>> From New York City, it's theCUBE covering Automation Anywhere Imagine. Brought to you by Automation Anywhere. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're in Midtown, Manhattan at the Automation Anywhere Imagine 2019 Conference. Our second time back. There's a lot of buzz in the air. You can probably see it over my shoulder and we're excited to have a partner on who's just starting their adventure with Automation Anywhere. She's Cay Gliebe, the senior vice-president of marketing and product management for OneSource Virtual. Cay, great to see you. >> Thanks Jeff. I'm very happy to be here talking to you, thank you so much. >> So, before we jump in, give us a background on OneSource Virtual for people who aren't familiar with the company. >> Sure. OneSource Virtual is really designed to help those customers who have purchased Workday for either their HR finance needs to get services, so if they need the platform implemented or they want to outsource their payroll, or their AP Automation, OneSource Virtual's their company. >> Okay. So, a lot of conversations about Workday as an important partnership I know for the Automation Anywhere folks, but you said you're kind of just getting started on this RPA journey, so I wonder if you can tell a little bit about how did you kind of happen stance on the category and why you think it's important and then how did you get connected with Automation Anywhere? >> Right. Yep, so, we had been looking all of last year really at how do we augment the automation that our company is really based on. So, we have a premise; we have some very core patented technology called Atmosphere that allows us to serve the Workday customer. And we know there are new solutions out there; robotics being one of them. We felt that it was the next, natural place for us to look and so, we started looking and then we said, let's go! And we really think about this in three different ways. One, we're a company first and foremost like everybody else out there, so we want to be able to bring robotic process automation to our own corporate functions. Then, we're a business. We have a product; our product happens to be delivering services and it's right for doing more digital automation. And third, we had a new idea regarding robotic process as a service and we want to be able to offer this digital worker in a fully hosted and maintain model where the customer can just subscribe to it rather than having to do all the investment themselves. >> Right. So, you said you signed the paper January 1. We're now at April 16th and you've just been house of fire, going bananas. >> We have been going crazy. We have engaged customers and partners and advisors. We've been talking to the analysts. We've been working internally, so it's been a very fast and furious four months getting going. >> So, I'm curious on the internal side before we kind of talk about the customer and the offering side. How's the implementation going internally? What are some of the things you're targeting to get started to get some early wins? I wonder if you can share some advice to other people that might be in your shoes thinking about bringing that in internally. >> Sure. We're looking at our services category first, so most important to us is to be able to deliver consistent, high quality services to our customers. Just like any other company and because we know that these are the same services that customers might buy, it makes sense to look at, for example, payroll. When you think about payroll services for a company, you're processing their payroll, you're auditing the data, you're doing a variety of things. Well, what about a payroll auditor who can be your assistant in our own company to help you deliver the services to your customer? We estimate this can probably save us about five FTEs based on our current usage-- >> Five FTEs? >> Not that we will get rid of those employees again; this is about providing assistant to the people that we have and for us, it's all about being able to grow without having to invest in as many people as we might have had to do in the past. The second thing is, you know, everybody wants margin. That's how you stay in business and can you improve the margins on the services that you're delivering? >> Right. So, I'm just curious. I think the whole RPA conversations was reframed a little bit this morning in the keynote. Not so much as the substitution for a person, but really an augment for a person just like a mobile phone is. Just like a laptop is. Just like all the other software tools are that we use. I wonder if you that's what you're seeing and you know, are people basically saddling up with their personal digital assistant as kind of a one-to-one or is it kind of a departmental? How is this thing kind of operating in the environment? >> We absolutely see it as a digital, an assistant to you. It is not, ideally, it's not a one-to-one replacement or a one-to-one assignment within the organization. The more we can make the digital worker cover multiple functions, then the more valuable it is. And because of our services side, that absolutely is the case. We have over 600 Workday customers now that we provide service to and so, we can take what maybe 30 people are doing and we can provide them all the same access to that worker for their customers that they're assigned to. >> So, have you already started to deliver these to your customers or are you still in the early days? >> Well, we have the first four developed and we're going to beta with five different customers next week. >> Do they have funny names or just regular names? >> We don't have names for