Robotic Process Automation (RPA) has garnered a great deal of attention as organizations pursue automation routine tasks through automation software. RPA automates tasks integrated into digital business process automation.
Wayne Ariola, Tricentis general manager of RPA, joins DevOps Chats to discuss how Tricentis brings its strengths and heritage in software testing automation into the world of RPA. The expansion into RPA makes a lot of sense when you consider testing technologies that operate on UX domain and data models, avoiding the pitfalls of brittle screen scraping approaches.
Together, Wayne and I explore how business process automation using RPA intersects with DevOps tools, processes and teams, and how RPA benefits from the experiences gained in the DevOps community. Join us on this episode of DevOps Chats as we explore RPA and DevOps.
As usual, the streaming audio is immediately below, followed by the transcript of our conversation.
Transcript
Mitch Ashley: Hi, everyone, this is Mitch Ashley with devopsy.kinsta.cloud, and you’re listening to another DevOps Chat podcast. Today, I’m joined by Wayne Ariola, who is general manager of RPA at Tricentis. Our topic today is RPA, robotic process automation, and DevOps. Wayne, welcome to DevOps Chat.
Wayne Ariola: Thank you so much for having me on this beautiful Friday. I’ve been looking forward to it.
Ashley: Best way to spend a Friday—well, second best, maybe. There might be a few other things—
Ariola: Exactly.
Ashley:– that might be above the list of this, [Laughter] but yeah, what a great day to do that. And I know we’ve had Tricentis, your CEO has been on before. Welcome back. Glad to have you on. Would you introduce yourself to our audience—
Ariola: Sure, absolutely.
Ashley: Tell them about you and, for those that don’t know, tell them what Tricentis does.
Ariola: Absolutely. So, my name is Wayne Ariola, as you stated, Mitch, and I’m the general manager of our RPA solutions at Tricentis. And I’ve done—I think I’ve done at least three of four webinars on devopsy.kinsta.cloud.
Ashley: Oh, yes.
Ariola: So, I’m certainly no stranger to the audience, the topics, nor the concerns, yet I wanted to actually bring forth the news about RPA and see if I can’t connect it to what’s going on in the end to end DevOps world today.
Yet, just a little bit about Tricentis, for folks who haven’t heard about Tricentis—you know, Tricentis is, today, considered one of the automation leaders out there in the world. You know, consistently across all major analysts who are always ranked as either (a) the number one leader, or, you know, right up there as number one. So, it’s been an interesting ride at Tricentis for the last five years as we’ve begun to kinda notch our way into the DevOps world.
The one thing we are known for us really making software testing more productive. And we do that via automation. So, we know as we look at scaled agile that things need to happen quicker and then you add in the idea of CI/CD or these kinds of concepts, and then you really wanna be fast and agile. And we’re the company that makes sure that testing is not your barrier to speed. And that’s what we’re best known for out there.
Ashley: Well, let’s start out by, I know RPA, robotics process automation, is kinda—is the hot thing or the new thing, however you wanna put it. How do you define RPA?
Ariola: So, I mean, poor DevOps people, right?
Ashley: [Laughter]
Ariola: I mean, DevOps was the sexy thing for such a long time.
Ashley: Oh, it still is. No, don’t break my heart, Wayne—come on, no.
Ariola: Good, good. You know, you guys haven’t aged out yet, so.
Ashley: No.
Ariola: And all of a sudden, you know, RPA is like the Millennial of topics, right, these days.
Ashley: Okay. [Laughter]
Ariola: It is definitely on fire. In fact, I have a slide that I use in presentations that I compared DevOps to RPA. And the DevOps folks, it looks like there’s a bunch of people dancing, but then I show a picture of RPA and it looks like a rave—you know, a big, huge party at a rave with lasers and lights and a whole crowd thumping to the music.
And that’s really what’s happening right now. I mean, the RPA world and the RPA market is just on fire, and it’s a bit crazy. But the reason why it’s a bit crazy is that the ROI associated with deploying automation or what is defined as RPA automation is really high. You get immediate value out of it, so it’s kind of like this—especially if you talk to CIOs, you know, they’re kinda saying that it’s kinda the no-brainer of today’s world.
