Unknown Speaker 0:00:05.4: 

So we've got an amazing session for you all today from Dynatrace. Becoming the glue across the business. We're going to understand what Patrick and the team are doing. So if we can click to the next slide, we'll do some introductions there. So go ahead, and we'll do some introductions. Patrick, I'll start with you. 

 

Patrick Orman 0:00:22.3: 

Sure, yes, I'll take it. So Patrick Orman, I've been with Dynatrace since 2017, and I joined the finance team then. In my current position, I lead our FP&A group. 

 

Jason Lawler 0:00:33.7: 

Hi, everybody, and thanks for joining. Jason Lawler. I'm the senior director of business finance at Dynatrace. I've been there since 2019, so about six years. Yes, I lead our business finance team. 

 

Caroline Weiss 0:00:45.5: 

I'm Caroline Weiss, I'm from Peloton Consulting Group, so I was the implementation partner for Dynatrace. I've been in the Anaplan space for the last six years, and I've been working with Dynatrace since their Anaplan journey began. 

 

Unknown Speaker 0:00:57.7: 

Awesome. Patrick, why don't you start us off. Just tell us a little bit about who Dynatrace is, what you do as a company, and then a little bit more about the FP&A function at Dynatrace. 

 

Patrick Orman 0:01:07.4: 

Absolutely, so I'll run through a few of the - where we sit, and then we can jump into more of the Anaplan road map. 

 

Unknown Speaker 0:01:11.9: 

Perfect. 

 

Patrick Orman 0:01:13.8: 

So overall, what is Dynatrace? We're a business-to-business focused enterprise software company. If you're a developer or an IT operations leader, or a CISO, you probably know who we are and what we do, but in a nutshell, our role is we have an observability platform, AI-powered observability platform, and we pull data from users, from apps, from infrastructure, and we use that to detect problems and proactively prevent outages, really just to ensure that IT environments and software that's being delivered works flawlessly. We've been a leader in this space for a long time. Over the last 15 metric quadrants, we've been in the upper right, and as of the 2025 evaluation, we're ranked number 1 in 4 out of the 6 critical capabilities. As a company, we've really scaled quickly in a fast-growing space. We're a subscription business model. We're a little over $1.8 billion in ARR. Global footprint, so over 4000 customers in over 100 countries and over 5000 employees in over 35 countries in terms of our physical presence, and we've been operating as a public company since 2019. 

 

Patrick Orman 0:02:30.1: 

Before I jump into, more formally, what is FP&A, and how do we think about our Dynatrace deployment, I just wanted to touch a little bit on, like, here are some of the questions and the themes that we touch on frequently across the business and the things that we get asked. It spans the full spectrum where we'll get questions about cloud cost optimization and, hey, what can we do in order to help control that or gain efficiency while not impacting customer experience? We'll get questions on the go-to-market side. Hey, how are we thinking about go-to-market planning, sometimes on a really granular, country level, or all the way at a global level, and how are we sequencing go-to-market investments? Things that tie closely to include headcount and workforce planning, so we stay very closely aligned on that. Then we get wonky finance questions, right, which is, hey, I noticed the euro moved 350 basis points; what does that look like as far as our operating margin outlook and impact? We just finished an IP transfer. What does that mean for our tax rate next year?  

 

Patrick Orman 0:03:33.6: 

So we really as a team try to understand not just the dollars, and control the expense, but really be smart about the way that we're understanding the strategy and how we invest. So more formally as an FP&A team, I think of us as really the glue that holds many of these different pieces together. If you think about our business finance team in particular, we're really adamant that those folks are deeply embedded with our functional business partners and understand again not just, where are we spending the dollars, and what's the budget and variances but really understand strategically what's going on in the business. We can be agile when we have different needs for shifting or changing investments and things like that. Then obviously there are a number of other things that we need to have our finger on the pulse of. If you think about workforce planning or consolidated board reporting, IR support, things like that, we really - I think we sit across a few different functions, and so as a result, we need to both have our arms around what's going on from a finance perspective, but also, we really need to understand strategically, how do these things link together? 