them at all. We've been very pragmatic at this point, so I do have to go back to the team and see if maybe we liven it up or get some ideas from our customers. >> Yeah, you have to have funny names or they won't put them on the wall right? >> Exactly. >> Now, I'm curious. So the third leg that you talked about was really offering RPA as a service clearly Workday is SaaS product, people are used to buying software and services now in that way. Is that hard to implement? Is it a repackage of what the Automation Anywhere people have or is this kind of a new flavor that you're co-developing with them or is it just simply kind of a go-to-market strategy? >> So, I would say a couple of things: one, everything that we do internally for a customer in our services side, we potentially could sell to another Workday customer that does it internally for themselves. So, instead of having to think about recreating and developing the same worker twice, we really can leverage it internally and then we can look at those customers who maybe they don't want to outsource their payroll department. They want to do it internally for whatever reason. They have the same challenges we have and it makes sense for them to be able to get access to the worker. So, I don't know that I can say is it hard or easy yet. We're such early stages, but we've created a portal, we have a way, we've worked through how we're going to set this up and at this point we're waiting for the results from the beta to come through. I can tell you that I have about 17 customers on our advisory board that all want it right now. Like when we showed them the demo, they're like: Can I buy it right now? >> Right now, right. So I was going to say, what are some of the lessons, surprises, as you've gone through this very, very short journey that you didn't expect or easier than you thought, harder than you thought? What are some of the unintended consequences, if you will of moving forward? >> Yeah. It's not about just doing one task, okay? It's very easy to create the one task and the robot that will do the one task. What's not so easy is to create a lot of tasks. So, then you need experts who understand the process, who can document the process. Then people to develop it. Then you want to test it. Then you have to make sure your delivery mechanism can be accessed by the people that you intend to have use it. And I think those are things that we thought through. We're working on where are the problems. Things that we know are actually going to be a bigger issue is for customers who buy in the R pass model, how do they feel about this security? There's this big fear of this digital worker and the reality is they don't hold data. All they do is perform a task that a person was going to do. They are less likely to ever know the data that a person will. A person could potentially remember what they saw. >> Right, right. >> The digital worker will never remember what they saw. >> Probably never get disgruntled. >> Not get disgruntled. They don't get married. They don't get divorced. All those things that get in our way of focusing on our work. >> So, do you see this potentially as an adjunct offering for basically everyone who's using your core services? >> Absolutely everyone using our services and any customer who is using Workday. I've talked to a customer, for example, who is based out of Europe. They absolutely are interested in how we can apply this for their HR function on a global basis. So, there are a number of scenarios to consider. >> Did you go into the store? Were there any bots in the store that were ready-made that you guys used or are you developing them all yourself? >> Right now, we're developing ourselves, but we're talking to about Automation Anywhere, of course, about how do we partner together? Workday is a partner of both of us and we want to make sure that we're bringing the right solutions based on that mutual interest. >> Right because you can potentially sell your bots in the store as well to it. >> Correct. >> Right. >> Correct. >> So, Cay, last question. Just to get your impressions of the show here, you've been here for a little while. It's quite a buzz going on. I don't know what other shows, I'm sure you go to Workday, a big Workday event. Kind of give people a general feel of what's happening here in Midtown this week. >> You know, this is the most exciting show and it's mostly exciting; people are loving. You can come build a bot, you can see what other people are creating, you can learn from many customers who are going down this path and journey and might be at the same stage you're at or they could be further down the path and help you really understand what you should be looking at. So, the connection and the networking and the way that the whole Automation Anywhere team brings everyone together is fantastic. >> Awesome. >> It's a great event. >> Well, love your enthusiasms. I think you're going to be very successful with this-- >> I hope so. >> with this opportunity. Alright Cay, well thanks for taking a few minutes of your day and best to you and the team in moving forward. >> Okay, thank you Jeff. >> Alright. She's Cay, I'm Jeff. You're watching theCUBE. We're at Automation Anywhere Imagine 2019. Thanks for watching. We'll see you next time. (bright music)

