Open Text Corporation (OTEX) Earnings Call Transcript & Summary

All right. Thank you all for joining us for the tech portion of the day. I'm Thanos Moschopoulos, I'm the Canadian Technology Analyst at BMO. And happy to kick things off with Tom Jenkins, Executive Chairman and Chief Strategy Officer of Open Text. Tom is the architect of Open Text's strategy having been CEO from '94 to 2005. I know this personally because I met Tom shortly after the company went public in '96. And Tom outlined how the company went public as the search engine powering Yahoo! -- but he didn't view that as a sustainable business model. And so he articulated a strategy to go become the leader in content management. And here you're all this time later with $5 billion revenue and leader in content management. So Tom to kick things off. Where are we talking to you as sort of a CEO today -- what would be the change? Was it a question of different skill set required for the next stage of growth. Was it a question of you want a better execution? -- maybe provide the rationale.

There was no difference of opinion with management and the Board on the strategy. In fact, the company is following exactly the plan that was approved by the Board. No, it was more on pace on how quick to move on divesting some of the noncore assets. That's really what it was.

Okay. And in terms of who the Board is looking for the next CEO, what are some of the characteristics are you casting a very wide net .

Well, the search committee, I'm not on the search committee. The search committee is made up of brand-new Board members because we want to take a fresh approach. And so the head of Search Committee is the former VP of HR or CHRO of Hewlett Packard, Kristen Ludgate. She just retired from HP and Cupertino a couple of months ago and also Bob Hau, who's the CFO of Fiserv; and Goldy Hyder, who's the CEO of business council in Canada. So really well-connected group. They'll run off and do that. I think their bias -- just like any other CEO changes, you tend to move your pendulum. After me, I'm an architectural engineer, we got John Shackleton, who is a solutions engineer, Mark another architectural engineer, I think you'll see their bias to go to someone that's a solutions engineering background simply because of product life cycles. Mark just refreshed with Aviator the entire product line of Open Text. So I think they'll probably look for someone to go sell it.

Great. So yesterday, you provided some new segmented disclosure outlining the revenue breakdown and cloud breakdown fruits of remain product pillars. So let's talk about that. So one of my key takeaways was the content business, which 40% of revenue, growing at 4% last year, 17% cloud growth. Let's drill into that? What's driving that 17% cloud growth? And how sustainable is that? .

Well, first off, we did the segment analysis, Chadwick, our CFO that had go back to EQ Bank after what happened with Andrew Moore. We had promised that we would do the segment analysis so that you could have a road map to see where we were going and how we're going to shape the portfolio. So -- you now have the data that we have. So at the Board, this is our data reviewed by the auditors, et cetera. And we try to get it to you as quickly as possible so that you can follow along as we go to remove some of the noncore assets. Now content, as you're asking, and the growth of it, it's really part of how we see going forward with the company. In a word, content is a very important part of training Agentic AI. That's really when we started on this journey many years ago, it wasn't called Agentic AI. It was more like predictive analytics and [ basic ] mathematics and things like that, and you needed content to be able to train -- and so you'll see content server, and that whole business unit play a core role. But that's not the core of the company in and of itself. There's actually 3 kinds of content that you use to train on AI. There's human-generated content, which is content server. But in the last decade, machine-generated content is enormous and quite frankly, dominates the content that we're creating in the world today. And that's something called ITOM, which is IT Operations Management. One aspect of ITOM is actually machine -- think of a nanosecond trader. That creates log files. Those log files become really important for training predictive analytics. The third group that's really important in all this data is business networks. And that's because it's the information traded between organizations. So that Business Networks division is very important to training Agentic AI. So you basically have 3. You have content. You have ITOM and you have business networks. And then you need to wrap it in security because all of that data has to be secure. It has to be secure at the edge, and it's got to be secure at the server. And that was the reason why we bought Micro Focus and the HP software catalog because they had all those -- the problem with something like an HP, it had not only all the pieces we wanted, but things that you would sell to Best Buy or to Mom & Dad, that kind of thing. And so those are the pieces in the retail part that didn't make sense to fit. There's nothing wrong with those business units. They're just not core to what we want to do going forward. So really, when you think of it, it's not just content server, it's those other units. I think maybe the way to think about content server and the growth is it grew that much despite the fact that the management team was distracted by 6 different business units. They have one thing to do then perhaps that will grow faster. But that's hard to say we'll wait for the new management team to talk about what they believe. But certainly, double-digit growth in the cloud, which is the core part of this thesis going forward speaks for itself. And that's why we wanted to do the segment analysis. So you could all see what we're aiming towards and follow us as we do it as we judge us by how we create those business unit divestiture and track us. The strategy committee that got announced at the same time as all this other stuff is made up of, again, veteran members of the Board, no management because we don't -- management's provide the information, but this is a capital asset allocation. And so the Board is going to do it. And we're lucky enough to have folks like Annette Rippert, who is the Managing Director just retired of Accenture out of Washington in Telco and Tech, folks like Fletcher Previn, who's the CIO of Cisco and prior to that was CIO of IBM. So we've got lots of real veteran people to do this. So measure our progress. And we've estimated -- it's somewhere between $0.75 and $1 billion out of the $5.25. So you'll see us take 15% or 20% -- and that's consumer products, things like developer toolkits and what have you. There's actually about 30 or 40 different product lines within those business units, but that's what you'll watch us to over this next -- it will probably be on a quarter because when you divest things, it takes a bit of time to be able to separate out. So that's what you'll see over the next 3, 4 quarters.

