Welcome everyone today. Just to kick things off, my name is Jake Roberge. I'm the research analyst at William Blair, that covers Dynatrace. And just for a full list of research disclosures, please visit our website at williamblair.com. But with that, I'd like to introduce Rick McConnell, CEO of Dynatrace. Thank you for joining us today. My pleasure, thanks. Good to be here, Jake. Yeah. I guess just to kick things off, maybe if you could level set with people that may be newer to the story. Maybe talk about just a quick overview of the business, the markets that you're addressing within observability, and just start with a high-level overview of the story. Sure. So, Dynatrace is in the business of assisting companies make their software work perfectly. That's sort of the starting point of the story. We do that by participating in what is about a $50 billion business or market for observability. And observability is really targeted around using data types like logs, traces, metrics, and these other elements to analyze software workflows and make them work better. So that's how we target and do what we do. It turns out that in a cloud world, it is harder, not easier, to make software work perfectly. So, what you have is an explosion of data, massive increase in its complexity, and these workloads are harder to make to make work better. So this is what we do. We analyze these workflows and these data types to deliver software that works fundamentally much better than it would otherwise. That's helpful. I guess just to also touch on some of the recent dynamics, you've talked a lot about kind of the increasing rate of adoption for these large platform deals, where companies are looking to consolidate a lot of observability workflows. So maybe talk about where the industry was before, and what's causing these platform consolidations, and then just what the move to these consolidated observability platforms does for you from a competitive positioning. Well, to start, virtually every application has some observability solution. It just happens to be the case that many of them were internally developed using open-source software or otherwise. And what's happened is, precisely as I said earlier, these workloads are getting harder and harder and harder to analyze and make work. So, imagine the case of a network operation center with 100 people staring at a sea of glass, trying to figure out what's broken, what's working, and then, how do I make it work better? And then something goes wrong, and your first question is: "Oh, my God, what broke?" And then you start triaging where it broke and how to fix it, and this turns out to be an increasingly difficult problem to solve. Now, observability software used to be deployed largely departmentally. So, an application team, an infrastructure team would deploy observability solutions, usually dashboards. Dashboard is a visual mechanism to see, is it red, yellow, or green? Is my software working? Is it not working? Is it sort of working? And in the event that it went red, then you would try to triage that and figure out where it broke and how to fix it. And in many cases, this could take minutes, hours, days, at times, to get your software working again. What Dynatrace does is we use AI, not just generative AI, but predictive and causal AI, that we've used for more than a decade, to automatically analyze workloads. In automatically analyzing the workloads, we can deliver not just a dashboard of red, yellow, green. We will tell you precisely where the issue is in your software to enable a rapid reduction of the number of incidents, but also in the amount of time it takes to repair an incident once it occurs. It is this automated mechanism that really differentiates Dynatrace in our market. That's helpful. And then, do you think platform consolidation is a theme that continues even as the macro improves, or do you think that's just the result of a tight kind of budgetary environment, where people are saying: "Hey, we need to eliminate the 10 or 15 different monitoring tools and go on to these broader observability platforms? I think it's a trend. Yeah. I mean, I think this, this isn't just something that's just happening occasionally or temporarily. I think it's durable. And the logic is that there are really three primary reasons for companies to look at sophisticated observability tools. One is around user experience. Software is down, users aren't having a very good experience, and you want to avoid that. Second one is productivity. If you have dozens of people sitting on a triage call, that means they're not innovating instead. And thirdly is around cost. If you have all of these different systems that you are trying to manually coalesce in a productive way to figure out what's going on in your systems, then not only does it not work very well, but it's very cumbersome and doesn't lead to a rapid outcome. So for these reasons, organizations are beginning to centralize the decision around observability rather than go with the departmental approach that they had before. By centralizing the decision, it speaks directly to this platform-type approach, where you want the best possible outcome. The best possible outcome comes from a completely integrated system that has one common data store, and that common data store brings together all of the observability data types into one data store that can be analyzed in unison using AI. And by doing so, you