Dynatrace, Inc. (DT) Earnings Call Transcript & Summary

A warm welcome to day 1 of Goldman Sachs Communacopia + Technology Conference 2024. It's a pleasure to have Dynatrace join us. Rick and Jim, it's a third year in a row, right?

Indeed, yes.

Absolutely.

Yes. So welcome back again. Thank you so much for continuing to -- thank you, Noelle, as well, for making this all happen. It's a very complicated logistics exercise here.

So Jim, let me -- maybe I'll start off with you, Rick. What's your vision for the company? I know this is a question that we keep asking you. And every year, certain things happened in the last 12 months that caused you to adapt the vision where you want to be, the goals, et cetera. So if you were to come back here 5 years, from now, 2029, what will have been the goals of the company? And how do you expect to materialize? And by the way, I think it's your fifth year anniversary since the IPO a couple of months back.

That's true. Yes, August 1.

So now since you've done in 5 years, what does the next 5 years look like? Where do you want the company to be in 5 years?

Well, the vision of the company hasn't changed in some time in that our vision is to ensure that software works perfectly for our customers. And this really does drive us every day. It's this notion that is end users, we expect every mobile app, every web transfer of financial funds, every commerce purchase to work perfectly. And when it doesn't, we get frustrated. We look no further than some of the outages that we've seen over the last several months to realize that we are all subject to challenge when software doesn't work quite the way you want it to. And observability is really a key antidote to that to allow software to work better, and that's indeed what we're focused on. Now beyond that, as you look at what do I want to see from Dynatrace over this period, which I think is really what you're getting at beyond just the vision, I would say several things. Number one, a market-leading share in observability. I think that our platform justifies this, and this is what we seek to deliver. A second is a sense of mission criticality from our customers. I love it when CIOs, CXOs, CTOs, whomever tell me, Rick, Dynatrace is indispensable. We couldn't operate without you. And I hear this frequently. So this notion that you really are indeed mission-critical to their results. We'd like to see reaccelerating growth in our business, which as observability becomes more and more mandatory, we see as quite possible. And perhaps lastly, we want to see ongoing increases in visibility of the Dynatrace brand sort of moving from a well-kept secret and how do you spell it to one in which Dynatrace got it. I must have Dynatrace to make my software work as well as it can be -- as well as it can work and as well as it should work. Those are some of the characteristics I would...

The only thing I'd add with all of that, if we can execute against that, we would deliver tremendous shareholder value over 5 years.

Yes.

You said reaccelerating. That's something that gets my attention as I'm sure gets your attention as well. We'll dig into that a little bit more. At a high level, Rick, you talk to customers a lot. What are you hearing with respect to tone of '25 budgets, priorities? And secondly, what kind of impact does GenAI have on customer budgets?

Well, I would say that generally, it depends on the industry and the feedback that I get from customers is mixed in calendar '25. It's a bit of an unknown. And I think the economic environment will help dictate some of the outcome of that. What we can control more of than what happens in the macro environment or broad-based spend or even GenAI budgetary allocation is what is the spend in observability. And this is where for all the reasons I indicated at the outset, I think observability is becoming more and more mission-critical. I mean you look at, again, some of the outage scenarios, some of the losses that occurred to companies who experienced those outages in a material way and observability can help address some of those issues. So I'd like to think that irrespective of what the budgetary broad-based macro outcome is and what the specific secular by secular spend might be in terms of that environment that the spend opportunity in observability can indeed still accelerate in almost any broad-based macro scenario.

Bringing up the disruptions that were caused by the outage. What was the experience of Dynatrace customers? Do you think that could be a catalyst for greater awareness of Dynatrace?

Well, the -- in the CrowdStrike outage specifically, I would say that the first thing is that, that sort of outage could happen to any company presumably writing software. It's -- we're all subject to software issues. And that's what we're trying to address, not a single outage or a recurrence of that outage. It is rather the fact that outages occur and how do you best prepare for them. In the case of that particular outage back in July, we, as Dynatrace, just to be very clear, could not have prevented the outage. You were going to go to blue screen scenario in any case. But from health care to airlines, to commerce companies, the feedback that we got at Dynatrace says, you enabled us to get back up and running back online much more rapidly with more resilience than were we not to have had you. And that's in a scenario in which time is money, you want to be back up and running as quickly as you can. You need to know what order to bring your systems back up. You need to know how to then manage those systems for best execution and best outcomes. And perhaps more importantly, you need to know once you bring them back up, are they all running as expected in a way that occurred before the outage. And that's where we really contributed in a material way to our customers to be able to manage their overall IT ecosystems and their software environments.

