Open Text Corporation (OTEX) Earnings Call Transcript & Summary

Thanks, everyone, for joining. Really pleased to have OpenText with us today. Tom Jenkins, Executive Chair and Chief Strategy Officer, been in the role for 9 months -- back in the role of 9 months now. Yes, welcome. Thanks, everyone.

Tom, you made some interesting comments on the last earnings call. Obviously, AI disruption is a huge theme. Can you talk about why OpenText may be immune to some of that disruption, sort of talk about the secret sauce and maybe why you're not an application software more you feed content into application software.

So on a broader level, what maybe the first thing to say is we're not an application software company. Yes, we're a software company. We're not an application software company. But also just application software itself, especially in the area of enterprise software, this is very difficult. You don't just switch technologies like this. We took a decade to go to the cloud. We took a decade to go to client server. I'm old enough to remember all of those. This takes a long time. This has been a rather dramatic response to AI. The other really interesting thing about this overall is that market participants are not stupid. They will -- if indeed AI is going to react and people are going to adopt it, market participants will simply acquire one of the other large language models that are falling by the wayside. I watched all these market participants do that for the last 35 years. So it's been -- and a macro thing, the last 3 or 4 years has been rather interesting. Specifically to OpenText, though, and on our call, we're not an application software company. We provide all the content that goes into applications. And in fact, if you could put the slide up, I brought a slide just as an engineer, it's always easier for me to see an image. If you think -- if you look at the slide, I'll just break it down for you very quickly. You take the content, I guess you can see it over here. You take the content. What's the content? It's contracts, it's e-mails, it's spreadsheets, whatever, all the content that goes into running an organization. You put that into an application. What's an application? That could be Microsoft Office. It could be SAP, it could be Oracle, it could be Salesforce. It doesn't matter. It all goes into those applications run by human being. And what do you get out the other side? You get operational efficiency, you get faster time to value, whatever. That's been the enterprise software business since IBM invented it 50 years ago in mainframe. So we've done that evolutionary step. What's happening now is we're replacing the humans or we're augmenting the humans with the bottom part with an Agentic AI or some form of very specific AI to either help the worker or to replace the worker. It depends on the situation. But the point is you have to train it. And to train it, you have to use the same content that you're giving the human. So OpenText does all the stuff on the left side of that graph. We don't do the applications. We provide the content that goes into the applications. And so what are we busy doing now? We're providing the content that goes into Agentic AI. So that -- and then, of course, they'll drive the same. So when you hear things like Anthropic and what have you, they're starting to talk about, well, maybe we can make the application software and replace the human and the application software that the human uses. Quite frankly, we're in variant to that. And by the way, as I said at the beginning, it's not going to happen anytime soon. But if it does, we're simply feeding the content to either the human or the robot. For us, we don't care.

And then can you -- on that content that you're feeding in, can you talk about any secret sauce, the metadata sort of business context that you bring in and sort of like why your decades of experience and data that you've been collecting?

