>> Live from Miami Beach, Florida, it's theCUBE. Covering UiPathForward Americas. Brought to you by UiPath. >> Welcome back to Miami everybody. You're watching theCUBE, the leader in live tech coverage. We go out to events, we extract the signal from the noise. A lot of noise here but the signal's all around automation and robotic process automation. I'm Dave Vellante, he's Stu Miniman, my co-host. Guy Kirkwood's here he's the UiPath chief evangelist otherwise known as the chief injector of Kool-Aid. Welcome. (guests chuckling) And Craig LeClair, the Vice President at Forrester. Covers this market, wrote the seminal document on this space. Knows it inside out. Craig, great to see you again. >> Yeah, nice to see you again. It's great to be back at theCUBE. >> So let's start with the analyst perspective. Take us back to when you first discovered RPA, why you got excited about it, and what Forrester Research is all about in that space. >> Yeah, it's been a very a interesting ride. Most of these companies, at least that are the higher value ones in the category they've been around for a long time. They've been around for over a decade, and no one ever heard of them three years ago. So I had covered at Forrester, business process management and some of the business rules engines, and I've always been in process. I just got this sense that there was a way that companies could make progress and digital transformation and overcome the technical debt that they had. A lot of the progress has been tepid in digital transformation because it takes tremendous amount of time and tons of consultants to modernize that core system that really runs the company. So along comes this RPA technology that allows you to build human equivalence that patch up the inefficiencies without touching. I came in on American Airlines and the system that cut my ticket was designed in 1960. It's the same Sabre reservation system. That's the big obstacle that a lot of companies have been struggling to really take advantage of AI in general. A lot of the more moonshot and more sophisticated promises haven't been realized. RPA is a very practical form of automation that companies can get a handle on right now, and move the dial for digital transformation. >> So Guy we heard a vision set forth by Daniel this morning. Basically a chicken in every pot, I call it, a robot for every person. Now what Craig was just saying about essentially cutting the line on technical debt, do you have clear evidence of that in your customer base? Maybe you could give some examples. >> What we're really seeing is that as organizations have to deal with the stresses, what Leslie Wilcox professor at LSE describes as the stresses within organizations and particularly in environments where the demographics are changing. What we're seeing is that organizations have to automate. So the best example of that is in Japan where the Japanese population peaked in 2010. It's now falling as a whole, plus all the baby boomers, people of Craig's and my age are now retiring. So we're now in a position where they measure levels of dangerous overwork as being more that 106 hours a week. That isn't 106 hour a week in total, that's 106 hours a week in addition to the 60 hours a week the Japanese people normally work. And there is a word in Japanese, which is (speaking in foreign language), which means to work oneself to death. So there really is no choice. So what we're seeing happening in Japan will be replicated in Western Europe and certainly in the US over the next few years. So what's driving that is the rise of the ecosystems of technologies of which RPA and AI are part, and that's really what we're seeing within the market. >> Craig, sometimes these big waves particularly in infrastructure, you kind of saw it with virtualization and some other wonky techs, like data reduction. They could be a one-time step function, and not an ongoing business value creator. Where does RPA fit in there? How can organizations make sure that this is a continuous business value generator as opposed to a one time hit? >> Good question. >> Well, I like the concept of RPA as a platform that can lead to more intelligence and more integration with AI components. It allows companies to build an automation center or a center of excellence focused on automation. But the next thing they're going to do after building some simple robots that are doing repetitive tasks, is they're going to say "Oh well wouldn't it be better "if my employee could have a textual chat with a chatbot "that then was interacting with the digital worker "that I built with the bot." Or they're going to say "You know what? I really want to use that machine learning algorithm "for my underwriting process, but I can use these bots "to go out and collect all the data from the core systems "and elsewhere and from the web and feed the algorithms "so that I could make a better decision." So again it goes back to that backing off the moonshot approach that we've been talking about that AI has been taking because of the tremendous amount of money spent by the major players to lay out the promise of AI has really been a little dysfunctional in getting organizations' eye off the ball in terms of what could be done with slightly more intelligent automation. So RPA will be a flash in the pan unless it starts to embed these more learning-capable AI modules. But I think it has a very good chance of doing that particularly now with so much investment coming into the category right. >> Craig, it's really interesting. When I heard you describe that it reminds me of the home automation. The Cortanas and Alexas and consumer side where you're seeing this. You've got the consumer side where you can build skills yourself, you know teenagers people can do that. One of the challenges always on the business side is how do you get the momentum when you don't have the consumer side. How do those interact? >> It's the technical debt issue and it's just like the mobile peak in 2011. Consumers in their hands had much better mobility right away than businesses. It took businesses five, they're still not there in building a great mobile environment. So these Alexa in our kitchen snooping on our conversation and to some extent Netflix that observes our behavior. That's a light form of AI. There is a learning from that behavior that's updating an algorithm autonomously in Netflix to understand what you want to watch. There's no one with a spreadsheet back there right. So this has given us in a sense a false sense of progress with all of AI. The reality is business is just getting started. Business is nowhere with AI. RPA is an initial foray on that path. We're in Miami so I'll call it a gateway drug. >> In fact there's also an element that the Siris, the Cortanas, the Alexas, are very poor at understanding specific ontologies that are required for industry, and that's where the limitation is right now. We're working with an organization called Humly, they're focused on those ontologies for specific industries. So if the robot doesn't understand something, then you could say to the robot Okay sit that in the Wells account, if you're in a bank, and it understands that Wells in that case means Wells Fargo it doesn't mean a hole in the ground with water at the bottom or a town in Somerset in the UK, 'cause they're all wells. So it's getting that understanding