get to the best possible outcome in the most rapid time possible. And this is why the decision process at large organizations is beginning to converge, I would say, is continuing to converge to a more centralized structure, where it's the CIO, the CTO, CEO of some sort, is now beginning to make increasingly the observability decision. As they make that decision, that actually directly speaks to Dynatrace's strength in the market. Yeah, that, that makes a lot of sense. Then, you've been talking more about partners recently. How big of a role do GSIs or hyperscalers play in this moving forward, in terms of being able to generate more leads for the platform, really start to actually lead deals versus just partnering with you on deals when customers are looking to consolidate so many different observability workloads? Yeah, for now, we have more than two-thirds of our deals are influenced, as we say, by partners. We have partners involved in the deal. They are originating about 30% or so of them. So I would, I would love it to be the case that Accenture, Deloitte, Kyndryl, DXC, our primary GSI partners, actually originated more deals. But I'm actually pretty happy that they're involved in the deals in the first place, because they do tend to accelerate deal closure, and they also often can centralize the deal faster than we can, and they make it bigger. We, as last quarter, we reported in our earnings in May, that we closed a nine-digit TCV deal, five-year deal with Accenture, for example. This deal probably would have been broken into multiple parts, taken a lot longer to close, and been much more fragmented across geographies if we closed it directly versus closing it with Accenture. So this is an example of the leverage we get, we believe, out of GSIs in particular. That's helpful. Maybe just transitioning over to AI, because that's a big topic in software land these days. Really? Yes, just a little bit. I hadn't noticed. I hadn't noticed. Maybe, maybe if you could talk about kind of what you've historically done with Davis AI- Yeah. And how that's transitioning into the opportunity you're seeing with Hypermodal AI, how that's been supplemented with generative AI recently. Sure. I thought you were going to ask me how generative AI is sucking all the oxygen out of the software spend in the market or something like that, which I've gotten asked today several times as well. Our view of AI is that it isn't just generative AI. Generative AI is a productivity boost to be able to supplement any other techniques with natural language interface to broaden the user access of the Dynatrace platform, which is fantastic. Love that. It brings the Dynatrace platform from SREs, for example, who know how to write scripts in Dynatrace, to a much, much broader array of end users who can now query the Dynatrace platform using our CoPilot solution, which is generative AI. This is pretty new, launched in the last quarter or so. But we think of AI from a Dynatrace perspective as Hypermodal AI, and Hypermodal AI actually includes three different AI techniques: causal AI, predictive AI, and generative AI. In the case of causal and predictive AI, we've had those in the platform for well more than a decade. This is not new to Dynatrace. Causal AI is designed to address root cause analysis. Something goes wrong, what happened? Where did it broke? Gives you a very precise answer as to where it broke so that it can be fixed rapidly. Meeting with the CIO of a large Australian bank, and he said, "I'm using Dynatrace to move my mean time to repair incidents from hours to minutes to seconds. That's my strategy." And we use causal AI to do that. Predictive AI takes causal one more level forward, which is to analyze billions of workflows over the course of, or billions of data, data types associated with those workflows over the course of time, to anticipate where there's going to be an issue and then help remediate the issue in advance of it becoming an incident. So we had a case that we sometimes talk about with British Telecom, BT, where their expectation of using Dynatrace was to consolidate a whole bunch of other tools and to reduce incidents, the number of incidents, by 50%, and to reduce the meantime to repair the incidents that remained by 90%. Back to my earlier comments around productivity, cost, user experience. Imagine the benefits of user experience and productivity if you can actually reduce your incidents by 50% and the amount of time you spend working on incidents by 90%. This is a monumental advancement in reliability and automation of software. ... That's really helpful from a platform perspective. Maybe since you mentioned it in the lead-up to that last question about a lot of investors wondering if AI is sucking the air out of the room, maybe you could talk about- No, you can't ask the question. I asked it first. Maybe you could touch on that and just what- No, you're supposed to answer that. What, uh- I'm asking you. What you're hearing from customers and their spending priorities heading into the back half of this year. Yeah, I mean, I can't speak to it more generally. What I would say for Dynatrace is we haven't seen that sort of impact in our business at this juncture. Okay, that's helpful. And then in terms of expanding the market opportunity, I think the other interesting thing about generative AI is it's another large workload that's moving to the cloud that needs to be