Open Text Corporation (OTEX) Earnings Call Transcript & Summary

Thank you for joining us this afternoon. I'm Steve Enders, part of the software research team here at Citi. With us for our next session, we have the team from OpenText. We have Tom Jenkins. I think you're Chairman of the Board. I have that right?

Executive Chair and Chief Strategy Officer.

All right. There we go.

Just to be clear now, I got all those other titles.

Yes, I know you get the extra stuff with it. Well...

I actually used to be that about 10 years ago. And before that, I was the CEO.

Okay. Well, there we go. Well, we're glad to have you here, and welcome back to that role.

Maybe just to start, I think it has been a bit of a transition time for the company for OpenText. Maybe we can talk a little bit about what's led to some of the leadership changes and now how you're thinking about that moving forward and what you're looking for in a new leadership team?

Yes. So uniquely, right at this moment, the company is actually in a search for a CEO and a CFO. That's why I came back full time. And how that happened was that at the end of our fiscal year, we had planned for a CEO change, but what caught us by surprise was the CFO change. And that's because our former CFO, Chadwick Westlake, his old boss had a heart attack and died a week before the end of the fiscal year. And he obviously went back to his old company to take over as CEO. So that created the unique moment for us where both executives were gone at the same time. So we have an interim CEO, long-time exec at OpenText, James McGourlay. I've been working with him for more than 30 years. So he's a steady hand. And Cos Balota, he's long-time VP of Accounting. So we've got 2 steady hands while we do the search. So the Board kicked off 2 searches. And so we'll hope to do that in the next few months.

Okay. And as you're looking out in the marketplace for both those roles, what is it that you're looking for? What's kind of the right profile, the right personality type to lead OpenText forward in the future?

Well, on the CFO side, we're looking for someone that can obviously handle at scale, handle the complexity of multiple units, that kind of thing. So a steady hand there. But not anything exotic, if you will, in terms of M&A or capital allocation. So not any particular unique skills. On the CEO, however, I think you'll see the Board -- and by the way, I'm not on the search committee. So the search committee will do that. But I think the Board will lean towards the pendulum going the other way towards more solutions and sales. Our previous CEO, Mark Barrenechea, was like me an architectural engineer. But in between Mark and I was John Shackleton, who is a solutions engineer. And if I had to bet that there will be an emphasis to go back to solutions.

Okay. All right. That makes sense. The pendulum swings the other way...

Yes, it makes sense, yes.

Yes. Maybe again, from a high level, as you think about the opportunity that's in front of OpenText and what would you, I guess, pitch an investor on? What would you say is kind of the core opportunity and strategy for the business today moving forward?

Training Agentic AI. That's the #1, #2 and #3 priority. Part of the reason why we made the move and the change was to go back to basics. So I think investors will see us become a single concept and not a multi-business unit because it became too complex to understand. I think with the opportunity going on with training of Agentic AI and the need for content and curated content, that's right down the middle of the lane for us. So I think you'll see us pair off some of the business units that don't make sense to that vision, and you'll see us execute from that. And it's a great market to be in. So it doesn't take a lot of thinking to come to that conclusion.

Sure. Sure. Maybe we can dig in there a little bit just on the future of the OpenText portfolio because I think to your point, there's a lot of business lines, a lot of business units that are within the OpenText arena. So I guess, what do you consider as kind of the core business for OpenText moving forward? And I guess, what do you think of the areas where maybe it makes sense to rationalize and look for opportunities to divest?

Yes. First of all, the issue of the business units within OpenText got exacerbated by buying all the HP software catalog when we bought Micro Focus. So that we were already creeping into multiple business units that accelerated that. And at the time, when all this is going on 4 or 5 years ago, Agentic AI, ChatGPT, it wasn't a thing yet. The business was expanding into multiple places within enterprise software. Clearly, now, everything is about AI. It's about the productivity gains of Agentic AI, et cetera. So in retrospect, what the company was doing 5, 7 years ago made a lot of sense for that environment. But going forward, training bots for very specific tasks within enterprise, that's consuming the world, not just enterprise software, but the whole world. So it was easy to come to that conclusion. So if you look at our business units, effectively, when you're doing something like training bots, you're talking to the CIO of General Motors or Coca-Cola or whatever. At the same time, it's probably not a good idea to also be selling software to mom and dad at Best Buy, right? Because that's what some of the consumer products do. Because remember, the Hewlett Packard portfolio was the portfolio of a massively scaled organization that did everything from developer ops to consumer security and things like that. So it's actually not that difficult to shape the portfolio to go back to basics because management has estimated that, that's about 15%, 20% of the total revenue. It's not like a huge amount, but it's enough to distract management, distract investors and to cause overall growth rates to go down. So by pairing that part, I think it gives the company an opportunity to reduce debt, gives the company an opportunity to focus on a single story. And besides, it's obvious to anybody if you have the opportunity where you have one of the largest archives of content in the world and the world needs that content to train their chatbots, it's pretty obvious what you should do.