Turning to you, Jim. [indiscernible] we're going to get a rate cut, maybe 50, closer to 50. Can you talk about the different ways in which Dynatrace can benefit if we are to get reduction in rates? How does the future play out in fiscal '25 in particular?

Yes. I mean, obviously, I'm not an economist. But...

No, the economist already said it. They already made a prediction.

I was an economist, I'm not sure I could answer that. I'm not sure that really helps you.

I mean, I guess I would say at the highest level, that would be good. I don't honestly believe that it is a constraint today in people's spend patterns. So I don't think it's a huge constraint one way or the other. So it isn't as if, oh, there's going to be a rate cut now. I'm going to see significant calendar '25 spend increase. I do think it does create a signal that the Fed believes that the economy is on the right path. I think it sends a lot of the positive signals around the quality and strength of the economy. And when you have that, that brings more confidence to businesses. I think more confidence to businesses means that, okay, maybe investment is appropriate. So I think it's going to be a net positive. But like I said, I don't think it's necessarily something that is constraining what people are doing right now.

I have a semi real-time update for you. I asked the same question of another CFO, Michael Gordon of MongoDB. He said the same thing that it definitely cannot be a negative. It has to be an incremental...

Right. Yes.

Glad we all have some resolution. After 3 years, it's been just so maddening, right? I mean the industry in '21, the average growth rate of the companies that I covered was 33%, 34%. Today, it's 10%, 11%. You guys are doing better than that through acquisitions?

Yes.

Certainly, we all are looking forward to better days.

Yes, we are.

Rick, back to you. Let's talk about AI. We cannot have a conversation without AI. You have 3 different approaches to AI. Maybe it's not different, but 3 approaches to AI, predictive, casual. Is it causal or causal?

Causal, not casual. Yes. We don't do casual AI.

It sounds like I did not get this right. So casual thing -- I've started in industrial engineering. So I know that it's got to be causal, generative AI. What are the different value propositions that each of these approaches offer?

So indeed, Kash, one of the biggest differentiators of Dynatrace is our -- what we refer to as power of 3 AI. And power of 3 AI includes not one, just generative AI, but in fact, 3 AI techniques, the ones you described. Causal AI is oriented to root cause analysis. So it enables you to find issues and resolve them rapidly. Predictive AI is oriented to anticipating issues and reducing incidents as a result of it. So eliminate the incident before it occurs, so you don't have to fix it fast that make it go away before it occurred. And then generative AI is oriented to natural language interface as we've sort of all discovered in generative AI to interact with the other 2 AI techniques to bring the power of the Dynatrace platform to a much broader array of end users. If you put all 3 together, you have an incredibly powerful platform. And our message related to these 3 AI techniques is that generative AI is, in any case, only as good as the underlying data store. If the underlying data store is faulty, the generative AI result may be a perfectly crafted lovely solution that is completely erroneous. In our industry and observability, it may tell you that there's an answer where there was correlation but not causation, for example. So the causal AI and the predictive AI techniques give you, by contrast, a deterministic answer. And the deterministic answer is based on the underlying data taken together in aggregation and in context to evaluate precisely what's happening in your ecosystem and how to get it resolved. And then generative AI just provides an interface, a natural language interface into that deterministic outcome. So it radically increases the probability of success of that interaction. It is the case that at Dynatrace, predictive AI, causal AI have existed in our platform for more than a decade. So this isn't something that we made up a year or 2 ago when generative AI really started to evolve...

Because of GenAI, I mean, is your core AI benefiting more because of the interest in GenAI?

Yes, I think so because there's more knowledge around AI and the benefits of it, so when we go talk about it. But I think that the generative AI is being munged together with all forms of AI with the assumption that they're all the same. And our message is that, no, they're not all the same. And it is the causal and predictive AI techniques that really lead to answers as to where the issues are in your platform. And that enables you to move from a red, yellow, green dashboard of, oh, there's a problem to instead, yes, there's a problem, here's precisely where the issue is, and here's how to resolve it to radically reduce incidents and improve your mean time to repair where you see incidents occurring.

Got it. So a year into generative AI, year plus, what are the lessons learned? And how are you crafting your product and go-to-market strategy differently to take advantage of it?

