewed at a cube event let's listen to to see what Jeanne younger has to say and then we'll come back and talk about it it's interesting because I also teach the Six Sigma courses there and one of them my slides I've had for years teaching that classes most business processes are like between 3.2 and 3.6 3.8 Sigma which is like 95 to 98% accurate and I said that's all the better we can usually do because of the expense that it would normally be to get us to a Six Sigma you look at the places that have Six Sigma it's life-threatening airline you know airplane engines you hope they're at least 7 Sigma you know those type of things but business processes 3 5 3 2 but now I get to change that because with our PA I can make them Six Sigma very cheap very cheaply because I can pull them in I got my bought it comes over pulls the information and there's no double king there's no miss keys its accuracy 100% accuracy this is a perfect example of how companies are applying robotic process automation to to improve existing business processes you would never try to get a standard business process up to Six Sigma it's just not worth it and as Jean younger explained now she can get there very inexpensively with our PA there many many other use cases but I wanted to share that one with you now the next slide I'm going to show you comes from ETR ETR is an organization that runs a panel is about a 4,500 user panel and they focus on spending intentions they do periodic surveys throughout the year they capture a fairly large number of users and what they're spending on that built this great taxonomy and we've been partnering with ETR to share with you some of that insights and what this slide shows is really spending intentions from the july 2019 survey asking about the second half spending intentions on the sector of robotic process automation you can see here the N is 1068 respondents in that July survey on the left-hand side you can see four vendors that we've chose to profile uipath automation anywhere blue prism and pega systems a company that's been around for a long time and is not exclusively focused on RPA they've got more of a business process focus and I'll come back to that but what this slide shows is really the spending intentions around four areas the bright red is we're going to leave the platform stop spending we're out of here the lighter red is we're gonna spend less in the second half the gray is we're flat the dark green is we're gonna increase spending in the lime green is where a new customer coming on so if you subtract the red from the green you get what ETR calls the net score and that is an indication of spending intentions and momentum so the higher the net score the better you can see here uipath leads the pack with an 81% next score ironically that's the identical next school net score as was snowflake in this survey we profiled the enterprise data warehouse market and snowflake was one of the leaders there so uipath and snowflake even though there are sort of different markets and different levels of maturity sort of around in the same net score so two very hot companies and you can see going down the list automation anywhere 69% blue prism 53% and pega systems 44% actually these are all very strong compared to some of the other market segments we track like for instance if you look at the disk array market and some of the legacy disk array companies some of the enterprise data warehouse companies you'll see sometimes negative scores now on the right-hand side and the black you see shared accounts what this says this is the number of accounts that were mentioned as intending to spend on or in the case of the dark red leave or in the case of the bright green add but the number of counts out of that 1068 corpus of data that mentioned these respective companies so you can see relatively small you know 68 for uipath 42 for automation anywhere 45 for blue prism and only 27% repair systems but these I remind you were still significantly statistically significant enough to at least get indications so you can see again your UI path leads but all of the companies are actually quite strong on a relative basis so the next slide that I want to show you Alex if you bring this up is a time series for some of these leading competitors over over time so we'll go back to January of 18 and the number of shared accounts back then was relatively small it was in the low double digits and in some cases the single digits but as we go to the right you can start to see it it increases in terms of the shared accounts out of that a thousand 1068 from this past survey so you can see uipath at that 81% next score of net score very high but but also automation anywhere very very strong blue prism you can see the decline in that yellow line but again very very strong with a 53% Nets so this space is is new and it's in it's very hot I say it's new and then it's been around for a while but it's really starting to take off and then you can see see Pegasus Thames you're lower than these other companies but still very very strong at 44% now we'll tell you the folks at Wycombe on the the analyst side of our house have gone out they've done some research they maybe it was about 18 months ago they they downloaded the UI paths Community Edition they tried to do the same for automation anywhere in blue prison they tried to get access to the software so they could apply it and you know run some robots against some mundane tasks they were only able to get the automation of the sorry the uipath software which was very simple to install and apply and you know some simple tasks they couldn't get the automation anywhere in blue president you had to go to resellers and it was sort of this complicated you know setup so that was sort of a red flag that we put up but but the UI paths you know claims that their stuff was easy to use some of their users that we've talked to you know talked about it in the context of low code and so we've we've clarified some of that we don't have as much data on automation anywhere in blue prism although we've covered automation anywheres events customers you know seemed quite happy and and reporting strong business impacts don't have as much information at this time on blue prisms on blue prism we have attended some of the peg assistance events just as observers I was saying before I come back to them they take more of a holistic approach to business process it's really not they're not positioning themselves as a standalone RPA vendor which you know frankly I wouldn't do if I were up against uipath and automation anywhere because they've got so much influx of capital they've got modern platforms that are ostensibly easy to use so packet system seems to be look going after our PA in a much sort of broader context around process business process engineering so in summer you just want to say so the very fast-growing market there's a book there's a lot of competition you got uipath automation anywhere blue prism there's about 15 or 20 players in this space that are sort of sizable it's a combination of as they say standalone robotic process automation players with integrated BPM players like Pegasus Thames it's important remember you're largely here automating existing procedures and tasks you know you're not doing a lot of necessarily re-engineering it so that's you know some people are concerned about that saying okay we're kind of paving the cart path at the same time practitioners are reporting that it's having a major business impact and and although they've also said that's not likely to reduce headcount rather we're redirecting resources you're not firing people because you're bringing in robots so people aren't necessarily losing their jobs over this they're just shifting away from that sort of undifferentiated heavy lifting that they hate doing mundane tasks automating that and moving on to more strategic items so a lot of discussion in the industry about artificial intelligence in in machine learning and some folks have said well AI and RP a they have nothing to do with each other I will say this that that machine learning has been injected into the RP a space via computer vision and a good example is it recognized a button like a send button if you know you're sending out you know emails or pushing a certain button every day at the you can automate that process so computer vision is a key part of this and again it's something that certain RPF Enders are touting I know uipath again talks about that a lot but the business impact is tangible and this is based on customer feedback a lot of customer feedback you know generally speaking you're seeing CFOs are hopping on to this they're seeing this is a really good way to take out some of the inefficiencies in their business refocus people on higher value activities and so we're going to continue to watch this RPA space I think it's going to be big we see big s eyes coming into this we're talking about companies like Accenture IBM Deloitte PwC Ernie Young those guys are starting to you know go after the space and I've always said this about the the big sis they love to eat at the trough so with there's money there they find it and they go hard after it so thanks for watching everybody we're gonna continue to report on this space this is Dave Volante with cube insights powered by ETR we'll see you next time