correct. >> I wonder if you guys could comment on this. Stu and I were at Splunk earlier this week and they were talking up NLP and we were saying one of the problems is that NLP is sometimes not that great. And they made a comment that I thought was very interesting. They said frankly a lot of the stuff that we're ingesting is text and it's actually pretty good. I would imagine the same is true for RPA. Is that what you see? >> You were talking about that on stage. With regards to the text analytics. >> Yes. So RPA doesn't handle unstructured content the way that NLP does. So NLP can handle voice, it can handle text. For the bots to work in RPA today you have to have a layer of analytics that understands those documents, understands those emails and creates a nice clean file that the bots can then work with. But what's happening is the text analytics layer is slowly merging with the RPA bots platforms so it's going to be viewed as one solution. But it's more about categories of use cases that deal with forms and documents and emails rather than natural language, which is where it's at. >> So known business processes really is the starting point. >> Known business-- >> One example we've got live is an insurance company in South Africa called Hollard, and they've used a combination of Microsoft Cognitive Toolkit, plus IBM Watson and it's orchestrated doing NLP and orchestrated by UiPath. So that's dealing with utterly unstructured data. That's the 1.5 million emails that that organization gets in a year. They've managed to automate 98% of that, so it never sees a human. And their reduction in cost is 91% cost in reduction per transaction. And that's done by one of our implementation partners, a company called LarcAI down there. It's superb. >> Yeah, so text analytics is hard. Last several years we have that sentiment out of it, but if I understand it correctly Craig, you're saying if you apply it to a known process it actually could have outcomes that can save money. >> Yes, absolutely yes. >> As Guy was just saying. >> I think it's moving from that rules-based activity to more experience-based activity as more of these technologies become merged. >> Will the technology in your view advance to the point, because the known processes. okay, there's probably a lot of work to be done there, but today there's so many unknown processes. It's like this messy, unpredictable thing. Will machine intelligence combined with robotic process automation get to the point, and if so when, that we can actually be more flexible and adapt to some of these unknown processes or is that just decades off? >> No, no, I think we talk at Forrester about the concept of convergence. Meaning the convergence of the physical world and the digital world. So essentially digital's getting embedded in everything physical that we have right. Think of IoT applications and so forth. But essentially that data coming from those physical devices is unstructured data that the machine learning algorithms are going to make sense of, and make decisions about. So we're very close to seeing that in factory environments. We're seeing that in self-driving cars. The fleet managers that are now understanding where things are based on the signals coming from them. So there's a lot of opportunity that's right here on the horizon. >> Craig, a lot of the technologies you mentioned, we may have had a lot of the technical issues sorted out, but it's the people interactions some things like autonomous vehicles, there's government policies going to be one of the biggest inhibitors out there. When you look at the RPA space, what should workers how do they prepare for this? How do companies, make sure that they can embrace this and be better for it? >> That's a really tough and thoughtful question. The RPA category really attacks what we call the cubicle population. And there are we're estimating four million cubicles will be emptied out in five years by RPA technology specifically. That's how we built the market forecast 'cause each one of the digital workers replacing a cubicle worker will cost $11,000 or what. That's how we built up the market forecast. They're going to be automation deficits. It's not all going to be relocating people. We think that there's going to be a lot of disruption in the outsource community first. So companies are going to look at contractors. They're going to look at the BPO contract. Then they're going to look at their internal staff. Our numbers are pretty clear. We think they're going to be four million automation deficits in five years due to RPA technology specifically. Now there will be better jobs for those that are remaining. But I think it's a big change management issue. When you first talk about robots to employees you can tell them that their jobs are going to get better, they're going to be more human. They're going to have a much more exhilarating experience. And their response to you is, What they're thinking is, "Damn robot's going to take my job." That's what they're thinking. So you have to walk them up the mountain and really understand what their career path is and move them into this motion of adaptive and continual learning and what we call constructive ambition. Which is another whole subject. But there are employees that have a higher level of curiosity and are more willing to adapt to get on the other side of the digital divide. Yep. >> You mentioned the market. You guys did a market forecast. I've seen, read stats, a little over a billion today. I don't know if that's consistent with your numbers? >> Yeah that's about right. >> Is this a 10X market? When does it get to 10 billion? Is it five, seven, 10 years? >> So we go out five years and have it be close to three billion. I think the numbers I presented on stage were 3.2 billion in five years. Now that's just software licenses and it's not the services community that surround that. >> You'd probably triple it if you add in services. >> I think two to three times service license ratio. There's always an issue at this point in emerging markets. Some of the valuations that are there, that market three billion has to be a bit bigger than that in eight or nine years to justify those valuations. That's always the fascinating capital structure questions we create with these sorts of things. >> So you describe this sort of one for one replacement. I'm presuming there's other potential use cases, or maybe not, that you forecast. Is that right? >> Oh no for the cubicles? >> Yes, it's not just cubicle replacement in that three billion right? It's other uplifts. >> No there are use cases that help in factory automation, in supply chain, in guys carrying around clipboards in warehouses. There are a tremendous number of use cases, but the primary focus are back office workers that tend to be in cubicles and contact center employees who are always in cubicles. >> And then we'll see if the non-obvious ones emerge. >> I think ultimately what's going to happen is the number of people doing back office corporate functions, so that's both finance and accounting procurement, HR type roles and indeed the industry specific roles. So claims processing insurance will diminish over time. But I think what we're going to see is an increase in the number of people doing customer experience, because it's the customer intimacy that is really going to differentiate organizations going forward. >> The market's moving very fast. Reading your report, it's like you were saying yesterday's features are now table steaks. Everybody's watching everybody else. You heard Daniel today saying, "Hey our competitors are watching. "We're open they're going to steal from us so be it." The rising tide lifts all boats. What do you advise clients in terms of where they should start, how they should get started? Obviously pick some quick wins. But what do you tell people? >> I always same pretty much the same advice you give almost on any emerging technology. Start with a good solution provider that you trust. Focus on a proof of concept, POC and a pilot. Start small and grow incrementally, and walk people up the mountain as you do that. That's the solution. I also have this report I call The Rule of Fives, that there are certain tasks that are perfect for RPA and they should meet these three rules of five. A relatively small number of decisions, relatively small number of applications involved, and a relatively small number of clicks in the click stream. 