(upbeat music) >> TheCUBE presents UiPath Forward 5. Brought to you by UiPath. >> Hello and welcome back to TheCUBE's coverage of UiPath Forward 5. We're here in Las Vegas at the Venetian Convention Center. This is day two. We're wrapping up Dave Nicholson and Dave Vellante. This is the fourth time theCUBE has been at UiPath Forward. And we've seen the transformation of the company from, essentially, what was a really interesting and easy to adopt point product to now one through acquisitions, IPO, has made a number of enhancements to its platform. David Cardenas is here. Deputy Director of Operations for County of Los Angeles, the Department of Public Health. David, good to see you. Thanks for coming on theCUBE. >> Thanks for having me on guys. Appreciate it. >> So what is your role? What does it have to do with automation? >> So I had been, actually started off in the IT space within the public health. Had served as a CIO previously, but now been moving into broader operations. And I basically manage all of the back office operations for the department, HR, IT, finance, all that. >> So you've had a wild ride in the last couple of years. >> Yeah, I think, like I've been talking earlier, it's just been, the last two years have just been horrendous. It's been a really difficult experience for us. >> Yeah, and I mean, the scars are there, and maybe permanently. But it also had major effects on organizations, on operations that, again, seem to be permanent. How would you describe the situation in your organization? >> So I think it, the urgency that came along with the pandemic response, kind of required us to look at things, you know, differently. We had to be, realize we had to be a lot more nimble than when we were and try to figure out how to enhance our operations. But really look at the core of what we're doing and figure out how it is to be more efficient. So I think we've kind of seen it as an opportunity to really examine ourselves a little bit more deeply and see what things we need to do to kind of, to fix our operations and get things on a better path. >> You know, I think a lot of organizations we talked to say that. But I want to understand how you handle this is, you didn't have time to sit back in the middle of the pandemic. >> Yeah. >> And then as you exit, what I call the isolation economy, people are so burned out, you know? So how do you deal with that organizational trauma? Say, okay now, let's sit back and think about this. Do people, are they eager to do so? Do they have the appetite for it? What's that dynamic like? >> So I think certainly there's a level of exhaustion inside the organization. I can't say that there isn't because it's just been, you know, two years of 24/7/365 kind of work. And that's tough on any organization. But I think what we realize is that there's, you know, we need to move into action quickly 'cause we don't know what's going to come next, right? And we're expecting that this is just a sign of what's to come and that we're just at the start of that stage of, we're just going to see a lot more outbreaks, we're going to see a lot more conditions kind of hitting us. And if we're not prepared for that, we're not going to be able to respond for the, and preserve the health and safety of our citizens, right? So I think we're taking a very active, like, look at these opportunities and see what we've done and say how do we now make the changes that we made in response to the pandemic permanent so that the next time this comes at us, we won't have to be struggling the way that we were to try to figure things out because we'll have such a better foundation in place to be able to move things forward. >> I mean, I've never served in the military, but I imagine that when you're in the military, you're always prepared for some kind of, you know, in your world, code red, right? >> Yeah. >> So it's like this code red culture. And that seems to have carried through, right? People are, you know, constantly aware that, wow. We got caught off guard and we don't want that to happen again. Because that was a big part of the trauma was just the unknown- >> Right. >> and the lack of preparedness. So thinking about technology and its role in helping you to prepare for that type of uncertainty. Can you describe how you're applying technology to prepare for the next unknown? >> So I think, so that first part of what you said, I think the difficulty we've always had in the public health side is that there's the, generally the approach to healthcare is very reactionary, right? Your first interface with the healthcare system is, "I'm going to go see my doctor; I'm going to go to the hospital." The work that we do in public health is to try to do everything we can to keep you out of that, right? So it's broad-based messaging, social media now is going to put us out there. But also, to be able to surveil disease in a different way. And so the holy grail for us in healthcare has always been, at least on the public health side, has been to try to see how can we tap in more actively that when you go see the doctor or when you go to the hospital, how can I get access to that information very, very quickly so that I know, and can see, and surveil my entire county in my jurisdiction and know, oh, there's an outbreak