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The Margin is a podcast from MGI Research that explores the evolving world of business monetization. Hosted by MGI Managing Directors Andrew Dailey and Igor Stenmark, the show features candid conversations with founders, CEOs, product leaders, and industry experts at the forefront of pricing, billing, and revenue operations. Each episode dives deep into the strategies, technologies, and trends shaping how companies generate, capture, and grow revenue—from subscription and usage-based models to AI-driven monetization. Whether you're in finance, product, or IT, The Margin offers practical insights to help you navigate complexity and drive growth in the digital economy.
Andrew Dailey: Welcome to The Margin, a podcast from MGI Research. This is Andrew Dailey, Managing Director and your host for today. Is AI going to destroy software margins and put legacy SaaS vendors out of business? What are the business benefits of AI, and can AI practically benefit finance teams? What does CFOs and COOs need to be doing today to ensure their businesses stay competitive in this new era of AI? To help shed light on these questions and more, I'm delighted to be joined by Todd McElhatton, the COFO of Zuora. Todd brings more than 25 years of experience as a CFO and finance leader at companies like VMware, Oracle, and SAP, where he was the CFO for North America, and also served as the CFO of SAP's Global Cloud Business Group. In addition to his current operating role at Zuora, Todd serves on the board of Teradata and is a member of its audit committee. Given his history working in finance, and at companies managing through critical periods of technology disruption, he's ideally suited to discuss the challenges and the hidden opportunities AI may bring to business, software companies, and finance teams. Todd, welcome to The Margin.
Todd McElhatton: Andrew, thanks for having me. Good to be here.
Andrew Dailey: So, of course, the topic of the day is AI. Let's jump right in and just start with, first, do you really think usage-based AI products represent an existential threat to the traditional seat-based pricing model of SaaS companies?
Todd McElhatton: I think there's a lot to unpack in that. There are certainly some companies that it is going to be an existential crisis for, especially companies that have the opportunity, or their products are just going to be subsumed by what AI can do. I think as you take a look at some companies where they're going to have an existential change in their workforce, think about autonomous driving. Think about autonomous trucking companies. If you have something that's seat-based on a, let's say, time and attendance, and all of a sudden 80% of your workers go away, and those become autonomous. That's going to be a real challenge for some companies. There are other companies that I think it's going to be a huge opportunity for them to reinvent themselves and find new business models and move forward. So I really think it depends on where the space of individual companies are.
Andrew Dailey: Well, let's make this real and talk about what's going on at Zuora. How are you modeling revenues in light of AI, and how are you thinking about pricing new AI products?
Todd McElhatton: I think recently there's been a lot written about software companies being dead and I think that that's an oversimplification of what's happening in the market. I'm going to take Zuora as an example. We are a system of record, and I'm going to say system of record companies are here to stay. And there's a reason they're here to stay. They deal with really complex business issues, they are mission critical, and probability doesn't work. You need to be precise. I take a look at Zuora customers. A small customer we may process 3,000 transactions a month for, and our largest customer we do 22 million transactions. So you think about what you hear about AI, and, oh, we have 90% probability of being accurate on the high end. Do you want that many of your transactions being inaccurate every month when you're invoicing your customers, having to collect and recognizing the revenue? That just isn't going to work. And so, when I take a look at a company like Zuora, I think AI is going to be a real tailwind for us. Because, first of all, companies are moving to different business models. They're looking how they can, as you said, Andrew, use usage and consumption-based models. We have a unique expertise there, which we're going to be able to help them navigate that change. That change also is more than just being able to meter and rate and bill, but how does revenue recognition work? How do you make sure you're collecting? Having a platform that brings it all together, I think is something that's going to be super unique to us and allow us to help. But if I take a look at how we are using AI internally, it's also giving us some huge opportunities to gain huge efficiencies and also bring ourselves into new markets. One of the things that we've been really focused on is how do we use AI to take our time to go live and dramatically bring it down? And we recently took a customer, and from the time they signed the agreement, matter of fact, the day they signed the agreement, we gave them a fully configured tenant, said it's ready for user testing. Six weeks later, that customer is live. That was our first customer, but I think we'll have about a dozen or so in the next, let's say, three to six months, and if we can prove that hypothesis, that'd be a huge open up for new companies that maybe wouldn't have gone to Zuora initially, or would have delayed a decision because of the time and effort it was going to take to migrate. So from that standpoint, that's going to allow us to provide a ton of value. I think another object that you had talked about is how will AI impact pricing? I think AI will only impact pricing If it's adding value. And that's certainly how we're looking at it at Zuora. There's certainly a lot of functions and features that we're adding, but the only way we're going to be able to monetize those is if customers see value. And if customers see value, and that drives incremental cost to us, because of maybe the compute costs they drive to us to deliver, then we'll certainly be able to monetize them. If they don't add value. We won't keep on doing them, nor will we monetize them.
