>> Narrator: Live from Las Vegas, it's theCUBE. Covering UiPath Forward Americas, 2019. Brought to you by UiPath. >> Welcome back everyone to theCUBE's live coverage of UiPath Forward here at the Bellagio in Las Vegas, Nevada. I'm your host, Rebecca Knight, co-hosting alongside of Dave Vellante. We're joined by Cathy Tornbohm, she is the distinguished VP Analyst at Gartner. Thank you so much for coming on theCUBE. >> Very welcome, nice to be here. >> And Guy Kirkwood, he is the Chief Evangelist at UiPath. Thank you so much. >> Thanks Rebecca. >> So, we're hearing so much of these mantras, these catchphrases of UiPath. "automation first", "a robot for every person", "we're re-booting work", these are the theme's that Guy was touting up on the main stage, Cathy. Beyond that, I'd like to hear from you a little bit about what you're seeing in the RPA space at the moment. What are the trends and the themes that you think are most salient? >> I think the most fascinating thing about RPA right now is that it's really highlighting the problems the organizations have. All their accidents of history are really being brought up by RPA. And then you've got these digital darlings that they're trying to compete with, the Greenfield site kind of people. And some of those don't have beautiful back offices, but let's not go there for a minute. So, it, RPA is an opportunity for companies to link their digital dreams with their existing legacy nightmares. >> And those legacy nightmares include all of the things that Guy was talking about today: the drudgery, the dreariness, those mundane tasks that take up so much of our time. >> Absolutely, and really, if you think about it, in organizations, typically less than 15% of the applications that they're using have got some sort of application programming interface. So if you don't have a way of linking them, you end up with this long turn of applications that aren't linked together, with people literally being swivel-chair integration between the applications. >> Well, why can't you just string a bunch of API's together and automate that way? >> Well, in fact, there's a guy called Ian Barkin who works for Symphony, one of their organizations, it was set up to create automations for organizations. So one of the services businesses since been acquired by Sykes. And he describes it as process sediment, and it builds up in businesses in the same way that sedimentary rock builds up over millions of years. And digging through that, so that you can actually become more efficient is very difficult to do. So doing it on API level means you got to join up all those things individually. Whereas, using RPA, if system 'A' has a user interface, and system 'B' has a user interface, you can just use RPA. >> So, Cathy, you've been following process automation as a category for a number of years. Why RPA, why is it so hot, and why now? We've heard that it's the number one software category... >> Cathy: Fastest growing, yeah. Fastest growing, from Gartner. We've seen spending data that confirms that. Why now? (sighing) >> It's the digital competition that companies are facing, and the recognition that they cannot continue to be quite as bad at some of the things that they are bad at. So it's really that business transformation story back again, business process re-engineering, the same story that we had with BPO like ten years ago, but now, with robots instead. >> Yeah, it's interesting, I was at a, we had a show last weekend, it was the CEO of Suze, Suze... How do ya say it? Anyway, Suze, she said to me, "Well, you know, digital transformation's really about business transformation." And you kind of said the same thing. I mean, thoughts on that? >> I mean, you look at the start of the outsourcing market, the BPA market, twenty years ago. The very first deals were actually IT outsourcing deals that then transformed the business using IT as the enabler. So the first deal that I got involved with ever, in the outsourcing market, was Perot Systems with a British and Asian company. And we were putting in business process re-engineering consultants who actually transformed the business using IT as the enabler for that. There is no difference now, in fact one of the, one of the partners here, one of our original customers, actually put together a plan where we did the implementation, you know, soup to nuts, so that we could find out how we fit in to that whole transformation piece. And our team put together a whole package on all the learnings that we got out of that. And I had to laugh, because they're exactly the same things that every transformation program has had for the last thirty years. >> You know, if you look at kind of the history of certain segments, and I wonder if, Cathy, if you see RPA as one of them, like if you could've figured out who was implementing ERP the best, you didn't know SAP was going to become the leader, but if you could've figured out who was adopting ERP, you could've made a lot of money in the stock market, 'cause those companies had a huge productivity boost. Kind of same thing with Big Data, nobody really made any money in Big Data, so-called 'Big Data', a dupe. But the guys who applied it probably did pretty well. Do you see RPA as similar where the practitioners are going to actually be the ones that add more value to the industry than the new, the newly minted billionaires? >> It's almost the opposite. So the more RPA a company needs, it means the worse they did at managing their ERP in the first place. >> So they're kind of a mess? >> Yeah, yes. That need to be cleaned up, yeah. >> Yes, if you've got a hundred and twenty four ERP's that don't talk to each other, and you want to close your books in any kind of reasonable time frame, you're going to be a massive adopter of RPA, which basically means the more rubbish you are and activity, the more opportunity there is to automate more of it. >> So, what are the metrics that matter when you talk to your clients? >> Well, what I try and encourage clients to do is to really focus on business outcomes. So, much as Guy probably doesn't want me to say this, I don't really care how many 'scripts', aka robots, you've built, or how many run times you've deployed. What I care about is the business impact that you've managed to achieve. So, whatever KPI's are important to you, so are you managing to collect more revenue? Are you managing to make your customers happier because you're managing to decrease average handle times? or increase right first time activities. So anything that you're doing that actually improves the good old business metrics, is