Pegasystems Inc. (PEGA) Earnings Call Transcript & Summary

All right. Why don't we get started here. My name is Rich Hilliker, and I'm a software analyst at UBS. We're thrilled to have Pegasystems here today. Ken Stillwell, CFO, and we've got Peter Welburn here. Great to see you guys again. I know you've been patients with the conference for a long time, so we appreciate you coming down a year after year. Good to see you guys again.

Good to see you, Rich.

Why don't we dive in here and maybe level set. For those tuning in, maybe not familiar with the story. Could you tell us a little bit about the company, the products that you sell, how that's evolved over time and maybe the key value proposition you're offering.

Sure. Pega has been around a bit of brand supporting our clients for a number of decades. And we really started as an alternative to writing code back in the '80s and the early '90s where when you wanted to build an enterprise great application, you really had to write software, you start by literally lines of code. And so we created this concept of having a kind of an alternative to that. by having some of the common actions that happen when you write code to be native to the platform so that you could actually configure right on the platform. That then evolved to be becoming kind of an orchestration engine where you would -- our platform would be a connection point to other applications that might kind of one-to-one talk to each other, but really was disconnected in the context of a workflow of a series of steps that you might engage in 2, 3, 5, 10, 20 different applications as part of that process. And then -- and that's kind of where we kind of sat -- almost this kind of this middle layer of this middle tier of orchestration engine. And over time, what -- as our product became kind of more feature-rich and our clients were using us for some of our core use cases, they started to look at us to say, "Hey, if I'm going to go out and buy a solution like a customer service solution or a sales automation solution or a marketing automation solution, I'm going to really take a look at what I might be able to configure on Pega." We had embedded robotics. We had decisioning, which was our -- we've had AI in the platform since 2010. It's not something AI, it's not something new. It's really just the context of how AI has evolved. We had -- we always had the concept of a case and workflow because we are starting to make it more feature-rich, clients looked at us as a way to build enterprise-grade applications where they might be able to be a little bit more flexible and kind of evolve over time in a less costly way. And so that's kind of our evolution was, replacement for code to really becoming that orchestration process engine. So now we're a digital contact center from any of our clients. We're doing inbound lead routing and decisioning in a kind of a headless environment with consumers when they come to websites for doing loan origination software. Like it's just really evolved into something where we have kind of certain types of activities where there's a lot of volume and there may be multiple systems that need to be connected and you want to automate them, Pega is really a perfect fit.

Got it. That's really helpful. Evolution, fraud platform, we hit on a lot there. Maybe we can take a step back and just kind of characterize the broader environment right now. Just -- I would love your thoughts just on what you're seeing and hearing and talking with customers? What you're feeling in the market in Q4 here and how that maybe compares to the first couple of quarters of the year?

Sure. I would -- if you kind of go through maybe the last 2.5 years, I think we went from being a little bit kind of -- and I'm saying this as a general statement on the economy. I think we were living a little bit in the fantasy land in 2021, thinking that the impact of the pandemic was going to have no long-lasting impact and that things would just kind of like we just figure it out and people would continue to buy. And I think a lot of trends changed. And in 2022, I think you started to see some recognition in the market, that interest rate -- that the supply chain have been permanently disrupted and that interest rates were higher. And all these kind of the things that we maybe didn't pay as much attention to for a few years. When -- as we entered into '23, I think that the Q2 of '23 to me, felt like a very confusing quarter. And I think that's because that's really when Gen AI hit, right? I mean that's really when people started to talk about ChatGPT. And then I think the investment community more than the buying community, really jumped to being like, oh my gosh, like every company is going to be out of business, and this is going to change the business model. And I think the actual companies were saying, well, we're going to try to figure this out, right? So I think now where we are is there's a much more clear path of what AI is and what AI isn't. And I think where you're seeing a lot of the spend around AI is where you would expect to see it. You'll see it in the Microsoft and NVIDIA, the people that are selling the infrastructure to support, running the AI model. When you look at the actual use cases of AI, I think they're still early in the evolution. I think clients -- there's some obvious ones like can I take a bunch of library text and create coherent answers to questions. Yes, I think that's a -- I mean -- and by the way, that's actually very powerful. I don't think it's that sophisticated, but I do think it's a use case that's out there already. And our clients are -- we've been kind of showing that use case to some of our clients already. When you go -- when you take that next step to say, what might AI be? And how might this change the way we work, I do think we're in the early innings for that. So -- and I think that AI is not going to necessarily steal dollars from the other enterprise applications. I think it will still mind share. But I think the dollars are coming, but I don't know exactly where it's going to come from. I don't think it's going to come from things that are foundational for the businesses. I think it will probably come from different ideation opportunities the clients have where they kind of shift that to AI. We see our clients really trying to figure out how they can augment existing applications and systems that they have with AI to be able to speed up the time it takes to process something, get better results, reduce the amount of time that a customer service rep needs to interact. So I think the economy has kind of went from like a little bit -- we were living a little bit like kind of outside reality to then thinking the sky was falling. And then AI hit and I think we've kind of settled down, and it feels like the buying patterns in Q4 -- certainly, it's not a strong buying environment, but I also wouldn't characterize it as weak either. I would say it's more kind of -- more of a normal environment that I've been seeing in the last quarter or 2 compared to earlier in the year when it was a little bit -- it was a little bit uncertain.