Andrew Dailey: Yeah, and that certainly rings true in all the conversations we're having with clients, and in all the survey data that we're collecting, and that CFOs and CIOs alike are willing to pay more for IT, for AI, if there's a business benefit, and if there's no business benefit, of course, they're not going to pay anything. So that's on the revenue side, though. What about the cases where you're including AI or infusing AI into the product and not able to charge for that? What do you think the hit could be to profitability and to your margins?
Todd McElhatton: It's an area that we're watching really closely. We're in the very early days of that. But what, again, I would go back and say is, I think what you'll see most companies doing is they'll put some sort of guardrails on what type of usage that you can have for AI, and once you go beyond those you'll have to sit there and say there'll be some sort of incremental upcharge or some sort of usage charge for that. But again, if you're going to have that usage or upcharge, there's going to have to be clear value that the customer's getting. Now, I agree with you, there's certain pieces of it that we're going to be able to embed in it, and it probably won't have a huge cost, and those will be things that vendors like Zuora will eat that, and that'll be a part of our ongoing margin. But I believe if we end up saying that we're going into applications that have a really heavy compute usage, there will have to be a way that we monetize that, because the only reason that we're going to be doing that is that customers see value from it, and it will have to give them great economics for us to want to continue doing it.
Andrew Dailey: So what you're implying is that you and everyone else in the market is going to have to have some way to track usage and consumption. Even if they're not charging for usage or consumption of the product, you've got to have some way to keep track of that.
Todd McElhatton: Absolutely, and you take a look at maybe some of the premium, versions of some of the AI tools that are out there for consumers. You have an ability to do a certain amount of search, you have a certain amount of query, then there's a governor. I know I've gone out to different things, and it's like, “hey, you'll have to come back tomorrow for this, or you can sign up for this package.” And so I don't think that enterprise software will be a whole lot different if you're finding that folks are using really are heavy users of things that are driving a lot of incremental compute and expense for the vendor.
Andrew Dailey: I want to go back to one of the comments you made earlier, which is as the Chief Operating and Chief Financial Officer, presumably precision and accuracy in numbers matters to you. Generative AI products and agents are probabilistic in nature, and you need deterministic outcomes. Where do you see, if anywhere, a fit for Gen AI and agents within finance?
Todd McElhatton: There are a lot of places where we're using it today. I think about Zuora's collection product. It happens to be our product, but the ability for us to go out and automate a lot of the functions that were done previously by people is being done agentically. The ability to do forecasting from what we're seeing coming back and forth and comparing it to previous periods, that's been a tremendous benefit for us. As a matter of fact, it's something we've productized and we're getting really good traction in the marketplace. But I think of in other places where we have routine reconciliations, preparing different memos, taking forecasting data, preparing different sets of analyses, and doing some of that flux analysis, there's a ton of places where AI, aided with the right amount of human supervision, can add a tremendous amount of value and take a tremendous amount of time off of our employees’ workday, and allow them to do things that add more value. So there's a ton of places where AI is absolutely going to transform finance, it's absolutely going to make us more efficient and do be able to spend more time on tasks that can drive value. But it's also going to need to be really thoughtful on how it's used. To your point, it needs to be auditable, it needs to be traceable, and we need to make sure that we just don't turn things over to AI and not be able to understand the end-to-end process.
