Information Services Group, Inc. (III) Earnings Call Transcript & Summary

All right. Welcome to another ISG Smartalk. We're glad to have you with us. Today, we are discussing Simple Solutions to your Scaling Challenges. Before I hand things over to our fantastic presenters, I just will quickly go over a couple of housekeeping notes with you. We are recording this webinar, and you can access the replay at the same link you used to register. Feel free to forward that link to any colleagues who may be missing today's session as well. [Operator Instructions] That about covers it on my end. So with that, I will now hand things over to Wayne Butterfield to kick off today's presentation.

Excellent. Thank you, Jillian, for the excellent intro, as always, and welcome, everybody. Thank you for joining us on this Thursday afternoon if you're in the U.K. early evening, I guess, in Europe and good morning to our friends over in the U.S. and beyond. So I'm really pleased for you to join us today. We've got a great presentation and discussion, obviously, some proprietary research also, which Erik, our esteemed -- my esteemed partner and friend, joining us will discuss. And of course, this is as interactive as need be. So I would love any questions, queries, fire them into the presenter chat, and we'll do our best kind of answer as and when we go through the show today. So without further ado, you've seen me. I'm Wayne Butterfield, I'm the Director of Automation at ISG Automation. And I'm joined today, it's my pleasure to welcome Erik over at RPA Supervisor. So Erik, hello.

Hello, Wayne, and everyone else. Thank you very much for having me on. And I'm looking forward to your presentation and to help with answering any questions on that. I'm the founder of RPA Supervisor. RPA Supervisor was built on, what should I say, frustrations of scaling up in more than 30-odd implementations of RPA that I have been party to over the last 10 years. And also in close cooperation with Blue Prism, although we're now supporting multiple tools. So that's the background. It's there to help you scale your RPA automations and drive your hyperautomation journey.

Fantastic. And for everyone's viewing pleasure today, just to give you a bit of an overview of what we aim to cover. So obviously, you've gone through the intro, which is great. We'll now -- I will talk about intelligent automation, and we'll start to talk about some of the reasons for scale or not. And we'll then get into the survey results, which I'm sure everyone is really interested to see what has -- what the latest research is that's being completed on RPA and some of those scaling challenges. We'll deep-dive a little bit, and I'll kind of quiz Erik on the role of RPA Supervisor in helping organizations scale. And then we'll obviously open it up to any further Q&A. Aim really would be to spend the next kind of 40 minutes chatting and answering any of your questions, of course, and then hopefully leaving a bit of time at the end either to wrap up or to answer any further questions. So we'll definitely try and finish within the hour, everybody. So do bear with us. What I will do is I'll bring Erik in at various different points throughout the presentation. So you don't have to listen to me all of the time. And this certainly shouldn't be death by PowerPoint. There's not that many slides. It's obviously -- it's generally good news. But there are obviously some that do make a great backdrop, to be fair. And I think the first one for me really is about kind of setting the scene. So I know on the phone, we've got people of all levels of maturity. We've got service providers. We've got fellow consultants and implementers. We've got customers, end users, et cetera. So we've really got a good spectrum of people on the phone who have been involved in automation in various forms over the years. This is the latest kind of view of intelligent automation, hyperautomation, whatever you want to call it, from ISG. We very much see that our automation is far beyond RPA, although today's discussion will focus more around the role of RPA. But it's certainly a tool in a toolkit versus the panacea for enterprise transformation. We absolutely see 3 elements to the role of intelligent automation, the growing interest that we see in process discovery and some of those technology types there, really, really important and seeing a lot of interest in those areas. The next webinar we complete actually will be specifically about that process discovery area. So keep an eye out in your inboxes for when that one comes live. Obviously, the stack of intelligent automation tools, we'd like to break these down into the characteristics of the technology rather than the complex nature of the technology itself. Look at technology as replicating a thing that you do rather than look at it to automate a process. So copying and pasting information, looking at an invoice, reading an e-mail, making a complex decision or communicating. And of course, the growing value now that we're starting to see through the use of technology to actually prove business value has been created. And it goes far beyond hours back to the business, which has been a well-trodden metric historically in the enterprise, certainly to do with RPA and the value that RPA creates. Of course, there are a lot -- the ecosystem itself is a lot bigger. And Erik, from your perspective, RPA Supervisor as a technology sits within this ecosystem, but obviously doesn't -- it's not actually on the slide itself. Where do you see the kind of future of -- if we think about monitoring the robots, I mean, do you see a future where you're monitoring more than one technology in your own kind of end-to-end process automations?

