Today’s guest is perhaps the leading CFO name in data and analytics, the ex-CFO of Tableau and DataRobot. Now as Founder & CEO at Caliper, Fletcher draws on over a decade of executive experience at the intersection of finance and analytics. At Caliper, his mission is transform cloud cost and usage data into actionable insights
In this episode Fletcher discusses
- The relationship between analytics and the CFO
- Subscription, net dollar retention, customer retention, and annual recurring revenue as key metrics
- Getting from CFO to CEO and the learning curve
- How we rely on AI and predictive ML and seasonal patterns to find anomalies
- Getting to base analytics and starting in AI
- Challenges and waste with cloud and holding engineers accountable
- The opportunity to save 30% on cloud spend
- Moving from Excel to Google Sheets
Connect with Damon LinkedIn: https://www.linkedin.com/in/damon-fletcher-bb8a6614/
Glenn Hopper :
Welcome to FP&A Today, I’m your host, Glenn Hopper. We have a great episode lined up for you today. Our guest is Damon Fletcher, a finance leader with a remarkable career that spans roles at some of the most dynamic companies in the tech world. Damon has served as CFO at Tableau and DataRobot, two pioneers in data and ai, and he’s now the founder and CEO of Caliper, a company transforming how businesses manage cloud costs through advanced analytics. In today’s conversation, we’ll dive into Damon’s career journey, exploring how his experiences have shaped his approach to finance and leadership. We’ll also discuss the innovative work he’s doing at Caliper, and how finance teams can harness the power of AI and data to drive their organizations forward. Damon, welcome to the show.
Damon Fletcher:
Well, thanks for having me, Glenn.
Glenn Hopper :
I gotta say, when I think we were introduced by a mutual connection, uh, Nathan Bell, I think is, is maybe introduced us. And, uh, as soon as I looked at, um, at your profile on LinkedIn, I saw two of my absolute favorite companies in in DataRobot and in Tableau. And I thought, man, this guy’s done the, he’s had the coolest job. <laugh>, going back to that, and even before that, you were at pwc, and now as a, as a founder of your own company, I just, I love that career path, and I was wondering if, for our listeners, if you wouldn’t kind of walk us through coming outta school, going to pwc and, and the, the path that you went on.
Damon Fletcher:
Yeah, absolutely. Well, thanks again for having us. So, yeah, early in my career, I, you know, after college, uh, got a master’s in accounting, like many of the, uh, you know, CPA, you know, people that started CPA firms and started at PricewaterhouseCoopers. I spent about five years in the Jacksonville, Florida office and then relocated my family up to Seattle to work on an IPO, uh, out in, uh, in Seattle, Washington. Uh, you know, the financial, uh, you know, markets collapsed in 2007, 2008, uh, with the kind of great recession and kind of pivoted, uh, my career and started focusing on tech, uh, primarily tech customers on clients of, uh, Pricewaterhouse and, uh, where with companies like, uh, F five Networks and ExtraHop and Aptio, uh, and then later became the CFO of, uh, Tableau Software. Uh, after, uh, after joining them shortly after their IPO and, uh, kind of progressed through the ranks there and, um, you know, spent about, you know, seven, eight years at, at Tableau and then later at, uh, DataRobot,
Glenn Hopper :
You know, working at companies like that, that are so focused on data and analytics. And then with what, what your focus was at, at the end of your time at PWC, have you always seen the relation between analytics and CFO and maybe different than someone who just had the finance and accounting background? How have those two skill sets kind of worked together in your, your approach to finance?