 

Unknown Speaker 0:04:54.5: 

So before embarking on your journey with Anaplan, what were some of the challenges that you were facing? You were getting a lot of questions from a lot of different parts in the business. Lay out where you were before you started the Anaplan journey. 

 

Patrick Orman 0:05:08.2: 

Yes, absolutely. I'll ask for some help from you guys too, but before we started, I actually was running our commercial finance team, which is a team that cover top-line and revenue forecasting as well as sales and marketing business partnerships, so I can talk from personal experience what that looks like there. Essentially, from a revenue perspective, we were running entirely in Excel sheets. That comes with a few different challenges that we were running into. So if you think about manual data handling, we had a lot of that, so taking big CSV extracts with maybe our deferred revenue waterfall, having to copy and paste that across different files. In the process of doing that, sometimes you'd have dimension members change, so if we add an entity, or we have an additional revenue account or something, that would force us to go in and then add lines in different tabs, and make sure everything is still linked and works well together. We ran into just a lot of inefficiency doing that, and it in some ways put us in kind of a vicious cycle in some instances where we would be spending a lot of time on the mechanics and not enough time with our business partners, really understanding assumptions, pressure testing our forecast. 

 

Patrick Orman 0:06:24.1: 

At the end of the day, we would show up in a forecast review and we would at that point realize, hey, we're not as tightly aligned as we should be. We've got to go back and do this inefficient stuff all over again. So we found ourselves in not a great place as far as ability to scale with that. There were a number of other areas where just running scenario analysis or FX-based analysis was also manual, so just a lack of agility, I would say, is where we were overall. 

 

Jason Lawler 0:06:53.1: 

Yes, and I can jump in from more the business finance side. Just like Patrick said, our entire headcount plan, workforce plan, non-personnel CapEx, all P&L was on one single Excel file saved on our network, and our team of seven or so FP&A business partners would literally have to stand in line and wait to get access. It would take 15 minutes to open, 15 minutes to save, often crashed just by the sheer size of this file that grew over time. It was an extremely inefficient process. We had tons of versioning issues, tons of data loss issues, and in addition to this poor model, we also had key FX analyses and scenario analyses, and variance analyses that were happening also in Excel and manual. So to the point that Patrick mentioned about scalability, this was not a scalable process as our FP&A team was continuing to grow, and certainly not scalable as we wanted to reach a $2 billion level company. 

 

Patrick Orman 0:07:46.5: 

Just to jump in really quickly too, one of the things that I've appreciated more as well, as we've moved past that is we had a lot of also just single-threaded dependencies. So you have the person who knows how this file and this process works, and it actually makes it very difficult to rotate talent and have folks pass the baton if you want to move people between positions or elevate people. So we were also having a struggle with that for some time where there were specific areas where we said, 'This is a really fragile process, and we need to be very careful with how we think about rotating people through that.' So a little bit hamstrung as well in terms of ability to develop talent and develop a team. 

 

Caroline Weiss 0:08:26.9: 

From the implementation side, as Peloton as the partner, we see this across multiple organizations within finance teams. They're using common solutions or it's very, very Excel based and it's super manual. So when we come in, our goal is to ensure that we're not just copy and pasting your solution, right. Jason mentioned he sat in line for 15 minutes and uploading to Excel. We want to get rid of that. So in addition to updating your actual calculations, we're also updating your business process. So we do that through plenty of sessions where we do requirements gatherings, we do design sessions to ensure that we're updating your full process from start to finish. You actually get that time back. Even as Patrick said, right, he couldn't rotate talent. Anaplan will start working for itself. Maybe you don't have to make 500 inputs anymore because they existed in 14 different Excel spreadsheets. You can make three that are live connected through your entire model. 

 

Unknown Speaker 0:09:18.4: 

Not only are you able to rotate that talent, but then you don't have a critical point of failure. That person decides to go on a vacation, right, or they're on leave. They're the only person that knows how to work that spreadsheet, right. That becomes a critical failure point as well. 