>> From Times Square, in the heart of New York City, it's theCUBE. Covering Imagine 2018. Brought to you by, Automation Anywhere. >> Welcome back everybody, Jeff Frick here with theCUBE. We're in Manhattan, New York City, at Automation Anywhere's Imagine Conference 2018. About 1,100 professionals really talking about the future of work bots, and really how automation is gonna help people do the mundane a little bit easier, and hopefully free us all up to do stuff that's a little bit more important, a little higher value. We're excited to have our next guest, he's Craig Le Clair, the VP and Principal Analyst from Forrester, and he's been covering this space for a long time. Craig, great to see ya. >> Yeah, nice to see you, thanks for having me on. >> So, first off, just kind of general impressions of the event? Have you been to this before? It's our first time. >> Yes, I did a talk here last year, so it was a little bit smaller then. There's obviously more people here today, but it's pretty much, I think it was in Brooklyn last year. >> It was in Brooklyn, okay. >> So, this is an upgrade. >> So, RP Robotic Process Automation, more affectionately, probably termed as bots. >> Yeah. >> They're growing, we're seeing more and more time and our own interactions with companies, kind of on the customer service side. How are they changing the face of work? How are they evolving as really a way for companies to get more leverage? >> Yeah, so I'll make one clarification of your sentence, and that's, you know, bots do things on behalf of people. What we're talking to in a call center environment is a chat bot. So, they have the ability to communicate or really, I would say, attempt to communicate with people. They're not doing a very good job of it in my view. But, bots work more in the background, and they'll do things for you, right? So, you know, they're having a tremendous effect. I mean, one of the statistics I was looking at the other day, per one billion dollars of revenue, the average company had about 150 employees in finance and accounting ten years ago. Now, instead of having 120 or 130, it's already down to 70 or 80, and that's because the bots that we're talking about here can mimic that human activity for posting to a general ledger, for switching between applications, and really, move those folks on to different occupations, shall we say. >> Right, right. >> Yeah. >> Well it's funny, Jeff Immelt just gave his little keynote address, and he said, "This is the easiest money you'll find in digital transformation is implementing these types of technology." >> Yeah, it's a good point, and it was a great talk, by the way, by Jeff. But, you know, companies have been under a lot of pressure to digitally transform. >> Right. >> You know, due to really the mobile, you know, mobile peaked around 2012, and that pushed everyone into this gap that companies couldn't really deal with the consumer technology that was out there, right? So then you had the Ubers of the world and digital transformation. So, there's been a tremendous focus on digital transformation, but very little progress. >> Right. >> When we do surveys, only 11% are showing any progress at all. So, along comes this technology, Robotic Process Automation that allows you to build bots without changing any of the back end systems. There's no data integration. You know, there's no APIs involved. There's no big transformation consultants flying in. There's not even a Requirements Document because you're gonna start with recording the actual human activity at a work station. >> Right. >> So, it's been an elixir, you know, frankly for CIOs to go into their boss and say, "You know what, we're doing great, you know, I've just made this invoice process exist in a lot better way." You know, we're on our path to digital transformation. >> And it's really a different strategy, because, like you said, it's not kind of rip and replace the old infrastructure, you're not rewriting a lot of applications, you're really overlaying it, right? >> Which is one of the potential downfalls is that, you know, sometimes you need to move to that new cloud platform. You don't want, to some extent, the technology institutionalizes what could be a very bad process, one that needs to be modernized, one that needs to be blown up. You know, we're still using the airline reservation systems from 1950s, and layers, and layers, and layers and layers built upon them. At some point, you're gonna have to design a new experience with new technology, so there's some dangers with the seduction of building bots against core systems. >> Right, so the other thing that's happening is the ongoing, I love Moore's Law, it's much more about an attitude then the physics of a microprocessor, but you know, compute, and store, and networking, 5Gs just around the corner, cloud-based systems now really make that available in a much different way, and as you said, mobile experience delivers it to us. So as those continue to march on and asymptomatically approach zero and infinite scale, we're not there yet, but we're everyday getting a little bit closer. Now we're seeing AI, we're seeing machine-learning, >> Yes. >> We're seeing a new kind of class of horsepower, if you will, that just wasn't available before at the scale it's at today. So, now you throw that into the mix, these guys have been around 14 years, how does AI start to really impact things? >> It's a fascinating subject and question. I mean, we're, at Forrester, talking about the forces of automation. And, by the way, RPA is just a subset of a whole set of technologies: AI, you mentioned, and AI is a subset of automation, and there's Deep Learning, is a subset of AI and you go on and on, there are 30, 40 different automation technologies. And these will have tremendous force, both on jobs in the future, and on shifting control really to machines. So, right now, you can look at this little bubble we had of consumer technology and mobile, shifting a