Damon Fletcher:
Probably because I grew up in the financial rank and file at, um, at Tableau, you know, it was a very data centered company. I mean, the product is very data, data-oriented, but I think the, the culture of the company was really to make decisions based off data to enable users across the organization to have access to, you know, financial data, you know, customer data, product data to be able to make kind of data-driven decisions. And I think that experience really taught me the value of being able to kind of dig in and ask questions and never accepting kind of the, you know, the high level results, but really diving deep. And, and that really helped us kind of, you know, formulate what do we wanted to build here at, uh, here at cper
Glenn Hopper :
Being at those companies. And then your approach to finances as, as well, I mean, I, it just, you kind of came up in, in the data world and as, as Tableau came out and became this very powerful tool that was out there, and then the, um, acquisition by Salesforce and all that. Were there, were there key turning points? And maybe it was, it came from just the environment and the, the understanding and role of data at Tableau, but were there certain key moments that you can look at and say, this is what really prepared me for that CFO slot at, at Tableau and then again at at DataRobot?
Damon Fletcher:
Yeah, I mean, there was a number of things. You know, when I first joined, I was handling primarily, you know, financial reporting and, you know, Sarbanes Oxley preparation. And then, you know, over time kind of gradually, gradually got more and more of, uh, the finance and other back office functions kinda reported to me. I would say, you know, the things that I, you know, were very strategic that I worked on at, you know, prior to being A CFO was, you know, helping the company migrate from being an on-premises, you know, software delivery model to a subscription model. That was one of the kind of key business transformations that we were going through. And, uh, had a key role in that in kind of launch of that product as, you know, as a, as a kinda the deputy CFO. And then I think, you know, doing things like, you know, as we, as we grew and scaled our business, you know, we had at some point 10 15 properties here in Seattle.
And, and, uh, you know, we, we built two brick beautiful new buildings and kind of migrating out of the, uh, old into the new and, and subleasing and things like that was another kind of strategic initiatives that, uh, the CEO at the time, Christian, you know, had me kind of spearhead of how do you transition employees from kind of a, a group of eight or nine buildings into two and, and then sublease the others for a period of time until you need them? And it was a very complex, kinda data-driven process of forecasting, you know, what your head count was gonna be by year and which buildings you needed and things like that. Those are kind of two strategic initiatives that I think helped me get into the CFO seat that were, I I call both of them very data-driven exercises.
Glenn Hopper :
Yeah. And the data-driven being such an important part of the office of the CFO now, thinking about you just being at the forefront and having access to the tools and people in that mindset, how did you leverage data and analytics to, to drive your strategy at the companies? And were there, like, are there some interesting KPIs or, or different ways maybe that someone at a, you know, a old school brick and mortar company wouldn’t have looked at it that way? And were there unique challenges as a, as a CFO in, in such a data centric environment? Because you’re, you know, if you’re just, if you’re saying all the data that I care about is our gl, that’s one approach, but if you’re trying to actually <laugh>, you know, incorporate data from all parts of the business and the, you know, uh, external data as well, I imagine, you know, it’s, it’s can be a wealth of information, but could also have challenges with it as, as well.
Damon Fletcher:
Yeah, I think there’s kind of two things that you have to do. One, you have to really define what are the most important, uh, KPIs and metrics that the company is gonna rally around. And, and those, you, you can’t have too many of those, right? If you, if you, if you, if you have so many metrics out there that the company is trying to focus on, I think you can get kinda lost in the weeds and, and not have kind of a strategic direction of where you’re trying to drive the company. One of the things that we focused on, and by tenure as CFO, was we were going through a subscription transition, so what was the percent of our customers each particular period of time that were, you know, subscription as opposed to our traditional perpetual business model that was, you know, delivered a software versus, you know, something that’s recurring.
And so we, we closely monitored that. We also started looking at annual recurring revenue as another example of a closely watched metric net dollar retention. So how much were existing customers from the year prior, how much had they grown? And then overall customer retention, uh, metrics. I think those kind of, in my, in my, where those were the four big ones that we focused on and, and really tried to educate investors on why those were important, educate our team on, you know, why those were kind of the, the, the highest level metrics that we were really focusing our business on. And then you would have hundreds of other KPIs and things that each individual kind of part of the team may be focusing on. If it’s, you know, deal desk, it’s how many orders can they process a particular period, you know, if it’s procurement, it’s like what percent of our, you know, spend is managed by po. There’s a lot of different things that individual teams would look at, but we didn’t, we didn’t kind of bubble those up to our kind of overall, um, OKRs that the, the company, uh, would report on, on a, on a quarterly basis. Uh, those were reserved for those most important top, you know, four or five that we, uh, we focused on.