observed, monitored, secured. Yeah. How are you thinking about the opportunity, just from a workload perspective, that generative AI could present to you over time? It is a great question because on the one hand, we use AI to execute our business of observability. On the other hand, AI actually results in more workloads, and more workloads is more to observe. So the more applications there are, the more workloads there are, the more applications there are and infrastructure there is to then monitor and manage accordingly. So, from our standpoint, generative AI is a terrific thing from a number of different angles, but one of them indeed is an acceleration of workloads that need to be managed and overseen. That makes sense. And then maybe shifting, shifting gears over to the, the go-to-market motion. It's something you've been talking a little bit about. Maybe you could just talk through what's changing with the go-to-market motion. How disruptive is it? You've, you've talked about 30% of accounts being redistributed, so maybe just talk through a lot of those changes, and how you see them trending throughout the year. We had a new CRO, Dan Zugelder, begin about 10 months ago, and almost immediately, we began evaluating, okay, what do we wanna adjust in our go-to-market to really scale this business materially? And that's really what we're after. The good news is, Dan came from VMware. He is used to scale, and so we're thinking not just six months ahead, but a year ahead, two years ahead, three years ahead. How do you build a business that grows from where we are today at $1.5 billion or so of ARR to something substantially greater than that, given the market opportunity in front of us? Because we believe that a company of that magnitude is supportable by the market. And as we looked at it, our discovery was that the biggest opportunity is really at the top end of the market. This is where the TAM exists, primarily in our view. And so the result of that is that that's where we wanted to increase emphasis. Now, we have not fallen off the notion of the Global 15,000 as our target customer base, so it's certainly not the case. We have just simply eliminated all of our reps who were working at the middle part of the pyramid and moved them to the top end of the pyramid. But we have shifted some, and the result of that is this 30% notion of account switchover. What I would say about 30% account movement is that in a normal year, it's maybe 15%-20%. Okay. I wouldn't compare 0% to 30%. It's- It's maybe a little bit higher, but it's not radically higher. And, and furthermore, we discovered that the typical strategic account exec at the very top of the pyramid typically had 8 or 9 accounts, but he or she would make their number on 3 of them, or maybe 4 of them, and they wouldn't really get to the other ones at the level of detail we could. But for strategic accounts, virtually all these accounts are doing more than $1 million a year for us in ARR today, and the vast, vast majority of them are maybe, maybe 20% deployed. So, we view this as an enormous white space, and this is why we saw, it's one of the reasons we saw such momentum last quarter when we closed $18 million-plus deals in one quarter. It was a record, a record closure for the quarter. It included our first nine-digit TCV deal. It included our largest ever, roughly eight-digit ACV, new logo, a large airline, and then many, many other accounts as well. So, we believe that this sort of consolidation trend of platforms and observability, et cetera, are driving this sort of momentum and inertia in the market that we can take advantage of. We wanna make sure that we have the capacity there to catch it. Yeah. So those are the changes we've made. That makes a lot of sense. And I guess now that those territories have been realigned, like, how have those changes been received by the go-to-market team? I know you've had some sales kickoffs recently, and so- Yeah ... maybe talk about how the changes have actually been received in the field. The sales kickoff that we just completed back in April was one of the best I've ever attended. I can say this because I didn't preside over it. I participated in it, though. Just an amazing response. Our account execs are fired up, and part of it is some momentum coming off of the Q4 performance for sure, but part of it is what they see in the market opportunity as well. Huge market coming our way with significant differentiation around Dynatrace and our story and our solution in that market space, which I think the typical rep would say as, "Wow, this is a big opportunity for me to really succeed and grow this year. That makes a lot of sense. Maybe just to take a step back, you and Jim have talked a lot about recently where pipeline is growing faster than ARR growth. There's visibility into a potential acceleration in ARR at some point. Maybe you could just talk about what are the building blocks that? Is it all macro? Is it these platform consolidations? Is it partners? Maybe walk through some of the biggest building blocks that gets you excited about that pipeline growth and the potential for acceleration down the road. The biggest building block, really, bar none, is the shift that's occurring in the industry really around the necessity of software working well. And that is driving, I'd say, this increased consolidation trend of software to work better using observability capabilities. And as that builds in momentum, I