>> From the SiliconANGLE media office, in Boston, Massachusetts, it's the CUBE. Now, here's your host, Stu Miniman. Hi, CUBE nation, I'm Sam Kahane. Thanks for watching the CUBE. Due to popular demand from the community, I will be interviewing the legendary Stu Miniman, here today. He is S-T-U on Twitter. Stu and I are going to be digging in to the 2019 predictions, and also recapping 2018 for you here. So, Stu, let's get into it a little bit. 2018, can you set the stage? How many events did you go to? How many interviews did you conduct? >> Boy, Sam, it's tough to look back. We did so much with the CUBE this year. I, personally, did over 20 shows, and somewhere between 400 and 450 interviews, out of, we as a team did over a 100 shows, over 2000 interviews. So, really great to be in the community, and immerse ourselves, drink from the fire hose, and some of the data. (laughs) >> So, over 400 interviews this year, that's amazing. What about some of the key learnings from 2018? Yeah, Sam,my premise when I'm going out is, how are we maturing? My background, as you know, Sam, I'm an infrastructure guy. My early training was in networking. I worked on virtualization, and I've been riding this wave of cloud for about the last 10 years. So, about two years ago, it was, software companies, how are they living in these public clouds? Amazon, of course, the dominant player in the marketplace, but we know it will be a multi-cloud world. And the update, for 2018, is we've gone from, how do I live in those public clouds, to how are we maturing? We call it hybrid clouds, or multi-cloud, but living between these worlds. We saw the rise in Kubernetes, as a piece of it, but customers have lots of environments, and how they get their arms around that, is a serious challenge out there, today. So, how are the suppliers and communities, and the systems integration, helping customers with this really challenging new environment, that we have today. >> I'd love to hear any OMG moments from you. What surprised you the most this year? >> It's interesting, when I wanna think about some of the big moves in the industry, I mean, we had the largest software acquisition in tech history. IBM, the company you used to work for, Sam, buying Red Hat, a company I've worked with, for about 20 years, for 34 billion dollars. I mean, Red Hat has been the poster child for open source, and the exemplar of that. It was something that was like, wow, this is a big deal. We've been talking for a long time, how important developers are, and how important open source is, and there's nothing like seeing Big Blue, a 107-year-old company, putting in huge dollars, to really, not just validate, cause IBM's been working in open source, working with Linux for a long time, but how important this is to the future. And that sits right at that core of that multi-cloud world. Red Hat wants to position itself to live in a lot of those environments, not just for Linux, but the Middleware, Kubernetes is a big play. We saw a number of acquisitions in the space there. Red Hat bought CoreOS for $250 million. VMware bought Heptio, and was kind of surprised, at the sticker shock, $550 million. Great team, we know the Heptio team well. We talked to them, some of the core people, back when they were at Google. But, some big dollars are being thrown around, in this space, and, as you said, the big one in the world is Amazon. One of the stories that everybody tracked all year was the whole hq2 thing. It kind of struck me as funny, as Amazon is in Seattle. I actually got to visit Seattle, for the first time, this year, and somebody told me, if you look at the top 50 companies that have employees in Seattle, of course, Amazon is number one, but you need to take number two through 43, and add them together, to make them as big as Amazon. Here in Boston, there's a new facility going up, with 5,000 employees. I know they're going to have 25,000 in Long Island City, right in the Queens, in New York City, as well as Crystal City, right outside of DC, 25,000. But, the realization is that, of course, Amazon's going to have data centers, in pretty much every country, and they're going to have employees all around the world. This doesn't just stay to the US, but Amazon, overall. So, Amazon, just a massive employer. I know so many people who have joined them. (laughs) Some that have left them. But, almost everything that I talk about, tends to come back to Amazon, and what there are doing, or how people are trying to compete, or live in that ecosystem. >> You're always talking to the community. What are some of the hottest topics you're hearing out there? >> So, living in this new world, how are we dealing with developers? A story that I really liked, my networking background, the Cisco DevNet team, led by Suzie Wee, is a really phenomenal example, and one of my favorite interviews of the year. I actually got to talk to Suzie twice this year. We've known her for many years. She got promoted to be a Senior Vice President, which is a great validation, but what she built is a community from the ground up. It took about four years to build this platform, and it's not about, "Oh, we have some products, and developers love it.", but it's the marketplace that they live in, really do have builders there. It's the most exciting piece of what's happening at Cisco. My first show for 2019 will be back at Cisco, live in Barcelona, and Cisco going through this massive transformation, to be the dominant networking company. When they talk about their future, it is as a software company. That actually, it blew my mind, Sam. You know, Cisco is the networking company. When they say, "When you think of us, "five to ten years from now, "you won't think of us as a networking company. "You'll think of us as a software company." That's massive. They were one of the four horsemen of the internet era. And, if Cisco is making that change, everything changes. IBM, people said if they don't make this move for Red Hat, is there danger in the future? So, everything is changing so fast, it is one of the things that everybody tries to sort out and deal with. I've got some thoughts on that, which I'm sure we'll get to later on. >> (laughs) As is Suzie Wee one of your top interviews of 2018, could you give your top three interviews? >> First of all, my favorite, Sam, is always when I get to talk to the practitioners. A few of the practitioners I love talking to, at the Nutanix show in New Orleans this year, I talked to Vijay Luthra, with Northern Trust. My co-host of the show was Keith Townsend. Keith, Chicago guy, said, "Northern Trust is one "of the most conservative financial companies", and they are all-in on containerization, modernized their application. It is great to see a financial company that is driving that kind of change. That's kind of a theme I think you'll see, Sam. Another, one, was actually funny enough, Another Nutanix show, at London, had the Manchester City Council. So, the government, what they're doing, how they're driving change, what they're doing with their digital transformation, how they're thinking of IOT. Some of my favorite interviews I've done the last few years, have been in the government, because you don't think of government as innovating, but, they're usually resource-constrained. They have a lot of constituencies, and therefore, they need to do this. The Amazon public sector show was super-impressive. Everything from, I interviewed a person from the White House Historical Society. They brought on Jackie O's original guidebook, of being able to tour the White House. So, some really cool human interest, but it's all a digital platform on Amazon. What Amazon is doing in all of the industry-specific areas, is really impressive. Some of these smaller shows that we've done, are super-impressive. Another small show, that really impressed me, is UiPath, robotic process automation, or