500 clicks, five apps, five decisions. Look for those in high volume that have high transaction volume and you'll hit RPA goal. You'll be able to offset 2 1/2 to four FTE's for one bot. And if you follow those rules, follow the proof of concept, good solution partner everyone's winning. >> You have practical advice to get started and actually get to an outcome. Anything you'd add to that? >> In most organizations what they're now doing, is picking one, two, or three different technologies to actually play with to start. And that's a really good way. So we recommend that organizations pick three, four, five processes and do a hackathon and very quickly they work out which organizations they want to work with. It's not necessarily just the technology and in a lot of cases UiPath isn't the right answer. But that is a very good way for them to realize what they want to do and the speed with which they'll want to do it. >> Great, well guys thanks for coming on theCUBE, sharing your knowledge. >> Thank you. >> Pleasure. >> Appreciate your time. >> Thanks very much indeed. >> Alright keep it right there everybody. Stu and I will be back from UiPathForward Americas. This is theCUBE. Be right back. (upbeat music)

>> Announcer: Live from Las Vegas, it's theCUBE. Covering UiPath Forward Americas 2019. Brought to you by UiPath. >> We're back, UiPath Forward III from Las Vegas at the Bellagio, you're watching theCUBE, the leader in live tech coverage, my name is Dave Vellante. Marie Myers is here, she's the CFO of the rocket-ship known as UiPath. Welcome to theCUBE, thanks for coming on. >> Thank you. >> So, wow. You must be under a lot of pressure to keep the ship moving in a fast direction. But I was just talking to Daniel, he said, you know, when we started the company, we had basic finance systems, kind of like every other startup, but that obviously has changed, so. Well, congratulations, I know you got a lot more work to do but how are you spending your time these days? >> Doing a lot of work, is what I would say. So, as you've kind of seen, that tremendous growth, so huge pressure to just scale the company and ensure that the company has the ability to meet the growth that we're experiencing. So right now I've been really focused on building the operational backbone and actually building a lot of robots for UiPath, actually. That's something I wasn't expecting but came into the role and really help build our own ecosystem around robotics as well. >> I was asking Daniel how much dogfooding, champagne sipping you guys have done and, if it has contributed to the growth and it sounds like quite a bit, actually. >> Absolutely, I'd say we're really hitting the gas pedal right now in terms of building out our own competency and kind of to your point, eating the dog food, drinking the champagne and starting to push the envelope on how we actually use automation and AI to really scale our own business. You asked me where I was spending my time and where I was focused, I literally moved my family to Bucharest for the summer to really focus in on helping to scale the infrastructure. >> So, CFOs usually have a philosophy, a framework, that they like to work with. Obviously you got to stay flexible. How would you describe your philosophy as to how you'd like to manage this company? >> Well clearly, for us we're at an incredible stage of momentum in the market, and the ability for us to continue to build distance in terms of being number one is critical, so in terms of strategy, supporting that number one position, being agile. Able to scale for growth and ultimately do so profitably is certainly the ambition that we have in mind. And that requires turning a lot of different dials, right? And being able to turn them at the right time but at the same time ensure that we've got enough, let's just say, cushion underneath to scale that growth, because the growth is happening very very quickly. >> So CFOs, today's CFO is definitely, I would say more strategic than when I first got into the business, we used to joke that the cheap financial officer. But, I think of CFOs that I really admire, guys like Mike Scarpelli, who was at ServiceNow, now he's at Snowflake. I think he was at Data Domain too, Tom Sweet at Dell, whole different example, they're doing crazy financial engineering. But, much more of a strategic focus. Want to throw gasoline in the fire, and drive growth, but at the same time, thinking about efficiency, so. How have you seen that role evolving and how does that apply to what you guys are doing? >> So I think your comments about the role of the CFO are really right on, I mean, what's perhaps even more interesting, I think, for CFOs that are in software and maybe in a space like we're in is that you ultimately also get involved in being an advocate for your business. In robotics process automation, almost 40% of the first use cases are in finance. So, you're out there supporting the business case with other CFOs who want to understand how does efficiency really, why they should buy from us and what's the business proposition? So you've got to balance the demands of the business with running the business and so, I think that does give you the very unique lens because you understand how this product, to your point, drives operational efficiency. And obviously all CFOs really care, that's right on the list of the top three. >> You know, that's interesting, Marie, because the tech company CIOs are always being pulled in. Because they're early users of some technology. It's not common anyway, that the CFO is one of the lead sales go-to people but it sounds like it is in your case. How much time do you spend in the field? >> I try to balance my time, because you could get pulled very heavily I feel because of the nature of our business into that but I think because robotics process automation has been a key entry point into finance, there's a lot of work for CFOs to do there. So I try to balance my time, but it is, I think, a very important part of our own learning for our company, we get a lot of feedback from our customers. And, even helps me in my role because I get use cases from customers that I apply internally to drive our own efficiency. >> Well, plus, you know, you can see what's happening in the field, you can feel the pain of the sales