of disease happening in this section of the county. We're 10 million people with, you know, hundreds of square miles inside of LA. There are places where we can see very, you know, specific targets that we know we have to hit. But the data's a little stale and we find out several months after. We need to figure out a way to do that more actively. Technology's going to be our path to be able to capture that information more actively and come up on something a little bit, so we can track things faster and be able to respond more quickly. So that's our focus for all our technology implementations, automation like UiPath has offered us and other things, is around how to gather that information more quickly and put that into action so we can do quick interventions. >> People have notoriously short memories. Please tell me (chuckles) any of the friction that you may have experienced in years past before the pandemic. That those friction points where people are thinking, "Eh, what are the odds?" >> Yeah. "Eh, I've got finite budget, I think I'm going to spend it on this thing over here." Do you, are you able to still ride sort of the wave of mind share at this point when putting programs together for the future? >> So whatever friction was there during the pandemic wiped away. I mean, we had amazing collaboration with the medical provider community, our hospital partners. The healthcare system in LA was working very closely with us to make sure that we were responding. And there is that wave that we are trying to make sure that we use this as an opportunity to kind of ride it so that we can implement all the things that we want. 'Cause we don't know how long that's going to last us. The last time that I saw anything this large was after the anthrax attacks and the bioterrorism attacks that we had after 9/11. >> How interesting. >> Public health was really in lens at that point. And we had a huge infusion of funding, a lot of support from stakeholders, both politically and within the healthcare system. And we were able to make some large steps in movement at that point. This feels the same but in a larger scale because now it touched every part of the infrastructure. And we saw how society really had to react to what was going on in a different way than anyone has ever prepared for. And so now is we think is a time where we know that people are making more investments. And our success is going to be their success in the longterm. >> And you have to know that expectations are now set- >> Extremely high. >> at a completely different level, right? >> Yes, absolutely. >> There is no, "Oh, we don't have enough PPE." >> Correct. >> Right? >> David: Correct. >> The the expectation level is, hey, you should have learned from all of- >> We should have it; we can deliver it, We'll have it at the ready when we need to provide it. Yes, absolutely. >> Okay, so I sort of mentioned, we're, David cubed on theCUBE (all laughing). So three Daves. You spoke today at the conference? >> Actually I'm speaking later actually in the session in an hour or so. >> Oh Okay. My understanding is that you've got this concept of putting humans at the center of the automation. What does that mean? Why is that important? Help us understand that. >> So I think what we found in the crisis is that the high demand for information was something we hadn't seen before, right? We're one of the largest media markets in the United States. And what we really had trouble with is trying to figure out how to serve the residents, to provide them the information that we needed to provide to them. And so what we had traditionally done is press releases, you know, just general marketing campaigns, billboards, trying to send our message out. And when you're talking about a pandemic where on a daily basis, hour-by-hour people wanted to know what was going on in their local communities. Like, we had to change the way that we focused on. So we started thinking about, what is the information that the residents of our county need? And how can we set up an infrastructure to sustain the feeding of that? Because if we can provide more information, people will make their own personal decisions around their personal risk, their personal safety measures they need to take, and do so more actively. More so than, you know, one of us going on camera to say, "This is what you should do." They can look for themselves and look at the data that's in front of them and be able to make those choices for themselves, right? And so we needed to make sure that everything that we were doing wasn't built around feeding it to our political stakeholders, which are important stakeholders. We needed to make sure that they're aware and are messaging out, and our leadership are aware. But it's what could we give the public to be able to make them have access to information that we were collecting on an every single day basis to be able to make the decisions for their lives. And so the automation was key to that. We were at the beginning of the pandemic just had tons and tons of resources that we were throwing at the problem that was, our systems were slow, we didn't have good ability to move data back and forth between our systems, and we needed a stop-gap solution to really fill that need and be able to make the