RPA, been called the gateway drug to AI, really phenomenal. I've got some background in operations, and one of the users on the program was talking about how you could get that process to somewhere around 97 to 98% compliance, and standardize, but when they put in RPA, they get it to a full six sigma, which is like 99.999%, and usually, that's something that just humans can't do. They can't just take the variation out of a process, with people involved. And, this has been the promise of automation, and it's a theme. One of my favorite questions, this year, has been, we've been talking about things like automation, and intelligence in systems, for decades, but, now, with the advent of AI machine learning, we can argue whether these things are actually artificial intelligence, in what they are learning, but the programming and learning models, that can be set up and trained, and what they can do on their own, are super-impressive, and really poised to take the industry to the next level. >> So, I wanna fast forward to 2019, but before we do so, anything else that people need to know about 2018? >> 2018, Sam, it's this hybrid multi-cloud world. The relationship that I think we spend the most time talking about, is we talked a lot about Amazon, but, VMware. VMware now has over 600,000 customers, and that partnership with VMware is really interesting. The warning, of course, is that Amazon is learning a lot from Vmware, When we joke with my friends, we say, "Okay, you've learned a lot from them means that "maybe I don't need them in the long term." But in the short term, great move for VMware, where they've solidified their position with customers. Customers feel happy as to where they live, in that multi-cloud environment, and I guess we throw out these terms like hybrid, and multi, and things like that, but when I talk to users, they're just figuring out their digital transformation. They're worried about their business. Yes, they're doing cloud, so sassify what you can, put in the public cloud what makes sense, and modernize. Beware of lift and shift, it's really not the answer. It could be a piece of the overall puzzle, to be able to modernize and pull things apart. An area, I always try to keep ahead of what the next bleeding-edge thing is, Sam. A thing I've been looking at, deeply, the last two years, has been serverless. Serverless is phenomenal. It could just disrupt everything we're talking about, and, Amazon, of course, has the lead there. So, it was kind of an undercurrent discussion at the KubeCon Show, that we were just at. Final thing, things are changing all the time, Sam, and it is impossible for anybody to keep up on all of it. I get the chance to talk to some of the most brilliant people, at some of the most amazing companies, and even those, you know, the PhD's, the people inventing stuff, they're like, "I can't keep up with what's going on at my company, "let alone what's going on in the industry." So, that's the wrong thing. Of course, one of the things we helped to do, is to extract the signal from the noise, help people distill that. We put it into video, we put it into articles, we put it into podcasts, to help you understand some of the basics, and where you might wanna go to learn more. So, we're all swimming in this. You know, the only constant, Sam, in the industry is change. >> Absolutely. (laughing in unison) >> So, things are changing. The whole landscape, as you said, is changing. Going into 2019, what should people expect? Any predictions from you? Any big mergers and acquisitions you might see? >> It's amazing, Sam. The analogy I always use is, when you have the hundred year flood, you always say, "Oh gosh, we got through it, "and we should be okay." No, no, no, the concern is, if you have the hundred year flood, or the big earthquake, the chances are that you're going to have maybe something of the same magnitude, might even be more or less, but rather soon. A couple of years ago, Dell bought EMC, largest acquisition in tech history. We spent a lot of time analyzing it. By the way, Dell's gonna go public, December 28. Interesting move, billions of dollars. As Larry Ellison said, "Michael Dell, "he's no dummy when it comes to money.' He is going to make, personally, billions of dollars off of this transaction, and, overall, looks good for the Dell technologies family, as they're doing. So, that acquisition, the Red Hat acquisition, yeah, we're probably gonna see a 10-to-20 billion dollar acquisition this year. I'm not sure who it is. There's a lot of tech IPOs on the horizon. The data protection space is one that we've kept a close eye on. From what I hear, Zeam, who does over a billion dollars a year, not looking to go public. Rubrik, on the other hand, somewhere in the north of 200 million dollars worth of revenue, I kind of remember 200, 250 in run rate, right now, likely going to go public in 2019. Could somebody sweep in, and buy them before they go public? Absolutely. Now, I don't think Rubrik's looking to be acquired. In that space, you've got Rubrik, you've got Cohesity, you've got a whole lot of players, that it has been a little bit frothy, I guess you'd say. But, customers are looking for a change in how they're doing things, because their environments are changing. They've got lots of stuff in sass, gotta protect that data. They've got things all over the cloud, and that data issue is core. When we actually did our predictions for 2018, data was at the center of everything, when I talked about Wikibon. It was just talking to Peter Burris and David Floyer, and they said there is some hesitancy in the enterprise, like, I'm using Salesforce, I'm using Workday I'm using ServiceNow. We hear all the things about Facebook giving my data away, Google, maybe the wrong people own data, there's that concern I want to pull things back. I always bristle a little bit, when you talk about things like repatriation, and "I'm not gonna trust the cloud." Look, the public clouds are more secure, than my data centers are in general, and they're changing and updating much faster. One of the biggest things we have, in IT, is that I put something in, and making changes is tough. Change, as we said, is the only thing constant. It was something I wrote about. Red Hat, actually, is a company that has dealt with a lot of change. Anybody that sells anything with Linux, or Kubernetes, there are so many changes happening, on not only weekly, but a daily basis, that they help bring a little bit of order, and adult supervision, to what most people would say is chaos out there. That's the kind of thing we need more in the industry, is I need to be able to manage that change. A line I've used many times is, you don't go into a company and say, "Hey, what version of Azure are you running?" You're running whatever Microsoft says is the latest and greatest. You don't have to worry about Patch Tuesday, or 08. I've got that things that's gonna slow down my system for awhile. Microsoft needs to make that invisible to me. They do make that thing invisible to me. So does Amazon, so does Google. >> What's your number one company to watch, this upcoming year. Is it Amazon, Sam? Look, Amazon is the company at the center of it all. Their ecosystem is amazing. While Amazon adds more in revenue, than the number two infrastructure player does in revenue. So, look, in the cloud space, it is not only Amazon's world. There definitely is a multi-cloud world. I went to the Microsoft show for the first time, this year, and Microsoft's super-impressive. They focus on your business applications, and their customers love it. Office 365 really helped move everybody towards sass, in a big way, and it's a big service industry. Microsoft's been a phenomenal turnaround story, the last couple of years. Definitely want to dig in more with that ecosystem, in 2019 and beyond. But, Amazon, you know, we could do more shows of the CUBE, in 2019, than we did our first couple of years. They have, of course, Amazon re:Invent, our biggest show of the year, but their second year, it's about 20 shows, that they do, and we're increasing those. I've been to the New York City Summit, and the San Francisco Summit. I've already mentioned their Public Sector Summit. Really, really, really good ecosystems, phenomenal users, and I already told you how I feel about talking to users. It's great to hear what they're doing, and those customers are moving things around. Google, love doing the Google show. We'll be back there in April. Diane Greene is one of the big guests of the year, for us this year. I was sorry to miss it in person, 'cause I actually have some background. I