Zuora’s COFO On Going Private and Pricing AI | Todd McElhatton

0:00Because you're using the most tokens doesn't mean you're the smartest engineer around or that you're producing the best value for the company. That's one of the things, especially finance leaders, we're sitting here struggling with is, I want people to use this technology. I want them to get the value out of it. But I also want to make sure the company gets the value. Probably 90 % of the decisions that we make are two-way doors. Run through those two-way doors. Go do it. You're going to end up moving a whole lot faster. We're going to gain a whole lot more yardage on the play. But on those one-way doors, those are the ones that we really want to think about.

0:27Those are the ones we want to bring in, you know, the right leaders and we want to be thoughtful about them, make sure that we understand all the repercussions on smart people learn when they get new pieces of data are willing to make different decisions. And I think it's really important for leaders to be like, oh, I've already made this decision and I'm going to look like I fail. All right, we've run this through. And now where we are, it's time to move on. Is this thing on? Yesterday's price is not today's price.

1:04welcome back to run the numbers my name is cj and on my podcast i talk to the world's top cfos and today i have a cofo on todd mckelhatton the cofo of zora this is the deep cuts folks pricing packaging and value okay todd is an expert on how to monetize a product and we go deep on how companies are monetizing AI. We also talk about expertise, how AI is reducing the need for expertise. And he argues the opposite, that it actually increases the value of experts. So what's everybody getting wrong here? We also talk about his time at VMware, the parallels he sees between the move from on-prem to cloud and today's AI transition there.

1:47VMware was a true trailblazer in that. And he also joined VMware expecting to help grow a business, but instead found himself helping to rethink the strategy he was brought in to execute. Then we link that to the Take Private of Zora and how they're operating now as a private company. For all those people out there who are trying to figure out how to price and package their AI software, especially if you came from the subscription and SaaS world, this is going to be a podcast that's pretty illuminating to you. And if you're interested just in the topic of Take Privates, Todd is pretty open about what the company has been working on and the transition from public to private life.

2:21All this and much more coming right up. Todd, thank you so much for joining me on the Run the Numbers podcast. CJ, I'm glad to be here. This is going to be fun because I feel like you were at the nexus of monetization and how pricing and everything is changing at Zora. So I feel like it's going to be two finance guys going back and forth just talking about the future of how we make money on things. You know, absolutely. And it's been really interesting here at Zora. We've had a front row seat on how things are changing with AI at a pace I have never seen in my career before. Everyone's debating whether AI should be priced by tokens or seats or outcomes.

2:56I'm a huge dork when it comes to how you price stuff. And it feels like we're arguing about the price tag, Todd, before we've agreed on what customers are actually buying. What do you think is going on in this debate? It is a really interesting point. I don't disagree with you from a standpoint of before we talk about pricing, it really becomes what value are customers getting? And once we determine the value, then I think we can start having a discussion on what does that look like from a pricing standpoint. Probably some of that is coming from the fact that people are starting to realize that as we are rolling out some of these AI tools, they can be super expensive.

3:33And so as those start impacting the economics, we've got to show the value. Once we show the value, then I think the pricing will fall out of place. What's an example of where AI should just be included and not charged as an add-on? Because I think every company is now adding some sort of AI module, even if they aren't an AI native company. And they're kind of in this back and forth of, do we charge extra for this? Or is this just like table stakes for us to have a great product? That is something I am hearing from CFOs everywhere. First of all, we got to really show value. Let's get people using the tool.

4:06Let's show them the value. And then we'll figure out the pricing point. Well, my perspective even think in general here is SaaS products should be evolving. They should be getting better. There's an expectation of that in the marketplace. When have you had just such a leap step in the capacities or capabilities that you're giving your customer that you've earned the right to have that conversation about having incremental pricing? So until you get there, I think it gets a little bit premature. And I think some companies, if I think back maybe a year and a half, even two years, Todd, the first companies that were experimenting with some sort of AI offering, they almost didn't want to get over their skis.

4:43So they said, oh, well, this is like an add-on module or feature that I'm just making it up. You pay$15 per more per seat in order to access that AI functionality. Do you think that a lot more companies are feeling more comfortable in the cost structure and how they deliver that, that it's just included in the product? I think there's a lot of things that can be included in the product. We're learning over time. Frankly, when we use AI, what drives the cost? What is the model? What does the query look like? And so as people get more comfortable, I think you're right. Some of that's going to be included, but there's certainly going to have to be ways to put some guardrails around that.