Glenn Hopper :
Gotcha. And you know, I think about the, the other data that you’re bringing in and the, and the KPIs and OKRs and stuff you’re using internally in your departments and across the company. And it’s, it’s a stretch from where we start in our career earlier where you, you kind of get that accounting foundation and you’re just thinking about the, the gl and it’s more just, you know, putting everything, um, in its place, being sure the controls are in place and all that. And then the transition I think of, of finance over the last, say, two decades, maybe maybe 25 years from moving, that, shifting that focus from, uh, the, the foundation, which obviously is important. You have to have, you know, your <laugh>, your controls, and you mentioned Sarbanes Oxley and all that, and you’ve gotta have all that in place. But now, I mean, that’s not even table stakes.
You’ve gotta, that’s, that’s where you start. And then it’s what are you doing with this data and becoming more strategic in that finance function and in, and in that time, you’re seeing the shift where more CFOs are moving into the office of the CEO, which didn’t used to be as, as clear a path. And I think for you, going from, uh, a couple of success successful runs as a CFO at, um, data-driven companies to founding your own, would you say, um, that the CFO, you know, if Warren Buffett called accounting the language of business, then you’re, you’re very fluent in that and you have the data and analytics. Would you say that the CFO role particularly helped you as you were going to, to found your own company?
Damon Fletcher:
I think my experience being operating a company at the executive level, whether you’d be a CFO or a C, you know, the CMO others, you, you’re, you’re involved in kind of, at least the way that we ran the company and every kind of major decision. It was kind of a, a kind of a, a committee process with the direct reports of Adam Ky and have a business review over kinda different functions and, you know, provide feedback to those kind of stakeholders in that particular department of here’s some strategic direction that, you know, we think the, the executive team thinks that she’s work. I think that experience really grounded me to be able to see a lot of cross-functional aspects of a company and then be able to, to roll that. I think we’re being the CFO helps most, when you’re in a kind of a early stage startup, is really understanding capital structures, uh, you know, agreements, you know, being able to raise capital.
Those are all very important, you know, aspects of being a, a founder that, you know, having that experience as a CFO really gives you kind of a, a, a leg up compared to maybe someone who grew up on the product side who hasn’t had experience running a board meeting or, uh, raising capital. And so there’s some aspects that makes it more simple, but then you, you have to, you know, with some CFOs, they, they haven’t had that experience being kind of an operator like we we did at Tableau and, and being part of that executive team of kinda making key decisions. And I think both of those experiences, uh, kind of help helped me prepare for this role.
Glenn Hopper :
Gotcha. So, so tell me about Caliper. You started the company, what, about two years ago now? Um, and I guess, you know, making that leap from CFO to brand, you know, blue Sky, brand new startup, I mean, it, it had to be, you know, something that you thought about for a while. So tell me kind of your mindset and, and what inspired you to start the company and, and, and walk me through, uh, caliper’s progression. Yeah. So first off, maybe tell us what Ca Caliper does well,
Damon Fletcher:
Absolutely. Yeah. <laugh>. Yeah. So Caliper, uh, so our website’s, caliper software.ai, you know, we help companies, uh, get better visibility into their costs and usage of their public cloud and other consumption services. So when, in my experience at Tableau and then later DataRobot, the cloud spend was, uh, the, the, you know, the, a variable cost that is most likely outside of bookings, uh, top line bookings to impact your ability to hit your numbers in any particular quarter because of the, the way that, you know, different people throughout the organization in a very decentralized way could turn on servers or save more data, change their storage, all all types of things that can kind of impact the amount of funds that you, you spent on, you know, the public cloud in a particular period. And so, you know, there was kind of three moments in Tableau’s history that we saw those kind of costs escalate faster than we anticipated.