data cycles to meet the data cycles. We had basically every day had to deliver reports and analytics and dashboards by like 10 o'clock in the morning because we knew that the 12 an hour and the five-hour news cycles were going to hit and the press were going to then take those and message out. And the public started to kind of come in at that same time and look at 10 and 11 o'clock and 12 o'clock. >> Yeah. >> We could see it from how many hits were hitting our website, looking for that information. So when we failed and had a cycle where that data cycle didn't work and we couldn't deliver, the public would let us know, the press would let us know, the stakeholders would let us know. We had never experienced anything like that before, right. Where people had like this voracious appetite for the information. So we needed to have a very bulletproof process to make sure that every single 24 hours we were delivering that data, making it available at the ready. >> Software robots enabled that. >> Exactly. >> Okay. And so how were you able to implement that so quickly within such a traumatic environment? >> So I think, I guess necessity is always the mother of invention. It kind of drove us to go real quickly to look at what we had. We had data entry operations set up where we had dozens and dozens of people whose sole job in life on a 24-hour cycle was to receive medical reports that we we're getting, interview data that's coming from our case interviews, hospitalization data that was coming in through all these different channels. And it was all coming in in various forms. And they were entering that into our systems of record. And that's what we were using, extracts from that system of record, what was using to generate the data analyses in our systems and our dashboards. And so we couldn't rely on those after a while because the data was coming in at such high volume. There wasn't enough data entry staff to be able to fit the need, right? And so we needed to replace those humans and take them out of that data entry cycle, pop in the bots. And so what we started to look at is, let's pick off the, where it is that that data entry cycle starts and see what we could do to kind of replace that cycle. And we started off with a very discreet workload that was focused on some of our case interview data that was being turned into PDFs that somebody was using to enter into our systems. And we said, "Well before you do that," since we can't import into the systems 'cause it wasn't working, the import utilities weren't working. We got 'em into simple Excel spreadsheets, mapped those to the fields in our systems and let the bots do that over and over again. And we just started off with that one-use case and just tuned it and went cycle after cycle. The bots just got better and better to the point where we had almost like 95% success rates on each submission of data transactions that we did every day. >> Okay, and you applied that automation, I don't know, how many bots was it roughly? >> We're now at like 30; we started with about five. >> Okay, oh, interesting. So you started with five and you applied 'em to this specific use case to handle the velocity and volume of data- >> Correct. >> that was coming in. But that's obviously dynamic and it's changed. >> Absolutely. >> I presume it's shifted to other areas now. So how did you take what you learned there and then apply it to other use cases in other parts of the organization? >> So, fortunately for us, the process that was being used to capture the information to generate the dashboards and the analyses for the case interview data, which is what we started with- >> Yeah. >> Was essentially being used the same for the hospitalization data that we were getting and for tracking deaths as they were coming in as well. And so the bots essentially were just, we just took one process, take the same bots, copy them over essentially, and had them follow the very same process. We didn't try to introduce any different workflow than what was being done for the first one so we could replicate quickly. So I think it was lucky for us a lot- >> Dave V.: I was going to say, was that luck or by design? >> It was the same people doing the same analyses, right? So in the end they were thinking about how to be efficient themselves. So they kind of had coalesced around a similar process. And so it was kind of like fortunate, but it was by design in terms of how they- >> Dave V.: It was logical to them. >> Logical to them to make it. >> Interesting. >> So for us to be able to insert the bots became pretty easy on the front end. It's just now as we're trying to now expand to other areas that were now encountering like unique processes that we just can't replicate that quickly. We're having to like now dig into. >> So how are you handling that? First of all, how are you determining which processes? Is it sort of process driven? Is it data driven? How do you determine that? >> So obviously right now the focus still is COVID. So the the priorities scale that we've set internally for analyzing those opportunities really is centered around, you know, which things are really going to help our pandemic response, right? We're expecting another surge that's going to happen probably in the next couple of weeks. That'll