Yes. Okay. So that's why I brought this along because if you want to understand that question, read this book. That's why I wrote the book because we are getting that question all the time. So this book is very similar. It's a modern version of the book I wrote about 25 years ago, which created the term enterprise content management. So this book is called Enterprise Artificial Intelligence, and it will become the Bible of how you build the Agentic bots. And just like the book that we wrote 25 years ago, defined enterprise content management. Okay. So let's unpack what all that means. So okay. Maybe the simplest way, and I'll back off, but I'll give you an overly simple answer. If you're feeding into an AI and you have a data lake, so let's say that's Snowflake or Databricks or something like that, that is like a big storm sewer going into a lake. It's just throwing a ton of data that then trains a very sophisticated large language model. Great. And so we've seen lots of applications come with that. What you're talking about is when you get into Pfizer or you get into General Motors or you get into Coca-Cola or you get into Nestle. And I can go on and on and on, regulated industries, industries that have responsibility around the data, industries that have all of your data, you don't want that going into a data lake and you don't want that going into Gemini or ChatGPT, et cetera, because through prompt engineering, we can basically get all your data eventually. I mean there's all kinds of guardrails and what have you. But the bottom line is you don't want it. And if you're a corporation and you have the Cadbury secret sauce or whatever, you don't want that in a data lake or in an AI. What do you do? Well, we have laws. We created laws 25 years ago when this first started to happen with data going into those applications. And the laws are called GDPR, general data protection regulation, PIPEDA in Canada, U.S. PDR in America and so on. So we have rules and it's fines, go to jail, like they -- all the country set out rules to protect your privacy so that you can't lose all your bank accounts so that people don't know what your latest medical report was, et cetera. It's your privacy. Okay. So we have a body of law. In fact, there's more than 10,000 regulations that relate to the handling of content. When you feed that content into a large language model and AI, it consumes all that information. It now has the same information as if you had it on a folder that you have to protect. So the law that has the responsibility for that corporation around your information, that same law applies to the AI. So you've got to be very, very careful. So the way I like to say it because the way we solved this 25 years ago is we created permissions. You would have permission to know that a document existed, but you couldn't see it. You could have permission to know the document existed and you could see it, but you couldn't modify it. You could have the permission to see the document, modify the document and create a new document and so on. There's actually 11 steps in the latter. And we created all that 25 years ago so that organizations could move away from paper and actually do this all digitally. So if you think of a data lake being a storm sewer, a content management system going into AI is like all the pipes that are in your house. And every pipe goes to the laundry, the washer dryer, it goes to the kitchen, it goes outside to the lawn, sprinkler, et cetera. And what does every pipe have? It has a valve. And that valve is the permission. So it's the same thing. So what we're doing is when you train an AI, you're training it with very specific pipes, not a big storm sewer. You have to do it that way or your company could go out of business because you'll be in violation of some regulation. So this is grown-up adult serious stuff. This is not stuff that you just put up on the Internet. And remember, and if you read the book, you'll see in Chapter 1, 90% of all the world's information is behind the firewall, and it has spigots and valves on it. So you can't get at it. The vast majority -- a lot of people always think that Google or ChatGPT has all the information. No, they have a fraction, a very tiny fraction of all the information out there. So that's a bit of a longer answer, but it's an important thing to understand.

Bringing it back to the business today on content management is what we're mainly talking about today. Overall, your cloud growth in the last quarter was a little bit over 3%, the cloud growth, but the content cloud growth was something like 15% or 16% growth, and it seems like it's been that growth rate last year. I don't know how long...

It's been solid on that about 8 quarters now, and that's cumulatively building because that growth rate is getting on a bigger and bigger number every quarter. And you know what's happening is CIOs are getting ready. They're getting ready because everything that I just mentioned to you, you have to have all your content ready to go before you start training those bots. So they call that curating the content. They've got to make sure they've got all the content in the cloud. You see, you can't train a bot if the content that you're managing is on a file server on a mag tape or something like that on some archival storage. It has to be live. It has to be accessible to train whatever Agentic you're building. So what you're seeing is you're seeing not even the first inning of the ball game, you're seeing the first batter. What they're doing is they're just basically getting everything digital. You'd be surprised, but -- the vast majority of organizations, even after COVID, COVID forced them to do all their customer-facing as digital, all the back end, which is all the stuff we manage, it all stayed on-prem, et cetera. They're now moving it into the cloud because they have to. It's the only way they can take advantage of AI.

Can you tie that into comments that you've made recently about how OpenText might be shifting over the coming quarters and years as you move more to the cloud away from the maintenance and support line. And you've talked about maybe how you've learned from other software firms in their transition and you're doing something a bit different this time around. What have you learned? And how do we see the trajectory moving over the coming year?