Absolutely. I mean we're already monitoring, I mean, RPA Blue Prism, UiPath and so on, integrating with Microsoft Power Automate platform, building connectors to our local platforms and so on. And then like a Gartner analyst said, you're actually a hyperautomation orchestrator, combining [indiscernible] and all systems with RPA and driving that hyperautomation journey that most organizations are looking to do.

Fantastic. I mean I often think of your technology as a technology managing technology versus what we have historically seen. And obviously, we've automated tasks that people complete, but they've been then monitored by people. And so you're almost automating the automator's role of monitoring. It gets confusing, but that's kind of the way I see it, at least.

Yes. So we are automating the automations. And my friends who are not in this space find what I do very difficult to grasp.

I have to tell my 6-year-old that daddy just builds robots. It's a much easier way of describing what I do to a 6-year-old and to other people than really what I do, which you just talk a lot. So talking about talking, let's kind of move on. I tend to kind of break down transformation into -- and certainly, hyperautomation, to these 3 buckets: kind of discover, remove and improve. And if you think about the earlier slide, these are the 3 kind of layers that we have. Now this is technology, and this is ways of working. And even lumping these together, it's not necessarily the panacea. It doesn't necessarily mean because you got all of these building blocks in place that you are likely to scale. There are kind of other things that we've really struggled with that maybe haven't been thought about as you increase the importance in automation within your organization. And we'll see this in some of the research later, but there's some inherent gaps in organizations that have failed to scale. So we absolutely see some trends in those that have, and -- but we've absolutely seen some gaps in those that haven't. Enablement is a really interesting one. So enabling as much of the business as possible to be able to take advantage of the technology stack that you have created is one -- we've seen and heard a lot about the concept of citizen developer. I'm working with a number of clients at the moment where they're creating lots of federated centers of excellence across their business to really try and take advantage. They're not owning it all centrally. They're owning the governance, they're owning process, et cetera. But really, they're trying to send the capability as much out into the operation as possible. And enablement -- digital enablement is a really key word. Obviously, from an ISG perspective, we acquired an organization called Neuralify last year, specifically to try and help organizations enable their workforce to be able to take advantage of intelligent automation. And the other one is optimizing. That's generally the kind of topic that we're going to talk about today. And there's some fantastic insights in some of the research that we'll talk about over the next few slides. But optimization has been something that I've probably failed to pay enough attention to recently. But one of the challenges with scaling is that the management that surrounds your robotic workforce can become really unmanageable and actually a huge cost burden in itself. And that actually can be a bit of a blockage of scale, because you realize that the more you do, the more you need to support, which is why today's conversation for those organizations that are growing is going to be so important and why it's really great that we're getting the word out there on RPA Supervisor as well. So with that, show me the research. Now just so everyone is aware, the research -- and Erik, I'd love you to kind of pitch in here. The research was completed by yourselves. I know another -- a number of other organizations pitched in, including ISG Automation. But just kind of give us a bit of background on what you were doing, why you were doing it, and what kind of what you hoped to find? And then let's get into the snapshot of actually what those findings were?

Well, it started at with me talking to the rest of the team and customers about all of the entities we've done over the years. So we've spoken to more than 250 user organizations of RPA and what their concerns are, where their challenges are. And that's how we sort of improved on our product and did that. But we never had anything to show for it, so go at. And that's why we say, well, we need to create a survey. We need to include our partners and go to the market and see what are really your challenges in scaling up and to benchmark organizations better.

Fantastic. Great. And we've actually had our first question. So let's answer that while we can before we move on, if that's okay?