One was when we originally moved from data centers to the public cloud. Uh, the second was when we went from perpetual to subscription, as I talked about earlier. And the third was when we launched data management, which had a different, you know, spend profile that are traditional, uh, Tableau products. So all three of those moments really meant like deep introspection about, you know, how do we get this cloud spend under control? And so what we tried to do at Caliper is take all those lessons learned from that experience and then bundle ’em into a product that’s, you know, ready to go in 15 minutes to of set up time for our customer. So we’re trying to kind of disrupt the existing, you know, providers in this area who take weeks and weeks to implement and have, you know, high, you know, tens of thousands of dollars costs. We brought the costs significantly down of managing this spend. And then on top of that, we, you know, get you set up in 15 minutes or less. So we’re highly disruptive to some of the legacy providers in this area.
Glenn Hopper :
What I love about the origin story of Caliper is that you firsthand saw the need for this. So it wasn’t like you’re, you just, you know, opened up a <laugh>, um, you know, got the whiteboard out one day and were like, I’m, I need to come up with a business idea and just started writing on it. It was, here’s a need that I have, we, how do we solve this? And it sounds like that Caliper came, came about very naturally through that. Is that accurate?
Damon Fletcher:
Yeah, absolutely. I mean, this was kind of the number one problem that, you know, we faced when I, when I joined DataRobot, they had, you know, rapidly escalating cloud spend and, um, you know, was, it was a big cross-functional initiative to get that on their control. And, you know, actually the, the individual who we hired to help with that has actually been an advisor for our company. Uh, and, uh, kind of the voice of the customer as we informed our roadmap. He left Data Robot and joined another company, but he’s, he’s been helping us kind of steer the product direction and, and doing a great job for us.
Glenn Hopper :
Gotcha. And so you have.ai in, you know, in, in your domain name and you have obviously if, if, if clients can get onboarded and set up in as little as 15 minutes, obviously you have a lot of automation. Are you guys leaning heavily into AI right now? Can you talk about how, how that’s integrated into your platform?
Damon Fletcher:
We’re doing a couple different things that are, I think, relying on machine learning technology. One is we are trying to bring in kind of advanced predictive capabilities. So predictive ML and, uh, statistical data science have really been able to kind of look at, you know, seasonal patterns within the data, uh, data and predict what is gonna happen in the next period of time, and then use that to find anomalies. Uh, so that’s, you know, an advanced, you know, statistical, uh, kind of model. And then the other thing that we’re doing is taking the results of our visualizations or our, or that statistical modeling I just mentioned, and in feeding them into a generative AI model that then provides the customer with action points. And so, uh, those are kind of some of the exciting features that we’re building that, we’ll, we’re calling kind of in intelligent insights is the, the overall kind of feature that we’re, uh, working with customers, kind of our prototyping phase to, uh, to see if, you know, if we can add more value by not only providing, you know, the, you know, what’s happened in the past, but, uh, really saying, Hey, this is what was anticipated to happen.
These are the anomalies we found, and here are some specific action points that you should take to, uh, kind of bring down those, uh, anticipated costs.
Glenn Hopper :
Yeah, and I love your approach to it because right now, I mean, there are so many companies out there that are just AI washing their company. They’re just sprinkling, they want to say AI and, and because obviously with your background at, at DataRobot and even even Tableau, you come from a data and analytics background. And so machine learning and predictive analytics and everything that you’ve done, I mean, that’s all deterministic and, and, you know, set reliable tested technology that can help your clients. So you, you implement that and then, you know, whereas most people don’t know, don’t understand what that means or whatever. Certainly everybody’s talking about generative ai and then the way that you’re able to layer in that generative AI piece to use it where it’s valuable to add to not, so it’s not just, you know, you have a, a, a chat bot that is, is using some rag setup and, and doing, uh, you know, minor features in, in the product. It’s really, you can see how that machine learning algorithms and, and things that way are adding value, but then maybe generative AI is just a better way to communicate with that data.