probably take us through December. Hopefully, at that point, things start to calm down. But that means high-data volume again; these same process. So we're looking at optimizing the processes that we have, what can we do to make those cycles better, faster, you know, what else can we add? The data teams haven't stopped to try to figure out how else can they turn out new data reports, new data analysis, to give us a different perspective on the new variants and the new different outbreaks and hotspots that are popping up. And so we also have to kind of keep up with where they're going on these data dashboards. So they're adding more data into these reports so we know we have to optimize that. And then there's these kind of tangential work. So for example, COVID brought about, unfortunately, a lot of domestic violence reports. And so we have a lot of domestic violence agencies that we work with and that we have interactions with and to monitor their work, we have certain processes. So that's kind of like COVID-adjacent. But it's because it's such a very critical task, we're looking at how we can kind of help in those processes and areas. Same thing in like in our substance abuse area. We have substance use disorder treatment services that we provide. And we're delivering those at a higher rate because COVID kind of created more of a crisis than we would've liked. And so that's how we're prioritizing. It's really about what is the social need, what does the community need, and how can we put the technology work in those areas? >> So how do you envision the future of automation in your organization and the future of your organization? What does that look like? Paint a picture for us. >> So I'm hoping that it really does, you know, so we're going to take everything that's COVID related in the disease control areas, both in terms of our laboratory operations, in terms of our clinic operations, the way we respond, vaccination campaigns, things of that nature. And we're going to look at it to see what can efficiencies can we do there because it's a natural outgrowth of everything we've done on COVID up to this point. So, you know, it's almost like it's as simple as you're just replicating it with another disease. The disease might have different characteristics, but the work process that we follow is very similar. It's not like we're going to change everything and do something completely different for a respiratory condition as we would for some other type of foodborne condition or something else that might happen. So we certainly see very easy opportunities to just to grow out what we've already done in terms of the processes is to do that. So that's wave one, is really focus on that grow out. The second piece I think is to look at these kind of other general kind of community-based type of operations and see what operations we can do there to kind of implement some improvements there. And then I'm certainly in my new role of, in Deputy Director of Operation, I'm a CIO before. Now that I'm in this operations role, I have access to the full administrative apparatus for the department. And believe me, there's enough to keep me busy there. (Dave V. Laughing) And so that's going to be kind of my third prong is to kind of look at the implement there. >> Awesome. Go ahead, Dave. >> Yeah, so, this is going to be taking a step back, kind of a higher level view. If we could direct the same level of rigor and attention towards some other thing that we've directed towards COVID, if you could snap your fingers and make that happen, what would that thing be in the arena of public health in LA County in particular, or if you want California, United States. What is something that you feel maybe needs more attention that it's getting right now? >> So I think I touched on it a little bit earlier, but I think it's the thing we've been always been trying to get to is how to really become just very intentional about how we share data more actively, right? I don't have to know everything about you, but there are certain things I care about when you go to the doctor for that doctor and that physician to tell me. Our physicians, our healthcare system as you know, is always under a lot of pressure. Doctors don't have the time to sit down and write a form out for me and tell me everything that's going on. During COVID they did because they were, they cared about their patients so much and knew, I need to know what's going on at every single moment. And if I don't tell you what's going on in my office, you'll never know and can't tell us what's going on in the community. So they had a vested interest in telling us. But on a normal day-to-day, they don't have the time for that. I got to replace that. We got to make sure that when we get to, not me only, but everyone in this public health community has to be focused and working with our healthcare partners to automate the dissemination and the distribution of information so that I have the information at my fingers, that I can then tell you, "Here's what's going on in your local community," down to your neighborhood, down to your zip code, your census tracked, down to your neighbors' homes. We'll be able to tell you, "This is your risk. Here are the things that are going on. This is what you have to watch