And -- so it's come from [ Habeeb ]. And his observation is that the failure to scale or adopt is usually a result of not having domain expertise integrated to own the outcome. And what's your observation being with respect to this? And what is your recommendation on how companies can better scale and adapt using RPA and AI as not a niche, but rather as the new DNA? So loads of interest on that question. Any initial thoughts, Erik?

Well, I think there's a good part of that question, which is more general for your side. From the RPA Supervisor point of view, we don't necessarily need that as the biggest challenge because the ones that succeed are the ones that realize that they need help with managing, monitoring, reporting and all of that. So they've already done some -- they've had -- already had some success. In general, yes, you need, I think, a champion and someone who understands it. What Supervisor delivers, and which is relative to the next session you're doing, is -- so what we didn't think we would help customers with was the, what do you call it, process mining. So most -- so the approach to process mining and the tools sort of build are for as of a top-down, supply-driven way of finding process. What we see with Supervisor, because we make the information available everywhere and the robots perform better than they did before, you actually get a bottom-up and demand-driven process mining, which wasn't a surprise to us, but it really makes a difference for a lot of our customers.

Excellent. I think it's a great question. I think so many reasons why organizations don't scale. I tend not to start with the technology either. I think it's process -- a lot of it is process, culture. From a process perspective, not having -- not every process that you look at, in fact, hardly any are pure, simple, repetitive, digital in nature and of a big enough scale to create meaningful change. So that's kind of one aspect. I think process, we've not done a fantastic job really of keeping our processes in check. We have what we write and what we document and then we have what we actually do. And often, the issue is disconnect. So process for me is a big thing. And you mentioned domain expertise. Absolutely, from a -- we need that expertise involved in the project. There's no point in a financial services expert trying to figure out how to complete processes in life sciences. They just don't have that understanding of the why. They can absolutely see the what, but they might really struggle with why, well, why is that done. I can see what, but I don't really know why. Because I think a large part of what we should be doing as consultants, as people in this industry, is not just automating something because we can, but actually automating something because we should do. And we should only do that if we really have looked at other aspects. Is this process needed in the first place? Is there a different way of being able to do this? And I think all of those are really important. And I think those organizations that have really thought about this as part of a toolkit versus the solution are those that really have -- will succeed in the long term. And then the second part of your question, really, about the DNA part, one of the things I did very early on in my journey, kind of '02 many moons ago, was I didn't just look at what we did, I looked at what we wanted to do. And I started to think about how do we think about automation at the very start of our kind of changed management process of our new solution process? How do we start to think about automation when we're starting to think about how we do things, new things in the business. We launched a new product line and new SKU code. We have a new product launch. All of these things, think about automation from day 0, not when we have a problem further down the line. I think that for me was probably the one thing that I'm really proud of in getting us to think about automation as part of our DNA, right? And that, for me, is something that -- not a great deal of organizations have really done. That's one of the kind of secret -- piece of secret sauce that I've taken to my clients over the last few years. So hopefully, that kind of gives you a bit of insight. I think it's a great question. So thank you very much, [ Habeeb ]. Really I appreciate it. So with that, let's get ourselves into the survey. So Erik, I'm going to ask you just to kind of run through some of the data points, and then feel free to let me kind of pitch in with my thoughts.

Sure.

So first question, how long have you been using RPA?

I mean -- right. Do we have a slide, because I can't see anything there.

Okay. It's on the slide tab, but don't worry. So I think -- what we kind of see here, I think -- and it's probably totally is about right is almost half, in fact, just over half of the respondents, and there were a significant number of respondents have been working with RPA for over the last kind of 3 to 5 years. And about half are either in that kind of POC all the way down to 2 years. Most of them, I guess, have not necessarily come up against the RPA wall. Most of them have not necessarily struggled to find new opportunity. But they're obviously starting to build something with longevity. And that likely means that there's lots of process, lots of maintenance, lots of things that are running in the background and probably quite a large support function. So I think it's a really good picture of where the market would be, in my view. So I think if we were to look at the sample and think, is that representative, I think this is a really good indicator that it is. It'd be interesting to think -- to see what the audience think and whether there's anything in here that is a surprise to you. Next question. I'll kind of hand it over to Erik because I think you can see the content now. Around bots and production, I guess, just what are your thoughts on this?