But this is, I mean, the DevOps folks are no stranger to this, right? So, we did, we went through this when we kinda went through the whole DevOps motion beginning with build automation, right?
Ashley: Right, yeah.
Ariola: You know, we kinda took a breath and we said, “Hey, this build process is manually painful and it’s difficult and it’s arduous.” And, you know, once we got through kinda the initial thing around the automating build, you know, the imagination associated with what could be automated then exploded, you know, and then you got into the DevOps motion, right?
And I would say it’s a perfect parallel. RPA is doing exactly the same thing. It’s kinda taking these preliminary type of motions associated with manual processes and the automating them.
Ashley: Well, you know, in a way, the way I think about it, Wayne, is, you know, to step back for a minute, the best developers I’ve worked with in my career have always been the laziest, and that’s a compliment.
Ariola: [Laughter]
Ashley: Meaning, they write the least amount of code, the automate everything—they don’t wanna do that manual stuff, right?
Ariola: Yes. So true.
Ashley: They wanna spend time on the things they enjoy working on. So, you know, in the DevOps world, of course, we’re big on automating things and maybe all of it isn’t automated, but it’s taking that same kind of, “Let’s take those things we don’t need to do manually and we really can automate it and look across IT, across business process automation—you know, the whole organization.”
Ariola: Yeah.
Ashley: That’s probably why it’s hot, because it’s not only in IT, but it can affect other parts of the business. So, I’m gonna lay claim to RPA’s roots being in DevOps. Now, you can tell me I’m totally wrong, but I won’t—
Ariola: No, absolutely not, given the audience I’m speaking to. I agree.
Ashley: [Laughter]
Ariola: I totally agree. But it’s true, though—I mean, think about this, Mitch. Let’s unpack that just for two seconds, right? So, take the idea of that developer who’s lazy, right, and the fact that—what are you doing? And if you would, say, ask the person what they’re doing at any point in their day, it’s like, “You know what, I’m writing a script to do X, Y, Z because I’m so sick of provisioning this particular application to this environment,” whatever it might be, right?
So, their knowledge base and their understanding of how to construct a script gave, especially in the DevOps world or the Dev world, these guys a leg up in terms of producing this automation to eliminate manual tasks.
Ashley: They’re the most productive, yeah.
Ariola: Yeah, exactly, and make that the most productive. But RPA is really trying to—and I hate to even use this word, but it’s the best way to describe it succinctly, is democratizing that, right? It’s giving people who are not as talented as your laziest developer the ability to actually create the automation to get rid of the mundane or manual tasks that are slowing them down, right?
Ashley: Mm-hmm.
Ariola: So, I mean, even by—Mitch, even by definition, you know, RPA is defined as a technology that predominantly leverages a combination of maybe UI and API or surface level features and applications to create more automated, routine, predictable data transcription or enablement work, right? So, automation work or executable work.
So, if you think about it, it’s a technology that sits on top of—a super structure that sits on top of apps that allows you to do things more proactively across applications. So, making sure that a manual task to transpose data, to move data, to initiate something, to do data entry is eliminated by the automation itself, which is really cool.
Ashley: You know, I kinda think of it as—I think of it as, an analogy would be just like sysadmins write scripts, right, to do things that automate it.
Ariola: Yes, yes.
Ashley: This is for other IT folks, but also can be end users, right, that automate filling out forms on online screens or doing some processing of “load this data into a spreadsheet, export it out to here, send it to here.”
Ariola: Yep, yep.
Ashley: Now, why do all that stuff by hand? Here’s an easy tool. Now, do you see RPA as primarily being rule based, or—I know you have an orchestration product. I don’t know if that’s primarily rule based, but how do you do RPA in a way that it’s accessible by as many people as possible?
Ariola: Yeah. So, I mean, also knowing the demographic of your audience, RPA certainly falls into the bucket of, nothing new has be invented here, right?
Ashley: Mm-hmm.
Ariola: This is [Laughter]—this is definitely technology that we’ve had awareness of in the past. But it’s been uplifted for our era, right? Is really what makes the difference, right?
So, you know, whether it’s rule based, whether it’s AI, whether it’s—it really depends on the task you’re trying to achieve, because not everything fits every scenario, right?
Ashley: Mm-hmm.