[ That's encouraging. ] Yes. Maybe we could dive in a little bit to earnings and recent guidance. I think earlier this year, your cash flow guidance started at $150 million. You raised that to $180 million. And I think on your most recent call, I don't think you guys typically update quarterly your annual guidance. But I think you did mention that cash flow for 2030, you might be able to be in the $200 million range. So I guess can you kind of help us unpack that and understand the momentum here on the cash flow generation side and kind of what's causing that?

Sure. So this was the first year that we really kind of guided cash flow. And I will admit that I was unsure how that would all play out, given that I didn't have a series of quarters or years to really kind of rely on the pattern of the business, and there was a lot of changes happening in the business, including us doing some cost optimization earlier and a couple of times in the last 18 months. So I was -- as I thought about guiding, I said if we guide $150 million -- and that $150 million that we guided was actually -- even had -- we added to that some onetime items that we actually are kind of nonrecurring items. As we got through the first couple of quarters, it was obvious we were going to beat that. And it was also obvious that we were going to beat that by a large margin. So when we actually talked to middle of the year, we kind of upped that number to $180 million. And that was really -- because I knew that I had a shot at $200 million, but I didn't want to go there yet. I just wanted to kind of see how it played out. Now where we sit is that number -- that $150 million, the equivalent of the $150 million is going to be much more than $150 million. In fact, much more than $200 million, because the $200 million that I mentioned is a number we're trying to get to of actual cash flow, right? And that's even not giving us credit for some of the onetime items that would be nonrecurring. So I think if you kind of get to the end of the year and we're able to achieve those numbers, the difference in our free cash flow generation is so noticeable from last year, but even from what we guided for the year. And I think that just shows the power of a subscription model and actually also maybe we can take a small amount of credit for our commitment of running the business and trying to optimize it and trying to make sure we were responsible with our spending. But I think it really just shows the power of a business that has over $1 billion of recurring ACV, highly sticky and our gross margins really accelerating from what was just over 50% just a few years ago to now approaching 75% on our way to 80%.

Wow. Okay. Well, that's definitely helpful. So I guess is it fair to kind of think of -- and you've been messaging the subscription transition, [ I think, ] since probably 2017. Is it fair to think that we're kind of in the later stages of that, we're starting to see the impact on the model as well as some of the actual core business performing and helping you with that cash flow generation?

Yes, I would frame the subscription transition as in the rearview mirror. I would say that we're -- we thought we would finish it at the end of '22. It kind of drug out probably a couple of quarters past there. So I would say the last quarter kind of -- we're there. Now, one caveat is that because we don't have all of our revenue in a SaaS model, we do have some variability because of the accounting of ASC 606, where term license revenue comes in a little bit more lumpy. But if you forget about revenue and you look at ACV and billings and cash flow, those are both normalized, right? So I think what you really just have to -- what we really have to watch is this -- revenue won't be as linear as ACV is, because of that kind of almost awkward timing of how revenue is recorded. The good thing is billings are unaffected by that. We build typically a year in advance or at worst case a quarter in advance with our clients. And so there is a level of consistency there with billing and collections.

Right, right. And that makes sense why you incorporate ACV growth in your Rule of 40 metric.

Yes, right. Yes. Yes, and that we use free cash flow as opposed to EBITDA because revenue could be higher or lower because of that weird accounting, but free cash flow is what it is.

Yes. Well, speaking of free cash flow, I think recently, you guys changed the definition. And I know there's -- we talked about the onetime items here and there. Can you help us understand why?