5:17And I think that is one of the big things we are working at Zora here with. It's one of the things I hear my peers are struggling with is trying to understand as I add some of this functionality, you know, what are the things that can go off the rails? Where can I end up something that was a product that had, you know, a nice 80, 85 % gross margin. And I added some function and feature or function and features to it. And now all of a sudden, you know, I've tanked my margins. Are there some companies that you've heard anecdotally going off the rails? I think we've all heard stories about different folks where companies have had, you know, these massive unexpected bills from their AI providers.

5:53One of the things that I think, you know, we probably saw a year ago was let's look at leaderboards where who's using the most tokens. It feels like everybody has taken that off because like anytime you sit there, there's lots of ways to game the system. And because you're using the most tokens doesn't mean you're the smartest engineer around that you're producing the best value for the company. That's one of the things, especially finance leaders, which you're struggling with is, I want people to use this technology. I want them to get the value out of it. But I also want to make sure the company gets the value.

6:21And so that's the big challenge that we have as finance leaders is let's encourage people to use the technology, but let's also make sure that we understand what is the value that we receive from it. Well, to that point, Todd, do you think that AI fundamentally changed what software companies sell? You've been in the software game for a while, or is it just how they charge for it? I think it's changing both of them. Frankly, there's going to be some software companies that don't make it. There's things that are absolutely going to be taken over by AI, and you won't have the need for the software.

6:50There's other places where software absolutely is going to be needed, right? Take a look at companies that have mission critical systems that are systems of record that require regulatory approvals, where they've got compliance issues, where there's audit requirements. Those are the things that perfectly fit in. But that being said, AI is going to bring in new competitors. It's going to have new demands from our customers where they're looking for faster updates to the software. They're going to look at maybe different pricing economics. So AI is changing both how we sell our software and what customers expect from it.

7:21On that latter point, something that I think a lot of people didn't expect, including myself, is that these companies could have super useful info, but it would be accessed in a different way, right? You're hearing about software losing its head or going headless. What are you seeing from your side in terms of UI, UX, and just the expectations of how customers traditionally have interacted with software? When I start thinking about it, I heard someone use a great example of, how do I use my software or these new AI tools as a teammate? How do I expand the capacity that I have? And how do I train that new teammate to help me do things that make me more productive?

7:56And our tasks maybe that I wasn't super excited about doing as a user. So you're really seeing that software being able to give people a tremendous amount of value that maybe the software on a standalone basis wasn't able to do a decade ago or even just a few years ago, frankly. I think there's also a change in expectations about how you ramp that software that you interact with. You wouldn't hire somebody off the street, right? And just expect them to know everything about your org. A lot of it is going to be context dependent on how that job to be done is worked out today. Context is really important.

8:25And it's interesting because I think I've heard a couple of trains of thought. One is, do we just go hire a bunch of folks that are right out of school? There's a generation of kids that, you know, they're AI native. They've been playing with this over school for the last several years. That being said, context really matters. Experience really matters. We're seeing lots of areas where something may come out of a model. It doesn't make sense. or the recommendation, you're like, okay, it doesn't feel like this is a fully baked solution. And so one of the things that, you know, is finding is how do you get that perfect person that is certainly familiar with these AI tools is willing to use it is really to rethink probably how they approach their job, but at the same time, have the ability to be able to use the judgment and to make that work most effectively.

9:15But I think what we're finding is experience really does count here. What do you think AI is doing for the value of experts within our org? Is it going up or down? I think it's really increasing the value of experts. One of the things that it allows, it allows them to be a whole lot more productive. It allows them to get more information and more sources of things maybe they couldn't have done. They're able to do that more quickly than what they've been able to do in the past. And so I think it's taking your experts and really making them much more valuable. One of the things that I heard recently is AI is a coming after your job.

9:47is coming after the people who don't use it. And so the people that are using it are really getting a tremendous leg up on others. That's where their value comes in from. I can't decide what is a more valuable ad if I would say a GM of a team, much like you as a CFO. Do I want to draft or hire someone who is really curious and a smart generalist who can deploy AI to be an expert in things or someone that has a deep T and can go super deep on, I don't know, maybe it's like SEC accounting or something. and they'll be supercharged by AI. How do you look at hiring for specialists versus generalists now?

10:22It really depends on what the function is. But I think you hit one of the first things that's most important is I'm looking to hire people and one of the things that I constantly hear is, how do you find people that are curious? How do you find people that are in an actual experiment? How do you find people that want to adopt that change and you can talk about where they're using it? There are certain areas, like you said, where you go down to SEC accounting and you go into certain rules and regulations that, hey, I need somebody that's really deep. But there's also a lot of times when you need someone who's got much more breadth.