Damon Fletcher:
Yeah, we thought about different ways of approaching it, and what we fear about you just, you’re purely relying on generative AI if you’re not using kind of an advanced statistical model to find the anomalies, is that if, if you follow some of the news stories on generative AI’s not really good at math sometimes, and it can hallucinate. So we’re really using that only to communicate, you know, try to take data and communicate the findings as opposed to doing calculations. And so we’re using, we’re doing all the calculations based off, you know, more advanced statistical machine learning models and then, you know, really using the, uh, generated AI for what it’s best at, which is summarizing, you know, a prompt or a query, uh, like a, if we generate a, a cross tab of your spend by a particular period of time, it can then summarize those peaks and those valleys and, and what action points the, the customer can take. And we think that’s a better approach than just purely pumping, you know, you know, cost of usage data and then allowing generat AI to try to do the math. I think if you, if you did that approach, which some companies are, I think you’ll find that customers won’t rely on the findings and then they’ll get little, little value, little utility out of the product.
Glenn Hopper :
Yeah. It’s that trust step the first time your AI hallucinates that trust is out the window. It’s so, yeah. So I, I think you’re, you’re doing it very smartly. And I, you know, with your background, I’ve pushed for this for a long time because I’ve, uh, I started in my career in telecom where we had just a, well, this is a million years ago, this is, you know, right around 2000. And we had so much data back then, and we didn’t have all the reporting tools that you do now, but in my first finance role, um, you know, predicting churn and telecom company, I was trying to get data from, so whatever sources I could to predict these churn events, ’cause we would, you know, we were turning 2% a month, and that’s a pretty significant, you know, it’s 25% a year. Um, and so as much data as I could to bring into the finance side to help predict that, it’s, to me, analytics and and finance have been tied together forever.
And I imagine your career is probably very similar just because of the, the places that you’ve been, even sounds like back to pwc. But I’m wondering, you know, and maybe, and maybe this is asking for anecdotal inputs if, if you, if you don’t have the data on it, but out of your clients and people you talk to in the industry, how do you feel like that the application of, of analytics in big data in finance, do you see more companies adopting that now? And how do you kind of see the role of finance evolving in these, in, in data-driven companies with, and, you know, you can speak to generative AI if you want, but I’m, I’m just thinking like classical ai, machine learning and statistical analysis and all that.
Damon Fletcher:
Yeah, I think there’s really a divergence in two types of companies. From what I can see. There’s companies who very deeply want to control the data and, and, and they, they tend to be more focused in highly regulated industries, uh, industries that, you know, have a fear of the employee base kind of leveraging that data for kind of inappropriate reasons. And those 10 companies tend to move very slow, um, and, and, uh, are not able to react to changes in their business as well. And then the companies that I, I feel, um, are, are generally higher performing are the, are the companies that really unlock as much data as possible and, and, and give that, and put that in the hands of the, the frontline, uh, employees that are trying to kinda make a difference in their business. So in your example, kind of churn, um, you know, that’s a, a very common area of focus for any kind of technology company is, you know, deeply trying to understand churn because it impacts your valuation so much.
