>> 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)

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape hello everyone and welcome to this week's episode of wiki bots cube insights powered by EGR in this breaking analysis we take a deeper dive into the world of robotic process automation otherwise known as RPA it's one of the hottest sectors in software today in fact Gartner says it's the fastest growing software sector that they follow in this session I want to break down three questions one is the RP a market overvalued - how large is the total available market for RP a and three who were the winners and losers in this space now before we address the first question here's what you need to know about RP a the market today is small but it's growing fast the software only revenue for the space was about 1 billion dollars in 2019 and it's growing it between 80 to a hundred percent annually RP a has been very popular in larger organizations especially in back-office functions really in regulated industries like financial services and healthcare RP a has been successful at automating the mundane repeatable deterministic tasks and most automations today are unattended the industry is very well funded with the top two firms raising nearly 1 billion dollars in the past couple of years they have a combined market value of nearly 14 billion now some people in the art community have said that RP a is hyped and looks like a classic pump and dump situation we're gonna look into that and really try to explore the valuation and customer data and really try to come to some conclusions there we see big software companies like Microsoft and sa P entering the scene and we want to comment on that a little later in this segment now RBA players have really cleverly succeeded in selling to the business lines and often a bypassed IT now sometimes that creates tension in or as I said customers are typically very large organizations who can shell out the hundred thousand dollar plus entry point to get into the RP a game the Tam is expanding beyond back office into broader on a broader automation agenda hyper automation is the buzzword of the day and there are varying definitions Gartner looks at hyper automation as the incorporation of RPA along with intelligent business process management I BPM and I pass or intelligent platform-as-a-service Gardner's definition takes a holistic view of the enterprise incorporating legacy on-prem app apps as well as emerging systems now this is good but I question whether the hyper term applies here as we see hyper automation as the extension of our PA to include process mining to discover new automations or new automation opportunities and the use of machine intelligence ml and a I applied to process data data where that combination drives intelligence analytics that further drives digital business process transformation across the enterprise so the point is that we envision a more agile framework and definition for hyper automation we see legacy BPM systems informing the transformation but not necessarily adjudicating the path forward we liken this to the early days of big data where legacy data warehouses and ETL processes provided useful context but organizations had to develop a new tech stack that broke the stranglehold of technical debt we're seeing this emerge in the form of new workloads powered by emerging analytic databases like redshift and snowflake with ml tools applied and cloud driving agile insights in that so-called Big Data space so we think a similar renaissance is happening here with with automation really driven by the money the mandate for digital business transformation along with machine intelligence and that tooling applied for a really driving automation across the enterprise in a form of augmentation with attended BOTS at scale becoming much much more important over time ok now let's shift gears a little bit question is the RP a market overhyped and overvalued now to answer this let's go through a bit of a thought exercise that we've put together and look at some data what this chart shows is some critical data points that will begin to help answer the question that we've posed in the top part of the chart we show the company the VC funding projected valuations and revenue estimates for 2019 and 2020 and as you can see uipath an automation any where are the hot companies right now they're private so much of this data is estimated but we know how much money they've raised and we know the valuations that have been reported so the RP a software market is around a billion dollars today and we have it almost doubling in 2020 now the bottom part of this chart shows the projected market revenue growth and the implied valuations for the market as a whole so you can see today we show a mark that is trading at about 15 to 17 times revenue which seems like a very high multiple but over time we show that multiple shrinking and settling in mid decade at just over 5x which for software is pretty conservative especially for high-growth software now what we've done on this next chart is we brought down that market growth and the implied valuation data and highlighted twenty twenty-five at seventy-five billion dollars the market growth will have slowed by then to twenty percent in this model and this thought exercise with a revenue multiple of five point four x for the overall market now eventually as growth slows RBA software will start to throw off profits at least it better so what we show here is a sensitivity analysis assuming a 20% 25% 30% and 35% for the market as a whole we're using that as a proxy and we show a 20/20 X even multiple which for a market growing the software market growing this fast you know we think is pretty reasonable consider the tech overall typically is gonna have a an even multiple of ten to fifteen you know X it really should be easy your enterprise value over a bit it's really a more accurate measure but but this is back in the Afghan on the balance sheet date and I'm a forecast all-out but we're trying to just sort of get to the question is is this market overvalued and as you can see in the Far column given these assumptions we're in the range of that seventy five billion dollar market valuation with that Delta now reality you're going to have some companies growing faster than the market overall and we'll see a lot of consolidation in this space but at the macro level it would seem that the company which can lead and when the Spoils is gonna really benefit okay so these figures actually suggest in my view that the market could be undervalued that sounds crazy right but look at companies like ServiceNow and work day and look at snowflakes recent valuation at twelve billion dollars so are the valuations for uipath and automation anywhere justified well in part it depends on the size of the market the TAM total available market in their ability to break out of back-office niches and deliver these types of revenue figures and growth you know maybe my forecasts are a little too aggressive in the early days but in my experience the traditional forecast that we see in the marketplace tend to underestimate transformative technologies you tend to have these sort of o guides where you know it takes off and really steep ins and it has a sharp curve and then tapers off so we'll see but let's take a closer look at the Tam but you know first I want to introduce a customer view point