just going to be fantastic. So those are the sort of metrics that, really, companies should be focusing on. Not how many scripts they've built, that's absolutely pointless. >> I mean, are they focusing on that? I mean, when you... >> Yeah, lots of people are. >> Yeah? >> Yeah. >> In terms of ROI, we hear from customers that it has had them more accurate, they're more efficient, they're cost saving on human hours of the mundane tasks. But, when you were up on the main stage talking about how we're rebooting work, we're changing this moment, is it sparking the creativity, the imagination, the time spent on strategy in the more higher-level things? Is that, I mean that seems like that's the goal of return on investment. >> It is, within those organizations that are the most mature. So, what we're seeing, is the bifurcation, really, of the market between those organizations that are just starting and scaling up what they can, internal senses of excellence. Those organizations that are using the partners behind us. Those organizations that are using external parties to help them develop that. So Delight, for instance, they are sort of a managed service business. And instead of using people, they're using automation. So, Delight, by accident, has a BPA business in Spain, but then they'll turn that into an automation-heavy business and then providing that managed service. And then, the smartest customers, including SNBC, who we heard from yesterday, are actually turning their back office cost operations into a front office of revenue generator. Now, that is radically different from what we've seen prior. >> So Cathy, I got to ask you, when I was on a plane out here, somebody texted me a picture of the latest hype cycle. And they said, they knew I was going to UiPath, they said, "RPA has entered the trough of disillusionment." I said, "Oh, awesome, Gartner's, Cathy's coming on, and I can ask her about that." Well, what's your take on that? >> I think as Guy says, some people have already sailed through the trough, they've already gone through the challenges, or some of the challenges, and they've already found these fantastic productive things. I mean, we're estimating that people will save close to a million dollars for a large company, and just not having to do re-work of getting it wrong first time with re-keying that data. So, where there's some fantastic savings available, that you know, some of the ones have gone through the trough and done that, a lot of the other ones, they kind of, they don't understand the limitations of RPA and all those other partner tools that they need to put with it. So, don't understand it, can't handle unstructured data by itself. It needs a sister tool, so, what Gartner's talking about right now is this concept of hyper automation where you look across all the different activities that you would need to, sort of replace a person. So the people that are heading into the trough as sort of this second wave of adopters that Guy talked about, that will really struggle because they didn't understand the limitations in the first place. >> Well then, you know the, sometimes, things like the Magic Quadrant, and the trough of disillusionment, they're somewhat misunderstood sometimes, people, you know they see 'em, Gartner's very clever with the way it works things, but, so how should we think about that hype cycle? It's actually, in a way it's progress, isn't it? For an industry where they start... Entering that trough. >> Its, what Gartner says, is all industries have to go through that type of growing pains. And I think that we're seeing that, UiPath's expanded massively, and that's always a challenge for companies as they grow very rapidly. And as companies try and, as they say, take these wrong metrics. So I think things like UiPath buying ProcessGold is fantastic, it's a really, really good move for them. And I expect to see a lot of other process mining companies acquired, brought in to the RPA fold, because, there's four reasons why companies are going to go into this disillusionment, right? These are the main challenges with companies trying to use RPA properly. One is, they don't know what the processes are. So ProcessGold will give you a really good indication, they don't know about the microscopic level, and they don't know about the macro level. So things like digital twins will be something else that we would expect to see very closely partnered with companies like UiPath. And they don't know how to orchestrate their resources. So, other companies, like Innate, that can help you figure out how to do that will become... So its kind of like we're sort of breaking down a lot of what happened in other software categories and re-building them all up, in the way that the business can actually adopt them, hence, the AI Fabric sort of idea. So they don't know the processes, politics, people will lie to you about what they do all day, so they can sabotage your process, and there's a lot of silos within organizations that hate each other and throw things over the wall. So that all needs streamlining, and the more you can do across silos, the more successful any automation project would be. Then you've got, when you take a person out of a process, you take their eyes, their ears, the mouth, the nose. How are you going to replace that when you're trying to take them out, because you've got the keyboard fingers thing with the RPA tool? You need all these other activities replaced, replicated, supported. And then you've got the economics of production, so actually making sure that the scripts that you've built are actually worthwhile and are going to be cost-effective. It's something that we're studying at the moment. So you've got all these, all these different barriers, from all these different angles that are really going to push this thing into the trough for a little bit. And that's why it's great that RPA companies are looking at ways to mitigate that for their customers. >> Now, remember we said, as the understandings. So RPA is really good at dealing with structured data. Rule-spaced activities, deterministic things. That's why in regulatory, highly regulated environments, it's very effective, and the regulators love this sort of stuff. Because it's deterministic. When you look at AI, then we look at it in four ways. So you've got process understanding, which is the ProcessGold acquisition, you look at conversational understanding, 'cause ultimately robots are going to be controlled by voice. So you have to understand, the system has to understand that, let's say you're sitting in a bank, and the robot