You know, just one or two points of improvement in churn can dramatically change your long-term valuation. And so, you know, you know, providing data, telemetry data around, you know, how the customers are using features or how many times they’re logging on, you know, putting that data in the hands of customer success reps you, is one kind of very easy way that you can make them be able to kind of spot and identify potential customers who may be more likely to churn than others, uh, by whether or not they’re using the product and how frequently they’re using the product. And so there’s some people who say, Hey, well, we can’t give that information to those particular customer success reps. Um, and they try to hold that back or for whatever reason. And so I just, you know, I would encourage many companies to really think, think closely about, you know, is this financially sensitive information that can move, you know, capital markets, and sometimes you have to control things for, you know, sarbanes oxley reasons and things like that. Or, you know, maybe it’s privacy if it’s, you know, individual information about employees or health records or things like that. But for most companies, you know, I think there’s an opportunity to unlock more data for people to make better decisions. And, uh, you know, that’s what we’re all about here at Caliber
Glenn Hopper :
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We’ve been talking about, uh, you know, democratization of data for probably 20 years now, <laugh> now as well. And we’ve been talking about digital transformation for 30 years at this point. You know, I think, and that, and still it’s, uh, in my day job, I was actually just right before this podcast recording, I left a meeting where we were talking about a digital transformation project, and this would be targeted for, uh, clients in the like two to 20 million, um, uh, revenue. So, you know, small SMBs, right? But the thing is, a lot of these companies, you know, they don’t have an analytics team. They, you know, they’re, maybe they have their, you know, on the very low end of that, maybe they have their, their, you know, tax accountant closing in their books for ’em or whatever, you know, they’re just very immature companies and we’re trying to figure out a way to help bring these companies into, to be doing data-driven decision making.
And, and part of that would be, um, you know, the finops side, the, the, the cloud management and everything. But I think about it can be a hard sell because a lot of times if you’re talking to, and, you know, maybe I’ll move away from the very small ends like pre CFO level companies, or maybe get to, you know, more than maybe 25 million range where they ha they have a CFO and all that, but the, a lot of CFOs are in, in that category of, of viewer talking about those old companies where I know GL data, and I, I don’t think we need to be sharing this other data with these people. So it’s, it’s hard to shift that, that mindset. And I’m wondering, just because with your background, you’ve been in, in companies that were so forward thinking, can you think of any practical steps that finance teams, if people, people are in that first category where they, they still, and it really feels like as, as AI becomes more prevalent and with generative AI as it becomes more accessible, if you haven’t done your, I’m doing air quotes here, digital transformation at this point, then you’re really about to be super behind the curve.
What would your advice to companies who are maybe laggards in this area of, of data and analytics, what could they do to sort of start moving in that direction? And I, I’m not even talking about getting to AI yet, but just getting to base analytics.
Damon Fletcher:
Yeah, I think the, the most important thing is get started. Um, I think the, the, the, the, the most common reason companies fail is they, they’re, they say they want to clean their data before they’re ready to analyze it. Um, and that is something that is continuous and never, you know, and, and by analyzing the data, you sometimes find kind of why it’s not clean and then can make changes. So I would say don’t wait to get your data in a central repository or clean it completely up before you allow your team to analyze it. I think that’s, you know, so get started, get started immediately, you know, finding the things that are most important to your business and, and, and look at those every day. I mean, for me at Tableau, it was, I got up every morning, looked at bookings, I looked at, you know, employee ads for the week and how many employees we had hired and how many had left.
I looked at, um, cloud spend, things like that, you know, that were big impacts of drivers of our P&L, you know, T&E spend. Um, and so, you know, those are kind of things that are really easy to unlock based off your, you know, the apps that you use, right? If you’re using Salesforce, right, you can create a, a bookings report and then, you know, pull that into kind of an analytics software. And, um, you know, I think, um, it’s, it’s pretty simple to do. Um, and so I, I would say for most companies, it’s just really get started. Don’t try to kind of get everything organized. The thing is just define what’s important for your business. Um, you know, even at a small company, even if you’re at $25 million in revenue, if you focus on too many things, um, you’re gonna fail. And so, you know, for a company that size, it’s probably some really key kind of product milestones that you’re trying to deliver to kind of, uh, increase the kind of shut size of, you know, your, your, your tam on the business side. I think things like bookings or trial conversions and things like that are probably super important at that early stage.
Glenn Hopper :
You can tell I got really hung up on data and analytics just ’cause like I said, you worked at two of my favorite companies and all that, but I do, you know, with your, with your expertise and where you are now and what caliper’s doing, I do wanna talk a little bit more about cloud spend for our, our listeners who are, you know, at companies that have a big cloud spend and, and sort of how they’re managing. Could you maybe walk me through the kind of client that would come to you that would have, um, where you guys would have the biggest impact? Like where, you know, where are they size wise, kind of their spend and, and what are they doing now that that caliper can come in and, and really make a difference?