lot of power to the consumer, and that's been great for our convenience, but now with algorithms being developed that are gonna make more and more decisions, you could argue that the power is going to shift back to those who own the machines, and those who own the algorithms. So, there's a power shift, a control shift that we're really concerned about. There's a convergence of the physical and digital world, which is IOT and so forth, and that's going to drive new scale in companies, which are gonna further dehumanize some of our life, right? So that affects, it squeezes humans out of the process. Blockchain gets rid of intermediaries that are there to really transfer ideas and money and so forth. So, all of these forces of automation, which we think is gonna be the next big conversation in the industry, are gonna have tremendous effect societally and in business. >> Right. Well, there's certainly, you know, there's the case where you just you can't necessarily rescale a whole class of an occupation, right? The one that we're all watching for, obviously, is truck drivers, right? Employs a ton of people, autonomous vehicles are right around the corner. >> Right. >> On the other hand, there's going to be new jobs that we don't even know what they're gonna be yet, to quote all the graduating seniors, it's graduation season, most of them are going to work in jobs that don't even exist 10 years from now. >> Correct, correct, very true. >> And the other thing is every company we talk to has got tons of open reqs, and they can't get enough people to fulfill what they need, and then Mihir, I think touched on an interesting point in the keynote, where, ya know, now we're starting to see literal population growth slow down in developed countries, >> Yes. >> Like in Japan is at the leading edge, and you mentioned Europe, and I'm not sure where the US is, so it's kind of this interesting dichotomy: On one side, machines are going to take more and more of our jobs, or more and more portions of our job. On the other hand, we don't have people to do those jobs necessarily anyway, not necessarily today, but down the road, and you know, will we get to more of this nirvana-state where people are being used to do higher-value types of activities, and we can push off some of this, the crap and mundane that still, unfortunately, takes such a huge portion of our day to day world? >> Yeah, yeah. So, one thought that some of us believe at Forrester, I being one of them, is that we're at a, kind of, neutral right point now where a lot of the AI, which is really the most disruptive element we're talking about here, our PA is no autonomous learning capability, there's no AI component to our PA. But, when AI kicks in, and we've seen evidence of it as we always do first in the consumer world where it's a light version of AI in Netflix. There's no unlimited spreadsheets sitting there figuring out which one to watch, right? They're taking in data about your behavior, putting you in clusters, mapping them to correlating them, and so forth. We think that business hasn't really gotten going with AI yet, so in other words, this period that you just described, where there seems to be 200,000 people hired every month in the ADP reports, you know, and there's actually 50,000 truck driver jobs open right now. And you see help-wanted signs everywhere. >> Right, right. >> We think that's really just because business hasn't really figured out what to do with technology yet. If you project three or four years, our projections are that there will be a significant number of, particular in the cubicles that our PA attacks, a significant number of dislocation of current employment. And that's going to create this job transformation, we think, is going to be more the issue then replacement. And if you go back in history, automations have always led to transformation. >> Right. >> And I won't go through the examples because we don't have time, but there are many. And we think that's going to be the case here in that automation dividends, we call them, are going to be, are being way underestimated, that they're going to be new opportunities, and so forth. The skills mis-match is the issue that, you know, you have what RPA attacks are the 60 million that are in cubicles today in the US. And the average education there is high school. So, they're not gonna be thrown out of the cubicles and become data scientists overnight, right? So, there's going to be a massive growth in the gig economy, and there's an informal and a formal segment of that, that's going to result in people having to patch together their lives in ways they they hadn't had before, so there's gonna be some pain there. But there are also going to be some strong dividends that will result from this level of productivity that we're gonna see, again, in a few years, cause I think we're at a neutral point right now. >> Well, Amara's Law doesn't get enough credit, right? We overestimate in the short-term, and then underestimate the long-term needs affect. >> Absolutely. >> And one of the big things on AI is really moving from this, in real time, right? And all these fast databases and fast analytics, is we move from a world where we are looking in the rear view mirror and making decisions on what happened in the past to you know, getting more predictive, and then even more prescriptive. >> Yes. >> So, you know, the value unlock there is very very real, I'm never fascinated to be amazed by how much inefficiency there still is every time we go to these conferences. (Craig laughs) You know we thought we solved it all at SAP and ERP, that was clearly-- >> Clearly