worked with Diane. Back before EMC bought VMware. I had the pleasure of working with Vmware, when they were, like, a hundred person company. Sam, one of the things, I look back at my career, and I'm still a little bit agog. I mean, I was in my mid-20s, working in this little company, of about 100 people, signed an NDA, started working with them, and that's VMware, with 600,000 customers. I've watched their ascendancy. It's been one of the pleasures of my career. There's small ones, heck. Nutanix I've mentioned a couple of times. I started working them when they were real small. They have over a billion in revenue. New Cure, since the early days. Some companies have done really well. The cloud is really the center of gravity of what I watch. Edge computing we got into a bit. I'm surprised we got almost 20 minutes into this conversation, without mentioning it. That, the whole IOT space, and edge computing, really interesting. We did a fun show with PTC, here in Boston. Got to talk to the father of AI, the father of virtual reality. It's like all these technologies, many of which have been bouncing around for a couple of decades. How are they gonna become real? We've got a fun virtual reality place right next door. The guy running the cameras for us is a huge VR enthusiast. How much will those take the next step? And, how much are things stalling out? I worry, was having conversations. Autonomous vehicles, we're even looking at the space. Been talking about it. Will it really start to accelerate? Or have we hit road blocks, and it's gonna get delayed. Some of these are technologies, some of these are policies in place, in governments and the like, and that's still one of the things that slows down crowded options. You know, GDPR was the big discussion, leading into the beginning of 2018. Now, we barely talk about it. There's more regulations coming, in California and the like, but we do need to worry about some of those macro-economical and political things that sometimes get in the way, of some of the technology pieces. >> I'd love to put something out into the universe, here. If you could interview anyone in the world, who would it be? Let's see if we can make it happen. It's amazing to me, Sam, some of the interviews we've done. I got a one-on-one with Michael Dell this year. It was phenomenal, Michael was one. It took us about three or four years before we got Michael on the program, the first time. Now, we have him two or three times a year. Really, to get to talk to him. There is the founder culture John Furrier always talks about. Some of these founders are very different. Michael, amazing, got to speak to him a couple of times. There's something that makes him special, and there's a reason why he's a billionaire, and he's done very well for himself. So, that was one. Furrier also interviewed John Chambers, who is one of the big gets I was looking at. I was jealous that I wasn't able to get there. I got to interview one of my favorite authors this year, Walter Isaacson, at the shows. When I look at, Elon Musk, of course, as a technologist, is, I'm amazed. I read his bio, I've heard some phenomenal interviews with him. Kara Swisher did a phenomenal sit-down on her podcast with him. Even the 60 Minutes interview was decent this year. >> The Joe Rogan one was great >> Yeah, so, you'd want to be able to sit down. I wouldn't expect Elon to be a 15-minute, rapid-fire conversation, like we usually have. But, we do some longer forms, sit down. So he would be one. Andrew Jassy, we've interviewed a number of times now. Phenomenal. We've got to get Bezos on the program. Some of the big tech players out there. Look, Larry Ellison's another one that we haven't had on the program. We've had Mark Hurd on the program, We've had lots of the Oracle executives. Oracle's one that you don't count out. They still have so many customers, and have strong power in new issues, So there are some big names. I do love some of the authors, that we've had on the program, some thought leaders in the space. Every time we go to a show, it's like, I was a little disappointed I didn't get to interview Jane Goodall, when she was at a show. Things like that. So, we ask, and never know when you can get 'em. A lot of times, it's individual stories of the users, which are phenomenal, and there's just thousands of good stories. That's why we go to some small shows, and make sure we always have some editorial coverage. So that, if their customers are comfortable sharing their story, that's the foundation our research was founded on. Peers sharing with their peers. Some of the most powerful stories of change, and taking advantage of new technologies, and really transforming, not just business, but health care and finance, and government. There's so much opportunity for innovation, and drivers in the marketplace today. >> Stu, I love it. Thanks for wrapping up 2018 for us, and giving us the predictions. CUBE nation, you heard it here. We gotta get Elon Musk, Jeff Bezos, and Larry Ellison on the CUBE this year. We could use your help. Stu, thank you, and CUBE nation, thank you for watching. (electronic techno music)

>> Live from Las Vegas, it's theCUBE. Covering Boomi World 2018. Brought to you by Dell Boomi. >> Welcome back to theCUBE. We are live at the Encore in Las Vegas, I'm Lisa Martin with John Furrier. We're at Dell Boomi World 2018, second annual Dell Boomi World, and we're here with one of Dell Boomi and Dell's biggest GSIs. We've got Jason Cook, the Global Client Account Lead at Accenture serving Dell. Jason, thanks for joining John and me today. >> Thank you. >> So, second annual Dell Boomi World, bigger than last year. They were talking today, a lot of interesting numbers. 7,500 plus customers to date. They're adding five new customers everyday. I saw the Gartner Magic Quadrant from earlier this year and iPaaS, they are right up there in that strong leader category. Talk to us about the relationship that you have with Dell Technologies and the business heat of Dell Boomi. >> Yeah, yeah, it's an interesting one. So, Accenture has become very big. I think we now have 470,000 global employees, and our brand and presence is technology advisory and delivery, it predominates what we did. What's interesting about Dell and, specifically, Boomi is being so central to the technology ecosystem, there's much opportunity for partnership. Where Dell is present with enterprise clients, we're present too. And we tend to have long-running relationships with those clients. Most of our clients are tenured over 15 years. So it gives us an opportunity to have the type of longstanding relationship that Dell has with clients and advise on technology trends, and change, and break into the best thinking of the marketplace in their clients as they look to solve problems, of course, Dell is central to that solution set, as Boomi is too. >> And yesterday, they announced a new technology partner program. Dell Boomi has a broad partner ecosystem that it partners, implementation, GSIs, talk to us about that and the maybe new business opportunities that it will give to Accenture. >> Yeah, so we've enjoyed a relationship over the past several years in Europe working with Boomi. And we incubated a program over there called Eccentric Growth Partnerships, where with emerging companies such as Boomi, we've gone to market, leveraged the Accenture channel, and then brought scale to those technologies to deliver at enterprise level for their expectations. It's been very successful, you know, seen on both sides is a real win. And we're now transferring that into the North American market, so we're based on the heels of that success. We're looking to formalize some of the things we've been doing internationally in North America. A larger market for both of us, and so it's expanded opportunity in both places. >> Jason, talk about Accenture's own transformation. We've been following you guys for, I've been following Accenture when they changed their name. But recently you guys have invested, in the past decade, really early in data science. You guys have been on the public cloud very early. You've been partnering with your customers. And so that's all great, you guys do a good job with that. But what's interesting is you're actually helping them change their business model. >> Yes. >> So how has your own transformation within Accenture dealing with Dell, he's been doing a trillion dollars in business. Millions and millions of servers sold. His customers are changing. You guys are in that business model, enablement business, you're helping customers. What's the big business model impact that's