So we were showing a disclosure that showed both our operating free cash flow, our operating free cash flow minus capital expenditures, but then we also added in the onetime items, like restructuring, onetime what we believe were onetime legal expenses, things that -- we were trying to get to an unlevered free cash. And us as well as I'm sure a lot of other companies, the regulators don't love when you come up with unique ways to measure free cash flow and we respect that. And so we said, listen, the best way to do this is to show the free cash flow kind of the way that the standard way, which is operating free cash flow minus CapEx. But then we'll still show the other disclosures so that investors could be thoughtful around understanding what might not recur in the next year, which was really the intent of why we actually did it that way. So that was the change we made. That does create a little bit of a difference between the $200 million that I'm talking about and the $150 million that we originally guided. But it's all in our disclosure. So I think our investors are -- it's pretty transparent. But our purpose was really -- the reason why we originally did that was to try to show what we felt like operators would want to see. But like I said, this has been a big hot button for the SEC around free cash flow and just being consistent. And actually, I can really appreciate and respect why they would want that. And so we just changed our disclosures to just be the more traditional approach.

Got it. They're traditional transparent, Okay. Sticking with cash flow, maybe one more question here. In June, you talked about your ambition to generate like $500 million in free cash flow. I think that's over the -- maybe the 3- to 5-year time horizon. Can you help us with the linearity as we get there? Should we be thinking of this as pretty straight line? In other words, like $375 million next year? Or is it going to be lumpy? Can you just kind of -- any high-level commentary?

So I've often explained that the first year after finishing the cloud transition is when free cash flow kind of really looks normal, which would be 2024. So when you look at 2024 and you start thinking about a free cash flow of like, say, call it, 25%, just picking a round number, that kind of -- but to get to $300 million -- excuse me, to get to $500 million, you'd kind of probably have to be more like in the high 20s and naturally a revenue number that's -- or billings number that's bigger than what we have right now. So you kind of are going to see a pretty big uplift in '23, probably a reasonable uplift in '24. And then I think things start to look more normal in terms of the annual additive amount of cash flow until kind of getting a couple of points maybe of accretion in those out years. But if you are going from -- if you go back to like '21 to '22 to '23, you go from minus 7 to 4, probably approaching [ 20 ], right, in terms of that trajectory if you accounted for one-time items. So that's where the real curve was. I think you'll still see a reasonable uptick in '24, then it will normalize.

Like building that recurring cash flow layer cake.

Yes. Yes, exactly.

That kind of cake, right? Free cash flow. Cool. So maybe on go-to-market product expansion. I think I noted that you guys did 2 reductions of force in 2023. Can you give us a little bit of thought behind -- or can you give us some color on the thought behind those reductions? And where do those fall? I think it was sales and marketing, but can you give us a little bit more color there?

The majority was in our go-to-market area, the first one that we did was we announced in December, we executed largely in Q1 of 2023. And that was around trying to reduce what we viewed were roles or functions that may be redundant. They may be unnecessary as we move towards selling, having a more cohesive selling team selling to a targeted number of orgs where we actually may have had more specialists and more kind of maybe horizontal resources when we're selling. So that we really wanted to attack that problem that we had really done to ourselves through -- from '20 and '21 and into the beginning of '22. The second one that we did was different, but related to the first one. We really wanted to anchor on. We are going to target less than 1,000 organizations and more likely 200 to 500 organizations that would be our primary targets. When we actually did the second one in Q3, it was around looking at the resources as they remain and saying, is this the right way to organize these resources? Do we want to actually put some of the teams together and closer to the customer? And when that happens, there would be redundant managers that may exist, like if you took different types of selling resources, but put them underneath a selling manager. Unfortunately, there may not be a manager on the other side that may have a role in the company. And so that was really how we -- the 2 phase. So we're now done with that. We feel like we have plenty of selling resources. And quite frankly, through either of these actions, we didn't take out really many sellers. They were more like the selling support resources. So we feel like we have a tremendous amount of selling capacity, and we think we can manage a growth rate that's easily in the double digits without needing a lot more resources in the near future. Now when we get to 2024 and into '25, naturally, if we continue to grow at the pace that we want to, at some point, we will need to add resources, right? But they will be under the model that we've actually established, right?

Got it. Okay. As we think about the actual motion of that capacity that you just kind of discussed, I believe that you started focusing on existing customers as opposed to brand-new customers to the platform. So instead of pursuing new logos, you're kind of focused on the existing base. Could you give us a sense of why and how that sort of played out the reasoning behind it and kind of how we've done so far?