So the simplest way to think of it is what the ERP firms did. SAP going from R/4 to R/4HANA, we share most of our customers with SAP or Oracle. They both did this over the past decade. What's happened with our customer base is this move to the cloud to train AI is causing them to talk to us about moving from the classic on-prem maintenance model to move to the cloud. So what we've been doing is we now have feature equivalents between everything that's on-prem and can be offered in the cloud. And so what we're doing is we're starting to do migrations the same way that you saw SAP and Oracle and others do. So you're going to see the cloud revenue part of OpenText expand. And you'll see overall growth being driven by that because -- and we don't know yet what the -- Steve did an analysis at Analyst Day to give everybody an idea of what it would look like. You'll start to see our maintenance number go down. You'll see our RPO number go up. It's like sort of deferred revenue in the old days. So you'll see an RPO number. And he's staying consistent with what Salesforce does and SAP and what have you. But the real thing that you'll see is cloud ARR go larger by a multiple of the maintenance. And the thing we don't know yet is what is that multiple. We know it's multiples. And so therefore, there will be substantial growth coming from it. We just don't know yet. So is it -- SAP, they started where they were 2x the maintenance. They got most recently the last couple of years at 5x the maintenance. We have to crawl before we run. But I think you'll see us do the same kind of trajectory. Now that's pretty dramatic. If we take an installed base of our core business, once we've gotten rid of the noncore business, it will be around $4 billion. Of that, there's about $2 billion in maintenance. We'll start rolling that off probably around 10% a year because it takes a lot of work to do the conversion. So if we roll off 10% a year, it's about $200 million a year. And if we get a 2, 3 or 4x multiple, so say we get a 3x multiple. We will be taking $200 million of maintenance down, $600 million of cloud ARR. That $400 million on a $4 billion base is a built-in 10% growth. And that's what SAP did and why they were so successful over the last 5 years in particular. So we're going to start that journey. That journey will be a consistent journey over probably the next decade as we roll off what is 35 years of built-up maintenance and convert it to cloud because they all want to train their Agentic AI. So that's one of the journeys that OpenText will be on.

And how do you think about the -- any margin implications of that move...

Yes. So we studied that a lot. And originally, when we first started communicating to the Street, I think, Steve, you were into the role maybe 1 month, I was in 3 months. And we started cautioning everybody, the margins might go down. Well, we've actually done more work now. We believe margins go up actually. Now when we say margins go up, dollar amounts go up because we're replacing $1 of revenue, let's say, 90% margin and taking $3 of revenue at, call it, 70% or 75%, it will be lower, but the dollar amount will be triple, right? So you'll -- when all the smoke clears, say, 2 years from now, you'll see our EBITDA go down, but our top line growth go up by much more. That sort of -- I'll leave it to Steve as he does more of the modeling and communicates it to the Street. I think with the new fiscal year and with Ayman joining as our new CEO, I think by then, they'll be able to tell the Street what they think the model is going to look like. But it's a journey we're on. It's a wonderful journey, but the way -- just like when everyone in the industry asked us, would we break out core and noncore so they could track our progress. Steve and Ayman will do the same thing. They'll break it out so you can track their progress.

And you mentioned like a sort of a 10-year dynamic that -- like what are some of the catalysts? I mean, obviously, customers coming up for contract, that will be a time you can go visit customers and ask them about an upsell...

Yes. The main catalyst will be AI. They -- like if you're a CIO today and your CEO does not see you getting ready to do Agentic across the whole organization, you probably won't be CIO very long. This is a massive wave that's just taking us along. You may ask, why do you guys estimate 10%? Why wouldn't you do 20% or 30%? This is a lot of work. This is what I was trying to say before about the Street thinking this will happen overnight. Think of any of your organizations. We have to go into the very bowels of your basement and literally take decades of software, of content. And by the way, some of this content, we have 1,500 connectors to word perfect, VisiCalc, like you name it, Db2, you name it, we got to connect all that stuff that some of you weren't even born when it was out. But those are in the corporate memory that is part of the training. You have to do that. So this is a highly complex move. We think we can do 10% a year. It's one of the reasons why -- and you know we cautioned everyone, we'll probably do some tuck-under acquisitions of professional services companies that have very specific knowledge around pharma, automotive, food, ag, that kind of thing because as you go into it, you need to be something of a subject matter expert. And we find that customers -- we would prefer to do partners. We find customers sometimes if they're doing lift and shift of something that they could get fired, they're going to want to know that person is from our company. And so I think you'll see us do some tuck-unders to be able to give us the capacity to be able to do it. But this is a big lift. This is a big decade-long thing. It's a high-class problem, but it's a journey we're going to be on.