out for." And the more that we can be more that focused and laser-focused on meeting that goal, we will be able to do our job more effectively. >> And you can do that while preserving people's privacy. >> Privacy, absolutely. >> Yeah, absolutely. But if people are informed then they can make their own decisions. >> Correct. >> And they're not frustrated at the systems. David, we got to wrap. >> Sure. >> But maybe you can help us. What's your impression of the, first of all, is this your first Forward? You've been to others? >> This is my first time. >> Okay. >> My first time. >> What's your sort of takeaway when you go back to the office or home and people say, "Hey, how was the show? What, what'd you learn?" What are you going to say? >> Well, from just seeing all the partners here and kind of seeing all the different events I've been able to go to and the sessions there's, you don't know many times I've gone to and say, "We've got to be doing that." And so there's certainly these opportunities for, you know, more AI, more automation opportunities that we have not, we just haven't even touched on really. I think that we really need to do that. I have to be able to, as a public institution at some point our budgets get capped. We only have so much that we're going to receive. Even riding this wave, there's only so much we're going to be able to get. So we have to be very efficient and use our resources more. There's a lot more that we can do with AI, a lot more with the tools that we saw, some of the work product that are coming out at this conference that we think we can directly apply to kind of take the humans out of that, their traditional roles, get them doing higher level work so I can get the most out of them and have this other more mundane type of work, just have the systems just do it. I don't need anybody doing that necessarily, that work. I need to be able to leverage them for other higher level capabilities. >> Well thank you for that. Thanks for coming on theCUBE and really appreciate. Dave- >> It's been great talking to you guys, thank you. >> Dave, you know, I love software shows because the business impact is so enormous and I especially love cool software shows. You know, this first of all, the venue. 3,500 people here. Very cool venue. I like the fact that it's not like booth in your face, booth competition. I mean I love VMware, VMworld, VMware Explore. But it's like, "My booth is bigger than your booth." This is really nice and clean, and it's all about the experience. >> A lot of steak, not as much sizzle. >> Yeah, definitely. >> A lot of steak. >> And the customer content at the UiPath events is always outstanding. But we are entering a new era for UiPath, and we're talking. We heard a lot about the Enterprise platform. You know, the big thing is this company's been in this quarterly shock-lock since last April when it went public. And it hasn't all been pretty. And so new co-CEO comes in, they've got, you know, resetting priorities around financials, go to market, they've got to have profitable growth. So watching that that closely. But also product innovation so the co-CEOs will be able to split that up, split their duties up. Daniel Dines the product visionary, product guru. Rob Enslin, you know- making the operations work. >> Operations execution business, yeah. >> We heard that Carl Eschenbach did the introduction. Carl's a major operator, wanted that DNA into the company. 'Cause they got to keep product innovation. And I want to, I want to see R&D spending, stay relatively high. >> Product innovation, but under the heading of platform. And that's the key thing is just not being that tool set. The positioning has been, I think, accurate that, you know, over history, we started with these RPA tools and now we've moved into business process automation and now we're moving into new frontiers where, where truly, AI and ML are being leveraged. I love the re-infer story about going in and using natural national (chuckles) national, natural language processing. I can't even say it, to go through messaging. That's sort of a next-level of intelligence to be able to automate things that couldn't be automated before. So that whole platform story is key. And they seem to have made a pretty good case for their journey into platform as far as I'm concerned. >> Well, yeah, to me again. So it's always about the customers, want to come to an event like this, you listen to what they say in the keynotes and then you listen to what the customers say. And there's a very strong alignment in the UiPath community between, you know, the marketing and the actual implementation. You know, marketing's always going to be ahead. But, we saw this a couple of years ago with platform. And now we're seeing it, you know, throughout the customer base, 10,000+ customers. I think this company could have, you know, easily double, tripled, maybe even 10x that. All right, we got to wrap. Dave Nicholson, thank you. Two weeks in a row. Good job. And let's see. Check out siliconangle.com for all the news. Check out thecube.net; wikibon.com has the research. We'll be on the road as usual. theCUBE, you can follow us. UiPath Forward 5, Dave Vellante for Dave Nicholson. We're out and we'll see you next time. Thanks for watching. (gentle music)