Ariola: So, if you—let’s try it this way, though. If you look at RPA and you take, let’s just take roughly 75% of the use cases out there, it falls into one of three buckets.
Ashley: Okay.
Ariola: One bucket is what I call poor man’s integration. Which is, you’re scraping information out of one system and you’re putting it into another system and then validating it in another or something like that, right?
Ashley: Okay.
Ariola: Meaning that you’ve gone to your IT group and you’ve said, “Hey, I got this integration project that I need” and they say, “I don’t have enough time.” And then you’re saying, “You know what? I’m just gonna do it myself with RPA” and you’re just gonna do it by scraping screens and moving and pushing data across multiple systems. Or maybe even—
Ashley: “Here’s some vise grips and a crescent wrench, go fix it up.”
Ariola: Exactly! Yeah, exactly.
Ashley: Okay, yeah.
Ariola: By the way, I call this poor man’s integration, or these kinda RPA use cases the best identification of backlog that you could ever have, right? You know there’s a problem here when you use it for this problem.
Ashley: Okay.
Ariola: So, the second group of activity that has been used is the augmentation or automation of manual tasks.
Ashley: Okay.
Ariola: And this is what you primarily hear about, right? So, instead of having me do the mundane task of pointing and clicking, going to another system, copying a number, bringing it over, taking—finding the core account number from a subsystem and pulling it into the work order, you know, pulling information from SAP and pulling it over to SFDC. You know, all that kinda manual stuff that’s going on in between. This is the second scenario that you’re just helping the human do something as part of their day to day activity, whether they’re processing an invoice or monitoring inventory or onboarding an employee or, you know, any kind of horizontal process that’s happening in the organization.
And then there’s the third scenario that it’s being used for, really, which is—validate critical checks. So, when I say validate critical checks, let’s take the scenario, like, that we all got indoctrinated to in the last two years, which is GDPR.
Ashley: Mm-hmm.
Ariola: Where, if someone opts out from an e-mail perspective of your system, you want to make sure that they’re opted out of all systems of record. So, you might want to build a queue of opt-outs, which, the RPA engine comes in, grabs a unique identifier such as an e-mail from that system, and then goes into all other systems or potential systems of record and making sure or giving us, you know, taking a visual snapshot that the individual has, in fact, been opted out.
So, those are kinda like the three general cases. And, of course, we then transist multiple horizontal, vertical, and technical domains for those particular uses cases.
Ashley: Well, I thought with that third example, you were gonna tell me that I wouldn’t have to click on that. I accept cookies any more on all these websites, but—
Ariola: [Laughter] You can set up an RPA [Cross talk] for that, no problem. You could do it.
Ashley: [Laughter] You could, actually.
Ariola: You could definitely do it—yeah, yeah, yeah. [Cross talk]
Ashley: So, talk to us about what would you say are the top one or two use cases that customers come to you and say, “Oh, you do RPA? I’m trying to solve this situation”—what is it?
Ariola: You know, it’s really funny, because it’s really across the board. And the industry is starting to sub-segment themselves now into vertical and horizontal type processes or technical—so, there’s three ways that the whole industry will ultimately segment. You’re gonna have pure plays, right, that are gonna be cross industry, cross horizontals. You’re gonna have some horizontal folks who are gonna go across—like, so, for example, we’re seeing new companies pop up that do just kind of HR RPA. Meaning, getting information in and out of HR systems, sensitive data—blah blah blah. And then you’re getting some vertical stuff. Like, you know, you have folks like, you know, Statenical and Edgver, which are Mphasis companies that are in the financial vertical that are really, really good at doing some stuff in the financial vertical.
Ashley: Mm-hmm.
Ariola: But in terms of us, you know, there’s really only—I would say there’s only about four or, three or four sure plays out there. Tricentis RPA is certainly one of those pure plays, and you know, we see a lot of insurance scenarios where you’re doing payouts, payment validation. We see a lot of things like supply chain data verifications a ton, a ton of that stuff.
We’re seeing a lot of IoT type scenarios where a sensor is collecting information from one particular device and it needs to be married up with other IoT type of devices out there collecting information, and via an API, it’s being all sucked together and orchestrated together with RPA in order to produce an outcome, right?
Ashley: Mm-hmm.