reps, you can tell which ones are kind of sandbagging, >> You're right, absolutely! >> 'cause they're all sandbaggers! >> You're right about that, so it's been great being at this event, I know a lot of the great reps and so you really understand, you've got a good pulse on what's happening in terms of the business and where the risks are in the quarter. So that's one advantage. >> What're the metrics that you're driving? I mean, obviously the conventional ones, throw those in, but. >> Yeah, I mean obviously productivity, very important for us, we've got a lot of folks we've hired so really understanding what that productivity looks like. The usual cast of characters, AR. Customer acquisition costs, really focused on, what is that first customer costing and then how we're managing our land and expand. What our upsell looks like, so I think the usual cast of characters. >> And then eventually, as all these M and As happen, you'll get cohort sales coming in and the like. So, is everything that you guys sell recognized on a deferred revenue basis? >> No, we're in the midst of converting to 606 right now so we're kind of like subscription one year on prem. So pretty conventional software, red rack. >> Okay, but as you move to the cloud model. >> That gives us a different model, yeah. And we have it, we're just starting that journey. >> It seems like, you see different models. You know, Adobe bit the bullet, Splunk sort of peeled the Band-Aid off very slowly and they both can work. But it seems like a lot of the, I'll call it game, maybe it's the wrong word. But that's what came to mind, is educating the street. On that metric, on that transition. You certainly see it, for instance, in Oracle's case. Putting a lot of emphasis on helping the street understand that transition. That's not your primary focus right now, I'm sure you're spending some time with the analysts, I saw many buzzing around here. >> There was a lot here in the last few days. >> Dave: Yeah, they all want your business! >> (she laughs) They all want your business! I got a lot of texts in the last 48 hours. >> Well, it's an exciting time. And you know, eventually you guys are going to do an IPO and why wouldn't they? Be smart to be here, but what are your thoughts on that? Is that something that you really don't pay attention to right now, are you preparing for that? >> I'd say we're just getting total transparency, we're just moving through 606. So we're digesting that transition first and we're just starting down the whole cloud migration path. So as we start to think that through it's going to be I'd say a priority for 2020. And it's going to be important, I mean, for this business we expect, who's to say what the uptake rate is as customers move to the cloud? But I suspect it's going to be fairly aggressive in our business just because of the nature of bots and how customers think about bots. >> Yeah, so, Daniel said on the previous segment, he said, look, IPO's in our future, probably not 2020, we need at least a year to get our act together. So we're looking at 2021 but it depends on what the climate is, et cetera. My question is, and I've talked to, I see you orange here, Pure Storage is a high flyer in the infrastructure business, they're all orange, so they paint the town orange. >> Seems orange is very popular right now. >> It's a great color, recognizable. But I was talking about, they're all about growth. Not about optimizing profit right now and that's the right play because the street's rewarding growth. You guys, clearly, all about growth. >> We've got the growth story buttoned down, yeah. >> Yeah, you've got that down. But you still want to put gas on the fire, right? So, right now you're still optimized for growth. >> Absolutely, you see what's happening here, right? So, yeah, I think that kind of-- >> And you're well capitalized, so that's not the issue. So the strategy, I presume, is keep growing, get escape velocity, because, the company that gets escape velocity and is the leader in this business, you guys are the leader right now. You're not going to rest, you're going to stay paranoid, I'm sure. But the one that leads is going to make the most money. That always happens. >> Well, extending that leadership role is part of our core strategy, right? Maintaining number one, putting distance. I think you've seen the products that we announced here the last couple of days, adding to the portfolio or giving us incremental TAM so we can grow across the space. I think growing both down the stack and up the stack is critically important for us as we think forward to the future, too, right? We just don't want to be a pure robotics process automation company. We want to look across AI, down the stack into process mining. >> How do you think about your TAM? >> That's a great question. So I've been studying up a little over the last few days preparing for the board meeting tomorrow. I mean, robotics process automation, TAM next year is about two and a half, or two and change in terms of revenue, two billion. I've been looking at it a lot more broadly because I do believe that it is defined today quite narrowly in terms of very traditional RPE. And that started very much in the back office. As we've spread automation and kind of created that platform mentality, the TAM becomes additive. You've got now the process mining TAM which I think we can clearly start to play in that space. And then also the BPMs and now, obviously, AI. So, I was just doing our own back of the envelope in the last few days and you can get, easily, I think now, above that $10 billion mark and it depends on how you start to think about AI as you go forward and that just adds incremental TAM. >> Well, and you throw in services, you're already there. >> Yeah, exactly. >> Probably be there by next year. I think generally, I'll just give you my quick opinion. I think the market's undercounting the TAM potential. And I haven't done a detailed TAM analysis of the, I don't even want to say RPA 'cause that's the core. >> Exactly. >> But I could see this thing expanding dramatically, we talked about cohort sales. Just talking to customers, you're like one to 2% penetrated and there's so many more use cases. As you bring in AI, which, I really think of AI as a horizontal. But if you start applying AI and bringing in automation as an adjacency to you guys, I think that TAM are going to be many many tens of billions beyond what you're thinking. >> That's exactly how I like to think about it, of course, I go back to my IDC friends and try to use some of their benchmarks. But I think they're somewhat conservative. And I think as the market matures and people understand the breadth of the category, I just think that when RPA started it was kind of pigeonholed as a back office opportunity. >> Yeah, I mean, I was at IDC for a long time and we were really crappy at long-term TAM analysis. And you saw it with, Craig LeClair was awesome today. >> Yeah, I love Craig. >> Love him, fantastic. >> Very witty. >> His forecast, however, and same with IDC, we were there, we used to do these linear forecasts and that's not how these markets grow. It's an ogive and a steep S-curve and I think that's my prediction. >> Marie: I couldn't agree more with you. >> We heard predictions this morning, I summarized the predictions and gave my own. And that's one that I see. I'd like to see a