So in terms of the segmented disclosure you provided yesterday, should we think of it as being the SMB cybersecurity and the DevOps businesses going away in their entirety? Or might the pieces of it that you end...

Yes. The double is in the details on that because some of the edge security, we want for the corporations that we sell to. So -- there is a bit of double in the details with that. But I'm trying to just generally give you an idea of where this will end up. But you're right. You're right, what you're saying.

And going back to the strong growth in content cloud, is that early signs of AI traction? Were there other factors like the SAP upgrade cycle kind of pulling you along? Or anything specific that you would point to? .

Well, you have to think of it, all of you, I'm sure, like I follow this in the media and all that stuff, you have to think of AI as 3 different buckets. So follow me, if you will, for a second. -- the AI that burst onto the scene is really generative AI, and it's the stuff that takes about 1 billion parameters and it's called a large language model -- and it captured everybody's imagination because it could do natural language. I can tell you back in the day when we were talking about search engines, we tried so hard to let people ask a question. But we didn't have the mathematics in the compute power to do what is called a complex bullion. So that's why all of you, as you use Open Text or Google or AltaVista, you could only put one word in -- so the great thing about what you saw with Chat GPT and perplexity is that you could talk to it in human language. That was the amazing thing about that. But if you think of the other pieces of AI, the media talks a lot about something called frontier models. That's about 1 trillion parameters. And that's what's coming and that's sort of the science fiction thing, where it's both utopian and dystopian. We're not involved in that. That's going to be something that nation states do. On the opposite end, with only, let's call it, 1 million parameters, so way less than what you're seeing in the public space is Agentic AI, where you're creating agents. That's where all the productivity gains are going to be for corporations like General Motors or Coca-Cola, Abema, et cetera. That's the sweet spot that we're focusing on. So now if you segment AI into those 3 pieces, we're trying to do the stuff that you're training, Oh, say, your Marriott hotels and you want a Chatbot to refer to a convention that wants a quote on rooms in a city sometime next year. Well, they need all the information internal to their organization about rack rate, occupancy and things like that. To do that, maybe the best way to think of this and why content server matters so much, you as a CIO and as a practitioner to train that bot, think of your host -- you have to go up to the attic and pull out a photo album before digital. And you've got a photo album of photos and what have you, and you've got to scan them in and you have to put that as part of your overall training content or you have hand-written letters that you've got to do Opto character recognition with or God forbid, you go to your basement and you got your old PC, and it's got word perfect in it or VisiCalc -- and if you're under 40 years old, you have no idea what that is. And yet if you're Pfizer, or your Boeing, those are the documents that have some of the critical information about a Boeing 787. And so if you're a CIO, you've got to go get all this stuff. And then you have to put it into a modern server and you've got to make that server so that it can be made available to dozens of large language models that you're going to be using. So what I'm trying to give you a peek under the covers of all this, there's a lot of stuff that's going to happen. And all these large language models -- they didn't exist in their current form 3 years ago or 5 years ago. So everything I've just described to you is what Open Text built in the last 2 years is called Aviator, and it does multi-cloud, so you may want it inside your firewall or you may want it up on a hyperscaler or you may want us to manage it as a private cloud. We have to be ready for all of that. And you may want [ Entropic ] as your model or you may want [ Coherus ] as your model. It depends on which model you believe is best for your industry. And then finally, you may want it for an ERP application or a CRM application. So if I'm giving you a headache, that's the headache that we've had facing us over the last 2 years, and that's why you saw our R&D budget go up so much. We're done. We've built it all. It's multimodal, it's multi-cloud and it's multi-app and it's called Aviator, and that's where we're going to go sell. So we've built it all. And that's what content server is sort of the the first indicator of.