Right. Right. That makes sense. So I guess as you think about this next stage for OpenText and the -- I guess, the pairing of the portfolio, how long do you kind of expect that to kind of take to play out? And I guess, what is kind of the -- I guess, what do you do with those proceeds kind of after the fact?

So with the announcement of all the changes, which is 3 years ago, we also announced that there would be a committee of the Board dedicated to doing this because we didn't want management doing it. We wanted the Board to do it because sometimes when you look at different business units, you fall in love with them a little bit and you think you can fix them all. And you probably can, but that's not the point. The point is to be focused on one. So the Board took over that responsibility to just do the capital asset allocation. So I think you'll see them move very quickly. I'm not on that committee either. But I think you'll see them go at a pace of one a quarter. They shouldn't go faster than that. That would be unwise. So I think that's what everyone can expect. And I think they'll probably do 2 or 3 business units over the next year.

Okay. And I guess as we think about that, is there like an approximation for how many units will kind of be...

No, I don't know that they've identified that yet. I think one looking at our portfolio, though, just as we've said, it's pretty obvious, there's probably about 15. It's probably somewhere between $0.75 billion and $1 billion out of the $5 billion and change that we do today. I haven't seen the detail yet, but it will probably be something like that. One of the things we are doing, though, so that investors can follow along with us, we're going to provide more detail on all the segments and their growth rates and what have you. So everybody can say, yes, that makes sense. That doesn't fit with the other pieces. So we're going to try and get that out in the coming weeks.

Okay. No, I'm sure that would be very welcomed by the investor community. So that's helpful for sure. As you go through this process, maybe this then kind of dovetails into the other part of capital allocation. What do you do with the proceeds? What do you do with the kind of go-forward capital allocation strategy?

Well, I think there's 2 parts to that. I think the onetime use of the capital, as we've done in the past when we did sell another business unit 1.5 years ago, we'll pay down debt because we have 2 tranches of debt. One layer of our debt, our original debt is long-term paper, 4% fixed. We're quite happy with that cost of capital. There's another layer, which is around -- we have about $6.5 billion of total debt. There's about $2.5 billion that we'd like to reduce from the proceeds of the sales because that's higher variable. And I think if we do that, investors will be happy because we'll see cash conversion rates come back up to what they historically were. We got caught just like everyone else when the dot plot went 200 basis points higher than all of us were expecting. So I think you'll see that at the sort of asset trading level one time. I think on an ongoing basis, investors can expect us to keep our historical EBITDA percentages somewhere around 35%. And I think they'll see us allocate that capital into 3 places like we have been doing. We'll keep our dividend and grow our dividend. We will keep buying back our stock. We're at the current course and speed, we're probably close to buying back 10% of our stock in the past year. So we'll just keep doing it. There's a lot of cash flow, so we'll keep doing that. And the third thing, investors will see us do tuck-under acquisitions, small. We won't do large ones. There isn't really any more compelling products or installed base out there. But you'll see us speed delivery, just as we were talking about in solutions. But I think investors can expect that. There's about $1 billion in free cash flow roughly, and I think we'll see a division between those 3 things. And in other words, expect us to continue what we've been doing.

Sure. I guess does it maybe change the mix of how we should think about those buckets between dividends, buybacks and the reinvestment back into the business? Or I guess, primarily want to dig into the last part about investing back into the business and what that looks like moving forward. Is that a continued area? Or is that...

Well, we've invested a lot back into the business because of AI. So the production of the Aviator product line to be able to -- see what happened is that we've had content in enterprise for -- since the beginning, 40, 50 years ago. But we didn't have the specific connectors to large language models because they didn't exist. We didn't know how they were going to be trained because that entire technology had not been existed. So we previously have had predictive analytics, decision support and APIs and what have you. So we spent the better part of the last 2 years while we were integrating Micro Focus also building out the entire product line to be able to interface. You don't interface with one LLM, you have to interface with dozens of them because in the enterprise, people are going to pick different large language models to build inside their firewall. So that took a lot of work. That work is done. So that is -- and so that's like an entire refresh product cycle that we've just gone through. So that's why the emphasis on selling now. Let's go sell what we built over the last 2 years.