Yes. Thinking about our conversation that I had with you when I first met you in September, you outlined a bunch of objectives, hire a new CEO, check divestitures, check.

Did them all.

Did them all, right? On the divestiture side, though, they've been on the smaller side, I think you've got some really big chunk there...

Yes. The small ones were easy to do because as we put them to bid, it was a single product line or a couple of product lines. The ones that you're going to see now that are in auction right now are very complex. They have 60 products in them. So that's why it takes longer. But yes, we're making very good progress there. And we made a commitment by the end of this year, we're getting out of all the noncore, and we will stick to that commitment.

Just to clarify, end of your fiscal year or...

We will announce -- okay. So nothing is perfect, right? But we will announce all of them by the end of our fiscal -- our fiscal is midyear. So we've got another 3, 4 months that we're just running the process. But sometimes after you announce it, you still have to transfer, and that will take 3 or 4 months. So I think you'll see us out of everything by the end of the calendar year, but you'll see what we got for it, when we're transitioning it, what the transfer agreements are. You should be able to see that by the end of our fiscal. Now nothing is perfect. We don't control the whole process, but we're well underway. We've got a very robust auction going on.

And there's been -- how have things maybe change in the past month with sort of all the software derisking?

Yes. So we got a lot of questions, not at all because what's going on in the market has been a reassessment of the value of future growth, et cetera. We're selling very good businesses that are not core to what we want to do, but they're being sold on a discounted cash flow basis. What's going on in the Street over the past month does not change their DCFs or anything. So -- and we reconfirm that as well. But remember, it's an auction. So we made a commitment to the Street that we would divest, and we will divest in the context of the market. But it's always been discounted cash flow. So that hasn't changed.

Got you. We talked a lot about what you're doing for enterprises on their AI journeys. What about OpenText? Maybe talk about how you're deploying agents how you're leveraging AI in your cost base and maybe tie that into your margin profile and the strength that you've got there.

So it's stunning. It's stunning. We are now seeing -- that's why -- how the Street reacted over the last month, it's because there's a kernel truth in all of this. It is stunning what is going on. I've never seen anything like it. I've been at this for 40 years, never seen anything like it. So what we've done now, we're starting -- and we'll make more announcements as our new CEO comes on. But you're going to see us, as they say, drink your own champagne, eat your own dog food, et cetera. This move from on-prem to cloud, we did it to ourselves first. And in doing so, we are making unbelievable savings. It's really quite dramatic. We're seeing in some job categories, 5 become 1, 5 to 1. It's just unbelievable. Now as that shakes out, I'll leave that for Ayman and Steve to talk about. But last call, Steve did talk about the cost savings program and that profile that the company had worked out. We're very much on course to deliver all of that and maybe more. But for sure, we're going to be able to deliver it. It's been amazing.

Yes. And as you think about the profile, you generate great free cash flow. You've talked about divestitures. You've got a little bit of debt. Maybe just talk broadly about capital allocation and again, guidance where the stock is trading today.