Andrew Dailey: I think we were at an event together a few weeks ago, and you were on stage and made a comment that this might be the year where we see the $100 million or $200 million restatement due to AI. Any comment on that?
Todd McElhatton: I absolutely think it's going to be true. I think I also gave an example. We had a member of our accounting team who was looking to do kind of an interesting something, or enter in a transaction that's not something we usually do, and went out and said, “hey, how do we book this? What's the right way for accounting of this?” and got this extremely detailed version of here's how you would do it, super compelling, gave all the examples, and was like, “hey, let's go with this.” And then she made the decision, “hey, let me run this through another tool, and just double-check this.” And it came back with a 180-degree different answer. And again, it was also equally.
Andrew Dailey: It's equally compelling.
Todd McElhatton: And I think the good news is that our team had the good foresight and judgment to say, “okay, I got this but let me verify it I'm going to look at it, it looks reasonable, let me verify it.” And I fear that we're going to have a bunch of folks that have stopped verifying things. It's like, “oh, I've got it from here, it must be truth.” I think it's like anything. If you take a look at how you source any type of information, there's very few of us that when somebody gives you one point of data, says, alright, I'm going to go all in and make a big decision based on just that. I'm not going to maybe triangulate with multiple data points. And so I think that's one of the things that, as leaders, we really need to make sure our people are doing, is that, sure, trust the tools, use the tools, but make sure you're verifying them, make sure you're using the same sense of rigor as coming to a conclusion as you would have done without AI.
Andrew Dailey: Yeah, so HI and HE, human intelligence and human experience, are as critical as ever.
Todd McElhatton: Absolutely, the models are as good as they're trained, and there's always going to be things that have changed, or things the model wasn't trained on, or could have been trained inaccurately. And so, just as you would double-check something in real life, when you got it from a source as a person, you should probably do the exact same thing when you're dealing with AI output.
Andrew Dailey: Yeah. Let's shift gears a little bit. It was just a little more than a year ago, last year, I think February 14th, right?
Todd McElhatton: Happy Valentine's Day!
Andrew Dailey: Zuora went private in an all-cash deal, valued at about $1.7 billion. Silver Lake, who's one of the most successful tech, arguably the most successful tech. private equity firm, out there, as well as GIC, which is the well-known, well-respected Singaporean sovereign wealth fund, are now your Partners in the business. Deal was announced five months prior to that. Describe the end-to-end process that you guys went through as a public company that then took the business private.
Todd McElhatton: So it's a really interesting process going private. We had some interest that came in, and our board of directors, of course, needed to figure out how to act on that. And because of the special structure within Zuora, and the fact that we had a founder who had an awful lot of voting control of the company, and we also had Silverlake, who sat on the board, who had a major pipe investment in us, it was determined the best way to move forward would be to form an independent committee. So that independent committee came about, and I'm going to say it's all publicly available. There's 20-some different folks that we talked to over a number of months about the, potential of them taking Zuora private. And ultimately, the board made the decision that teaming up with Tien and Silver Lake and GIC was the best outcome for the business, and we ended up going private. And it was a really interesting experience. We went through a lot, we spent a lot of time with different, sponsors and private equity firms, and we learned a lot. I think it was really interesting to look at how they looked at the business, and I think it gave us some new insights to the business, as you saw different ways people questioned things, and how they dissected the business, and how they analyzed it. I think it helped us a lot understand, hey, are there areas that we could maybe do some things differently? And, it's been a really positive experience for us, and ultimately. Silver Lake and GIC consummated the transaction, and it's been about 13 months now that we've been private, and quite frankly, they've been 13 of the most productive months that I've had here.
Andrew Dailey: Yeah, we'll get to that. What was the best advice you received during that process? Because presumably, that's a highly scrutinized process. A lot of shareholder view into what's going on. You've got to disclose everything. What was the best advice you got through the process?