longer-term forecast. Maybe we'll work on that. >> Well, we'd love that, I think that's going to be important. I think, part of it's just the maturity of this category. And as folks are starting to understand the breadth of the application, if you think about it, that's why there was so much early work in finance. Now you're starting to see the business spread across the enterprise, right? And I think as it spreads across the enterprise it just adds that incremental TAM and it becomes a gateway to AI. >> I've been using ServiceNow as an example, even though a totally different business, they had a much heavier lift, they started in IT, and went on, so it took longer for adoption. But there's a lot of similarities that I see just in terms of extending beyond just the core of the business, growing the ecosystem, I think is a critical part of that but as far as the customer adoption and the applicability of your technology, I think it's got a lot of legs, so. Like you say, Marie, we'll work on that a little bit. >> I'd love that, thank you. >> Dave: Appreciate you coming on, it was great to have you and wonderful to meet you. >> Enjoyed it. You too, thank you very much. >> You're welcome. Alright, keep right there, buddy, we'll be back to wrap up UiPath Forward III right after this short break. You're watching theCUBE. (electronic music)

>> Narrator: Live from Las Vegas, it's theCUBE, covering UiPath Forward Americas 2019, brought to you by UiPath. >> Hi everybody welcome back to Las Vegas, we're at the Bellagio at UiPath Forward III, day two of theCUBE covers. theCUBE is a leader in live tech coverage. We go out to the events. We extract the signal from the noise. Erik Alexis here is the Vice President of Global Intelligent Process Automation at GE. Eric thanks for coming on. >> Yeah absolutely excited to be here. >> So, you guys have a COE, you're obviously heavily involved in essentially running the COE, is that right? >> Yeah that's my role at GE. I lead our Global Center of Excellence for intelligent process automation. Our journey started with UiPath a while back in 2016. So, it's been an incredible journey so far. >> And I want to get into that. So, before I do, I was struck by the Forrester analyst, Craig LeClair this morning made a statement. I don't know if you're in there, but he said, "Yeah COE, setting up a COE, "maybe that's asking too much." But I talk to a lot of people that have a center of excellence. Maybe it's definitional but what does your COE look like in terms of just it's role, size? >> Yeah it's a great question, so I think in terms of the role that we play more broadly, I mean we provide a lot of the technical expertise, the hands-on development and the operational support for our business units. And so we've really kind of developed that expertise over time, and we use our business units to really drive and identify the opportunities that come in through the COE. So, in terms of the size of the COE, we've got in total number of heads, we've got about 50 primarily technical resources there, that are supporting development as well as ongoing operation. >> Awesome, okay so let's talk about your journey. When did it start? What was the motivation behind it? How did you make the business case, and we'll get into it. >> Yeah so our journey started back in 2016, GE, we used to have a shared services organization that we had a very forward-thinking CEO at the time who wanted to really disrupt the way that we worked. And so RPA was something that was just coming out and kind of getting noticed by a lot of these shared services organizations. And so throughout the year we assessed a couple of technologies obviously landing on UiPath for a number of reasons. I would say in terms of our journey 2017 was kind of our year to prove the technology. We wanted to see if this stuff could really work long term and operate at scale. Given that I'm still here obviously, we proved that was correct and then 2018 was kind of the year of scaling and operationalizing kind of a sustainable model to support our business units across the board from an RPA standpoint. So, really building out a proper structure, building out the governance that goes along with building robots and building a kind of a resource team to continue to support the bots that we were at scale at that point, so maintaining those bots is critically important. And then 2019 has really been the year and I think the theme of this conference in general, a bot for every person I think that's the direction we're moving in 2019. We've kind of perfected the concept of the back office robot and the development of those, and running those at scale. And now we're moving towards a whole new market share when it comes to attended automation and citizen development. >> So, in '16 it was kind of kicking the tires it was almost like R&D. And then '17 was really essentially a proof-of-concept right so still a small team, a two piece kind of team kind of thing right? And then when you talked about scale, helped us understand what's involved in scale, I know it's also another big theme of this conference. What are the challenges of scaling and how did you resolve those? >> Yeah that's a very good question. I think it's a question that has been very common throughout this entire conference. I would say when I think about scaling what I've noticed over the past few years is that, the actual bot development is about 25% of the work that you need to do, right? When it comes to scale there is everything outside of the actual development is the important part. So, how are you funneling opportunities into a pipeline, how are you streamlining the entire process reengineering of fitting an RPA into an existing process, what's governance you have in place to make sure that the code of that development is clean and can be maintained long term? And then more importantly I think that people overlook, people think of scale as being able to develop a lot of bots. I think more importantly what scale is is being able to efficiently maintain a large portfolio of bots, and that's what I've realized this year. We've got now about 300 automations in production and your reputation as an organization is really on how well you maintain those bots, because if your bots are consistently failing, and you're not fixing them quick enough for your functional users to leverage them, then you lose a lot of credibility. So, I think that's been a big learning for us as we reach scale. >> That's interesting I mean I think about scripts, how fragile scripts are and you got a lot of 'em, and they almost always break. And so what is the discipline that allows you to have that quality of bot that is maintainable? Is it a coding discipline? Is it a governance? Is there other automation involved in maintaining those bots? >> No there is and I think the team that's under me, my technical team has done a phenomenal job of setting this up, but we've got some very rigorous standards that we've put in place around. We do have reusable components for example that need to be used on every single robot that goes into production, so that when I look at for example a bots login, that bots login is going to be the same across all my bots. So, every developer who's going to be maintaining that bot knows what it is and how to fix it. I think the standardized logging as well to make sure that we've