happening in the market right now. >> Well, I think you know, as it pertains to Accenture, yeah, we've grown. I would say one of the hallmarks of the growth has been around digital, and I think 60% of our revenues are now digitally oriented, which are in the areas you described. So that's become our brand and presence, and the majority of what we do in the marketplace. I think the things that we're doing to serve clients, which are several of the things we've done internally, have been around all sorts of digitally-enabled journeys, whether it's the intelligent enterprise, the connected customer, the adoption of platforms, and the expanded use as a service within enterprises. There are plays within all those spaces where we end up bringing enablement to those clients. You know, examples would be, in the retail space, you know, growth and expansion of omnichannel techniques, so that the same customer experience exists across anywhere in retail. Programs around single views of customer are very, very common for us globally. Traditionally, less technical areas of the business, like a supply chain operating that's dominated by manufacturing and fulfillment and brick and mortar in the retail space. The real time visibility challenges that have historically been there are only now being able to be solved by technologies, and so there's several different. >> And the cloud certainly is horizontally scaled, so it impacts all industries that you play in, so, good for business. But the challenge that the CIOs have that we talked to, we hear and want to get your reaction to is, okay, I loved technology scale. I need to have proof points. I got to have mile markers that are going to be attainable with time-to-value. But the number one thing they say is I got to bring a competitive advantage into I.T., in a cloud construct that's horizontally scalable and work with partners in areas that aren't core. So, leverage supplier relationships, but build a core intellectual property or competitive advantage with I.T. How do you guys help them? What are some trends? What are those I.P. moments for your large and medium-sized customers? >> Yeah, I think that because we have the heritage of both advising on and delivering technology, where we tend to work closely with CIOs is around the speed-to-value, delivering on programs. We represent a wealth of experience and work in the marketplace, and those learnings can be brought to different clients, and fundamentally that's what's valuable to them. So I think that when we talk about cloud enablement, it's often a matter, too of thinking through, what are the specific business outcomes that can be delivered from the use of technology. And so, clients for example, I can think of some clients, that one company that has 1,400 legacy applications in a cloud footprint. And yet the business initiatives that come into the IT-- >> They must use containers a lot. >> Yeah, well exactly. The questions that come into the I.T. organization are often ones around how can we improve our visibility to product line profitability, as an example. And so, the use of cloud, the use of integration technologies like Boomi accelerates the ability to connect information from that disparate environment and deliver outcomes. >> And specifically more tactical, to get those outcomes, what specific things do you see? Is the cloud native? Is it the role of data? How are CIOs getting down and dirty, saying okay, I'm going to lock in on this as territory, we're going to build around and build on top of. Data, cloud, and IoT's new, and everyone knows what IoT is, it's going to be part of, either physical and/or low-hanging fruit. But what are they building on from an I.T. standpoint? Is it the data, is it the network? Is it the storage? So what do you see there? >> Yeah, I think it is the data. I think that's where we see, data-led seems to be the thinking in most of these cases around getting information consistently consumed throughout. 'Cause the world has become so data intensive that access to data is not the problem. It's the integration, and the derivation of value from it that's-- >> And scale, too, I mean. >> And scale, right, yeah. >> Hello cloud, so cloud and data seem to be. >> And it's become more distributed, too. And so dealing with distributed data sources and normalizing has been a-- >> That's where Boomi comes in, integrating all that stuff in, so cloud and data seem to be the pattern across the board generically speaking. I mean, obviously certain industries financial, service, oil, and gas have unique requirements. >> They all have their own cases for it, whether you're a distributed bank, or whether you're a distributed retailer, or whether you're dealing with oil wells in distributed locations, you run into common problems across all industries. >> And integration is so much more, as the iPaaS market has evolved, it's so much more than integrating applications. It's integrating applications, data from existing sources, from new sources, the API economy is essential for that. To enable an organization to create a customer experience that's going to allow them to use that data, and continue to get more customers, more data, and evolve faster than their competition. But transformation is a big challenge, right? And here, well, and even Dell Technologies were, the theme was about making it real, making it real for digital transformation, security transformation, huge priority, workforce. How, when Accenture is going in to integrate at, whether it's a retailer or an oil and gas company, how do you help them start? What's that start of a transformation? >> Well, it often is the transformations you were just referring to. Our typical engagement profile ranges from how do I engage my workforce in a new way? Or how do I improve visibility across a distributed network of retail stores, or banks, or what have you? And so those are the transformations, and then inevitably, the connection of information across those things become the enabling source. If you take, as an example, a customer experience program where, let's talk about a government example where they want a single view of a citizen, a tax payer, whatever it may be. There's so much information on that person in so many disparate places that has to be brought together in a cohesive way. Not only that, but brought together and then used effectively in serving that person. And that's where you see a lot of value. >> Jason, I want to pick your brain while you're here, 'cause Accenture's always got the smart people who know what's going on. And you got big customers, big examples. There's a dynamic right now between two kind of personas. Kind of making it generic for the conversation now. Persona one is the business executive who is responsible and chartered to drive the digital transformation with new and improved applications. Taking advantage of the legacy, bringing in the new, managing them either on their own schedule. And the second persona is the person deploying cloud. So how are companies organizing around these personas? One's got to be under the hood, I got to do multicloud I got to do Kubernetes, I got to do all these things. Stateless applications, stateful applications, integrate them all together. I'm deploying it. And then the business persona, hey, take that hill, more apps, more outcomes. So how are companies organizing around these dynamics? What's the best practice? >> Yeah, along the lines you describe. So, specifically, the business functions are becoming aligned with application domains, and those tend to be programmatically managed. And so we see structures around that programmatic management. To be very responsive to business needs, and particularly as clock speeds accelerate on delivery, maintaining that partnership is very, very important. Likewise, on the infrastructural side, we see alignment there too to take advantage of creating platforms, and enablement, and infrastructure, and delivery capabilities that can deliver on that promise. >> So they're working together on pizza teams, or like agile teams? >> So it's a customer-focused model for the programmatic work and it's an industrialization and an acceleration on the infrastructural side. And that's, again, where there's a strong fit with some of these-- >> Do you have a favorite example, speaking of that? So many departments, lines of business, need to have access to the same data to be able to develop new products and services, tune things, make things better, faster than their competition. So there's this sort of democratization and this need to be able to share the information so that