Well, there's obviously a ton of hype, Kash, around generative AI. And I think the vast majority of companies are still looking for the diamond in the rough, so to speak, how do I really take substantial advantage of this. Our perspective is that generative AI in our case, brings, as I said, the Dynatrace platform to a much broader array of end users, and that has enormous value because whether you are a developer, whether you're in operations, whether you're a subject matter expert, you're in site reliable engineering, the platform will bring advantage to you and generative AI is a much simpler interface than writing scripts. I actually think it extends the productivity as generative AI typically does, and it extends the value of the platform to more users.

Got it. Maybe Jim, you can weigh in on this as well. Internally, have you deployed generative AI technology? What kind of benefits are you seeing?

You're talking about within Dynatrace?

Within Dynatrace.

So it's interesting that you bring that up that we are a bit of a microcosm of the companies that are leveraging it. And I would say the first thing that you have to -- every company, I think, especially enterprise-oriented companies, which is where our target customer base is, is you have to have good governance around it. So we actually have a whole governance council to ensure we're actually going to consider introducing a tool that has GenAI attributes that we know how it's being used. We know the data sources. We know is there specific Dynatrace data that's going to be used to help maybe train that AI tool for other customers. And so the way I view GenAI is that we're in the experimental phase. And I think a lot of companies in the experimental -- I think it has tremendous promise. I think it's going to lead to a boost in productivity in a lot of different areas. I know for Dynatrace, we're still really early days in it, but I don't think that's unique. I think many companies are cautious but optimistic about what it can do. I think it can and should improve developer productivity. It can and should produce -- improved productivity in general for a lot of attributes, even within the financial and operating accounting functions. Things that today are done by humans that you could automate and do in a much better way with GenAI. So I still think it's early days. I do think that enterprise-oriented companies are very cautious to make sure that they're doing it in a cautious way and in a planful way.

So you have seen some early proof points internally with the productivity and finance and accounting function, et cetera...

Interestingly enough, someone was telling me that there's actually -- I think it was Noelle, our IR leader, that there's actually technology that could write an earnings report with GenAI. So we haven't done that yet.

Yes, we heard about it...

And no, we haven't used it for that, just for the record.

If you could generate an earnings script draft or something you can look at it and say, yes, it's kind of 30% of the way reported earnings for free cash flow. You don't need to write that, but then come back and change it, learn from that again. Yes, but we would not subject our intelligent clients to generative AI reports. We are -- we will not do that. I know some people have tried that, but we put some original thought to analyzing Dynatrace learning. The great Matt Martino will acknowledge painfully. So what are those 3 takeaways that are -- what are you surprised by? The next thing I want to touch upon is after we talked about the GenAI internal climate. The observability space is less fragmented than before, but you've talked about tool sprawl and cloud native centers, et cetera. In your mind, what gives you the right to win in this space against a landscape that is somewhat less fragmented, but still fragmented. There's a lot of intention to be the provider of choice. Why do you win?

Yes. I think we would often say, Kash, it's 3 differentiators, 3 primary differentiators. The first is contextual analytics. And this is based on a common single underlying data store for all observability data types, which we call Grail. And by capturing traces, routes, logs, et cetera, all in one data store in context, behavioral analytics, real user data, et cetera, we have incredible visibility into the data and in terms of what that data means in context. And it is incredibly powerful and extremely unique in our industry. The vast majority of our competitors would have multiple different data stores that they have to manually tag to bridge together to develop insights, and that is a much more complicated thing to do at scale.

Will you mention who those are?

You name them. I mean nobody really in our...

Your strength is the unified architecture...

Exactly. Nobody really maintains a single integrated data store in our market. And even imagine the number of customers that use a multitude of different tools. So you talk about tools for all, tool consolidation, fragmentation. We had this case of an airline that we talked about 3 or 4 months ago who was using 10 different tools. By definition, if they're using 10 different tools, there's no common underlying data store. They can't be. Because they're using different architectures from each tool source. And they may be using one for applications and one for infrastructure or one for end user experience, et cetera, and it's very fractured. So common data score, common reference architecture is invaluable. Second is, and we talked about it at length, so I won't rehash it, but AI. We're -- many of our competitors will talk about generative AI, but nobody has predictive AI and causal AI. And those AI techniques are what lead you to the deterministic outcome. The answer is not just dashboards or data. And then third and finally, it's really around automation, which is that given the explosion of data and the massive increase in complexity that companies are trying to manage against, it's impossible to do AI operations or even to navigate software environments the way you used to. I walked into a network operations center of a large oil and gas company with the principal that I was meeting with there. And I looked at a network operations center that had more than 100 people, well more than 100 screens on the wall. And his answer was, Rick, Dynatrace needs to help me get rid of this. And it was indelible in the sense that it's becoming unmanageable. And generative AI is actually making the problem even worse because it's accelerating the route to production of more applications. And so the problem is getting worse, not better amidst move to a cloud, generative AI, more applications, more data, more complexity, harder to manage manually, you must automate that outcome. So contextual analytics, AI and automation really are why Dynatrace wins.