10:52So it really does depend on what the role that you're looking to fill. Yeah, and you've been at orgs of all different sizes and something that I've observed is companies get larger, people's jobs get more and more specific. And I'm wondering if that will continue with AI or it'll allow people who have traditionally been a jack of all trades to go even further because they can almost scaffold any blind spots they have with AI. One of our customers is a bait AI native company and was, you know, they've hit$40 billion of ARR and they've got 2 ,500 people and they have less than 100 people in their finance function.

11:27I think it's maybe 50 or 60. And if you think about just that massive scale that they've been able to achieve with very few people, I think what you're going to see is some of the areas where people went really deep in these large companies. You're not going to have that need as you're going for. So you're going to need to have people that have a lot more breadth. So you think about it, some of these large companies really do. They got people that you sit in your two by two box and that's all you do. And then you report to somebody else who kind of puts it all together. But I think what you're going to see AI is it's going to push it so people are earning more end to end and being much more broad because a lot of the tasks that get consumed in those large teams aren't going to be needed as being before.

12:05You bring up a great point because there's traditionally been one or two layers of, I'll call it like synthesizing or compiling or aggregating that happens. And I've been at all different layers within a traditional SaaS org of this, right, where you're trying to move up this hierarchy and your job becomes more taking the insights from other people and packaging it in a way for management to make it as useful as possible. I kind of wonder if those layers kind of fade away with AI at all. I think the layers are absolutely going to fade away. I mean, if I think about four or five years ago, when you talked about someone's success when they raised, you know, did a raise and what they were doing, you hear is we raised X amount of dollars and we added 100 people this quarter.

12:46And that was best. And now it's like, hey, I've raised some money, but I've got a handful of teams, a peak on my team. So you're seeing these teams getting much smaller, much more agile. And frankly, the output that's coming out is exponentially higher than it was with those larger teams. So I think you're absolutely going to see things where smaller, more agile teams that are delivering a whole lot more. And that's certainly what I'm seeing here with our engineering organization. We're seeing folks that are really able to do things where in the past it'd be like, come back to me in three, four weeks or something.

13:17And now it's an engineer is like, hey, I've got a handful of agents that are working on it. I'll have the answer for you in the morning. And it's just a totally different way to think and gives you a totally different perspective how to think about time. Every decision a company makes is inherently a financial decision. Folks, I've been trying to tell you that for 300 episodes. So it's wild that most finance teams have to spend the week on what already happened. While my favorite movie is Back to the Future, we'd be living in the past. Speaking of movies, here's a terrible plot. Tired accountant chases down a receipt from March and then polices a$20 Anthropics subscription.

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15:46Or just tell Julio that CJ sent you. That'll probably work too. Remember when pricing was simple? One product, one subscription, one invoice every month. Those days are over. The AI economy is changing how everything gets bought and sold. We're seeing usage-based pricing, hybrid contracts, and something called a credit. The finance systems built for vanilla subscriptions weren't designed for this. This isn't just a rev rec problem anymore because outdated revenue architecture can kill a great pricing idea before it ever reaches the market. RightRev lets you recognize revenue in whatever shape it comes in.

16:20Whether you're launching consumption credits or testing entirely new commercial models, RightRev gives finance the flexibility to support whatever pricing model comes next. So product teams can keep on innovating and finance teams can keep pace. If you're architecting revenue for the AI economy, learn how RightRev can help. Visit rightrev.com slash CJ. That's me. That's rightrev.com slash CJ. Yeah, something that I've observed talking to CFOs like yourself is there seems to be this shift in terms of what you consider a budget envelope for allocating resources within your company. Because to your point, Todd, traditionally companies raise a bunch of money.

16:59It's instantly how many people will we hire? But now the more and more what I'm seeing is we have this money. Do we want to spend it on AI and have more agents to deploy? Do we want to buy tools? Maybe it's Azora. And then do we want to hire people? but it's almost as if all of these things are competing for the best marginal use of the dollar. As a CFO, your job is to allocate capital. And like you said, is that capital goes to people or it goes to tools. We are seeing more and more where people are saying, maybe I had some attrition to organization and I don't want to back though. I'd much rather have it in token costs.

17:35And that's one of the things we've moved to in the upcoming budget cycle is you'll have a people budget and you'll have a token budget. I'm indifferent as long as you get the deliverable on how you spend that. I want to make sure I get the return just as I would look to get a return from a large team. I want to get a return from a large token budget. But if a leader tells me they can deliver better with more tokens than people, we'll do more tokens. From your seat, what's more difficult to budget and forecast, your hiring plan or your token allowance? I think we're really starting to learn a lot about tokens.

18:05Matter of fact, we've gone this year from a standpoint of a lot of our original AI tools were seat-based and everyone is moving away from those. We've got one that's got two years left on it. So we're kind of happy about that. But everything else is on a token and we're really having to start to get able to give our people the tools that they need to understand what's driving consumption. So that means having real-time dashboards because it's an interesting thing. It's almost like going to a restaurant, I've used this analogy, and someone giving you a wine list and saying these are all really good wines.