 

Patrick Orman 0:09:30.1: 

Right. 

 

Unknown Speaker 0:09:33.0: 

All right, so look, there's a lot of places that you could have started your journey with Anaplan, there's a lot of use cases out there. Tell us about the first use case, where did you start, and then we can walk through a little bit of some of the other use cases that you've rolled out at Dynatrace. 

 

Patrick Orman 0:09:44.7: 

Yes, absolutely. So we probably started in a bit of a different place than typically when I talk to folks, where they started. So we started with revenue. As I mentioned, we had a strong desire to have a top-to-bottom-line integrated financial model. Where we stood, as I said, is we had an Excel-based model for revenue. We had done some work in workforce planning and non-personnel expense in the common solution, but with revenue, we had hit the wall as far as, how are we going to architect something and build something that gives us the flexibility that we need from a revenue planning perspective? So we did a little bit of evaluation across a few different tools, and I think, where we really found the value in looking at Anaplan, where we said, 'This is probably the direction we want to go,' is - again, I think it's all about the ability to tailor in many cases your build to what your business process is. This idea of unconstrained dimensionality lets you plan the way that our sales team or our marketing team, or other operations teams really think about the business and then map that into the financials. 

 

Patrick Orman 0:10:54.6: 

We can have the flexibility to keep it very oriented around that and also adapt that as business processes and operations evolve and change their strategy. So there was a big flexibility element that we liked as well, and then, honestly, one of the other notions that I really liked was this idea that you could have folks on the FP&A team really own the modeling, and this idea of citizen developers within functions and within finance that could actually understand what's going on under the hood of the model, get in there, make tweaks and changes as we need to, and be nimble. I think there are instances where you'll have a tool, and you'll dump a bunch of requirements on your poor implementation partner, and they'll come back, and you hope the build is right, it's usually pretty good, but then you're less nimble. You're constrained as far as, well, what happens when things change? What happens when somebody pops the hood open and says, 'Hey, how does this calculation work?' or, 'Something seems off; what's going on?' That, particularly for a finance team, is scary, and I think that we saw a lot of value in just the ability to have a platform as well where we could really have our hands on what's going on under the hood. 

 

Unknown Speaker 0:12:09.0: 

Well, even as you frame out your conversations to the stakeholders, and the business stakeholders, it changes that conversation, right, because when you get those questions, you can explain how it's working, why it was designed that way, why maybe the numbers are a little bit different than others. So again, I think that's a great call-out. 

 

Patrick Orman 0:12:21.7: 

So as we jumped into the revenue model, we started with a data hub, so we set up our foundation of, okay, what are the key data sources we need to be importing? We even did some, what is our pattern for where we're going to pull this from, so we have a data warehouse and booming integrations that run, and we set up the pattern for how we want that to work. We set our foundational things around, how do we want to think about list management, how do we want to think about versioning and how that would work in a future state? Then from there, we really took the time when we moved into the actual revenue model itself to think through that process, and our business process, and refine it as we went through the revenue modeling exercise. So within about, I think, a 16-week build, we made our way through revenue. As we were doing that, we were adamant - and probably, Caroline, you were kind of done with me by the end of the build, where I was very specific about, well, here's how the workflow needs to work, and the UX, but I think we nailed that well. Then in doing so, we were also able to just build into the model a lot of the analytics that, in the past, would take us just a lot of time to figure out. 

 

Patrick Orman 0:13:35.1: 

So when we think about foreign exchange rate and FX impacts, that kind of stuff is just baked into the way we do version-to-version compares. It's not something anyone has to calculate. We have that just set up so that whenever we're looking at two things, we can understand and bridge the FX impacts. That's really helpful as far as being able to understand, pass out the noise from what's going on in terms of exchange rates. We, in addition, did a much more structured capture as far as, how do we think about variance analysis, and how do we think about risks and opportunities? We, at this point, have just a very clear capture of what those parameters look like as we go through the planning process. Jason, I know you drove more of the subsequent evolution, so I'll let you jump in, post-revenue. 