think that's really one of the biggest catalysts that we see. The second one is new products, the addition of log monitoring, log management, the addition of application security to our portfolio. These are elements that provide more traction for customers in adjacent spaces. Then thirdly, we've adjusted over the course of the past 15 months or so now our licensing approach to what we call the Dynatrace Platform Subscription, DPS, we refer to it as, which basically moves us to an ELA, an enterprise license agreement-type approach, where you simply make a commitment of dollars over the course of a 1-3-year span, and then you just consume that over the course of time using that subscription model. It seems to be gaining pretty substantial traction in terms of consumption by customers using that model relative to our prior model. We, in fact, are seeing consumption that is consumption growth that's double the rate of our prior pricing model in DPS customers, and so that lends us some pretty significant upside opportunity as we look to the future, as well as we add more DPS customers to the install base. That's helpful. A common feedback point that I get from investors is just, "Hey, Dynatrace is a great company. It's operating behind a really large market, but there are other large players in this market." And so I, I'm curious to get your take on, how do you compete in a market where there's other large players that people could adopt, and how do you eventually become one of those long-term winners? There are other competitors in our market, I had noticed. It is important to us to continue to focus on differentiation based on our strengths, and where we win is at the larger account size, for all the reasons I've described earlier. Our competitive differentiation is really in three areas. One is in contextual analytics. By having a single common data store that captures all of these data types in one contextual data store, we then can provide a level of automation and capabilities that others simply can't provide. Second is Hypermodal AI. We've talked about this, but the notion of AI analytics applied to those common data types gives us an advantage in the market by being able to get to answers, not just red, yellow, green status indicators or dashboards. And then the third piece is, in fact, automation itself. As I am privileged enough to talk to CIOs around the planet, their comment to me is not, "Oh, how do you fix problems faster?" Of course, they wanna do that. It is: "How do I eliminate incidents altogether?" And if you get to the point where you trust the answers from a platform like Dynatrace applied to these issues, then you can actually automate the solution. I'll give you the simplest of examples. Let's say that before maybe you were gonna run out of capacity on a server farm sitting in AWS in Virginia. Why that would ever happen or should happen is beyond me, but it happens all the time. What if, instead, we could predict, based on your usage and flows, that that was gonna happen, and then automate the solution by provisioning more capacity in real time to eliminate the issue from having happened? That is a very rudimentary example, admittedly, but there are so many others that I could give you that enable and speak well to the notion of automating activity to be able to prevent issues from happening in the first place, and this is what our customers wanna see. No, that makes sense. Then, you've recently launched two pretty big new products with log management and application security. You recently talked about on the last quarter that you might be pushing out those $100 million ARR targets in the next year versus the prior expectation of fiscal 2025. Could you kinda clarify what you exactly meant on the push-out of those targets? Then how does the trend of customers moving over to the new DPS pricing model kinda give you visibility and the ability to map consumption versus ARR? It's interesting, but and maybe this is not intuitive, but by moving to DPS, it actually upfront in ARR gives us slightly less visibility as to how you expect... to use the portfolio. It used to be the case that we would license a number of host units for you to use with application performance monitoring or infrastructure monitoring, and we would license logs and application security independently. The feedback that I used to get from customers when I first began at Dynatrace two and a half years ago, and I would go ask them: What do you really... I asked them all the same things. What do you like about Dynatrace? What do you not like about Dynatrace? Two, what do you like about Dynatrace? The feedback I would get from customers is, "Your product, your solution, is awesome. It works great. It solves my issues. It does what it says it's gonna do. You drive enormous value, and, and we have, we have benefited substantially from its deployment." On what we do not do so well, it was, "Your licensing model is not great." And I think that was sort of the generous way of putting it, and it was because you had to provision all of these different applications separately. You had to, you had to contract for us to do log management, and then you had to contract to do AppSec, and then you contracted to do host units. It was very arduous. We put in place DPS to address this. And in so doing, what we essentially enabled was, just give us a spend commit, you can use it however you wish against a particular