18:37and you just order one and then like, I didn't realize that wasn't a$40 bottle of wine. That was a$400 bottle of wine. And so we need to make sure that our people as they're using these tools can understand, okay, how are the queries impacting their TOFI usage? How is the model impacting their TOFI usage? And I think as people get more sophisticated and understand how to be more efficient on their usage, that'd be really helpful. But right now, we're developing dashboards and helping people learn. But I think we're in the early days of that, but it's definitely a muscle that every company is going to need to learn to build.

19:08And that awareness is so critical down to the individual consumer, right? It's not just the managers that are in charge of this. It has to be the person with fingers and the keyboard understanding how they impact what's spent. Yeah, I think one of the things that we've done is we've given every employee, they got a token budget. We try to make that token budget based on what we think makes sense for their role and what they need to do. They have visibility on how they're using them. And when they run out, look, they can go back and get more. And if we're seeing good value, we are making that available.

19:37But I think it really is how do you change the DNA from a standpoint of, look, you've got a budget. Here's how that budget is used, giving them the tools to see, oh, if I use this model here, it's a third of the cost and I pretty much get the same output. Or I really do need to use this more expensive model. And we're starting to learn is, you know, how do you bifurcate people on teams where it does make sense for certain folks to have a lot more tokens. And that's one of the things that we're learning. and we're learning it with our business partners. I love how you said you're going down to what you think a role would use, right?

20:08Because if you just go down to the department level of, oh, each person in engineering gets this many, well, an engineering manager may not use the same amount as an engineering VP who definitely isn't going to use as much, I would think, as an engineer IC who is just coding all day. You know, absolutely. I think, you know, there's also roles that you might see in other functions that surprise you what folks are using it for. And then you start really digging in and it's like, oh, we're getting some fantastic efficiencies here. We want to encourage where we're getting good return people to use it.

20:37But it really is, like you said, getting down to figure out who's learning and how are they using it. And frankly, I would imagine over time, there's folks who will take it away from because it's like we're not getting good value. On that point, Todd, one of the biggest complaints I hear from CFOs is, look, I know AI is creating a lot of value. I just don't know why my bill is what it is. It's almost just this black box. Do you think the industry has a transparency problem? It's so early on that I think we're in the early stages of learning here. Over the long run, you're absolutely right. When you have these token budgets that are becoming something that nobody was talking about two years ago, that's probably one of the top discussion points right now.

21:18It's something we're going to have to learn about. It's something that everyone's going to have to get an understanding of what drives the cost and what drives where we want to invest. Over time, I think we'll get a lot better. We're all learning. I think different companies are at different places in that learning curve, but companies that are probably the furthest along are giving their employees the tools and they are spending the time to educate them on what drives the usage of those tokens. Todd, you touched on it at the top of the pod of how there was this mad rush for activity for activity's sake, but now CFOs and boards are saying, well, what are we using these tokens on?

21:53What are the jobs that we're completing here? If you tie it back to that, it becomes even more nuanced at the departmental level, right? Because you have a finance team, you look at what the finance team is using it for. We don't have a quota. We also don't have code commits that we're doing. So in order to fully understand, I think the value, there need to be value metrics that are specific to whatever the job function is. And maybe we're not totally there yet. And some of our different functions, for example, in finance, some of the things that we're able to get through in the timing where maybe certain parts of our clothes took days are now taking hours.

22:26You see where we are materially getting a whole lot faster. When I see folks are saying, you know what, we had a nutrition here. I don't need to backfill it. I do start to then see, all right, I'm getting real value there. I'm also seeing, frankly, you know, my organization on the finance side that I own is spending a whole lot more time with the business rather than looking back at closing the books. When I see business leaders wanting to include these finance team members on their team to help drive decisions and analytics of the business, that makes me feel like, you know, we're driving a whole lot of value, especially when I'm not pushing one of them, but they're, you know, actively seeking out their advice and experience.

23:03What's one element of the closed process that's become faster or easier with AI? For our standpoint is, you know, with our Zora revenue tool and some of the ways that we're using AI to read every one of our contracts flag where there's any type of exceptions to make sure that we're getting the revenue recognition right. That was something where you might have to read 100 contracts or amendments as you're going through the closed cycle. And the fact that you can have all that summarized in a few hours is super helpful. We're also seeing in our collections area, we've actually got a Zora tool that is utilizing extensive AI knowledge, and it's really cut down our time that it takes that we spend with customers collecting, and it's also materially improved our cash flow.