got robust logging for every single robot is incredibly important because again that's going to be critical when somebody goes to try and fix the bot. >> So you are like an app store, you're enforcing rules like Apple for developers. >> Exactly. >> Okay so let me ask you a question. See now several years in if you had a mulligan, what would you do differently? >> Yeah I think that's another very good question. I think when you first start with this technology, it's unbelievably exciting, because it's something that you can immediately see the difference and the impact it can make, and so you want to try and apply it everywhere to everything, to solve every problem. And I think that's kind of where we got a little ahead of ourselves. We weren't as thoughtful as we should have been when we started taking in the use cases that we were bringing in and while I sit here and tell you that we've got 300 automations in production, I've also decommissioned about 90 automations as well. Because you kind of live and you learn as you go through that process on. This doesn't make sense for RPA. It's not driving the value anymore. It's not driving the right value for the company. >> And is that because the process needs to be reworked before it's automated or there are other factors? >> Yeah I think there's a couple of factors there. I think number one, some bots are intentionally just for short-term use. We look across the portfolio, some bots you design for to operate for two weeks for a massive for example document transition or something like that. So, that's a common reason for decommissioning. I would say secondly you just picked the wrong process. It's not big enough. You think this is perfect for RPA, but it's saving somebody maybe five or 10 minutes a week, which in reality do you really want to put all the effort and to continue to maintain something like that on a back office level? So, I think the size of the processes and the complexity you've got to be thoughtful about as well. >> Thinking about a bot for every worker, what does that actually look like? Is that like you get a laptop and you get a bot? How does that actually manifest itself? >> Yeah I think as I've talked to some of the teams and Daniel as well about this, it's really around I mean imagine opening it up just like any other application on your computer and Excel, you've got that sitting on your desktop and you use that for a number of different things. I think that's kind of how I envision it and everyone when they come into GE, they'll get their laptop and it's part of their kind of package of software that they get. One of them will be UiPath and I think again if GE where I see that as the future. We've got to be thoughtful about how that's rolled out because you want to make sure it's done the right way and you want to make sure that that succeeds and what comes along with that is a lot of education. There's a lot of people that need to be educated on the technology in order to roll that out effectively. >> It's part of the onboarding part, just part of the HR onboarding, and so you open up your laptop and based on your role you'll have a library of bots that are applicable for your job. Is that kind of what you envision? >> Again I think that's kind of the future state and so HR will have a common library that they can pull from and Finance will have a common library that they can pull from. And I think the announcement this weekend of or this week of our StudioX is going to make life significantly easier. So, if you need to kind of edit any of those components or make any custom steps, you can do that with StudioX, but I think having a pre-built set of bots by function would be extremely important. >> And StudioX is the citizen developer right? So, okay now how do you then enforce the edicts of the COE if Dave Vallente's writing automations. >> It's honestly a question that we haven't answered yet and I think that's the piece that we're trying to solve for now, to roll it out more broadly. And I think part of it's going to be training right? Educating the broader group, part of it is giving them access to front office robots and so you do have the code back at the orchestrator so that you can see kind of what's going on and make sure if there are massive changes that need to be made, you can make some of that centrally, so I think figuring out how to centrally maintain and store some of that code is going to be important. >> And the idea of moving beyond this what they call this morning the snowflake into the snowball. So, reusable components is something that I've heard a lot about. That's not trivial yeah right because mapping the right component for the right job is always going to be some kind of unique, not always, but there could be some unique element to put in words. So, what are your thoughts on kind of future? I mean we touched on some of them. It sounds like even though you started early, 2016, it sounds like you still got a long way to go. What's the roadmap look like for you guys? >> Well it's really never-ending because you know you see how quickly the industry is changing and how quickly these automation platforms. I think we're at the point now where these are no longer RPA platforms. They're automation platforms with all of the different features and you look at the broader ecosystem of the technologies being pulled into play. I think it's moving from robotics process automation into intelligent process automation. And that's really our goal and leveraging the ecosystem that the UiPath is built is I think what we want to do more of going forward. >> And the primary measurement of value to you, I'm inferring is time saved from doing non-differentiated tasks, is that really a key metric or are there others that you're looking at, bottom line dollars that you're saving or what? >> I think the way that we measure productivity is really in three major buckets. One is the hours saved so that employees can do other things and I would say that is far and away, the largest bucket that we have. But I think additionally you've got to think about direct cost out. I mean if my finance team comes to me and says, we're thinking about hiring a person to do this why not an RPA? Why can't we use an RPA to do that instead? So, it's not like anyone's losing their job over. It's just figuring out a better way to supplement your existing workforce. Then I would say the third way really is thinking about the compliance element of things. So, and that's often overlooked. You may not save anyone time. You may not save anyone hours or dollars, but what you can do is expand for example in your audit function, expand your testing or sampling of a certain criteria, instead of sampling maybe the top 20 risky units, you can now sample a 100% of a population, which fundamentally changes how you can get comfortable with your financial statements and other elements of the compliance. >> Talking earlier just I asked is sampling dead because of RPA right? >> It really feels like that you know. >> Dave: Eric it's super knowledgeable. I really appreciate you coming on. >> Absolutely. >> Dave: Congratulations on all your success really. >> Thank you very much Dave. I appreciate it. >> You're welcome. All right keep it right there everybody, we will be back with our next guest right after this short break. We're live from UiPath Forward III from Las Vegas. You're watching theCUBE. (upbeat music)