Okay. Maybe I'll ask a little bit on -- I guess, to that point, now that you've made this investment, what does that mean for kind of go-forward R&D? And I guess, on the other side, since it's now time to go sell, does that mean the mix of sales and marketing should tick up from here? And is it kind of reallocating buckets? Just how do you think about that?

Yes, absolutely. It just makes sense. We're through it. In many ways, enterprise software companies go through these cycles all the time. And so the pendulum swings, and you'll see us spend more in sales and marketing and less in R&D. And it's normal. That's a normal cycle.

Sure. Okay. You mentioned M&A before. I do want to ask around kind of what that will look like. But before going into that, just as we think about Micro Focus, maybe we do a little bit of a postmortem on that acquisition. Just what were kind of the learnings from it? What is there maybe that you can apply moving forward as you think about the OpenText strategy from here?

Well, I'd say, first off, would we do it again? Absolutely. If you were to go on Perplexity or ChatGPT or any LLM out there and say, who has the most data connectors to train Agentic AI in the world, OpenText. And then you ask why? It's because they bought the HP software catalog and archive. That was a massive archive. There were only 5 players. There was Oracle, SAP, IBM, Microsoft and Hewlett Packard. The other 4 are not available. So that was a huge jewel in the enterprise software universe. In retrospect, I would say that all of us, both on the Board and the management team wish that we had gone faster to concentrate on the core. But hindsight is 2020. We should have worked on some of this stuff faster. But from an execution point of view, the EBITDA of the overall company is at 35%. So it was executed well. We just needed to do it faster.

Sure. Okay. All right. Maybe then dovetails into the other side. Just as you think about the go-forward M&A strategy, it seems like there's some tuck-ins that you would kind of think about. Just how -- what kind of opportunities are you looking for? Maybe what are the areas where it would make sense to kind of lean into that a little bit more versus what are areas maybe you'd be a little bit more kind of cautious about kind of entering?

Well, I think the days of us so-called buying content archives for $0.10 on the dollar are over. Everyone has figured out the massive value that they are. We just saw recently the sale of Informatica, which is a kissing cousin company to OpenText to Salesforce. And that went at, I don't know, 5.5, 6x revenue and 25, 30x EBITDA. So our ability to pick up assets in the content and data space are quite limited now. But besides, we're at a cycle now where our emphasis is really picking up go-to-market solutions companies, resellers and especially in the era of nomenclature, because when you're dealing with oil and gas or you're dealing with automotive or pharma, as you train the bots, it's actually the nomenclature, the knowledge of the supply chain, the knowledge of the word transmission in automotive has a very different context than pharma. So you really need to have teams that can accelerate your ability to convert. And so I think you'll see that, that will be the emphasis going forward.

That's really about finding the context that helps you train those models?

Yes, absolutely.

Okay. are there certain, I guess, maybe like technology areas or market expertise or customer footprint that you would be kind of targeting for those tuck-ins or...

Regulated industries. Absolutely. Because those are the industries that we have built our biggest content archives with and have the greatest industrial knowledge, greatest customer relationships where we can compete and win. So that will be our focus.

Okay. That makes sense. Maybe wrapping a little bit of a bow on some of the M&A or portfolio side of it. But I guess, once you kind of go through this bigger transition over the next kind of couple of years, what does the new OpenText look like once you're kind of through the portfolio rationalization? And how do you kind of think about -- is it just kind of a content-focused business? Or are there kind of other areas where maybe it makes sense to...

Content-focused business because everyone may be getting tired of talking about AI and Agentic AI, but the reality is we're going to be spending the better part of the next decade rewiring the world. And that rewiring will require training with content, curating the content. And remember, when we speak about content, a lot of times, we as human beings, we think of the content in the public web, let's say, TikTok and Meta and what have you. That's actually only 5% of the world's content, 95% of the world's content is behind the firewall. I wrote a book called behind the firewall to explain the fact that in the early days of the Internet, Boeing, for example, had an intranet and internal Internet that was many times the size of the public Internet. This will take us the better part of a decade to convert all that content, and the content is in 3 types. The content is human-generated content, machine-generated content and content between organizations or business networks is what it's called at OpenText. Those 3 types of content are all critical if you're going to train a bot to remap a supply chain for General Motors. You need all 3. So you'll find that those 3 business units within OpenText with a cybersecurity wrapper will be the core of the business.

Okay. That makes sense. We're about halfway through this. If there's any questions in the audience, we want to make sure to get to those. Yes. We have a mic coming.

So with the strategic changes, what changes in terms of your financial policy with regard to financial leverage?