Ariola: We’re seeing a lot of things around tax and payroll type steps and validation. A lot of stuff going on around SAP as well, by the way, for some reason.
Ashley: Mm-hmm.
Ariola: So, getting stuff in and out of SAP. And this is, there’s two major things going on, here. First of all, from a merger/acquisition perspective. So, in order to gain the short term benefits of any M&A activity without necessarily having to invest in the entire integration plan, you know, you can use RPA to assist you in moving data or updating records or updating customer numbers, right?
Ashley: Mm-hmm.
Ariola: And then you’re also seeing scenarios like it being used for S/4HANA migration, which is also really interesting. So, those are kinda the things you’re seeing, but it’s all over the place.
Ashley: Yeah. Yeah, you know, I love the IoT example, because—I know it’s not your technology, but everybody knows “if this, then that,” right? That’s sort of the universal—
Ariola: Yes.
Ashley: Doesn’t work for every scenario, but it certainly is a great example of a really simple way to do RPA for IoT events and happenings. Talk a little bit about why did make sense for Tricentis to expand from automating testing to more generally providing an RPA solution.
Ariola: Yeah. So, thank you for asking that, because I do happen to get that question quite often. So, at the core of—Tricentis’, you know, a real differentiator in the marketplace is this technology we have called model based automation.
Ashley: Mm-hmm.
Ariola: And most of what you’re gonna see today out there from RPA vendors are scripted technologies or technologies that use image based controls to understand screens. And the script based technologies and this image stuff, by the way, is the prime reason why software test automation has been so difficult. Because scripts fail.
Ashley: Yeah, I was just gonna say. [Laughter]
Ariola: Yeah, they’re brittle. They basically are hard to update. It’s hard to maintain. You know, it’s the old adage of keeping in sync with the code base and, you know, RPA is highly susceptible to changing UIs. And this is where we shine.
So, our model based automation is actually, takes a much, much more technical approach. So, where most of the vendors out there, if not all of them, interrogate a UI from a screen perspective, we actually interrogate the implementation.
Ashley: Mm-hmm.
Ariola: And understand the UI from its more technical implementation perspective. So, if you take SFDC or if you take SAP or you take ServiceNow or any of these big, large vendors, the complexity of the UI even through a browser is pretty significant. So, the fact that we actually interrogate it at a technical level to build an abstracted model gives us the ability to deliver real, resilient automation.
And what I mean by that is that, you know, we—universally, in our platform, you cannot script. If you wanted to script, you’re gonna have to go somewhere else, because you can’t script, because ours is model based. So, everything that we’re doing is actually produced from technical observations of the application itself. And then we allow you to put those observations or components that you discover—reuse them as LEGO blocks, right, and put them into different flows.
So, the good thing is that, when the UIs change that are part of the automation, (a) if you have to make a technical change, you only make it in one spot, and that change propagates throughout all instances or all bots that are using that automation, and (2) because we actually do a highly resilient technical implementation, you know, we self-heal our technology or our bots in roughly 80 percent of the change cases.
So, this is why were successful and still are successful in software testing, and this is why we decided to bring this to RPA, because it faces the exact same challenges.
Ashley: Well, it’s almost a knowledge based approach, thinking about it as a model oriented solution, if you hearken back to screen scraping days, which is the brute force—
Ariola: Yes.
Ashley:—this vector is where the information is at that you’re testing—
Ariola: Exactly.
Ashley:—to a model based, which is more of a canonical based approach, which is a defined—
Ariola: Absolutely.
Ashley:—you have a way of determining what the information is and then you can detect when it’s changed. “Hey, there’s a new field. There’s a new—this field’s changed,” you know, whatever, it’s not in place.
Ariola: Yes.
Ashley: Now you have some reference model to pull from. It makes a lot more sense now. You can put logic based or flow based logic into an automation process rather than having to script it into everything as manual. I think that’s what you’re saying.
Ariola: Absolutely.
Ashley: Do I have it right, here?
Ariola: You have it 100 percent correct. So, it also gives us a broader reach within the organization as well. So, you don’t have to rely on the highly technical skills to actually produce the automation or, even more importantly, maintain the automation that’s required by your business.