Todd McElhatton: I think the best advice you get is from your outside counsel, is to make sure you run this thing by the books, and that everybody has the same access to the same information, and we again just ran a really tight process where everybody had all of the information, and it was interesting. I think, at the end of the day, I want to recall, I think we generated about 139,000 pages of due diligence for all of the different, participants that looked at the company. So, and that was all sealed off in the, due diligence room.
Andrew Dailey: To the degree that you're willing to or able to share, you mentioned some of the things that you learned in terms of how other people look at a software business. What was most enlightening for you?
Todd McElhatton: I'm going to put it this way, I think when you look at things sometimes as you're in the day-to-day, you don't have the opportunity to kind of zoom out, and you sit there, and you may think, hey, we've made a lot of improvement in one particular area, but then somebody gives you a different way or a different metric to compare it against, and you're like. I hadn't thought about it that way. That really makes a lot of sense, and there's maybe more room where you can do a lot better than what you thought you were. You kind of sat there and said, we're at X, and we made huge progress to get to Y, but quite frankly getting beyond that. there's also a lot of room. And so just having that aperture opened up, and taking a look at different ways to look at things, and having people ask sometimes questions, you're like, “oh, that that was kind of a really basic question,” and sometimes when you really get down and you're working in things, sometimes things that are, at the root, you didn't kind of—maybe not at the root, but you didn't kind of sit there and consider it the same way.
Andrew Dailey: Was it hard as a management team with a founder and a significant shareholder as a part of that team? Was it hard to kind of create that separation or that distance to have that perspective on the business?
Todd McElhatton: No, it wasn't. I mean, I think Tien obviously founded the company, is super passionate about Zuora, but he also understood his fiduciary duty, and quite frankly, has always wanted to do what's right for Zuora, its employees, and customers. And I think we feel really fortunate that we ended up where we did, and I think that's worked out very well for all of those constituents.
Andrew Dailey: Yeah, given the tumult, let's call it, in the public equities markets lately, and private credit market for that matter, it's probably fair to say you don't miss the quarterly march and are pretty happy to have investors with a slightly longer investment horizon by being private. What can you achieve, or what are the things that you can do now that you couldn't do as a public company?
Todd McElhatton: I get asked that question a lot, and one of the things I'll say is I don't think we made bad decisions as a public company. I think we worked really hard to do the right things. But that being said, you are judged on 90-day intervals, and oftentimes the people that are judging you are stretched really thin. They've got large portfolios, or they're analysts that are covering a lot of companies, and they just don't have the time and the resources to go really deep. And so they kind of go an inch or two deep, and based on that, there's conclusions that are drawn, and decisions are made, and that has a huge impact on if the share price goes up or down. And so, there's a lot of times where you'll optimize on those 90-day cycles. And one of the things that we're doing right now, and I think this has been something that's been really a breath of fresh air for all of us, is having the discussion of “look, we started off with a plan, we were going to do X, Y, and Z,” but the reality is if we did these things you find different things that happen during the year. We'd be in a lot better shape as a company in two years.” It's like, well, why aren't you doing it? Let's do it. And so there was a number, I can think of, like, three specific instances last year where we sat there and said we had a plan, but we wanted to do two or three different things differently. It had an impact to the financials, and you may have sat there and said, well this hit kind of this was going to be a little bit of a slug in a quarter. But it put us in a much better place for where the company wants to be and should be in two years, and we've done it. And employees are happy, customers are happy, and I think, ultimately, all the shareholders that we have, and that includes GIC and Silver Lake, and employees who have invested back in the company are going to be much better off for that. And if I take a look at the level of customer satisfaction we have we've seen a big increase in that, and again, it's really allowed us to maybe make some investments in customers that it would have been harder for us to do that in a public environment.
Andrew Dailey: You know, the one benefit of being a public company is it's a 90-day measuring stick and probably sales and finance the most of all. Do you feel like you lost any of that kind of intensity, or the quarterly drive that helps close business? Does that get lost when you go private, or does that stay the same?