Again, it fits very well with all the -- my experience, personal experience and all the interviews and so on. And there's a good correlation between the number of bots and the number of processes and the maturity. So surprisingly, few have got lots of bots. There's a lot -- there are lots of organization that can scale up their automations a lot. It's what I see from this. And you saw from the journey they're taking.

I mean I was really surprised, I mean, looking at this. I'm not necessarily really surprised. I think, again, it's a real indication of where the market is. That there are a number of robots -- 45% of organizations with less than 5 bots. Yes, I think it's a really good indication when we talk about scaling and we talk about maturity. Yet we've got nearly half of organizations who have -- over half of them have been doing this for 3 to 5 years plus, yet still 5 of them have got -- half of them have still got less than 5 bots, a really insightful information. It backs up a lot of things that I say. It always surprises me when I see this kind of insight in the flesh, though.

I think it also represents the fact that it's more accessible. So small organizations are also picking up. And I think we'll see this more and more and more managed service providers. So you only get sort of -- you start with 2 processes or 5 and so on. You don't need the whole center of excellence and so on to run it. And then you scale up as you go.

Fantastic. I mean thinking about the next one, so again, generally, with scale, how do you manage your robots? Obviously, this one is a really important metric for you guys with the solution that you have. So I guess, what were your thoughts on this? No real surprises from me. Just explain to the audience kind of what MSP is?

Managed service providers. So most of them are actually -- they've got -- maybe built a process to do the management for them. And in-house tools are also very often quite simple. But some of the reporting we see in larger organizations are quite impressive, but really requires a lot of resources. And it's not surprising. It's a new tool. And as you know, we're actually building the market because there aren't many tools around or any really to do what we do.

Absolutely. And then again, the next question, kind of what is holding back your ability to stay? I guess there's load of insight here from the survey. So just thinking about what's holding back organizations saying that they hadn't implemented process mining, development costs was quite a high one. Reporting and insight, obviously, that will be a very useful one for you guys. License utilization is holding them back. So I guess, what they're really talking about there is this ability to manage their licenses in an efficient manner. Low return on investment. We've seen this over and over again. And I guess we are certainly starting to see the shift on where development work is taking place, at least from an ISG Automation perspective, to try and help with some of that return on investment. But there are a number of different things, I guess, you are helping with. And what we will talk a little bit about that, that kind of try and address at least some of these. And if you think about -- if these are the reasons that people are saying we're struggling to scale because of these. The more of these you kind of tick off, I guess, the more useful your tool is to help an organization scale their automation efforts, right?

Yes. And I mean, development costs, there's not much our tool can do about that. It may help with some design issues. But other than that, a, there's a huge difference in perception from RPA Supervisor customers and non-RPA Supervisor customers on this. But this is to be expected. I think process mining is interesting. I think it's interesting that, that's a problem, that there's so much to automate, there's so much potential, so why isn't the demand in the organization driving that forward? But it is a problem in lots of organizations.

Excellent. And last, but not least, and I guess this really helps with kind of showcasing at least some of the reasons as to why. This is about -- I guess, the output here is around technology improving bot utilization. So this really is kind of cementing the kind of why message with you guys. I mean talk to us a little bit about this and how this insight should be useful to the audience.

Yes. So the graph on the left just shows the percentage of organizations using a tool with a number of processes they've automated. And not surprisingly, the higher the number of automated processes, the higher the need for a tool. But we also see organizations using very few processes starting with a tool like Supervisor to sort out that bit early on. And when you get beyond 100 processes, it becomes very expensive and very difficult to provide the level of service and get to utilization and so on that you need per bot for your business.

Fantastic. Brilliant. So really interesting research that -- this is the first time, I believe, that much of this has been shown. In my thinking, this is just a snippet, isn't it? We've kind of picked some specific points for today's webinar, but obviously, there is quite a lot more to the report. So yes, this is obviously a sneak peek to everything else. And I'm sure that will be shared in due course, right?