That's a great question. I'll repeat the question. Would there be any changes to financial policies approach, et cetera? Actually, no. The current plan for the fiscal year was approved by the Board. We had no issue with that. So I think the margins, the growth rates, we hope to shrink to grow. So we hope to take some of those business units that are growing slowly simply because they weren't perhaps getting as much attention as they should have gotten. But in terms of margin, all these units are generally plus or minus 5%, all about the same kind of margin. So it's not going to have any shaping from that point of view, not that we can see. We did sell a mainframe unit several years ago that had like 85% margin. That had a big impact. But we don't see a big impact going forward. It should be about the same.

And was there a comment about leverage in there?

I'm sorry. So on the balance sheet -- yes.

So just wondering if there's anything magical to the 3x leverage target or might that be -- might that above...

Yes. I think you'll see us come down below 3. Historically, for 30 years, we always kept our leverage sort of around 2, 2.5. I think that's what you'll see us come back to. I think leverage is obviously a very investor-friendly thing as long as it's in the right ratio. And so that's what you'll see us do.

Okay. Perfect. Thanks for that question. I want to dig into the product side a little bit more here. Just on -- I think you talked about we're in a content age. Generative AI is going to be the next -- is the decade for the next -- or the story for the next decade. Maybe we can talk about Aviator. Just where is it at today? How are customers thinking about or adopting that solution set? And what is kind of the future of the generative AI strategy look like for OpenText?

I would say that this is an evolving area. I don't think anyone can say that this will be the dominant LLM. I think that there are many layers to your question. I think CIOs are debating where do they go from here? Because we've had a massive move from where we had the so-called IT white tower on-prem inside the firewall to the use of whether it was private cloud or with hyperscalers. And I think with AI, it's a bit of a different game. And they have to decide what parts of their business they're okay to keep data at a hyperscaler level and what parts of their business do they want to keep data in a private cloud or on-prem. And then CIOs I've talked to, once you start that discussion, then they start to say, okay, then what does that mean? Am I a hybrid company now because they were all moving to the cloud and to the scalers. So it's a real dilemma for them. And I don't have a crystal ball to tell you which way they'll go. We, just by history, have both because we began in on-prem, so we can support on-prem. But then over the past decade, we've moved to cloud services, private cloud as well as to a SaaS model on hyperscalers. So it's sort of -- it's really up to each individual company to decide how they're going to do that. So now with Aviator, we built our product line so that it would satisfy all those 3 areas. Now obviously, that's more complicated to build. It took us longer than, say, some of the pure-play content players, but it gives our customers maximum flexibility. The other layer, so you could call that a multi-cloud architectural approach, but you also have a multimodal architecture approach in the sense that which models will exhibit themselves as being preferred in particular industries, et cetera, because part of the dilemma that we have is that most of the models everyone knows in the audience were trained effectively on public information. So there's so much training you can get from Reddit and Wiki and what have you. But then as you go deep inside the automotive industry or you go deep inside the pharmaceutical industry, where the -- will there be models that emerge that are preferred by that industry. We don't know that yet. We're architected to be both multi-cloud and multimodal because we can't predict that we'll leave our customers to decide because one day, they may want Anthropic or maybe they want Llama. We don't want to decide that. We've certainly made strategic partnerships with various LLMs just to give our customers sort of a predesigned choice, but we have to stay in an open architecture. We've always been that. We have been the Switzerland, if you will, of content for more than 30 years. And I think our clients will expect us to keep doing that. So that's what made Aviator a 2-year development process because it had to be multi-cloud and it had to be multimodal. So that took a lot of thinking. The team did a great job on it.

Okay. No, that's great to hear. And I guess as you think about what the future of the portfolio looks like on the generative AI side, just what does the road map look like? How do you think about the use cases that it makes sense for OpenText to address and own for customers?