the entire business can grow together. Do you have a favorite example of an organization of any industry that you've worked with that you've seen really do that well, so that business, at the end of the day, everyone's playing well together because they have to. The business now is connecting customers, vendors, partners, and delivering experiences that are truly differentiating. >> Integration programs, data programs, data lake programs, data science programs often have a governance mechanism out in front of them to prioritize the needs of their business. Both in the back, in terms of enablement of different sources of information being accessed, but also the uses on the front end. And so that is a practice that we're seeing grow exponentially. The other thing that's interesting, I think, in terms of best practice is that as intelligence accelerates and companies become more analytically driven, the traditional process of continuous improvement which used to be defined in terms of Six Sigma events and other things, where once in a while a function would be evaluated for efficiencies becomes a continuous capability. So in this governance model, the ability to refine, and tune, and improve things like integration, AI, analytics on a continuous cycle as opposed to having it be event-driven is certainly an emerging trend and a best practice that we see a lot of. >> Well, Jason, thanks so much for joining the program with John and me today, and sharing with us what's new with Accenture and Dell Boomi and how you're helping customers globally truly transform. >> It's a pleasure, thank you for having me. >> And for John Furrier, I'm Lisa Martin. You're watching theCUBE live from Boomi World 2018 in Las Vegas. John and I will be right back with our next guest. (electronic music)

>> Announcer: Live from Miami Beach, Florida, it's theCUBE, covering UiPath Forward Americas, brought to you by UiPath. >> Welcome back to Miami, everybody. You're watching theCUBE. We're at UiPath Forward Americas. Dave Vellante with Stu Miniman. TheCUBE is the leader of, what are we the leader of? (laughs) >> Live tech coverage, Dave. >> The leader in live tech coverage. I've been blowing that line every week. Thanks for watching, everybody. We've got a great segment here. Jean Younger is here. She's the vice president, Six Sigma Leader, Security Benefit. She's to my near left, and Donna O'Donnell is here, director of key accounts at UiPath all the way from New York. Donna, thanks for coming on. >> Thank you. >> Dave: Great to see you guys. >> Thank you for having us. >> Thank you. >> All right, so we're well into day one. We're getting the Kool-Aid injection from customers and UiPath constituents, but Jean, let's start with you. Talk about your role, what's the company do, fill us in. >> Our company is an annuity company. We sell financial products for life insurance and annuities. We have about 30 billion under management, so it's a fairly large company out of Kansas. So, my role there is as a Six Sigma leader. We go in and we look at areas that need improvement or across the company, and one of the things I found, I'd been with the company almost five years now, and what I found is a lot of times, we're really good about putting manual processes in and never getting rid of 'em. We have day two issues of a tech. A tech goes live and you got a list of day two stuff that didn't get fixed, never gets fixed. It's just easier to do it, and cheaper, to leave it manual. So we have a lot of that in the company. With my job, seeing the various processes throughout the company, I was like what can we do to get rid of some of this stuff, get rid of that, get knowledge work back on the worker's plate instead of manipulating a spreadsheet or creating a report that they do every morning and it takes 'em the first 30 minutes or the first seven hours of their day is creating this one report every single day. We started looking at technology and came across UiPath. >> See, we call it GRS, getting rid of stuff. >> Jean: Yep. >> So, Donna, your job is to make these guys successful, right? >> Absolutely, so basically I just facilitate the smart people within the company. I listen to the business needs that Jean and other large clients have. We bring the resources, the products, and if we can't find it, we will absolutely find it and do everything we can to meet the needs. >> So, what's your automation story? When'd you get started? Paint a picture for us, the size, the scope. >> Okay, so last year about this time is when I started looking into it. I had just rolled out of another area that we had completely destroyed and built back up, and I was on to my next escapade in security benefit. >> Dave: Are you a silo buster, is that the new-- >> Yeah, I kind of go in and fix things. I'm kind of a fixer is basically what my job is. We'd rolled out and came back into Six Sigma to start looking and this came up. I'd seen the technology and I was like I wonder if it could work in our company. And so, we started doing kind of dog and pony show. We'd pull the different silos in, talk to 'em and say hey, here's what RPA can do for you. Is that something that you have some processes that might work? And we knew that there were processes in there, but we brainstormed with 'em for about 30 minutes. And out of that 30 minute, hour long conversation, we came out of there with about a hundred processes that people had already identified. And we kept going through there, I took that information, I built a business case, 'cause I knew to get the money, I needed to show them that there would be cost out potentially, and/or that I could take resources and move 'em into more critical areas that we didn't have the staffing. And so I had instances where, one of them that we're doing is out of our HR department. During the raise and salary time, they had two individuals that spent 60 hours a week for four months doing the same thing, same report over and over, and that's one of the processes we're actually going to implement here pretty soon. So, I came up with 'em and put the business plan together and asked for the money, and after kind of a long journey, I got the money. >> Long journey. (Jean and Donna laugh) >> It's never short enough is it? Jean, I mean, one of the things, Six Sigma is really good at measuring things. I mean, that's how you understand everything. You want to reduce variation. There was a line that really jumped out at me at the keynote is I want to go from pretty accurate to perfectly accurate, and when you were describing that there were a lot of things that were manually done. I mean, I lived in engineering for a lot of years and it was anything that somebody had to manually do, it was like oh wait, how can we change that? Because we didn't have RPA 10 years ago when I was looking at this, but how are you measuring these results? You talked about people doing repetitive tasks and the like. What other things are you finding to help get you along those reducing the variation inside the company? >> You know, it's interesting because I also teach the Six Sigma courses there, and one of my slides I've had for years teaching that class is most business processes are between 3.2 and 3.6, 3.8 sigma, which is like 95 to 98% accurate, and I said that's all the better we can usually do because of the expense that it would normally be to get us to a Six Sigma. You look at the places that have Six Sigma. It's life threatening, airplane engines. You hope they're at least Seven Sigma, those type of things, but business processes? 