 

Jason Lawler 0:14:21.6: 

Yes, the successful revenue implementation was definitely a huge proof of concept and gave us that momentum to take that leap to then build our full workforce planning, non-personnel CapEx, and really the full P&L into Anaplan as well. So we started with leveraging our HCM, bringing in census data to be doing actual employee-level planning from a workforce perspective. We streamlined a ton of our calculations on the forecast side by leveraging drivers for things like merit, bonus, fringe expense, travel expense. Most of our non-personnel expense planning was now streamlined with driver-based calculations in Anaplan. Then Patrick talked a lot about our data hub and our versioning, and FX analysis, and we were able to mirror a lot of that on the expense side too. We automated all of our FX analyses, understood the impact that currency had on expense, but now that it's linked to revenue, we can understand currency impacts on gross margin expense or gross margin percentages, operating [?company 0:15:14.4] percentages, and really understand the full top-to-bottom FX impact on our P&L. 

 

Jason Lawler 0:15:20.7: 

Similarly, we align with the version management data hubs, and now we have full versioned P&Ls that we can do variance analyses on that are synchronized and standardized and centralized. So overall, by bringing both revenue and workforce expense, full P&L into Anaplan, we really shaved days off of our forecast process and just streamlined everything. 

 

Patrick Orman 0:15:40.8: 

Yes, so I'd characterize that as our core financial model that we were able to build, and I think it took us - it was 16, 18 weeks on revenue, and probably 6 months on the workforce planning and non-personnel CapEx, all of those things. Past that point then, we really just started knocking out some of these operational adjacencies. So thinking about things like our LRP, that was a pretty straightforward addition. Once we had that core financial model added in, we were able to work with actually our accounting team on building some additional modeling to get more of a full GAAP P&L view, working through some transfer pricing and things that help us work better with tax in order to share assumptions and go through our quarterly exercise there. Now we're into stock-based compensation and share count modeling, and so there's a lot of operational adjacencies that once you get that core, from a finance model perspective, set, it becomes very apparent, and I can start to knock some things out. A fun one we did, honestly, was the EoQ flash results you see there. 

 

Patrick Orman 0:16:49.1: 

This is one where, as we approach the end of the quarter, we like to get a really good and more real-time read on, what are our results going to be, and more focused on top-line. So how many new logos? What is going to be our net retention rate? What is going to be our renewal rate? What is going to be our revenue in different segments? So what we set up there was a live feed from a few different data sources, Salesforce included, where we could hit refresh and we'll get a read on, hey, here's where we're looking for the quarter to land. That's been great as far as visibility, but then also, from an execution perspective, just to have that read as you're coming in, in those last weeks, it actually helps you think through, okay, where are my big swings and sensitivities? So I think there's been both a benefit as far as visibility for our management team, and then also a little bit of helping on the execution side. 

 

Unknown Speaker 0:17:39.8: 

That's awesome, and that's a different value conversation with the business, right, again. So Caroline, coming to you, this road map looks very linear. We started at a certain point, drove all these use cases. Talk a little bit about, has the progress really been linear? How has this road map evolved, right, from your perspective? 

 

Caroline Weiss 0:17:57.6: 

Right, so we did go in that order. We went revenue, then expense, and so on, as you guys can see on the screen, but businesses change, right. I'm sure all your businesses are changing. Every day, there's something new going on, and we always want to make sure your Anaplan models can change with your business. You never want it to be your business is changing but you can't forecast for that. So when we're building with Patrick and Jason, and other clients as well, we're asking, what is it going to look like in six months, maybe a year, five years? You might not know the answers, but we're thinking about that when building, so we're never going to hard code a path in and be like, this is the only way. So an example that we've mentioned is, right, we started with revenue in 2023, but this year, it actually came up that revenue is going to be changing, although they're adding a new revenue type. A lot of these [unclear word 0:18:41.7] businesses go via a subscription manner, but they're adding more of a consumption way for revenue, so they wanted to add revenue overages into their model. Their current revenue model has the very traditional subscription model where you book it, it waterfalls out, and then it hits your revenue, right. 