>> Announcer: Live from Miami Beach, Florida, it's theCUBE covering UiPath Forward Americas, brought to you by UiPath. (upbeat music) >> Welcome back to Miami Beach, everybody. I'm Dave Vellante with Stu Miniman. This is UiPathForward Americas. We're talking about robotic process automation. We're seeing the ascendancy of a new marketplace. You're watching theCUBE, the leader in live tech coverage. Let's see, let's get into it. So Param Kahlon is here. He's the UiPath's Chief Product Officer. Welcome, so we're going to get into some of the product stuff. We haven't really dug down deep today, so that's great. >> Thank you. >> Jairo Quiros is here. He's the Vice President of Global Shared Services, an RPA COE, center of excellence, leader at Equifax. Welcome, thanks for coming on theCUBE. >> Thank you, thank you. >> Jairo, let's start with you. Tell us about your role. I love the title. (Jairo laughs) You got automation in your title. Do people embrace you when they see you coming or run? >> No, no, no. Actually, that's very interesting. I've been with the company for 20 years now, so I'm responsible to lead Global Shared Services all across from business operations, financing, accounting, you name it, IT security, right? So, coming along with automation has been quite a journey for us. First of all, we love the product so thank you, Param for everything you guys do at the service, as well. But truly, automation, what it means to us is pushing our workforce to do stuff that is of more valued added to our customers, removing the but out of the human which is critical to us, so no fear of buts anymore. And it's been two years. >> The product's at the tip of the iceberg, I'm hearing. There's a whole lot of other stuff beneath it, culture, obviously process, mindset. >> Jairo: Yeah, correct. >> We will get into some of that. But Param, tell us about your role as Chief Product Officer. You make it all happen. (Param laughs) >> I'm responsible for making sure we can listen to what our customers want, what the market wants, translate that into requirements, and deliver that in the form of products. That's all I do, it's very simple. >> You're a translator. >> We translate it, transform it into requirements that can be given to the product team, their development team that can go write software for it. >> Kind of like that AI layer in UiPath that translates all this data into something that's actionable, right? >> Param: Absolutely. >> Jairo, you were saying you liked the product before. I mean, our personal experience is we could actually download it and play with it, and we're not ultra technical, some of our guys are. What do you like about the product? >> Well, I think many things. I mean, first of all, I think it's very easy to use, right? So, it's built for execution, right? For instance, in our case, we're having a lot of junior engineers coming on board. So we go out to colleges and recruit people that are passionate about process. So what UiPath offer us is a way for them to entry our operation and actually perform tasks and do, and realize results pretty easily. So then, they can see the work being done and appreciate it. >> So who are the users in your organization? Is it a spectrum? You got the sort of RPA developers and then you got business users, as well? Describe that. >> Well, it's a combination, right? So we built the COE over the past couple years. It's inclusive of not only configurators, but also analysts and people that can understand the business. So when you look at through the process, start thinking about how do you design for automation? So this tool allows a very comprehensive very easy to use and we see they make progress release after release, so it's very exciting. >> Alright, Param, why don't you walk us through the announcements that you made? What's new to the platform? Some enhancement to the community. >> Yeah, so we've done some really key announcements in this event today. The first one that we're very excited about is UiPath Go, which is our marketplace that enables broad innovation across our entire ecosystem of customers and partners. We can create on a platform or we can put it in a marketplace and then everybody else can easily access the innovation that's available there. We also released 2018.3 which is the third release we've done this year, but probably the most comprehensive release that we've done 'til date in the history of Enterprise Automation. So we're very excited about launching that release today, as well. And third, we've announced a $20 million fund that will fund our partners that will co-innovate together with us in bringing out new RPA capabilities, new machine learning and AI capabilities into the marketplace. Those are three key announcements. >> What are the-- >> I'm just-- Sorry, but from my understanding, you run on a quarterly cadence for the release of the primary product, correct? >> We're in a quarterly cadence, yes. >> What are the critical aspects of the new release? >> So, there's a few things we've done in the main release. One of the first things we've done is we've allowed for re-usability of the software. So if you're using a lot of components, if you've built a way to automate a certain process, it could be as simple as, here's how I log into a application, a financial application. The rest of the people in my organization don't have to go reinvent that thing themselves. They can reuse the component, the way I've built it, so they can be reused to process every single aspect of the customer, as well. We've made it very easy for our customers to upgrade to new versions of the software, as we're releasing very rapidly, we want to make sure that the upgrades are easy, but the upgrades are also seamless as in they don't affect any of the existing processes that are running in production. So we support version management and package management so we make it easier for people to manage that. There's some other capabilities that we've done. We've supported internationalization of the platform, so now customers in Japan can use our product in Japanese, customers can use it in Spanish, they can use it in Deutsche, German, so we've allowed that in this release, as well. Another cool thing we've done is allowing humans to provide input to what the robots need to do by putting a form that they can use to provide input to them, so it can provide a better symbiosis of humans working together with robots to achieve more processes and more automation in the ecosystems. There's a lot of stuff, this is some of the highlights. >> So what do you think? I mean, what of those, what of that compendium is of interest to you? >> I think, you know, I've been a member for a year now, from, of their customer advisory board, so they truly listen to what we need to say, right? Because the robotic aspect of it is critical, but there's so many other aspects, such as the analytics. So, understanding the business outcome, right? What's the bot producing? Not necessarily the bot that's up and running, but really, what's the impact to the business? I think that's part of the feedback that we've been given in UiPath, they're really working hard on that. The other aspect which is important also is how do you move forward from simple RPA to more complex automations? So, the human in the loop approach to things is