So Jim, to bring you back in the picture, I know that you're very involved on the go-to-market side, although you don't run things. But as a CFO, you have oversight into all the big changes. Can you talk a little bit about the -- why you made the go-to-market changes? And Rick, if you feel need to jump in, please join the discussion. A bit of detail behind why you did it and what exactly were you hoping to accomplish with the GTM changes? And how would you rate your satisfaction at this point?

It's a great question. So I would say the first word I'd use is the changes we're making are very offensive oriented. So sometimes you can make changes to be defensive. This is a very offensive-oriented change that we -- our CRO has been in the company now a little over a year. And so in his evaluation of our go-to-market model, he very much believed in the target market of very large complex environments. So this notion of targeting the Global 15,000 made a lot of sense, very large, complex hybrid environments. But when he looked at our resources and he looked at how our resources were covering the market opportunity, not all customers are created equal. And so the Global 500, so think of the top of the pyramid, of the Global 15,000, the TAM and propensity to spend is significantly weighted to that top of the pyramid. And he looked at the resources that we had there, and we had many accounts per rep. And he knew that deeply that we -- the model was kind of not correct that you really needed to reduce the number of accounts per rep to be able to get the penetration and traction that you wanted. And so one of the big changes we made was around customer segmentation. So there was a customer segmentation change where we -- in the top of the pyramid, Global 500 accounts -- we moved from 8 to 10 accounts per rep to 4 to 5. And the whole premise of it being to get much more intimate with our biggest customers to have a better understanding of their environments to be able to go deeper with them. That could be penetrating a new logo that we didn't have today and more specifically for a customer that we did have being able to go deeper with them. So very much weighted. So some of that was adding new capacity and some of that was repurposing reps that were maybe covering, for lack of a better term, the enterprise space below that. So that was a customer segmentation was one component of it. Investors have asked, "Oh, so you're whale hunting now, you're seeding the market below the Global 500." No. This is just a reweighting of some resource there, so we have more capacity to cover that opportunity. We're still going after the Global 15,000. So that was one change. The other change is we had talked about in the back half of last year, we were seeing this emerging trend of growing tool consolidation deals. And some of our pipeline was getting weighted towards them. We didn't -- we needed to evolve our sales plays. And so the sales play for Dynatrace has historically been a very successful land and expand, find an application owner, do a POC, land and then expand from there. And that has served the company well. We now have 3 sales plays. So you have customer segmentation and then 3 sales plays, still the same tried and true land and expand with application performance. There is now an end-to-end observability sales play. There is now a third sales play around cloud modernization, which is companies that are thinking about digital transformation initiatives and things of that nature. And so we've built more enablement and sophistication into the sales plays so that you have better segmentation, more focused sales plays with enablement around that. And then the third area being much deeper focus on partners. So the model with partners was -- I don't want to say one size fits all, but there was an element of that. But the way you manage with the GSI and the way you work with a hyperscaler and the way you work with a regional channel partner is different. And so we have a new channel leader, and there is a much better segmentation of our partner strategy now, teaming agreements to know how partners play in a particular deal. And so what I would say in aggregate between customer segmentation, sales plays, enablement and partners is it is a much more sophisticated go-to-market model that we're moving to. And so we feel really good about it. So -- and the whole point of making these changes is to reaccelerate growth for the company, both in new logos and in expansion. So the opportunity is there. We just needed to tune the model a little bit.

You were leaving money on the table. By the way, that was great. Are you sure you're just the CFO. You spoke like a COO, CFO, I mean...

Yes. I mean...

Wearing the hat of a CRO and...

He's good that long, don't you think?

Yes, that's great. That's great. Love that. So as a result, are you seeing that manifest in the quality of the pipeline, the quantity of the pipeline? How is that process bearing fruit?