 

Caroline Weiss 0:18:57.7: 

It goes from there, a pretty standard subscription model. Very complicated. I made it sound simple, but it's actually very complicated. 

 

Unknown Speaker 0:19:04.1: 

So simple, so easy! 

 

Caroline Weiss 0:19:05.3: 

It's simple now. Overages were very different, right. So let's say Patrick had asked me to - we just need the same type that's going to follow the path. Patrick could have done that in a day, just to clarify, but this was a new path, so what we did is, within I think a four-to-six-week sprint, you were able to add this revenue overages for this consumption side of the house for revenue. It essentially allowed them to evolve with their business, and it was actually very cool to see. I was on one of their investor calls that are public to everyone, and they were talking literally about their forecasting revenue overages, and how the business is moving that way. So super important, just when you're talking to a partner, making sure they're asking those questions because that means that they're thinking about really, how do we make this model adapt to whatever is to come? To be honest, you're never going to know everything that's coming. 

 

Unknown Speaker 0:19:55.7: 

That's awesome. 

 

Jason Lawler 0:20:01.5: 

Yes, so we did also want to take an opportunity to showcase in a little bit more detail one of the analytics that we did build out as part of our [?bar 0:20:08.2] expense, headcount, non-GAAP P&L build. So what you'll see here on this slide is, this is our scenario analysis, or variance analysis, and you can see, in the teal columns, we're actually bridging the changes in the variance from one scenario to the next. You probably can't read it, but in between those two columns, we're isolating the impact of what's true business and operational versus what is driven from an FX perspective. This is in a full, non-GAAP P&L view outlined by our revenue types and our expense types by function, and then, in that red box there, you see we're actually double-clicking into one particular function and providing a little bit more detail, breaking down, okay, what were the actual business drivers behind that summarized level? Then in a bar chart format, waterfalling the build of, okay, this was the favorability, unfavorability driven by X, Y, Z. Prior to this in Anaplan, on the theme we've been talking about, it was all in Excel. 

 

Jason Lawler 0:21:06.4: 

It would have to be created in a centralized Excel from one team, shared with our business and commercial finance team to then populate, then share it back with our corporate finance team to consolidate and create this one picture. It was a very fragile process, and something as simple as inserting a row in the wrong place would just completely blow up the [over speaking 0:21:25.7] P&L. 

 

Unknown Speaker 0:21:25.7: 

Then you'd start all over again. 

 

Jason Lawler 0:21:27.3: 

So again, just very inefficient, not streamlined, and this build here has really allowed us to not only improve efficiency and streamline our ability to bridge from one zero to the next, explain business [unclear words 0:21:39.8] impacts, but it's really centralized and standardized where we have our variance analysis, so it's not living in mystical Excel files on people's OneDrive. It's living in Anaplan, and it's accessible for the business finance team to go back and say, 'Oh, what drove this on favorability two scenarios ago?' Why don't we click this one drop-down and go find out? Late at night, you're trying to figure out - I don't want to go call Jason or somebody on Jason's team, so let me just go see if I can figure out what the driver was of why we were unfavorable against the budget, and it's all saved right here. 

 

Unknown Speaker 0:22:17.1: 

So you're bringing all that data together, and you're allowing your business stakeholders to have access to it to answer their questions without having to come to you. The data is trusted, right, so it's not stale data, it's not old data. So again, it's a great example. I really appreciate you sharing that. 

 

Patrick Orman 0:22:30.8: 

I think, too, there's always, well, you should have a strong process, agnostic of the tool, but there is also an interplay there where - having a tool that helps you structure that and enforce the standards and the way that you think about the bridges, and how you categorize them. Very helpful as well. 