Well, we made a commitment in August that all the stuff that we did with the noncore, we would retire debt. because we wanted our debt down to the traditional multiples that we've always had. And so as we retire noncore, we're also retiring EBITDA. So we've got to make sure our debt stays commensurate with that. So we're managing that down. And by the way, the EBITDA of all these businesses are roughly the same. So there isn't like some high EBITDA business that we're selling or whatever. It's all basically the same. And they all sort of come in around 33%, 35% EBITDA across the board, whether they're core or noncore. So you'll see us as we take a ballpark, if we take down 20% of our EBITDA over this next year because that's sort of what we were guesstimating, we'll take down 20% of our debt to go with it, but we probably will take more than that because our traditional debt-to-EBITDA is around 2.5. I think you'll see us try and get ourselves to that. And we've got a couple of debt towers coming up, and we'll take advantage to remove those. And Steve is the expert. He'll be doing the refi and all that stuff. But on one level with the capital, we made a commitment to the Street last year that that's what we're doing. And so far, that's what we've done is we've sold something, we've taken debt down. The second area of capital allocation is acquisitions. We're only doing tuck-unders right now. The organic growth opportunity before this company demands that we spend all the time on that. So we will not distract ourselves with acquiring something large. We won't do that. What you will see us do is those tuck-unders to help the organic growth. Dividend, we'll keep our dividend. I think the fourth pillar of all this helps the dividend because I'll explain why. We announced a couple of weeks ago that we expanded our buyback program. With all that's going on in the market, you can imagine our response if we are able to do -- we announced $500 million, I believe, Steve? If we do $500 million at a stock price of $25, that's 20 million shares. That's about an 8% accretion. Buying ourselves is way better for all of you than us going off and buying something that we got to take a risk on and integrate and all that stuff. It's just easier to convey shareholder value. So I think you'll see us be, especially at these prices, very aggressive over that time. What that then does is for the same dollar amount, dividend. And we've always said roughly, we like to keep the dividend around 20% of our overall cash flow generally. That will make it really easy to provide growth in the dividend over the next few years.

Final few minutes here. Maybe we can talk about your new CEO that's coming in, Ayman. What -- first off, maybe why was he the right individual for the role? And what do you think -- we'll ask him the questions later, but what do you think he saw in OpenText that got him excited to come?

Well, what was great about Ayman is that he grew up about, I don't know, 5 blocks from our headquarters and yet has had a spectacular career internationally. And so he's coming home. He went to University of Waterloo, and we're on the campus of the University of Waterloo. So it's wonderful to have Ayman come. Ayman, one of maybe a handful of executives in Canadian history that have operated a company of the size that he's operated because he ran IBM Americas. It's about $60 billion. So that's about 10x the size of OpenText. So we were thrilled to have him. But what made Ayman even more interesting was that we've been competing against Ayman for 25 years. He knows our entire product line. I would argue maybe better than we do because he competed against it. So all these product lines that we have, he's managed all of them. And so -- and then the last thing that we really liked about Ayman, Ayman because IBM, it stands for I've been moved, right? So IBM runs all over the world. And as we see the world geopolitically change, having regional country organizations matters again. The master of doing this is IBM. I remember as a young engineer going to Japan and arguing with Japanese engineers that IBM was really an American company, not a Japanese company. IBM is outstanding at integrating into cultures and Ayman is. Ayman set up a lot of Asia for IBM as it started to open up. And I think you'll see a level of sophistication in our go-to-market. Because remember, when we talked about this before, the Board really wanted someone not from the engineering side, even though Ayman is an engineer knows all this stuff, but someone that really cut their teeth and lived in marketing and go-to-market and customer-facing. That's what we get with Ayman. We've never had an exact with that level of experience at that scale in the company ever. So it will be really exciting for us.

Yes. Looking forward to that. Final minutes, just on the changes. There's been some changes to the Board as well, a bit of a refresh. Just talk to the audience about that a little bit.

Yes. Our Board, we had COVID and then we bought the Hewlett Packard software through Micro Focus. And so we had the Board stay a little bit longer than their past before date kind of thing. We did that on purpose because of all the changes. The Board refresh now, I believe there's only 2 of us left that have more than 5 years on the Board. And we've changed so many. We're sort of slowing down a little bit now, but the whole Board has changed over. And we've had some wonderful people join the Board, the CIO of Cisco, HR VP from Hewlett Packard. George Schindler, of course, who you know, just retired as CEO of CGI last year. So yes, like some really -- I've now missed a couple of really good board members that have joined, but some really good Board members. Margaret Stuart, of course, long-time sales executive. But yes, it's -- we've had a couple of Board meetings now, a lot of different perspectives. They are coming in as all multinational operators. And I can see the difference in the Board meetings a way. The previous Board was a great Board, brought the company to a $5 billion size. This Board knows exactly what it takes to get to $20 billion.

Got it. Awesome. Tom. We'll leave it there. Thanks, everyone. Awesome. Thanks, Tom.