Sure. So if you think about our business, we've got call it, 750 clients. 200 of those clients are about -- spend $1 million or more a year. So we've got a reasonable concentration of our ACV with 200 clients. We know that there is a few hundred more clients that are under $1 million that probably should be well above $1 million. So that gives us line of sight to existing clients that were already penetrated a reasonable amount the next cohort of clients where we feel like we have some business with them, but not as much as we should. And then we went out and targeted some specific new logos, really like kind of less than 50 companies that we currently don't do business with, but they look like some of the clients that we already have. And so that would be -- an example would be if we had State Farm and AIG as clients, but we didn't have Progressive. That would be the type of -- that's an example of why we might want to cover a company like Progressive. So those are -- that was -- so we have some new logos very managed, but we're not going broadly in like almost in a territory selling model like we had done with our corporate market strategy back a few years ago.

[ Got it. Okay. The very point of strategic focusing on growing the existing... ]

Growing existing with very selected net new logos. And then we have our product called Launchpad, which is Launchpad, essentially, what we did was we realized that if we were going to go after new logos in more of a mid-market area that we shouldn't do it with Infinity. We should actually do it with a multi-tenant solution that was built more for kind of a one application sell to many clients versus -- Infinity is more one solution sell to many use cases, right? So you might go to a client that have one solution or one platform where you sell multiple use cases. We wanted to flip that and say one solution that you sell to multiple clients, but that isn't our selling model. So we decided to go through partners or through independent software vendors or partners. And that -- we're in the early stages of that, but that gives us kind of an opportunity to actually over time, go after some new logos, but through a partner, right, with a solution that's more fit for that versus Infinity, which is enterprise grade, which is more for the 1,000s or so targets that either clients that we have or future targets.

That makes sense. Got it. Maybe we can shift back. I think you said earlier on generative AI but maybe we can kind of return here given such a big topic this year. You talked about AI being on the platform since 2010, 2011. So there's nothing new to Pega necessarily. I guess how do you contextualize like the evolution of AI, maybe not as broadly as over that timeframe, but like how does this next kind of chapter of the AI story play out for Pega here? Do you see it as like a threat or an opportunity for a model-driven software development platform like yours? Or how do you see this sort of evolving? How does it become complementary? Or how do you kind of evolve to make sure that you're...

So maybe I'll start with our view of what our AI did before the Gen AI kind of evolution. So we bought a company called Cordiant. They had a product called Customer Decision Hub, CDH. What -- I'm going to be very kind of general in describing this. But really, what it did was, it allowed you to create kind of a library of rule sets. And those rules were like if-then statements. They were kind of directives on how to take certain actions based on. And then what you could do is you could watch the activity of workflow, and you could learn from that. You could auto update the rules to say, "hey, originally, when someone came to a website and they made the following 3 clicks, I typically would put up a call to action. But that doesn't seem to be working." So maybe that's not the actual right next step. So maybe when they hit those 3 clicks, I need to ask, I need to show them a video or I need to give them a certain set of selective, what would you like to do next? You're kind of almost letting the system explore typically in a non-customer service-driven or non-sales driven environment, consumer on a website, and they're moving quickly and you don't really have the ability to have a human decide what to do. That was really our version of AI. What that allows you to do is, you could apply that to workflow, you could apply that to URLs and web applications. What Gen AI does, it allows you to do a different and very powerful kind of dimension on that, which is, it allows you to take text, it allows you to take information, and it allows you to put that information in the context with other information and really almost a free form way that traditional AI models couldn't actually handle. And so not only can you create rules AI where you use robotics and rules and kind of an almost trial and error to create kind of an AI engine, you can actually use voice AI, layered in with the rules with the text and the libraries, not only what you have, but what you're actually capturing to create quite an impressive AI kind of revolution around what the system can do. So when we look at it, we view it as the furthest thing from a threat, as you could imagine. We view it as a reason why clients would want to deploy enterprise grade applications, but still be nimble, but still be agile. And so one -- the 2 biggest -- 2 of the biggest factors that we think are where AI can really drive changes, how fast you can actually get an enterprise-grade application live, right? If you think about the traditional non AI-based way is you would deploy the product, you go through a series of design changes, you'd plan it out, you would start to configure the application. In today's world, with AI, you don't have to do any of that. The system, if you say, I'm an insurance company, the ChatGPT equivalent should be able to say, well, this should be your 3 use cases you're thinking about building. Which one is it? You click one. Great. Give me 3 seconds. Here's a starting application based on what I know from everything either in your libraries, in the public domain and whatever you want to connect it to. And so now you've got basically a designed almost set of choices that might have taken you 90 days in the traditional, and that's aggressive. It might have taken you a year. So you now have companies that would say, "All right, I'm interested in using Pega where I wouldn't have otherwise maybe thought of Pega as a vendor because now the speed and time to market is so much faster." The other thing it can do is once you're actually live, it can actually learn what changes need to be done to the application, not only recommend them, they can actually execute those changes. And you can come in, in the morning and say, here's all the changes I made to your application. Would you like to accept them or not? I mean that would -- that's like revolutionary in terms of how software is typically evolving. And those are just some of the early stage use cases. I can only imagine how we're going to come up with as an industry so many more interesting ways to leverage it. So we're really excited about AI. And Pega Gen AI is available on Pega '23. We've got clients using it as we speak. I mean it's pretty exciting. I think what we don't know is we don't know where this is going to go, like in terms of like which use cases are really going to be the most powerful and what new things that we haven't even thought about. Are we going to use it for, but right now, it's just a very exciting time to think about how it applies to helping our clients.