23:49So those are great examples I see where we've been able to use AI to give us a much better outcome as a finance function. Okay, Revreca, I've heard of this one. That makes a lot of sense. It's a lot of rules-based stuff, which AI, I think, is pretty good at. Can you touch more on the collections piece? Because that seems to have a pretty heavy human element to it in terms of who's on the other side of the equation. It does have a really heavy human element, but one of the things you see is it's a really super manual. And so the question is, where do you spend time? And if you've got a promise to pay from somebody and it doesn't come in, how do you automate that so you don't have to have anybody ever touch it.

24:25Maybe 90 % of those was all themselves. They don't need another human touch point where in the past they would have had it. The other thing that you start to see is you can have pattern recognition from a standpoint of, all right, here's a customer that for the last five years always pays six days late. A collector wouldn't know that probably. Yeah, totally. That's just how it works. This customer always pays late. So let's go ahead and we'll wait till after that period to spend time on it and it comes in. So it's like, you know, you've sat there and you've cut out doing something that's really non-value add.

24:59It also may give you some really good insights on your customers that are consistently paid on time or early. And now all of a sudden they're paying late. Does that give you some insight into something that's happening with that customer? So we found that our collections tool has immediately improved the productivity of our collections department. And frankly, you know, we could probably double the size of our business without having to make any changes and the size of that group. I find it's the long tail of customers that you're chasing where you're spending two hours chasing, I don't know, a couple hundred bucks.

25:29Todd, that takes the same amount of time to chase somebody that owes you$200 ,000, right? If you're like a B2C business where you've got a lot of small dollar invoices, it just doesn't make sense. The juice isn't worth the squeeze. You'll spend more time, like you said, trying to collect the$99. It'll cost you more than what you collect. How can you use technology to be able to sit there and done those customers and communicated with those customers and answer their questions and go back and even be able to have a conversation with them with an AI agent is something that you're seeing is a lot of value for teams.

26:01Can you say more about the agent piece there? Because collections does feel like a spot where agents could be helpful. What we're really finding is much more valuable rather than having an agent that does like a specific task. How do you train an agent to do a role and really do from start to finish of that role. Now, that's not always going to be possible. And there's always going to be times here at Zorro where we've got people in to make sure nothing goes off the rails. But being able to train that agent, every individual contributor now has a team of agents that they manage. And think about those agents almost like being intern.

26:35The more time you spend with that intern, the more time that you educate them, the better and more effective they are. And so if we start thinking about our teams that way, I think it gives us a whole lot of incremental capacity. But again, you've always got some human that's in there that has to be managing those agents and staying on top of them, just like you would like a new intern or someone that's new to your business. Todd, I want to switch gears and talk a little bit about time to value. I've heard you say that time to value is becoming one of the most important metrics for CFOs. And like I said, I'm a total metrics dork.

27:08So I stuck to this one. What made you realize speed to value matters just as much as the cost? Well, first of all, it has a huge impact on the overall cost anyways. Longer it takes you, the more resources are involved in something. The other way that we learned, especially in our business, is there's only so much capacity to do incremental projects. And a lot of those projects involve finance, they'll involve IT, they'll involve different areas within the business. And if you can take that and shrink that down to three months versus nine to 12 months, all of a sudden, companies are able to do a whole lot more.

27:44But that project that they were originally doing, it's going to be much more, it's going to bring the value in much quicker. But secondly, it's much more likely to go live because the longer it takes things, we all know different things happen. Economic things happen in leadership and sponsorship. So if you can sit there and tighten it, you have a much better chance of getting the project live. You can get the value much sooner and then it gives you opportunities to do other things. You make such an amazing point. And I've seen this happen before where you sell a deal and then the internal champion, because it takes six months to implement, just isn't there anymore.

28:18You're taking potential objections or own goals off the table. Yeah, there's an old saying, time kills deals, but I'm a big believer we've also talked about implementation time kills deals. The sooner you get that up and running and it becomes part of the workflow and it becomes part of the company's DNA in our product, it's a mission critical system. So once we have it in their life, our chances of not only retaining that customer, but growing it are just exponentially better. So, you know, it's within our interest to get those customers live as soon as possible. And that's one of the areas that we spent a lot of time on investing in AI to really allow us to see some big breakthroughs.

28:54How is AI making implementation easier? We just introduced a tool here at Zora called Milo. And Milo is really allowing us to take a lot of heavy lifting that our customers were doing in the implementation. And it's allowing our AI agents to do that. We've been able to do that because we've taken almost 20 years worth of information. We fed into the models. Our experts have been involved with it. And what we're seeing now is, you know, we could do one of two things. Even before we sign a contract, we can turn over an environment to a customer with their data and they can play with it and see how our product will work.