not the case. Funny work to do. >> But, it's even interesting, even from last year, you mentioned that there the significant delta just from year to year is pretty amazing. >> Yes, I've been amazed at the level of innovation in the core digital worker platforms, the RPA platforms, in the last year has been pretty amazing work. What we were talking about a year ago when I spoke at this conference, and what we're talking about now, the areas are different. You know, we're not talking about basic control of the applications of the desktop. We're talking about integration with text analytics. We're talking about comp combining process mining information with desktop analytics to create new visions of the process. You know, we weren't talking about any of that a year ago. We're talking about bot stores. They're out there, and downloadable robots. Again, not talking about last year at all. So, just a lot of good progress, good solid progress, and I'm very happy to be a part of it. >> And really this kind of the front end scene of so much of the development is manifested on the front end, where we used to always talk about citizen developers back in the day. You know, Fred Luddy, who was just highlighted Service Now, most innovative company. That was his, you know, vision of Citizen Developer. And then we've talked about citizen integrators, which is really an interesting concept, and now we're talking about really citizens, or analysts, having the ability via these tools to do integrations and to deliver new kind of work flows that really weren't possible before unless you were a hardcore programmer. >> Yeah, although I think that conversation is a little bit premature in this space, right? I think that most of the bot development requires programming skills today, and they're going to get more complicated in that most of the bot activities today are doing, you know, three decisions or less. Or they're looking at four or five apps that are involved, or they're doing a series of four or five hundred clicks that they're emulating. And the progression is to get the digital workers to get smarter and incorporating various AI components, so you're going to have to build, be able to deal statistically with algorithm developments, and data, and learning, and all of that. So, it's not.... The core of this, the part of it that's going to be more disruptive to business is going to be done by pretty skilled developers, and programmers, and data scientists, and statistical, you know, folks that are going through. But, having said that, you're going to have a digital workforce that's got to be managed, and you know, has to be viewed as an employee at some level to get the proper governance. So you have to know when that digital worker was born, when they were hired, who do they report to, when were they terminated, and what their performance review is. You gotta be doing performance reviews on the digital workers with the kind of dashboard analytics that we have. And that's the only way to really govern, because the distinction in this category is that you're giving these bots human credentials, and you're letting them access the most trusted application boundaries, areas, in a company. So, you better treat them like employees if you want proper governance. >> Which becomes tricky as Mihir said when you go from one bot to ten bots to ten thousand. Then the management of this becomes not insignificant. >> Right. >> So Craig, I want to give you the last word. You said, you know, big changes since last year. If we sit down a year from now, 2019, _ Oh. >> Lord knows where we'll be. What are we gonna talk about? What do you see as kind of the next, you know, 12-month progression? >> You know, I hope we don't go to Jersey after Brooklyn, New York, and-- >> Keep moving. >> I see Jersey over there, but it's where it belongs, you know, across the river. I'm from Jersey, so I can say that. You know, I think next year we're gonna see more integration of AI modules into the digital worker. I think with a lot of these explosive markets, like RPA is, there's always a bit of cooling off period, and I think you're going to see some tapering off of the growth of some of the platform companies, AA, but also their peers and compatriots. That's natural. I think that the area has been a little bit, you know, analysis and tech-industry loves change. If there's no change, there's nothing for us to write about. So, we usually over-project. Now, in this case, the 2.8 billion-dollar market project five years out that I did is being exceeded, which is rare. But I expect some tapering off in a year where there's not a ceiling hit, but that, you know, you end up with going through these more simple applications that can be robotized easily. And now you're looking at slightly more complicated scenarios that take a little more, you know, AI and analytics embedded-ness, and require a little more care, they have a little more opaque, and a little more thought, and that'll slow things down a bit. But, I still think we're on our way to a supermarket and a lot of productivity here. >> So just a little less low-hanging fruit, and you gotta step up the game a little bit. >> I guess you could, you said it much simpler then I did. >> I'm a simple guy, Craig. >> But that's why you're the expert on this panelist. >> Alright, Craig, well thanks for sharing your insight, >> Alright. >> Really appreciate it, and do look forward to talking to you next year, and we'll see if that comes true. >> Alright, appreciate it, take care now. >> He's Craig Le Clair and I'm Jeff Frick. You're watching theCUBE from Automation Anywhere Imagine 2018.