Todd McElhatton: Absolutely not, and if you asked our head of sales, I think he would tell you that I have not relented at all. But when you look at it. The interesting thing is we had a very good board, and our board was really helpful. But our board now is intimately involved with the company, and they've got skin in the game. It is their cash and their equity that is tied up, and that is the only way they get paid, is if this company does well. And so, you certainly have board meetings that are, as a matter of fact, probably more frequently. And you have much more greater level of detail and analysis, and it's just not analysis for a standpoint of, hey, let's pick something apart, but it's like, what's working well? What should we do faster? Were you having problems? How can we help you with it? But I would say the scrutiny of a privately owned company where your board members have put cash in and have an expectation. is much greater than you'd ever have in the public market. So I would say our level of discipline has absolutely increased. I think we ran a pretty tight ship before, but we, absolutely have that level of discipline, and those quarters matter as much now, whether you're public or private.
Andrew Dailey: Yeah, and you're right, there's a level of… there's an ability to have more substantive conversations at the board level. Because everyone around the table's got a better understanding of the business. It really just changes the whole conversation. So… you know, going back to the AI theme here, AI's been massively disruptive for companies. You know, if you just look over the last month, and the number of CEOs. That have been replaced, or who are suddenly retiring. That's taking place. Valuations have been going up and down and sideways for SaaS companies. And at the same time, the AI startups are being lavished with, with capital at previously unheard of valuations. As someone who, presumably, you're looking at the markets actively. And looking at M&A opportunities. Where do you see valuation multiples going, given everything that we've just been through in the last You know, not even 60 days.
Todd McElhatton: I mean, I think the one thing that experience gives you is, hey, there's always ebbs and flows in the market, and I can remember back in 2000, when we talked about a lot of these dot-com companies were coming out, and think about the names that were going to take over the world. And some of them never made it more than a few quarters, had fantastic valuations, And famously imploded. And then there was also some businesses that came out and are today's giants. So I think we're going to see some of that, and I think you're going to see companies today, where people have said, oh, is this company really going to exist? There's going to be the same thing. There's going to be companies that absolutely thrive in that. And so I think it really does depend on the company, I think it depends on their level of innovation, their ability to change with the market space, and move forward. So I think it's you can't brush it over with one you know, stroke of paint to say everyone's going to end up looking like this, and these AI companies will rule the world. It would not surprise me if some of the companies that have a tremendous amount of funding today, we find out, are one-hit wonders. And some of them, maybe, that are just coming up turn out to be truly the stars of the next decade. But I think it'll take a little bit of time for us to find out, and some of the companies that have been around, I think are going to find ways to flourish, and they'll even have greater importance as they move forward, and they'll use AI as an accelerant, and they'll use the information and data that they've had that have led them on the journey for however many years they've been along to really accelerate in the area where they have expertise and domain expert… or where they have domain expertise.
Andrew Dailey: Where do you think companies can find the dollars to… incremental dollars to invest in innovation? There's a lot of… a lot of pressure on folks like yourself to deliver increasing profitability. But to do that, it comes at a cost, right? So, where do you find the dollars to fund the investment that's got to go into new AI products?