So, let's talk about the go-to-market. So I hear you that you have the technology ready to go. But when you're trying to get the attention of the CIO and there are a bunch of other vendors who are also making the case that they are the ones to go to for AI. How do you get that mind share? How do you feel about the go-to-market motion today and how it can be improved?

It's the reverse right now. We don't have enough people to service the demand that we have. I think you'll see us start making tuck-under acquisitions for some of the verticals so that we can service the demand. Quite frankly, this is the kind of thing where it's not just Open Text, the whole industry. We don't have enough people that are articulate in all those things that I've just said to you. So actually, it's can we keep up to the demand. That's the reverse problem. Now how long will that last? Who knows? But the reality is right at this moment, every organization in the world is paying attention to this because if they don't, they'll be out of business. So this whole idea of AI first. You've seen the tech companies do it primarily first Open Text has got its margins up quite nicely by doing this. So I think you'll see all the CIOs of all the organizations have to do this, and our challenge is to keep up to it.

Another takeaway from the disclosure yesterday was that the analytics and ITOM businesses had double-digit decline last year. what would be your outlook for those and the plan to stabilize them?

Yes. On top of all the other things going on with OpenText, whether it's the extra R&D bump that we had to do. With Micro Focus the Board, the management, we all thought it would take a year to integrate it because we've been doing it for 30 years, and we've done well over 350 different acquisitions and mergers. Well, guess what? When you buy Hewlett Packard and it's $3 billion, and it's got 6 different business units, it doesn't take 1 year, it takes 2 years. And we didn't know that at the time. I think we obviously know it now. And what you saw in that second year was 2-year maintenance contracts. Sometimes they're firing us, sometimes we're firing them because we wanted to get rid of poor margin business. So it's a little bit of a mix of that still. You'll have a much clearer view this year, where you'll see them, you won't see big declines like that, but you'll see single-digit growth and single-digit decline. And the other thing people have asked me, by the way, is generally, the margins are all the same. When we sold the AMC unit, that was unique because it was a mainframe unit. But actually, most of the business units that we disclosed yesterday, we're trying to get the margin information to you as well, but that's harder, because you have to do allocations and the auditors and the audit committee have to go through it. It causes here, and he was saying to me earlier this morning, they'll try and do it by the end of the quarter, but -- that's a hard one for them because they have to unpick. It's like putting Humpty Dumpty back together. They have to unpick a lot of things to be able to attribute margins to each -- but generally speaking, the way you might think of the margins is we're about 35% and plus or minus 5% depending on the unit. Some of the units and Cos has this in a lot of his analysis where we do a lot of managed services, they're lower. And some of the ones that are SaaS, which are very high margin, they're higher from the 35% and -- but generally, if you were to think about 90% of the business, it's within a ripple of 35%. And what we will do like we did with the divestiture with AMC, we will always return to norm. We'll always manage the business. And the reason why you might see a quarter or 2 of deviation is that, say you sell a business and you've got 6,000 developers and 2,000 developers are going to the divestiture, you still have the building. And so you have to manage through either moving people or cutting the building down. So there's a little bit of of variation there. But I think, generally, you might think of it as a 35% business and should be about mid-single digit once we get down to the core, which is what you're seeing with content server. Content Server is sort of a good proxy of what is our North Star.

I'll pause any questions from the audience? I'm sorry. .

What are the TAM of aviators?

That's interesting. We were talking earlier. The TAM of the Aviator is actually going to be quite modest. -- because it's not where we'll make the money. And the same thing happened to us with search engines. We used to think that we would sell search engine. Search engine became an enabler. Aviator is really an enabler that connects a large language model to our content server. And so what happens is what we're experiencing is there's 2 ways we make money. When you're up in your attic and you're bringing down word perfect off of a hard drive or a [ mag tape ] or whatever, first, you have to convert it. So we're getting a lot of conversion sales. And then you got to reload it onto a content server because usually, when you have an archive, you don't pay anything for it because you just put it on a brick or a [indiscernible] and you leave it. So actually Aviator is selling -- and I think you'll see from Aviator tens of millions of dollars, but it will unlock hundreds of millions of dollars with content server business networks, et cetera. So it's a bit counterintuitive. You have to have it, though. You have to -- it's like an API, but you have to have it.