here's Eric's Lac Eric Lex who's an RPA pro at GE talking about his company's RPA journey play the clip 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 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 that you know we were at scale at that point so maintaining those bots is critically important 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 you know a whole new market share when it comes to attended automation and citizen Development so this is a story we've heard from many customers and we've tried to reflect it in this graphic that we're showing here start small get some wins prove out the tech really in the back office and then drive customer facing activities we see this as the starting point for more SME driven digital transformations where business line pros are rethinking processes and developing new automations you know either in low code scenarios or with Centers of Excellence now this vision of hyper automation we think comes from the ability to do process mining and identify automation opportunities and then bring our PA to the table using machine learning and AI to understand text voice visual context and ultimately use that process data to transform the business this is an outcome driven model where organizations are optimizing on business KPIs and incentives are aligned accordingly so we see this vision as potentially unlocking a very large Tam that perhaps exceeds 30 billion dollars go now let's bring in some of these spending data and take a look at what the ETR data set tells us about the RPA market now the first thing that jumps out at you is our PA is one of the fastest growing segments in the data set you can see that green box and that blue dot at around 20% that's the change in spending velocity in the 2020 survey versus last year now the one caveat is I'm isolating on global 2000 companies in this data set and as you can see in in that red bar up on the left and remember our PA today is really hot in large companies but not nearly as fast growing when you analyze the overall respondent base and which includes smaller organizations nonetheless this chart shows net scores and market shares for our PA across all respondents remember net score is a measure of spending velocity and market share is a measure of pervasiveness in the survey and what you see here is that our PA net scores are holding steadily the nice rate and market shares are creeping up relative to other segments in the data set now remember this is across all companies but we want to use the ETR data understand who is winning in this space now what this chart shows is net score or spending velocity on the vertical axis and market share or pervasiveness on the horizontal axis for each individual player and as we run through this sequence from January 18 survey through today across the nine surveys look at uipath an automation anywhere but look at uipath in particular they really appear to be breaking away from the pack now here's another look at the data it shows net scores or spending velocity for uipath automation anywhere blue prism pegye systems and work fusion now these are all very strong net scores which are essentially calculated by subtracting the percent of customers spending less from those spending more the two leaders here uipath and automation anywhere August but the rest rest are actually quite good there in the green but look at this look what happens when you isolate on the 349 global 2,000 respondents in the survey uipath jumps into the 80 percent net score territory again spending velocity automation anywhere dips a little bit pegye systems interestingly jumps up nicely but look at blue prism they fall back in the larger global 2000 accounts which is a bit of a concern now the other key point on this chart is that 85% of UI customers and 70% of automation anywhere customers plan to spend more this year than they spent last year that is pretty impressive now as you can see here in this chart the global 2000 have been pretty consistent spenders on our PA for the past three survey snapshots uipath again showing net scores or spending intensity solidly in the 80% plus range and even though it's a smaller end you can see pay go with a nice uptick in the last two surveys within these larger accounts now finally let's look at what ETR calls market share which is a measure of pervasiveness in the survey this chart shows data from all 1000 plus respondents and as you can see UI path appears to be breaking out from the pack automation anywhere in pega are showing an uptick in the january survey and blue prism is trending down a little bit which is something to watch but you can see in the upper right all four companies are in the green with regard to net score or against pending velocity so let's summarize it and wrap up is this market overhyped well it probably is overhyped but is it overvalued I don't think so the customer feedback that we have in the community and the proof points are really starting to stack up so with continued revenue growth and eventually profits you can make the case that whoever comes out on top will really do well and see huge returns in this market space let's come back to that in a moment how large is this market I think this market can be very large at am of 30 billion pluses not out of the question in my view now that realization will be a function of RPAs ability to break into more use cases with deeper business integration RBA has an opportunity in our view to cross the chasm and deliver lower code solutions to subject matter experts in business lines that are in a stronger position to drive change now a lot of people poopoo this notion and this concept but I think it's something that is a real possibility this idea of hyper automation is buzzword e but it has meaning companies that bring RPA together with process mining and machine intelligence that tries process analytics has great potential if organizational stovepipes can be broken down in other words put process data and analytics at the core to drive decision-making and change now who wins let me say this the company that breaks out and hits escape velocity is going to make a lot of money here now unlike what I said in last week's braking analysis on cloud computing this is more of a winner-take-all market it's not a trillion dollar team like cloud it's tens of billions and maybe north to 30 billion but it's somewhat of a zero-sum game in my opinion the number one player is going to make a lot of dough number two will do okay and in my view everyone else is going to struggle for profits now the big wildcard is the degree to which the big software players like Microsoft and sa P poison the RPA well now here's what I think I think these big software players are taking an incremental view of the market and are bundling in RPA is a check off item they will not be the ones to drive radical process transformation rather they will siphon off some demand but organizations that really want to benefit from so-called hyper automation will be leaning heavily on software from specialists who have the vision the resources the culture in the focus to drive digital process transformation alright that's a wrap as always I really appreciate the comments that I get on my LinkedIn posts and on Twitter I'm at at D Volante so thanks for that and thanks for watching everyone this is Dave Volante for the cube insights powered by ETR and we'll see you next time