29:28Or we're seeing, you know, we can sign an agreement and what would have taken maybe six to 12 weeks before we could start to test. They got the environment that's there and it's ready to test on day one as soon as the contract is signed. So that provides a tremendous value. It takes a lot of the heavy lifting off of our customers and we've been able to do it. If you think about the experience that we've built in, what's going into that user testing is going much quicker because it's a much higher quality data just because of how we've structured it and all the learnings that we put in place that don't happen on a one-off engagement when we work maybe some of the old ways that we did.

30:02I very rarely heard this before, Todd, in finance, almost, I don't know if you'd call it product-led growth, but basically being able to use your own data before you sign a contract. That's kind of unheard of in the finance and accounting world. I think it's an area where we're showing if we can get that data and sometimes customers will give us big chunks or just small pieces of it. But I think it really helps when you can sit there and say, rather than theoretically, here's a demonstration. Here's a proof of concept. Here's your data. Here are your business processes. Here's how you operate.

30:33And here's then the output that we can give you with our tool. I think you just trust it more, too, because I've been on demos where it's like, here's a hypothetical$100 million revenue company. They spend$80 million a year and their profits are$20 million. It's like, okay, these are just round numbers. I can't really see myself in this tool. I think about the Arzora tools. You know, they work in the quote-to-cash process, which is super complicated, like you said. But if you're able to sit there and show someone, here was your pain point. Here's your data from last quarter. I see where your tool did exactly what, you know, my team took three weeks to get done.

31:09And it was done within an hour. all of a sudden, you know, it becomes a very different conversation. And those are the types of conversations that we want to have with potential customers. You mentioned agents. What are you seeing in terms of forward deployed engineers? This is a term that's being thrown around a lot. One of the things I was just talking about is, you know, how do we move away from demos and how do we go ahead and take your data and show you what we can do and take it from there? So, you know, that becomes ready to use on day one is absolutely where things are going. Who do you think owns that work?

31:39Is it the job of the vendor selling the software to get in there and help you rig it up? Is it the job of the customer to make sure they have resources allocated? Is it somewhere in the middle? You're always going to need to have a certain level of customer engagement. They've got their data. They understand their processes. But I think the question becomes is, how do you go in there and make that lift as light as possible for that potential customer? But that being said, I think you've got to make sure you've also got the buy-in from the customer to like, yep, this is my data. Yes, you understand my process.

32:07and as you're rolling through it, they're like, okay, I understand how this works in my business. And I think as you just said, it's not a theoretical. I see my business and I see pain points and I see pain points being resolved. A wise man once told me that every startup is really just a loosely functioning disaster. Ain't that the truth? If your startup needs a little extra support, and let's be honest, who doesn't need a little help now and then? You're in for a pleasant surprise with Fidelity. Fidelity Private Shares helps early and growth stage companies stay investor ready with cap table, data room, and scenario modeling all in one place.

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35:13That could be you too. So head over to cloudcapital.co, that's cloudcapital.co, and find out how much you could save. Todd, I want to talk about VMware for a bit because you had quite the run there. But before we do, what parallels do you see between the move from on-prem to cloud and now today's AI transition. How you do business is really changing. Who's in control of the data and how does that impact business outcomes is exactly what you're seeing there. I think the biggest difference though is just the speed at which this is happening. Being able to envision something and then having something on your desk where it can be used and people see business outcomes, you know, where in the past people were willing to look at things from, you know, months or years.

35:59Now it's like hours and days. So you joined VMware, you're expecting to help grow a business, but instead you found yourself helping rethink the strategy that you originally brought in to execute. What were the first signs that the original assumptions may have shifted compared to the reality of the business? I think sometimes it helps when you got a fresh set of eyes and you come in and you don't have the encumbrance of, you know, how people originally thought about it. But in this case, Basically, it was a business that came in. We had the vision to be able to really host a lot of that capacity on our own data center sites.

36:31And it started taking a look at what that capital buildout was going to be. It was really clear that it was something that was not only going to exceed the balance sheet of the company, but it was something that the investors, you know, had no interest in underwriting. And so it really gave us, you know, kind of a pause and how do you go back and relook at this and think about the problem very differently. So it sounded like it was much more capital intensive than maybe you originally thought. This was a time when we were all sitting there going, oh, my goodness, I can't believe that a hyperscaller is spending a billion or two billion dollars a quarter on CapEx.

37:03And, you know, today, you know, that might be, you know, a day's worth of CapEx. So you're in this scenario. How do you avoid falling into the sunk cost trap when you've already invested so much time, money and credibility in a strategy to make sure it doesn't happen? A couple things are really important when you look at the, like you said, sunk cost trap. One is to be able to go through and just talk about, okay, if we want to do all of these different things, what are the things that need to happen? And just as you start lining up, I want to say maybe it's a business case, but you just start walking people through.