Okay. So that takes you to another level. So architecturally, the big debate, a 30-year-old uses an LLM as an operating system. A 50-year-old uses it as basically a search engine. And so we have different user cases and the dilemma is we believe we have to satisfy both. You can't tell the 50-year-olds, we're expecting you to have a conversational experience with your LLM app, et cetera. And you can't tell the 30-year-olds, well, we're constraining you that you can't use an LLM as an operating system. So there is a real diversity in the installed base. There are cases -- I don't want to call out specific customers, but there's cases where we have to satisfy both users. And so even though these applications could, in fact, be GUI free because they really are, we actually are still building GUIs to interface because that is what a large part of the population expects. I think what we'll find is as we get better, let's call it, agentic coaching, if you will, I think we'll find that we will obviously go to a GUI-less app, but we're not going to get there anytime soon. Human beings are human beings, and they will take time. And so that's the complexity. When you talk about as we go down into the classic enterprise applications and how those interfaces occur, that's going to be complexity. Second complexity that we see -- I wrote a book on this called the Anticipant. And the premise of the book, I wrote it with Mark Barrenechea, our former CEO and General David Fraser, who commanded troops in Afghanistan. The trick here in building apps is the users have to anticipate because you can't react. Think of flash crash all those years ago. The humans didn't know that the market was going down for about 15, 20 minutes. And that's a lifetime for nanosecond trading. So the dilemma that we have is as we build these apps, the humans have to manage the bots, but the bots are so much faster. And so there is a degree in these applications that you have to start to anticipate. We're seeing that today in cybersecurity. We're averaging -- I think if I got this right, we're 200,000 breach attempts per second. Think about that, 200,000 breach attempts per second. You have to architect your bots so that they're anticipating the other bots and you cannot participate at that nanosecond level. You can only reach yourself back. So I'm sure you're -- sorry, you asked that question, but that's the kind of stuff we have to think through as we go through this because we have a wide range of use cases.

Yes. No. I mean it's interesting times, right? And how quickly the tech is evolving here. Maybe we can connect it back a little bit to the financial side of the equation. I think Aviators have been out for 2.5, 3 years, something at this point. Just what contribution is that having today to revenue or to bookings? And maybe how do you kind of think about what that means for the go-forward financial model for [indiscernible]?

Yes. It's a great question because we debated how this was going to -- and now Aviator itself, although it was released in its first version about 1.5 years ago, it was really last year's Aviator that you could really deploy. And this year's version will really, really, I think, please our customers. But here's the thing, just like so many other disruptive operating system-level technologies, they themselves are not the drivers of revenue. I remember in my era, we came up with search engines. And we thought, oh, search engine, this is great. They were free within 24 months. And I think that's part of the dilemma that vendors have right now that they've invested billions into this and yet customers perceive the utility as table stakes of what they're doing within the application. So in fact, the way we look at Aviator revenue is the revenue that it's enabling in the content servers. And so the content archives, the records management, all of those utilities that come with increased use of content, that's actually where we're making our money. And when you track us, management has been giving you all the content, cloud revenue bookings growth, that's where the money is. And that's where they've had double-digit growth. So that's how you can tell. It's actually -- Aviator is an enabler. It's actually the core products that are growing. But without Aviator, you cannot access them to curate the data to then train Agentic AI.

Sure. So it's a second order effect.

Yes, it's a second order effect.

Okay. That makes sense. I have a couple of minutes left here. I just want to see if there's any last remaining questions in the room there.

It's also obvious.

Yes, right. I think one of the questions we've gotten from investors, just think about the past few years, what can OpenText do to kind of like improve execution and just kind of get back on kind of a steady foot and improve that moving forward?

Well, the execution operationally has actually been pretty good. Here we are 2 years later, having done an acquisition, which was of the equal size. So you took $1 billion multinational and added a second $1 billion multinational. And 2 years later, you're clipping along about flat growth and 35% EBITDA. So from an operations execution point of view, we're pretty happy actually. And so now it's to go into that growth cycle. So I think the big message for investors is, I think all of us wish we had gone faster, but it was a pretty complex integration. And I think what investors have to look for now is, do we pare down to get to that core fast in this next year and grow from there. I think that's really the watch word for us is can we rationalize that portfolio and grow from that core? Because when you see the segment analysis, you'll see the core is growing. And so we want to make that really easy to track.

Okay. That makes sense. In the last minute here, let's think out 5 years, we're kind of through all the -- kind of what the core OpenText is at that point. What does the business look like? And maybe what are we kind of talking about what OpenText is moving forward as we get to that time period?

I hope for investors that it becomes a boring name that it's mid-single digits in its growth. It does tuck-unders for another mid-single digits. It keeps to its operating discipline of 35%, 40%. One of the great things for investors is can OpenText like other tech companies do the AI-first strategy, move away from Rule of 40 and maybe start to see Rule of 45, Rule of 50. That remains to be seen whether the industry can do that because we're a price competitive industry. We'll see. But I would say that's what investors should look for. Back to basics for OpenText. We're not doing any more big transformative M&A. We'll do tuck-under, but expect more of the same, what we did for 30 years.

Yes. All right. That makes sense. I think we can leave it there. We're out of time. But Tom, I want to thank you so much for being here today. I want to thank everybody in the room for joining us as well.

Okay. Thanks.