Ashley: So, does this open up different people that you’re selling to in the organization? Are you still selling through the DevOps test organization in IT and you kind of expand what other places you can apply your RPA technology? Are you now calling on business units, end users, other application areas? What’s that mean for your business?
Ariola: So, whoever has the problem, we certainly want to talk to about assisting them to solve it. You know, within the DevOps space, there’s a lot of conversation about maintaining the scripts that are automating everything around my infrastructure is painful, right? So, there’s conversations that are even in that horizontal area. However, you know, the skill set that’s mostly in that domain is highly technical, so, you know, there’s a lot of preferred—a lot of preference to actual scripting there. But within the line of business, there’s certainly a lot of conversation going on, and that broadens the conversation.
But believe it or not, you know, when you’re talking about tests and test automation, although we do think of it as kind of a Dev test in motion, when you look at what Tricentis does, which is more end to end testing and protecting the end user journey because we cross applications, we have a lot of conversations with the business analysts. We have a lot of conversations with the line of business.
Ashley: Mm-hmm. I can see that.
Ariola: RPA tends to skew that more to the line of business, but what we’re noticing distinctly these days is, RPA is coming back to IT. And there’s a real, really interesting reason for that, and it’s what’s called the RPA death spiral. Which, it goes something like this. You asked IT to do an integration for you, but they were too busy. You decided, “Hey, by the way, I’ll use this RPA thing to bridge the gap right now” and you called in an RPA vendor and a service partner and you got your initial flow or bot stood up.
Ashley: Mm-hmm.
Ariola: But then again, you just don’t wanna—you don’t wanna spend a lot of money keeping that service partner on site because it’s expensive, and they go away. And once they go away—guess what? The interface changes on one of the automation sequences or bots that you have enabled and the bot breaks. And as soon as that bot breaks, [Laughter] where are you gonna go to? Well, you’re gonna go to IT.
Ashley:Well, I can imagine.
Ariola: And then IT—yeah.
Ashley: Yeah, people come back to IT because the problem that they’re automating gets bigger than they want to handle or can handle.
Ariola: Absolutely.
Ashley: Or they need access to resources—“Hey, I need single sign on here to get to this information. I need this database that isn’t—
Ariola: Absolutely.
Ashley:—easy for me to get to as an end user.” So, lots of reasons.
Ariola: Absolutely.
Ashley: You know, things happen outside of IT because they’re easier, but then we need to go back to IT because they’re necessary to get what you need.
Ariola: Absolutely. That’s why it’s kinda swinging back to IT. Now, also what’s happening is, when the line of business acted kind of like a shadow IT or kind of a rogue IT shop and adopted the technology, you know, now the CIO is essentially inheriting the maintenance tab.
Ashley: Mm-hmm.
Ariola: And now this is why, you know, the conversation is swinging right back to IT and the CIO.
Ashley: I can see that. Yep.
Ariola: And we’re back—from Tricentis’ perspective, you know, we’re back on home turf talking to the nerds that we like to talk to.
Ashley: Mm-hmm. Well, this has been great. I really appreciated having you on, and a new topic for us on DevOps Chat with Tricentis. I don’t believe we’ve talked with you about this before. It sounds like you’re a big enough believer, you’d change your job to be the general manager of RPA.
Ariola: [Laughter] Yeah.
Ashley: I can tell you’re committed.
Ariola: There’s no goin’ back—there’s no goin’ back now, yeah.
Ashley: Exactly.
Ariola: I’m committed.
Ashley: Exactly. Well, it’s been fantastic, Wayne. Thanks for being on the podcast.
Ariola: Absolutely my pleasure, Mitch. Thanks for having us.
Ashley: Well, I hope you come back and we get a chance to talk to you again and maybe we can dive into some of the use cases you’ve solved for customers and some of the learning, so we’ll save that for another time, okay?
Ariola: Love to do it.
Ashley: Great. Well, you’ve listened to another DevOps Chat podcast. I want to thank my guest today, Wayne Ariola, who’s general manager of RPA at Tricentis. And, of course, thank you to our audience for spending your time with us today—it’s valuable, and we appreciate it. My name is Mitch Ashley from devopsy.kinsta.cloud and you’ve listened to another DevOps Chat. Have a good day and be careful out there.
— Mitchell Ashley