37:34This happens, we've got to do this. And you just walk people through. You can build a really clear picture of that. I understand that maybe this has got some difference. Maybe we do need to revisit. it. Even in sales teams, I think is one of the things that is interesting is someone to be working on an account and they work so hard on it. It's like, they're so close. You come from the outside, like, this is just never going to happen. You know, it's got all the red flags, but it's like, but I've put nine months in this pursuit. And sometimes it's saying, you know what, I understand you did that.

38:00You're going to end up with zero in another three months. Toss this one away to, you know, move it as, you know, not going to move forward and go spend your time on something where you can make some money. I think sometimes you've got to have the willingness to look to say, hey, the world has changed. The assumptions that we put down when we started, they were maybe in the right assumptions there, but for whatever reason, it's not where we are today. And I think the ability to say, we made judgments based on the facts we had at that point. Things are different now. We're never gonna get there or it's highly unlikely or to get there is gonna be so cost prohibitive that it just doesn't make sense for us.

38:33But you've gotta have that willingness to be able to pivot. And I think organizations and as leaders, You know, it's really important for us to allow our teams to be able to do that, to say, hey, we progressed on this when we started on it. It seemed like this made a lot of sense, but where we are today, we're better off shutting this down and moving on to something else. And I think that's one of the things that, you know, really good leaders help teams do is take a look at whether it be a sales cycle, whether it be a major product, is being able to be really objective about them is super helpful.

39:01What did you learn about pivoting to create value? Because I really do think that there's an art in pivoting. How do you make sure that you're looking externally, not internally? You know, it becomes really easy. I think at times organizations become really internally focused and not realize what's happening in the greater good. I think the second thing is, do you have teams that are willing and do you have, you said, an environment that you're willing to have hard discussions and for people to raise their hand and say, you know what, this doesn't feel like it's working. Something's not here. And I think the last thing is smart people learn.

39:33And smart people, when they get new pieces of data, are willing to make different decisions. And I think it's really important for leaders to be like, oh, I've already made this decision. And I'm going to look like I fail to sit there and say, all right, we've run this through. And now where we are, it's time to move on because this is going to move forward. But those are the things that are super important for organizations to have. And you kind of get that through culture and the DNA of the people that you bring in. Strongly Hell believes they're probably better for religion. and not for business decisions.

40:01You've got to be willing to sit there and say, I've got to be pragmatic. And I had a belief here, but the facts are telling me different or the environment has changed in such a way that I should pivot. Do you think the experience of VMware of pivoting helped you as a CFO taking your current company private? I think it's really good to have a whole bunch of different experiences in your life. And I would sit there and say with that experience, it was something that was really unplanned. It was not the growth that we expected because it was basically a business unit that had been ramped up and had a lot of investment.

40:32And we ended up dismantling it, bringing in a partner, and then selling off the rest of the pieces. I think it's a really good experience. And I think it's one of the things that, frankly, there's been a good news and a bad news. A lot of folks that are probably 15 years of experience haven't seen a lot of down cycles in their career. And I think having those experiences when things go well and things aren't going well is really important. For our next segment, I want to ask some better questions brought to you by our friends at EY. And let me tell you, they think a lot about great questions across enterprise risk, audit, diligence.

41:05They're a smart bunch. So I'm going to ask some smarter questions right now. I've talked to multiple CFOs in the podcast, and they've reflected that there is a generation of leaders who have never had to manage in anything but a good time. I think you have to go through multiple waves in order to figure out how to make those tough calls. It's easy to always be saying yes to stuff and coming up with more projects to fund, but it's a lot different when you have to go about it with a different budget envelope. One thing that's fascinating about AI is nobody truly knows exactly where the value pools will end up.

41:38Do you think going private effectively gives you the option to experiment more without having to justify every experiment in a quarterly earnings call? We're no longer focused on, like you said, the 90-day cycle. I can probably think of five different examples in the last 18 months. We've gone to our board and said, you know what, this is the right decision for the company in two or three years, and we want to do it. But it's going to have this near-term consequence that maybe wasn't our plan. And in every one of those cases, we've gone ahead and done it. The private equity investors, they're probably much more knowledgeable than most public boards.

42:11They've written a check for it. They're going to be super disciplined. So it's not like you have a free ride, but they've got conviction in what you're doing. And if you have a good plan, they're certainly willing and have a different time horizon than maybe an investor on a public company stock. So that certainly gives you a lot of freedom to do some things that are much longer range. But no one should misinterpret that as a lack of discipline. Can you say more about the involvement of the boards and the focus and maybe the value they're able to add in the private markets versus public? A couple of things that I've seen with our board is they are aware of our marketplace.