rate card, and that's what we've done. But what it's also done is it forces us to use consumption as a measure for deployment of logs and application security and other elements. And that is a retrospective measure, as opposed to a prospective measure using ARR. And so this shift is part of the cause for us shifting out, when we believe we hit some of these numbers in AppSec and log management. What I would say in each of these areas is, customers have grown 100% year-over-year in each of the areas. The growth has grown substantially in terms of usage, so we feel good about both spaces, but it's gonna take us a little bit longer to get there on a consumption basis. No, that makes sense. It's a when, not an if, with 100% year-over-year growth- You'll get there. ...... The DPS pricing model seeing growing much faster than the other customers, it's just a when, not an if. So most customers you're landing with log management today are really... I know a lot of them are trialing just new workloads- Yeah ... before moving over their existing workloads from those more legacy incumbents. So maybe talk about the subset of customers that have moved over the whole farm, where they're saying: Hey, we're not just giving you the new workloads, we're also giving you the existing workloads. How large of an uplift could that be for you, and then how long does it typically take a customer to get to that realization? The answer to your last question, of how long does it take? It varies wildly. It's... The way we look at log management is, first of all, enormous market. I mean, take a look at many in the market, Splunk and others. I mean, it's a giant existing market. Our view, before I sort of level down to how does log management roll out, is simply that the way the log management market has evolved relative to observability is that they've evolved relatively independently. That's not gonna continue, because it really doesn't make any sense in the end. Those should converge. Why should they converge? It is because the contextual analytics that I talked about earlier, coming out of the Dynatrace platform, delivers better answers based on having all of the data types for observability in one place. So having logs, traces, metrics, behavioral analytics, real-time, real user experience, those sorts of things all together delivers the best outcome in things like incident management and resolving issues. So that's, that's one of the reasons that we believe that all of this will converge, frankly, irrespective of Dynatrace, and even if you listen to other vendors in the space, they'll tell you the same thing. It makes sense to converge these data types. Now, when you get to log management, the way we expect it to roll out is POC or trial, early rollout, later rollout, and then a migration of competitive workloads over. We have customers, out of the 600 log customers, at each of those four stages, and some of the larger ones have done major competitive takeouts already and are already running on the Dynatrace platform. Others are gonna go at a varied rate to be with making that transition. Ultimately, makes sense to us to have a converged observability inclusive of log management infrastructure and solutions set running on the platform. Yeah, that makes sense. And then I know it actually, it takes some time to actually start impacting the marketplace, but have you seen any change maybe on the POC front, just as a result of the recent acquisitions that have taken place? I know we've seen Splunk get acquired, Sumo Logic. Even on the APM side, we've seen New Relic get acquired. So have you seen any impact to the competitive ecosystem following those acquisitions? I would say certainly in, in Splunk's case, way too early to tell. It's, there is, there's certainly some, I'd say, customer concerns about what happens, but Splunk is very entrenched in, in customers. And, and so, you know, I think that takes a while to play out, and we'll just have to watch it accordingly. In terms of some of the other, some of the other vendors in the space, you know, I do think it's, I do think it's impacting, it's impacting the environment, at, at the margin. Yeah, that's helpful. Maybe last question of the day here. You've recently gone into application security. Maybe talk about how that adoption has been trending, and just the opportunity that you see ahead to expand into security. Sure. Our, our application security business, I believe, can be a substantial business, for us at Dynatrace. This is why we're investing in it accordingly. Having said that, security is a pretty crowded space with lots of giants, and the strategy that we've deployed at Dynatrace is very specific, which is that we want to be competing in areas of application security where observability data makes a differentiable has a differentiable impact. So, in areas like the, you know, the Log4j crisis, or vulnerability analytics, or, runtime application protection, RAP, cloud SIEMs, these areas are the areas that we'll be investing in in security because, these are areas where having access to the full suite of observability, analytics, and instrumentation makes all the difference in the world, and so that's, that's where we're investing, and I think it can be a, a very dynamic and interesting space for Dynatrace as we look ahead. Yeah. Great opportunity ahead of both. Thanks, Rick. All right. Appreciate you spending the time with us. Thank you, Alan.