Damon Fletcher:
Yeah, so we help a number of companies at different levels of maturity. I mean, we have, you know, startups who are spending, you know, $120,000 a year on AWS and they’re using our product. Maybe one person in their fb and a team or finance team has, or their CTO has access and are kind of, uh, looking at things like which of their machines are turned on, you know, nights and weekends, or, you know, what storage have their engineers, uh, selected? Should the upgrade to the latest, uh, kinda source so they get the take advantage of the best price? Are they, you know, looking at their spend by day and, and by hour to see if there’s kind of unusual fluctuations? Those are kind of things that the early stage companies could do as they mature. I think, uh, let’s say they’re spending five or $10 million on, um, the public cloud.
You know, at that point there’s probably have multiple public clouds. So we’re helping them connect both their AWS, maybe their GCP data, pulling it into one kind of single pane of glass, allowing them to maybe create virtual tags. So, you know, create departments or cost centers within our platform that they can, uh, analyze their business based on their, you know, that level of maturity. They’re probably starting to explore doing things like reserved instances or savings plans. And so we can help them, you know, see, you know, how much of your spend, this, any particular period of time, day, week, month has been covered by a savings plan. How much is on demand? Are you leveraging the opportunity to do some kind of, uh, tasks that make sense on spot instances and what’s that coverage? And so that’s when you get into more complex use cases.
And then allowing them to use our product to kind of drill in and ask questions, you know, by different departments or by different teams of kind of those kind of more complex, um, you know, processes. And so we, you know, we’re, we’re helping companies at the early stage all the way up through earlier, you know, public companies that are just getting started with, uh, analytics. And then one thing we’re, we’re really trying to do is expand the number of things that we help them with. And so we launched, uh, a snowflake, uh, cost and usage connector, so we can help them with like, not only can help them with cloud use cases, but we can tell them, you know, which queries are costing you the most within your snowflake instance and who’s, what teams are, you know, driving that, um, you know, that increase you saw this past month. And those are, you know, insights that people have generally never had just from looking at their, you know, billing console on Snowflake. And so, uh, we’ve been able to, you know, really help companies gonna get that cost under control, which may be not as big as cloud spend, but might be growing more rapidly.
Glenn Hopper :
What’s your sense of how well most companies are doing, you know, ’cause at fp a today, we, we think a lot about KPIs and I, I think about if you were on the FP and a team that was, you know, watching cloud spend and all that, like, I, I know there’s the, the dashboards that are built in and all that, but there’s the domain expertise that you have as an FP and a person, and I know you could be embedded in learning, but then there’s sort of the IT expertise and understanding this is why we spun up these clusters and, you know, this is the burstable part of it, but understanding the variable cost, I mean, regardless of size, what’s, what’s your impression? I mean, is I, I guess this is kind of speaking to the TAM of, of Caliper, but what <laugh>, um, how much of a sense that most companies have on their cloud spend or how to control it when, when you come in, what do you think?
Damon Fletcher:
Yeah, I would say the vast majority of companies that we meet with unfortunately don’t, uh, focus on it. It’s a lot of money that’s wasted in our, in our, uh, in our broader economy on, on public cloud. So you, I think you have a, you have, uh, kind of a challenging situation. You have the office of the CFO who cares deeply about, you know, budgets and kind of getting costs under control, and they, like you said, they, they just feel uncomfortable asking questions and kind of digging into, you know, a a cost that’s being managed by another department. And so I think it’s very important for kind of the, you know, whoever owns the dev budget within your FBA team, maybe if you only have one person that’s the, the, the, the VP of finance or the CFO, if you have a FBA team, you might have someone dedicated to the dev team.