3.5, 3.2. But now, I get to change that because with RPA, I can make them Six Sigma very cheap, very cheaply, because I can pull 'em in, I got my bot, it comes over, pulls the information, and there's no double-keying. There's no miskeys. It's accuracy, 100% accuracy. >> So, what's the ripple effect in terms of the business impact? >> Cost savings, efficiency, customer experience. I mean, think about it. You're a customer, you get your policy, your name's wrong. How happy are you? You're not real happy. You send it back. So, no more of that. I mean, that's huge. So anything touching the customer going out of our business should be exactly how they put it on the application, especially if it was typed. Now, if it was handwritten, all hands are down on that, but if it was typed, it should be accurate. >> Donna, that's really powerful. I worked in a large corporation, we had a Six Sigma initiative and we know how much time and effort and people we were going to put in to have this little movements. >> Incremental change. >> An incremental change here to say. >> Donna: Pretty amazing. >> Blown away to tell you, Six Sigma and it's cheap. Well, what are you seeing? >> And I absolutely see. So, in addition to cost savings, it makes her more agile. But the big thing is, it makes it error free. The robots work 24 hours a day, seven days a week. Runs on itself, and Jean's going to get those efficiencies that she needed. >> How about let's talk more about the business case? I'm interested in the hard dollar piece of it. I've talked to a number of people at this show and others, and they tend not to just fire people. They got to redeploy 'em. Sometimes the CFO goes well, where's my hard dollars come from? So, where did your hard dollars come from? (laughs) >> From the CFO. (laughs) And right now, I have to prove that out yet. We're just in its infancy. We're just starting to bring up processes. In fact, yesterday and today we're dealing with several processes coming up, and so realistically, right now I've got about 300 processes. We haven't timed 'em all out yet, but I know right now that's between probably 12 and 15,000 hours of time savings that we will get on an annual basis. >> Okay, what one of the customers said today is, one example they used is they actually put it in next year's budget >> Correct. >> Which I loved. In other words, we're going to do more revenue for the same headcount, or less cost or whatever it is. That's a reasonable justification, maybe even better, right? Because it's got some forward motion to it. Is that kind of discussion and thinking come up? >> Headcount is under discussion right now. We're going through budgeting right now, and so yeah, that was part of the way that we justified the less headcount. Instead of hiring to fill another position, we would remove jobs from a certain person and be able to shift them into another role. And so that savings, non-hiring, as well as one of the processes we're doing is in our investment area. They couldn't afford to get another person. They couldn't get another headcount, so I gave them a headcount with a bot. I'm doing all their processes that they've only been able to do on a monthly basis, we're doing 'em every day. It's 52 processes they're going to do every day. It's an amazing, I gave 'em a head right there, bam. >> But we're also finding that the folks that were doing the mundane and repetitive tasks can focus on more creative work, more interesting work that they believe in and that they're motivated to do. We see that happening all the time. >> What does that mean for culture inside your company? Was there resistance at first? I have to think it's got to improve morale that it's like oh wait, I'm not getting in trouble for making mistakes now and I can go focus on things that fit better. >> You know, I think ultimately it will. Initially, there was a feeling gosh, the bots are going to take my job. But that was one thing we were pretty careful about initially going out and just saying what is it that you can't do? We all work 50, 60, some of them people are working 70 hours a week, and if I can take 10 or 20 hours away from them, they are lovin' us. There's individuals that are saying come here. I'll show you what I need. They also realize the ability of the bot to do it right all the time takes a little stress off of them, because they know they're going to get the right numbers, then, to analyze, 'cause that's a big thing. In the finance area, in the close, in the accounting area, what we're doing there is we're taking a lot of those simple process that somebody has to do and do them for them so then guess what? We can close earlier, get our books closed earlier in the month, as well as allow them longer time to analyze the results. So instead of the book's closed and then we go uh-oh, found a problem. Got to reopen the ledger and make an entry, we have less and less of that. Those are expectations that are set right now for our teams is that hey, let's get rid of the stuff that we can, and then let's see what's left. >> And Dave, I used to meet with clients and they used to say wow, this is a really interesting technology. Tell me about it. And now they're like holy crap, I'm behind the eight ball with my competition. How do we get this going quick? How do we get it going fast? In 2016, it was a $250 million industry, and by 2021, it's going to be a $3 billion industry we learned today. So it's pretty powerful. >> I think those numbers are low, by the way. >> I think they're low, too. What they said today, it's going to be a $3.4 billion industry. >> I think it's a 10x factor, probably by 2023 to 2025, I think this is going to be a $10 billion business. I've done a lot of forecasting in my life. That's just a gut feel swag, but it sort of feels like that. I think there's some pieces that are, there's some blind spots in terms of use cases and applications that we can't even see yet. Culturally, the light bulb moment, just listening to you, Jean, was the, first of all you're saying, you want your weekends back? Yeah! And then the second is it sounds like the employees are involved in sort of defining those processes, so they own it. >> And that's how we're scaling. I mean, we already realized we're a bottleneck. Our COE is a bottleneck and so we're like hey, right now, finance, it's not the end of the year. It's end of quarter, but those process are lighter than end of the year. So hey, can we get anything done? They're doing our documentation for us. They're actually taping themselves doing it, they're writing up the documentation. We come in and we look at it, and then we have a programmer doing it, but we're talking about how do we move that programming piece down to them as well, so we can get our scale up? Because I can't get through 300 processes in my small COE without a lot of help from the business. >> But Dave, most of our clients, the way that they scale very quickly is through partners. So, partners can do one of many things. They can be the developers, they can be the implementers, they could create the center of excellence, or they could pick which are the low-hanging processes. When we started off with Jean while she was going through the approval process, I brought out four partners, I gave 'em my own little mini RFP. They each had a four-hour time slot. They presented in front of Jean and we narrowed it down to two, and two of the partners are here at this event today. Most clients need to depend on partners. >> Well, that's key Donna, right? And I've said before, when you start seeing the big names that are around here, you know it's an exciting space. They don't just tiptoe and play around and games. They do some serious work for businesses. We got to turn the conversation to diversity, generally, but I also want to ask you specifically about women in tech. So, Stu and I were in a conference at Splunk earlier this week. The CEO of Carnival had a great line about diversity. He said, a big believer in diversity, of course. He's African American, and he said 40 years ago when I cracked in business, there weren't a lot of people I worked with that looked like me. I thought that was striking, Stu. I think there's always been women in tech, but not enough and a lot of stories about things that have happened to women in tech. It's changing slowly. A lot of women enter the field and then leave because they don't see a path to their future in things they like. What do you guys think about the topic, two women here on the panel today, which is our pleasure to have you. You can see, we need help. We have women working for us, (Jean and Donna laugh) but there's an imbalance there. >> You're right. >> What do you tell someone like us who's trying to find more women or more diversity and bring them into their-- >> Jean has many opinions in this space. Go ahead, Jean, I love your opinions in this space. >> I told the story at one of the UiPath events. I've been, as a lawyer, chemist, I've always been in pretty much a man's world. That's been my life in corporate America, and all along as I looked back, Donna was the first woman that sat across me to negotiate a contract. The entire time that I've been in the tech world, in the business world in corporate America, I had women working for me when I was at an insurance company negotiation very large contracts and stuff. They were on my side of the table. She was the first woman that I negotiated with on the other side of the table, and I think that's really sad, and I think we all have to look and say, how can we do better than that? How can we make us diverse? I look around here and you have all colors, all sizes, it's wonderful and it energizes you. And I