 

Unknown Speaker 0:22:46.9: 

Right. We were talking about it in preparation, and I liked your point, Caroline. It's like, look, if you have a process that's inefficient and you layer on an amazing platform like Anaplan, it's still going to be an inefficient process, right, so that process re-engineering and really thinking about how you can change the way you've always done it. I think the worst thing you hear is, like, well, it's not how we've always done it. This is the way we've always done it. Well, it hasn't worked, right. Go ahead, Caroline. 

 

Caroline Weiss 0:23:08.1: 

You took the words right out of my mouth. Jason walked us through this process, and it was like, well, we're not doing that anymore [unclear words 0:23:16.1]. This is where, I think I mentioned before, Anaplan can work for you, right. This is how we want [?our flex to be built 0:23:22.1]. So Jason puts in his expense, the actuals run in, and he puts in some forecast drivers, and it populates automatically, so you're not anymore having the process where you're sending it to three different people. So Anaplan can really work for you, and this is where your partner comes in and says, 'Okay, I get what you want at the end; we're going to give you a totally different path to get there now.' Hopefully, it will save you time where you can answer the questions that are way more strategic, way more important than, how does this Excel work, and how do I open this? 

 

Unknown Speaker 0:23:51.3: 

Is this recent data? Is this outdated data? Do we trust the data? Then you spend all your time on that versus actually moving the business forward, right. 

 

Caroline Weiss 0:23:58.4: 

Exactly. You're actually creating more business and grow. 

 

Unknown Speaker 0:24:01.0: 

Yes, awesome. All right, so again, big investment, a lot of use cases rolled out. Give us some of the impacts. What are some of the gains that you've seen? 

 

Patrick Orman 0:24:11.8: 

Yes, I'll move relatively quickly because I think a lot of these are resolution of pain points that we talked about earlier. So eliminating manual data movements, getting much more efficient, enforcing process standards systematically in the tooling. Super helpful. Probably the bigger things are more like the bullet number four there, having more time to bring insights to the business and really having our business partners be able to spend their time having strategic conversations with our leaders, talking about the direction, and how can we plan for things, or how can we - what supplemental or ad hoc projects do we need to be thinking about in order to drive the business forward? That's a huge value add, to take things like this and make it much more efficient. I'll say as well that one of the big drumbeats of our CFO is we need to drive as much systematic interlock as we possibly can between both finance in the business and then between the functions within the business. I think you might have caught on our road map slide, one of the more recent modules that we're building out, or models that we're building out is about marketing management, so there's a whole… 

 

Patrick Orman 0:25:26.3: 

I would say that's a nice step that we're taking now towards a more connected - truly functional, connected planning approach where we'll have our marketing team actually driving that and pushing down budget assumptions at a very detailed level. We can start looking at things like campaign ROI and some of the really exciting next steps with that. So that's been a huge one. Then I think there's also the element that I mentioned earlier as well, where rotating talent and developing the team is actually helpful for that. There are areas where I think, previously, I would have been very nervous about, okay, let's move this person here and have some talent rotation and exposure to new areas. Now that you have an application that's very clearly laid out and it's easy for someone to come in and learn it, and step through a systematic process flow that you know is well controlled in terms of the calculations that are running and everything, that helps you sleep a lot better at night when you're making those kinds of moves. 

 

Unknown Speaker 0:26:22.9: 

As you grow your team, it also opens up the aperture of the talent pool out there, right. You can say, 'I can bring different skill sets.' I don't need to bring somebody who just knows Excel or just knows this. You can bring somebody who brings maybe a different strategic point of view into the team, right. I love that angle on it. Jason, do you want to add anything on there? We've got some time. 

 

Jason Lawler 0:26:42.5: 

No, other than just reiterating the integrated planning across the functions. You took the words out of my mouth. Usually, when we present any forecast or plan, the first thing our CFO will ask is, okay, is this aligned with marketing, is this aligned with sales, is this aligned with the functions? So really interlocking the operational side and bringing in marketing and other operational aspects to build that full, integrated financial plan. 