It's a great question. I'd say it is still a little early. The changes we made were in the beginning of our fiscal year, which would have been in April. By the time you moved accounts, it was May. So I'd say we're still in the early stages of it. But what I would say, Kash, is that the first quarter was a very solid quarter for Dynatrace. And so there was a risk that these changes cause freezing. And the sales organization is what are we changing and they pause. And we didn't see that. So the good news is there was no disruption. We managed through it quite well. I'd say the benefit of it, Kash, around have we now seen an expansion in the pipeline, I'd say it's starting. It's starting, and that was what we expected. So the manifestation of the productivity improvements are expected in the back half of the year. So that's the thesis. The thesis is we have 6- to 9-month sales cycles. These changes will take a while to settle in. We'll be in a much better position. I will say that the other thing that I didn't mention is on the sales leadership side, I feel really good about, one, the CRO; and two, the sales leaders that he's brought in. So I think he's brought in sales leaders that have kind of been there, done that. They've seen scale. And so it's still early days, but I'd say I'm cautiously optimistic that we're on the right path.

Thank you, Rick. Just on that very topic. You talked about hiring several individuals with a lot of experience scaling go-to-market functions at several companies. So can you talk a little bit about what these individuals could do for Dynatrace that you couldn't do before?

Well, what I've learned through a few times through in taking organizations from $1 billion to $5 billion is what gets you.

Can you just give long-term guidance?

Yes. No, no. I'm not giving long-term guidance. From prior experience, Kash, the skill set required to get you to $1 billion is often different than the skill set that gets you from $1 billion to $5 billion. I mean you need to be able to really deliver material scale. And the people we had in the organization a few years ago did an unbelievable job getting Dynatrace to $1 billion unquestionably. But figuring out partners and go-to-market pricing evolution and so many other elements to get you to $3 billion-plus or $3 billion, $4 billion, $5 billion is a different skill set. And we've now made many of the changes to put people in roles who have done that before. Dan Zugelder, our CRO; Laura Heisman, our CMO; our partner leader, Jay Snyder. I mean these are all people who have had that experience before. I am absolutely thrilled with each of them in the role, thrilled with their initial months. And Dan had been there for just over a year, but very, very enthusiastic and excited about the people we have in place.

You're happy that the team finally coming.

Absolutely. Yes. Our leadership team is incredibly strong.

You know it. You feel it when the team is coming in...

Yes, I just -- I couldn't be more excited about the leadership team that we have in place today.

That's great. I realize this has gone so smoothly that we have only 3 minutes left. Anybody wants to jump in with a question? Who wants to be a prompt engineer? Mike, go ahead, please. Mike, you don't need a mic.

First of all, thank you for your time. And secondly, [ if you do see upside plays out in the business this year, where are you likely to see ] [indiscernible]?

If the upside plays out, where are you likely to see it, if I could paraphrase the question.

Yes. I would say where we're likely to see it is in more expansion. I do believe that. I think you'll see it in more expansion. I think you'll see it in NRR. I think that's the likely area that -- and the reason is twofold. One, I think these changes are geared towards getting deeper with customers. Two, we have a higher weighting of our business that's up for renewal in the back half of the year, and you tend to see expansions in and around a renewal. So I'd say the area that would surprise to the upside would be on the expansion side.

I would just add to that, that I do believe that the log management space is ripe for disruption. And I absolutely believe over the coming, not 1 to 2 quarters, but let's say, 4 to 6 quarters, that could absolutely represent an acceleration opportunity.

San Francisco-based company that got acquired by the San Jose-based company you're talking about the...

Possibly. I mean it does create a disruption in the industry without exception.

Got it. Any other questions? So -- Why don't we just wrap it up with -- since we have a minute. What is it about the Dynatrace story is not that well understood, even though you spent 5 years as a public company, there's always some area that if you feel like this is something that people are not getting, including this -- look, Kash, he's not getting this thing. What are we not getting yet?

I think the element of Dynatrace that is most misunderstood is Dynatrace is on-prem and other vendors.

[indiscernible], right?

Other vendors do cloud, and that just couldn't be more inaccurate. Today, the vast majority of new logos are SaaS. They're cloud-based. A majority of revenue is SaaS, and that's where most of the investment is going in our technology and innovation. So it's -- we actually like the fact that we are a hybrid and have a hybrid solution that can satisfy the largest organizations on the planet, both on-prem and in the cloud. And we see that as an advantage, not a disadvantage.

Mongo talked about the same thing as well. They have something called Enterprise Advanced and then they have the Atlas. And they're like this thing is actually doing quite well for [indiscernible], right?

Yes. It's a huge amount of revenue, and it's a substantial opportunity.

Well, on that note, thank you once again.

Thank you very much.

This is third year in a row.

Thanks for having us.

Thank you, all.

Thank you for your questions as well. Thank you so much. Have a lovely day, and continue to have fun and learn.