am really a true believer in a really diverse workforce. I look at that and I think, 'cause they bring so many cool ideas, they think differently. Young, old, you put 'em all in a room and it's just amazing what they come up with, and I think if business leaders would hear that and think about that instead of hearing the same type of person, what's that same type of person that has your same background going to give you? He's not going to give you the transformation, or he or she. It's going to be kind of the same, what you're used to. You need that jolt, and I believe the more diverse people that we have around the table trying to solve the problem, it's amazing. I sat, last week, and I had a 22-year-old woman come into my office, Shirat, who's 30-ish and from India, and I had Amy who grew up in Topeka, hasn't left Topeka, myself. We were sitting around a table and another guy came and he probably 30. So you had a big, broad range. Somebody just out of college, me that's been out of college a long time, sitting around the table and we came up with, they thought they were dead in the water, and within 30 minutes of us just throwing different ideas out, we came up with a solution that we could continue going with. I mean, their faces were downtrodden and everything when they walked in, and when they left, we were excited, we were ready to go. Now, if we don't nurture that type of conversation, we're never going to get diversity. That's what diversity's about. If you think about it that way, wow. We went from having a problem that was a total dead stop and we weren't going to be able to proceed to 30 minutes later having a great solution and keeping running. And I truly believe it was because we had a diverse group of people around that table. >> Studies have been done of the clear value of diversity, the decisions that are made are better and drive business value. One of the challenges is finding the people, and it was pointed out to me one time, it's just because you're looking inside your own network. You got to go outside your own network, and it takes longer, it's more work. You just got to allocate the time, and it's good advice. It's hard work, but you got to do it to make change. >> And sometimes you got to take a chance. Sometimes, because it is outside of your network, you're not comfortable necessarily with the answers they give you or the way they approach a subject. I mean, you've got to feel comfortable, and CEOs and CFOs and the C-suite has to start thinking about that, because if you wanted to be transforming, that's how you transform. You don't transform thinking the same way every day. You're not going to transform. >> Let me ask you a question. You said you're a fixer, so I wrote down the adjectives that I would use to describe a fixer, and I want to know if this has been the way in which people have described you. You got to be smart, you got to be a quick study, you got to be a good listener, you got to be confident, self-assured, tough, decisive, collaborative. Are those the adjectives that have described you as a fixer over the years? >> Yes, I think those are you qualities, by the way. >> I don't doubt they're your qualities. Is that how people refer to you in business? >> Yeah, I think so. I mean, I've done the test where they say are you a collaborator or do you push? And I get the mix. I'm either a collaborator or I'm a person that's pushing her own belief, and I know exactly who said I was a person that was only pushing her own belief, and I know the ones that said I was a collaborator. But that is, you got to be collaborative. >> I believe you have those attributes, but the reason for my question is a lot of times when it's a woman fixer, those aren't the adjectives that they would use to describe you. It would be abrasive or combative. I mean, you hear adjectives like that. Same exactly attributes as a male fixer, just described differently. Has that changed in your view? >> I go about things probably a little bit differently than men do, and I've had to adapt. Like I said, I've been a chemist. What was I? 8% of the community of chemists is a woman, so I've had to adapt my style. And I do a lot of drive-bys, I do a lot of one-on-one discussions over the lunch, over hey, do you have a few minutes? I need to talk to you. So, I do a lot of that type of collaboration before I ever get into that big meeting where I'm pushing my one direction. I've got my buddies all lined up already, and so I don't think it feels like I'm abrasive or that I'm, because I've fought those battles privately already. So maybe I've adapted my style that I don't get those types of reactions, but that's what you got to do. You've got to learn how to work the system. >> At the same time, I think that, and this is a compliment, I think Jean on the outside, it's tough to earn her respect in the beginning, but if you do, there's nobody more fiercely loyal than Jean. So you got to earn your way in there, and that's got to be consistent, like a 15-step process to get there. (Jean laughs) >> Yeah. >> And you can't let go because if you let go-- >> Dave: They're hard to get, huh? >> She's going to make you think on number six day you're not good enough, and then you just got to keep on going. So I understand what you're stating, Dave. You have to keep on going, and if you get there there's nothing that Jean wouldn't do for you. As she's here, she's on the advisory board of UiPath. She is the most, once you prove yourself, that's it. It's going to be hard to change that, but it's not easy to get there. >> So this inherent bias, people are tribal in nature and they're biased. Does things like automation and RPA, AI, does it eliminate that bias or does it codify it? >> Wow, interesting question. I don't know, I don't know the answer to that. >> Dave: I don't think anybody knows. >> I don't know that either. >> I've never really thought about it. I mean, to me RPA is just another tool in my toolkit, you know? And if I can fix it with AI, great, or UiPath, if I can use that to fix it with RPA, great. If I need another toolkit, I'll go use that toolkit. But I do know that it's a way that individuals, you can get a lot of young people into your organization that have great ideas. I'm stocking up with interns and I'm using, like I said, woman we hired, she was my intern, graduated in May, and the next day she had a full-time job. And she's done a phenomenal job. And that's what RPA has done for our business, because it's an entree in that then they're in and they're doing this simpler technology, then people see how wonderful they are and they can go and move into bigger and better roles. And that's what I'm trying to encourage is get some really smart people in with this tool, and that's what UiPath has enabled, I think, people that maybe they're not the best coders, or maybe they're not the best BAs, but you put that together and they're knocking it out of the park. The young ones are knocking it out of the park on this technology. It's amazing. >> We did several blockchain and Crypto conferences this year, you want to talk about diversity, and I mean it's old money, it's new money, it's women, it's people in turbans, it's people with color. It's actually quite amazing, and one of the older investors, I asked him what's your secret? He said, "I surround myself with millennials." (laughs) >> Jean: Correct. >> That was good advice, but very diverse crowd in Crypto. You don't have to be Ivy League, Silicon Valley and white, Caucasian, to be successful, right? >> Dave, I was representing RPA at a Women in Tech conference last week in the FinTech environment, and I was talking, sitting next to Crypto and Bitcoin and at the end, the lines lined up for RPA. And I would say to the girls, why are you lined up for RPA? And they basically said you are the disruptor. RPA is the disruptor. There was a speaker here today that says RPA's the gateway drug to artificial intelligence, which is absolutely true. RPA is operational right now, it's working today, and there's elements of AI that are here today, but there's elements that are future technology. But RPA's completely ready to go, operational, mainstream in most enterprise companies. >> And I know we kind of went off topic there but it's relevant and it's important and it's a passion of ours, so really appreciate you guys coming on theCUBE. >> Thank you. >> Thank you, Dave. Thank you, Stu. >> All right, keep it right there everybody. Stu and I will be back with our next guest right after this short break. You're watching theCUBE live from UiPath Forward in Miami. Right back. (upbeat electronic music)