Tom, on the divestitures, so I know that the process is being spearheaded by the Board, but divesting the business obviously messy process. And so how do you ensure that doesn't become a distraction for the management team just operationally over the next year as you carve out those assets?

Well, actually, the -- the management team is actually a management team that's really oriented to selling to the CIO of General Motors. They're not a management team oriented to doing dealer networks within Best Buy and attach onto a laptop. So it's actually -- those units are good units. They're just being ignored, because it's not where the management team really has its expertise. So I think you'll find that those units won't grow, they won't decline, they'll just stay as they are. And our initial indication is a lot of interest because there's nothing wrong with these business units. They just don't fit with what we're trying to do. So there's actually quite a lot of interest for them since we made the announcement.

But I mean, just all the G&A heavy lifting that needs to be done to kind of split them off. I mean, are there ever teams matching that?

I was talking to Cos about that, so you can ask Cos about that he gets all the hard questions. Don't ask me the hard question. But Cos just went through this with AMC when they sold a mainframe unit, they know how to do it. But one of the reasons why you'll see us do this over many quarters, we could sell all those units in one quarter. the dilemma is as you're getting at, you have to do that facilities rationalization and it's better to do one business unit a quarter over the next 2, 3 quarters. it comes out to be roughly, we think, 2 or 3 business units. And so you should think of us as doing this every quarter you should expect a drumbeat from us of every quarter doing another unit. .

Any other questions from the audience? So Tom, going back to margins. Why is 35% of the rate margin? If you have this big opportunity, you can be doing 30% margins, which is still be amazing. Maybe drive some incremental growth. .

It's an interesting question for the industry, not just for Open Text. I think many of you in the investment community with AI first should be demanding that all the tech companies do more. I think Rule of 40 should be replaced with -- I mean the management team at Open Text won't be happy. But I think all of you should be demanding that with AI and the increased efficiency you should see something better than the Rule of 40. What will it end up being in terms of the growth in the EBITDA? I can tell you with AI, we're reducing everyone from developers to RFP responses to legal. A lot of this is -- and you're going to see that filter its way through society, whether you're Marriott hotels or your Bank of Montreal, you're going to see that. Where it ends, I don't know, but it will be more. I just -- I don't have a good enough feel yet. Do we -- Rule of 40 has been around for a long time. And will we go to a Rule of 50, probably. But how soon will we get there? I don't know.

Almost out of time, maybe one last 1 I'll squeeze in is, does it still make sense for you to own your own data centers, just CapEx intensive. -- a lot of other opacities.

That's a great question. Do you know if you had asked me that 3 years ago, I would have said, no, we're [ mothballing ] or reducing our data center footprint. But all you have to do is look at what New York Times is suing OpenAI and Microsoft and they're suing them because I suppose they're worried that tomorrow morning's New York Times could be written by the bot better than their editorial team. And that's not a slide on the New York Times. That's the reality of what's going on with the Agentic AI. These bots that we're deploying for customer support are better than our 30-year best employee like this is why this will be adopted at such a fast rate. So if you then think about that and you think about Marriott, et cetera, if you're a CIO and you're talking to your CEO, do you necessarily want to have the crown jewels that go to the rack rate or the occupancy, do you want that up in a hyperscaler. I think we're starting to hear -- and one of the reasons why you're seeing our license revenue which we thought was going to go to 0, may not. I think we may be moving into a world of hybrid. And that's why I had said before Aviator was going to be a multi-cloud where it's on-prem, all the way to hyperscaler because stuff like your website, which is public, you don't really care if it's in a hyperscaler. But some of these things that are proprietary that are inside your firewall you may want in a managed data center. So we're sort of watching this unfold and we have to be driven by the customer. But right now, Aviator is built on a hybrid approach where if you want to stay on-prem, if you want us to manage it in our data center or if you want to take it to a hyperscaler, we give you the choice. So we're trying to be led by the customer.

We're on time. Any parting words Tom.

No, thanks for your interest, and I hope we make this an easier story to follow. .

Thanks, Tom. .