Todd McElhatton: From my standpoint, I think we've thought about it in a couple different ways. Maybe I'll just kind of take you on our AI journey. I'd say a year ago, we wanted to really get people started comfortable with, hey, what is AI, what can it do, and how can you, as an employee, use it on a day-in and day-out basis? And our employees really took that seriously, our leadership took it seriously. I want to say we invested in a dozen different tools, and just wanted people to kind of play with it. See what you can do, see how it can help you in your everyday work. And what we found is, we got 90% of our employees plus our daily users of AI products and tools. So, that's been great, they've gotten comfortable with it. But where we really take it from last year to this year is, it can't be a hobby anymore. And so, I've kind of sat around and said, there's 5 areas we're really going to focus on AI. First of all is. on the productivity from a standpoint of our tech ops and support. What can we do to take things off people's plates that are kind of the rout, the mundane, people are looking for an answer. But we can do it much quicker, much more efficient, and allows those people in those roles to really spend time where customers are challenged, and they're going to get a better outcome. And we feel like that's a great way we can, A, get more efficiency and more customer satisfaction. If we take a look at the productivity of our people that are developing code, we've seen a portion of our environment get up to two times more productive. And we think by the time we get to the end of the year, we'll get almost all of those folks more productive at that 2X, or maybe a 3X level. And so I think when we see that level of productivity, that might allow us to take some people that are doing code, maybe we move them to PM roles, maybe we move them into PMM roles, so we can get more, innovative, and we can roll out more products and features. And so that's an area that we're really focused on. We sit there in our time to go live, or our time to value, as I talked about. You know, being able to bring a customer live in 6 weeks is incredible. If we can really continue that on and make sure that every one of our tools, our advanced revenue, our billing, our collections products are all doing that, that opens up huge new opportunities for us in the marketplace to sell. And so we're really focused on that. We're focusing on our services business. How do we develop SOWs and architecture plans much more quickly? So again, we can take out labor, but we can move faster with our customers. And then it's always interesting in the go-to-market space when you hear that 50% of your sales and marketers time is not spent with customers, but it's doing administrative things. And we've got a couple initiatives underway where each one of these initiatives can probably put one to two points of growth or savings to the bottom line. So if you sit there and say, I've got five of these things, and each one of them have one to two points of impact to the business, that opens up a lot of investment opportunity for you. And that's really how we're approaching it, is how do we get really focused, where are the pools of potential efficiency or growth, and make sure we put all of our wood behind those arrows?
Andrew Dailey: And presumably, if you can get an incremental 25% productivity out of sales, for example, that's tremendous.
Todd McElhatton: That is tremendous. And so, we're taking it slowly, we're wanting to make sure we absolutely have proof points. The one thing that I've done is I've got my head of internal audit is actually the person that's in charge of tracking what are the gains that we're getting. So I want to make sure that we're actually getting real hard savings or real hard gains. It's kind of not the soft and squishy, well, here I think Tien Tzuo, who's our founder made the comment, I absolutely agree that we're getting more productive, but what I need to understand is what's happening with this level of productivity. Is this level of productivity going into something that creates value, or are we just off on a side project that doesn't create any incremental value? So we've really got to make sure that when we get that value, that we're then able to redeploy it into something, that effort and time, into something else that drives further value to the company.
Andrew Dailey: Yeah. In closing, what's one thing every CFO should know about Zuora but doesn't?
Todd McElhatton: I think the one thing that every CFO needs to know about Zuora is the fact that we have a quote-to-cash platform. That literally can allow you to evolve with almost any business model that you need. So if you start thinking about how quickly businesses change, especially in, like, in the last couple years, we went to a recurring revenue model. Then from recurring, it's like, well maybe I want to make some sort of commitment. Now you're seeing, maybe I make a commitment, but I can use that commitment in a… think about marketplaces. You can use it for the company, or you can use it outside that marketplace. I have consumption that I want to use. I want to have metering and rating. I have revenue recognition, and the ability that we have a technology platform That is getting much easier for people to implement. That can future-proof your business, and really allow you today to go in, and instead of having your accounting teams or your engineering teams build this functionality yourself, or doing these things manually, we can really open you up to a lot more efficiency, but quite frankly, we can allow you to have that agility that you need to switch to these business models in real time. And I think that's one of the things that I'd really like to see people be able to take advantage of, and I think that is a huge, that's been a huge driver of growth for a lot of our customers that we've taken through over the last couple years as they've gone through this journey. And I think it's one of the things that, more and more you're going to see Zuora, when you take a look at a tech stack, you're going to say, absolutely, Zuora's part of any modern company's tech stack. That's got a recurring or consumption revenue, model.
Andrew Dailey: Fantastic. Todd, thanks for being on The Margin.
Todd McElhatton: Thanks a lot. It was good to talk to you, Andrew.