doesn't understand something, you say, "Okay, robot, stick that in the Well's account." It has to understand that Well's, in this case, means Well's Fargo. It does not mean a hole in the ground, water at the bottom, or a town in Somerset, in the UK, 'cause they're well's. So getting those ontologies correct is so important. So, that's conversational understanding. Document understanding. Because, as Cathy said, companies are still wading around in paper. So, understanding what those different documents are and how to action them is going to be really important. And finally, you're looking at visual understanding. So understanding and viewing things on the screen exactly the same way that humans do. So it's getting that combination right. >> So for RPA to live up to the hype, and there's a lot of hype, and it's a good thing, it's fun to track. It's got to go presumably beyond cleaning up the crime scene, if you will, to this new vision that you and Guy just laid out. What is the distance between, I dunno, sometimes I say 'paving the cow path', which gives you a nice hit, but as you say, it's 'cause companies... Ya know, they're messed up, to this vision of this, actually the guy from Pepsi today talked about it, this fabric of automation across the organization. How big of a gap is that? >> It's very different by every different company on the planet, really, in terms of their accidents of history, what their IT application landscape looks like, and what their business landscape looks like. And when you try and put the two things together, that's where you find the opportunities for any type of automation. >> Well come on, that's such an 'it depends' answer. (laughing) At the macro, will... In your expert opinion, will RPA live up to the hype? So many trends haven't, enterprise data warehousing, Big Data, Doob, all that stuff. You think RPA has the potential to crack through that. >> You mentioned a very good point. I think the most successful companies are the ones that actually will take the person that's managing the data and analytics of how their process is performing, and doing that with their automation strategy. And there are very few companies that've actually worked that out. They've still got totally two walls and they just meet up here at the CEO. So, unless companies actually take a more active business outcomes approach, and look at their end-to-end processes of order to cash and source to pay, these problems will carry on for some time. >> Well that's a great point, I mean, so it's data, it's machine intelligence, I guess Cloud for scale, you guys made a SAS announcement today, it's "automation first", to use your buzz word. >> Cathy: You need it all to come together. >> And it's really developing those best practices in your role as Chief Evangelist in helping understand what the most successful companies do, and then making sure that's implemented. >> Well that's why I spend more of my time listening than I do talking. Because the very nature of being a Chief Evangelist is the best job and the worst job title in the world. It's the best job because I spend my entire time talking to people like Cathy who know about what's happening within the market, and then feeding it back into our organization so we can make the right bets, so we can make the right acquisitions, but develop the right things. The bad thing about the job, is that I keep getting an inordinate number of people on LinkedIn saying, "So pleased that Jesus has entered your life." And I'm not that type of evangelist. (laughing) >> It's in the title. >> You know there's always this age-old debate in the industry of best of breed versus kind of a sweet approach. You see in SAP, for instance, acquired an RPA company, In Four talks about it. And then you get the specialist, UiPath. How do you see that shaking out, as the industry gets kind of more consolidated, how do you see a company like UiPath thriving, continuing to thrive? >> Gartner's going to predict coming in our new prediction series, but... Roughly 20 to 30% of enterprise adoption of AI, machine learning activities for process-based activities, will go through the RPA market. So, and with the IBPMS market, sort of combined together, that process management, because RPA has managed, cleverly, to capture the imagination of the business person. So, actually, there's a lot of IT departments that are talking to us about, how do we, how do we enshrine this activity, foreshadow IT, that's happening in the business, and make it successful, put governance plans in place so it will actually be successful in the way that it's actually now dealing with its own crime scene... (laughing) (mumbling) Its own rubbish, in a much better way. And I think that responsibility of business to understand how it can automate things and how it can manage things will really help a lot. So, I think the RPA players are well-placed to either be acquired into that bigger set of the established, large... Software providers, all to kind of keep blazing a trail for independence of the business. I'm not so sure about this idea that everybody should be programming their own scripts, I think that's a challenge. And I think the new interfaces will help mitigate some of the problems that we've seen with that approach, that hasn't been, haven't been very well done historically, so that's another area that will probably be a bit trough of disillusionment, but, actually, well-managed RPA projects have actually got a really good chance of delivering back very interesting benefits for businesses. >> Yeah, as a discreet innovation category, it does kind of feel that way, and often times, those markets are winner take most, the winner makes a ton of dough, number two makes a little bit of money, number three kind of breaks even, and everybody else gets consolidated or goes out of business, so, you guys go big or go home. That's kind of... Your posture. >> Tomorrow morning I'm doing, I'm doing my predictions for next year, and one of them is that the challenger RPA vendors, and indeed the service organizations that are small, are going to continue to consolidate and get acquired next year. So that's the 2020 prediction for us. >> Great. Well, Guy and Cathy, thank you both so much for coming on theCUBE. It was a great conversation. >> Oh, good, thank you. >> Thank you very much, indeed. Thanks Rebecca. >> Dave: Thanks you guys. >> I'm Rebecca Knight for Dave Vellante, stay tuned for more of theCUBES live coverage of UiPath. (techno music)

>> 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. 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