important. We call that those small black boxes, you know people with 20 years of experience, they understand how to make decisions but those aren't documented, right? So, now we're giving the opportunity for that human to become part of the process, right? So that is very powerful to us. >> So one of the aspects we've been looking at, the marketplace seems interesting. I'm wondering if you've had a chance to look at that, are there things that you would consider using, and anything that you might even consider contributing in the future? >> I think so. I think this is a whole movement, it's a community today, so no matter where you are, developers, they love it. My guys are telling me, "When is this out?" Because, you know, they have I mean, they're so much hungry to get stuff done and to share what they can do, it makes a difference not only for our company, but for the world, right? So it means something. >> That's interesting. Your company's been around for a long time. You're not worried about, I mean, this open mindset is really intriguing to us, you're not worried about putting your IP in there? Or do you feel like, this open community, we're going to get back as much as we give? >> No, of course. Of course, there are controls in place, and of course, there'll be a protocol in place, but you know, at the end, you're making a difference in the world. So if someone wants to, for instance, have a mortgage because they're wanting to buy a house, you want to make it easy, right? At the end, that's the end goal. You know, for EquiFax and for all the institutions that are in the same sector. >> So from a product standpoint, we just have Craig LeClair on, he couldn't directly call out UiPath. It's not cool, right? I mean, he has to be independent. But, look, he wrote the report, UiPath went from third on the list to first on the list, out of I don't know, 10, 15 vendors. It's like the Gardiner magic quadrants, all these rating systems, right? We don't do 'em, but we read them because they're good, and they're informative. He said in there that last year's features have become this year's table stakes. And some of the things that are differentiating companies, and obviously UiPath won so I presume you have the differentiation ears. Analytics and governance. Those are two big areas, I see the heads nodding. Maybe you guys could each talk about that, Jairo let's start with you, why are those things important? You address the analytics, you kind of address governance, as well, but maybe you can summarize. >> I mean, we address governance as the get-go, and it's an evolution. So for instance, you know, really, truly when we're looking into RPA, it's not only so much about a tactical approach to a specific problem, but it's really turned into a strategy, right? So if you want to scale, you need to have the proper controls in place. So, these guys have done an amazing job integrating with tools such as Cyberart, for instance which is reall important for many companies. They're trying to secure their systems and make sure that the bots are operating on their very secure environment. >> So you guys not only you were in the place position, now you're in the lead. Now the pressure's really on. It's like the Red Sox, Stu. (laughs) So, how'd you get there? What is that enables that? Architecture? Mindset? Culture? You know, give us the insights there. >> Yeah, first of all, let's say we're super excited about being in the first place. I think it's really good, it's a really good testament to the hard work the team is putting in there, so we're super excited about that. We believe that our success and the product roadmap depends upon hearing a lot from customers and making sure that we're responding to their customers. So I think that's what we have done for the most part is ensuring that if there are things that our customers need, if there are things that our customers think our platform and technology is moving toward, we're actually doing the kinds of things that'll actually take us there. So a lot of the innovation that we've done on the platform has come from a direct result of engagement and working with customers and bringing their success into there. Specifically, the governance and analytics, those are very important aspects of what we're doing on a product. Most of our customers are very large corporations like Equifax, other corporations. They will not use our technology if we couldn't support the level of governance and compliance that they need from the ability to run those processes, especially when they're running autonomously without having a human look over what's happening. So that was a core part of what we've invested in. Analytics is also something that we've invested but we'll continue to make more investments there. We're now hearing from Equifax and other customers that people don't want to just get analytics that is responding to what the robots are doing but they want to understand what sort of business impact the robots are having on the corporation. So we want to build an analytics platform that is ingesting not just the robot workloads but bringing in information about line of business systems, as well, to be able to give the reports and perspectives that somebody can look at that and say the robots have done so much for me. Not just in terms of number of hours, but in terms of the business outcomes that I've achieved through the work the robots are executing. >> Jairo, I want to ask you about innovation at Equifax. We've observed many times in theCUBE that innovation in the tech industry used to march at the cadence of Moore's Law. Oh, new chip's out! We've got to do, we can now put better, faster data warehouse. You know, more storage, whatever it was. The innovation model is changing dramatically. And we've observed that it's a combination now, it seems, of data plus AI plus cloud, for scale. So, what do you think about that sort of innovation sandwich? Do you buy into it? How are you guys applying innovation in your business? >> I mean, I'll tell you I got a similar question the other day, you know. It's about, you know, I live in Costa Rica, right? So we surf all the time, right? So it's about riding, you know, the wave, right? So it's not about riding it, right? If you don't ride it, then you're going to drop, right? And then you're going to fall behind. >> Dave: You're going to be driftwood. >> So, yeah, innovation is there, you know. It's that demand for all companies. For us, innovating not only about how do we approach customers and consumers and we put them first in everything we do, but in how we operate internally. Creating a culture that drives automation, right? So giving time for people to think about stuff, you know, that makes a difference, right? I think that's how I can summarize innovation as of this moment. >> So, Stu had a question. >> So, if I understand this right now, we can blame the robots if our credit score isn't good enough now, right? (laughs) >> What do you think? Blame the robots, right? >> Blame the robots, always. >> Blame the innocent, as we say. Well, guys, thanks very much for coming to theCUBE. >> Param: Thank you. >> Param and Jairo, it was great to have you, appreciate it. >> Thank you again. >> Alright, keep it right there. Stu and I will be back with our next guest from UiPath Forward Americas. You're watching theCUBE. (upbeat music)