 

Unknown Speaker 0:27:10.0: 

All right, so again, it's all amazing and we have all this value, and you're transforming financial planning at Dynatrace. What were some of the challenges? Obviously, there are bumps in the road, lessons learned. Everybody wants to know what they should avoid, right, so maybe you can share a little bit of that, Caroline. Just some of the bumps in the road and maybe some of the lessons learned. 

 

Caroline Weiss 0:27:29.2: 

Yes, so I'll start with that. I would say there's probably three key lessons learned, challenges that at least I summarized. Jason and Patrick will definitely give a few more. Joe spoke about it this morning where data is extremely important. We heard about that at the keynote. We heard about AI as well, right, like garbage in is garbage out. So a lot of times, we're all ready for the implementation and ready to go, and then it's like, oh, where are our actuals, and it's like, I think they're here. Maybe you are planning by subsidiary department. Across different actualized data, right, maybe you have different subsidiary codes and different department codes, so it's like - it is a source of truth. So it really is getting your data ready because, at the end of the day, if we start forecasting on bad actuals, your forecast is probably going to be inaccurate, right. So that's definitely something, as we've evolved and moved into different use cases, stock-based comp, end-of-quarter tracker, we've got into datasets that maybe aren't as - used every day, right, versus revenue actuals. You know your revenue actuals, hopefully, I guess. So data is super important because it just makes the rest of the build go really smoothly. 

 

Caroline Weiss 0:28:32.2: 

Then you get to go live. The data is good, the forecasting looks good. The Anaplan model is doing all the calculations as needed. We're ready to go. So that was number one, data. The second is really the team needs to be ready for an agile transformation. So I give huge props to Patrick and Jason and all their team members for this. We're asking a lot of questions along the way. We're not just asking how you do it, but also the why of why you're doing it, right. You can explain the whole calculation, and I might be like, but why? I don't get it. It doesn't make sense. Obviously, as a consulting partner, we've worked with tons of clients before, and we have that expertise to say, 'Hey, actually, we've seen client X, Y, and Z do it this way; here's how we typically see it.' So because that's happening within maybe a 16-week sprint, or an 18-week sprint, or sometimes an 8-week sprint, you need to be ready to be able to make those decisions quickly, and say, 'Okay, this is going to be our new calculation.' If we're shuffling our feet for six weeks of the eight-week project, we're not actually going to build a full P&L. So that's just more of a mindset for the team. Then the third is - not to toot my own horn. 

 

Caroline Weiss 0:29:38.5: 

I would say it's really, really important to have a really strong implementation partner. So we've been working together [over speaking 0:29:44.7]. We've been working together for three years, and I think we've built a lot of trust between the three of us, and the rest of our Peloton team and the Dynatrace team. If Patrick is asking me something, and I go, 'Honestly, Patrick, I don't think this is right,' or, 'This is a constraint, we can't do this for this reason,' we have a lot of trust between the two where he realizes that I'm giving you as much up-to-date information as I have, and we have a lot of it, don't worry. It's very rare we'll say no, but sometimes we'll be like, this is actually a better path because this doesn't make sense, right. So having that strong relationship will make it a lot smoother because I'll go to them with information, they'll come back to me, and I'll be able to make edits and updates on the fly that work for them because I know - also, with the [unclear words 0:30:31.6], I now know exactly the types of pages Patrick and Jason like. 

 

Caroline Weiss 0:30:35.1: 

So it's like, even small things like this, we're always learning and updating with each other, and having a partner you can trust, I think, makes the implementation process, at least from my side, much easier. 

 

Patrick Orman 0:30:47.5: 

Absolutely. 

 

Unknown Speaker 0:30:48.4: 

Patrick, can you touch a little bit on the CoE? You talked about that when we were prepping for this. How you thought about the talent that you needed to bring in to support this platform, and especially, probably, you didn't foresee it to grow like it did. Talk a little bit about lessons learned on that front. 