42:47They know the different dynamics that we have. Their experiences are really super relevant when we're talking through decisions we want to make, maybe problems that we face. On top of that, they've got a lot of skin in the game. They're paying a lot closer attention, I would say, oftentimes than maybe public boards are. That level of expertise that they have and that they can go down and that they know your asset and they know the marketplace is really a lot of value to the management team. Do you think a lot of public companies are optimizing for reversibility? In other words, do they avoid making bets that look bad for a few quarters, even if those bets will create enormous long-term value?

43:25I think it depends. I mean, there's obviously companies that have done really well in the public and have made some of those investments and they've taken some pain along the way. it's much harder to do in the public market. And so, you know, there's a time and a place for a public company and there's a time and a place for the private. And we just felt right now is the right time for us to be a private company. How do you think about the concept of one-way and two-way doors as a CFO? I mean, you're making calls that sometimes you can rewind, but other times it pushes the company in a direction where, hey, this is the course of action.

43:55These are the tracks we're going to be on. How do you think that those decisions? Recently, you know, one of the things I've said to our teams are, I need you guys taking more risk. I need you to move fast. We hire people because they're smart people and they have good judgment. Probably 90 % of the decisions that we make are two-way doors. And so run through those two-way doors, go do it. You're going to end up moving a whole lot faster. Make sure we sit there when we find out something's not working. Hey, we can go back and we can do something else. But in general, we're going to gain a whole lot more yardage on the play.

44:24But on those one-way doors, those are the ones that we really want to think about. Those are the ones we want to bring in, you know, the right leaders and we want to be thoughtful about them, make sure that we understand all the repercussions on. But most of the decisions we make are two-way doors. Let's enable our people. Let's have them go do that. Throw the ball deep. And if we have people that continually make bad decisions, that's something else to deal with. But because we may have one or two people that make a bad decision, let's not restrict the entire organization from being able to run.

44:51Because in general, we've got really smart people and they know what to do. Let's get out of their way. Todd, I'm going to take you into what we call our long ass lightning round. So the first question I ask every successful leader on the show is give me an example of something you've screwed up on the job before. It could be here or a previous role. The euro had just come out and we had priced a deal all in euros and the currency absolutely took off and made it for a really ugly P &L for a while. What did that teach you long term? As you start getting engaged with things that maybe you don't have deep experience on, make sure you reach out and constantly get you know, counsel from others.

45:28When folks are younger in their career, it's like, oh, it's a sign of weakness if I'm asking for help. And I think it's never a sign of weakness for making sure you got the best available data. Never fail alone there. If you could tell your younger self something knowing what you know today, what would you tell them? When you decide you want to go in an area, go for it. I always had an interest in finance and, you know, that's where I really focused myself on. And I think that's really good practical advice. You know, as you start getting deeper, you can start adding more value and it really helps you progress in your career.

45:56Can Can you walk me through your finance software stack? What tools does your team use to get the job done? Our most important thing that we use is our Azora application. It does run all of our, both the cash. But look, there's a lot of great tools. We use Workday's Adaptive Planning. We use Blackline. We use Koopa. There's quite a few off-the-shelf tools that we use, you know, to run really efficiently. We're pretty much able to close the books in about three days here. One of the things when I first got here, I want to get the clothes way down. And I think a lot of people are like, why are you so obsessed with this?

46:26And I just kind of explain it to folks from this way. It's like I can either spend 15 days of the quarter looking backwards or I can spend five days looking backwards and 15 days looking forwards. And I want our team looking forward. And I think now we can spend 85 % of our month looking forward. There's a lot better value to the company. Last one I got for you. What's the craziest thing you've ever had someone try to expense? I had a business leader that was giving out these gift bags that looked like they were more like something that you would get at the Oscars. Her intent was she wanted to motivate people.

47:00It's something that maybe they wouldn't buy on their own and to really reward good performance. And she had fantastic followership. The problem was, you know, just the optics of someone getting a$25 ,000 to$25 ,000 gift bag is probably not the controls that you need to have as a large company. the company and probably is it the right optics that you want to have for the organization as a whole. Todd, this has been a blast. Thank you so much for coming on the show. Thank you, CJ. Run the Numbers is a mostly media production. Yelling an intro by Fat Joe. Artwork by Meg D 'Alessandro. Nothing said on this podcast is intended to be business or investment advice.

47:33It's the sole opinion of me, a guy who feeds his dog way too much ice cream and has a history of net operating losses. LOL. If you like this podcast, hit subscribe and give us five stars. It will take like two seconds and our algorithm overlords love it drink water call your mom and have a great day peace