Absolutely. Very powerful and exciting. How do you think about -- so with -- how do you think about monetizing it? Or how do you model out potential monetization of that over time given it's so new and it could change so much. How do you think through that?

Yes. So there's -- so it's interesting. Commercial models, although theme on the surface relatively when you think about building technology, you don't typically think of the commercial model being a complicated piece. Like you build good tech and then of course, people want to pay for it. But just trying to think about the right way to monetize it. I mean we have a couple of obvious ways to monetize it. One obvious way we have is we typically contract with our clients on a consumption basis. And so as AI drives more decisions, more activity, more -- that's one way that's already embedded in the contracts. It's really a volume based. That might work. That's certainly an option that we've leveraged. Another option might be to actually pay for the actual AI engine itself, right? Some clients are uplifting like user license as an example. We don't -- that's not as relevant for us because we don't have as much user-based licensing. And it's a little bit counterintuitive to think that I'm going to make money selling AI that should reduce the number of people that have to support your clients. And so how would that work? So you're going to actually have -- you're going to need less, but I'm going to charge you more for it. It's a little bit -- it's a little bit kind of disconnected to the value prop. However, if you have user-based contracts right now, that may be your only mechanism that you could use to drive value. So for us, it's really around the volume and the activity and really around the actual processing that happens in the AI kind of engine or cloud.

[ Okay. That's really helpful. ] Maybe another -- if I can [ squeak ] a number of questions here as we're kind of winding down on time. We talked about how ACV is a really important metric for Pega. And I think that this year, you guided 11% to 13% ACV growth. I think in Q3 in constant currency, you grew about 10%, so just slightly below that range. I'm wondering how you think about growth for the full year at this point? Is it a risk? Is there an uptick in Q4 that kind of gives you a better comfortable feeling about that initial 11% to 13% ACV growth Guidance?

So certainly, I think where we are at the year being on the low or even slightly below the low end of the range is not a desired outcome, right? I mean I think there's some very real things that we dealt with in the year. Quite frankly, some of the -- some of the changes that we made to our sales structure probably weren't helpful in the short term. We've also had some sub kind of disruption in engagement with our clients around things like AI and other things. So it has been -- there's definitely been some -- it's been an interesting year for a lot of companies. But I think us landing toward the low end of that range is definitely feasible. And I think we're not thinking that our growth rate is continuing to decline. I also understand how hard it is to have the growth rate just immediately rebound as well. But we have a lot of activity in Q4. Q4 is our biggest quarter, as you know. And there's a lot of pipeline to go after and a lot of, quite frankly, renewals that happen in Q4 that you could sell on top of. So I think we're feeling pretty good about how we're going to work to finish the year. I think our range of where we land, quite frankly, isn't going to probably vary materially from where we are right now, right? I mean, just because it can only move so much in a quarter.

Well, very helpful. I think we're just out of time. I feel like we could have gone for quite a while here. It always fun to be up on stage. And again, we're really grateful you guys made it back to the conference this year. Thanks, everyone, for joining, and thanks to Pega, Ken and Peter, thanks for being here guys.

Awesome. Thanks, Rich.