 

Patrick Orman 0:31:02.4: 

So I think that what we found was that momentum gathers pretty quickly internally, and that's both a statement about within finance where we quickly realized, hey, we want to do more of this; we see these different use cases we can knock out, but then especially too, when you start thinking about, how do we connect other functions from a planning perspective, and needs that will exist across those other operational models. So one of the things, honestly, I wish we had gotten the ball rolling on, even just earlier than we did was building out a CoE and having that internal expertise. There's no replacement for participating in a model build to understand the model. Apparently, AI will do that soon. That's actually great for me. Maybe that was a - it won't be a pain point, but I really think that getting trained on how the model works, understanding what's going on under the hood, and being able to be dynamic and change things on the fly. You really want a CoE resource early who can see how things have built and evolved, in order to have that be seamless once you get to scale and you start bringing in these other questions of, okay, how are we going to bring other parts of the organization into the fold? 

 

Unknown Speaker 0:32:12.6: 

You're on level three, right, already? 

 

Patrick Orman 0:32:13.9: 

So personally, I guess I was our own little CoE for a while. On that point, the other thing I would say is that learning the platform and actually spending the time - this is a little bit of a go-to-school pitch, but learning the platform really does help as far as, when you're in an implementation, even if it's not my hands on the keyboard, doing everything on the back end, it's super helpful to be able to speak the language, understand the art of the possible, and the tool, so I would just encourage - if there are folks that are jumping into an implementation and haven't done some of that, it's well worth the time you'll invest. I think it's a couple of weeks, honestly, to do the L1, and then if you want to take it all the way through, it's a couple of months. That would be another major learning. We've been pretty adamant as well on our team that we have some resources within FP&A that have done some of that as well and can help speak the language. Ultimately, financial modeling is a technical thing on the back end, and spreadsheets, and so it's important for folks to be able to have that comfort, I think, as well in the back end of an Anaplan model. 

 

Unknown Speaker 0:33:19.4: 

Well, especially as you have business stakeholders, like marketing or sales operations that are coming from a different lens, and they're asking you, well, how does this work, or why is this data coming out this way? You can at least answer that with some confidence versus, oh, I don't know. At that point, then your business partner is like, okay, well, you don't know; why would I come on an Anaplan platform with you, right, so I think that's good. All right, so what's next? Obviously, this is just the start. A great journey so far. Jason, obviously, there was a really amazing keynote earlier. I don't know who gave it. It was really good, though. 

 

Jason Lawler 0:33:48.1: 

Yes, agreed. 

 

Unknown Speaker 0:33:48.4: 

It was Adam. Adam's keynote was really good. What excites you? We've got a lot of innovation coming. What's next for Dynatrace? What excites you about where you're going with Anaplan? 

 

Jason Lawler 0:33:57.3: 

Yes, the AI, very exciting, obviously. Even just the simple things of the thought in your brain, like, oh, what was our margin last quarter, what was our revenue? As opposed to having to go click around, find the P&L, and figure it out, I can just type that exact question in, so very exciting. I love the shiny, new things. Also, what I'm really excited about that feels a little bit more short-term, mid-term, and is more tangible to me is just echoing what we talked about, about building Anaplan out into more operational aspects of the business and really growing our honeycomb and continue to the right. The value we've seen in Anaplan from a finance perspective has resonated, which then resonated with the executives at our company, which then led the marketing team to pursue Anaplan for their promotional program spend, like their budgeting, their allocations, and I just see a lot more use cases. We're continuing to push into the business more with Anaplan and really driving that interlocking plan. 

 

Jason Lawler 0:34:53.6: 

So if you think about more of operational workforce planning, not financial workforce planning, where you get the business into Anaplan, and they can do territory planning, or they can do coverage model planning of CSMs or AEs, SMEs, and then have that automatically integrated back into our financial model, it has immense value… 

 

Unknown Speaker 0:35:14.1: 

That's awesome. 

 

Jason Lawler 0:35:14.6: 

…that I'm very excited about. 

 

Unknown Speaker 0:35:15.7: 

Yes, that's great. Well, congratulations. Amazing journey. I think that's the last slide, and we've got about ten minutes or so for some Q&A.