They should be using a tool like Caliper, whether it’s our product or some other company, to better understand what’s going on in their cloud spend and holding the engineers and asking question, holding them accountable, asking questions about spikes, asking questions about, you know, did they use the right size machines? Could they go down a size? You know, like, you know, just really kind of digging in and, and looking at the spend on a regular basis. Because I think the engineers, they, they have a different, um, while they, you know, generally someone in the CTO’s office owns that budget, they have a competing priority of like delivering high performance software, delivering on schedule. They’re not necessarily thinking, how do we do it as most efficiently? And so I think there’s gotta be a partnership, and that’s one of the things that I think we do best compared to some of the other tools is because we’re really an analytics platform as opposed to kind of out of the box kind of, uh, uh, you know, a dashboarding tool.
I think it really allows kind of that inspection and really diving deep and really understanding what’s going on. And I think the best teams that we have, you know, have a partnership between fp a and fi and, and it, you know, it or, or TE or, uh, the dev organization, and they’re looking at it collaboratively on a kind of maybe five or 10 times a week from what I can tell from our data on telemetry data. And that’s, I think, the best performing organizations. I think, you know, if you want to, if you wanna say how big a a market is that I, I think most companies, based off where we’re at, we generally help ’em save 30% on their cloud spend. So if they’re spending a million bucks, that can be 300 grand for our investment in Caliper for 10 seats is gonna be $9,000. So you can, you know, you can save your company, you know, $290,000, uh, by spending 9,000 bucks to provide them with some tooling to better, um, to better manage that spend.
Glenn Hopper :
Years ago, I worked at a couple of, um, um, e-discovery companies and we had a, a, a lot of data, you know, as you’re, uh, bringing in, you know, all the discovery information in, in a lawsuit could, you know, terabytes and terabytes of data from, you know, from single clients. And, uh, one of them was using a WS and the other one we had our own data center. And I, when we were using AWS, it was as A-C-F-O-I, I didn’t know what I was, and I consider myself kind of a tech forward CFO, but I, you know, I didn’t, I didn’t understand the intricacies of, of of, of the cost on AWS and we hired a, a firm to come in and the ROI ON that was still, I mean, they, you know, it, it was, it was people, it, it was a lot more people than systems coming in and, you know, we paid them whatever a month, but they ROI was simple because they got the savings, um, in there. And it sounds like where you are now, and maybe this is where the industry has gone, it sounds like you’re able to automate, you’re, what you’re doing is not, uh, consultant intensive, right? It’s a lot just the software and then maybe a little bit of handholding from you guys. How does that, what you guys are doing compare to some of these old companies that would come in and help you manage your AWS spend?
Damon Fletcher:
Yeah, so we rely on partners to do the consulting. You know, my, my, you know, as a business model, we’re just trying to stay away from offering professional services, but we have, um, seven partners that we’ve onboarded since we launched last year. Um, and they provide based off different, uh, what the customer needs from an expertise that we have some partners who manage cloud on behalf of customers. So they, small businesses who, who need a website or needs, you know, need some AWS infrastructure and you don’t have an expertise on your team. We have partners who can do that. We have partners who can help you, Hey, I want to, I have a 10 million our AWS budget, and I want to find some strategies to bring that down by 20, 30% in their consultants. And they come in and they do kind of a, you know, they use our software, but then do, you know, hourly consulting or outcome-based consulting where they say, Hey, we can migrate your on demand workloads to these particular savings plans, and we think we can save you, you know, $300,000.
And then they’ll take a fee for that, uh, kind of o onboarding work. Um, we provide the tooling and then the, the, the partners provide the, uh, the consultation, you know, just being, you know, a technology company. We do try to help our customers. And so many of our customers, you know, they, they don’t necessarily need a full-blown consulting engagement, but they just need a few insights from their data. And so, you know, we’ll, we, when we onboard them, we show them how to use the product, and then we also give them some observations based off kind of benchmarking that we’re seeing from other companies. And I think that’s sometimes just helpful for them to say, Hey, you know, oh, I didn’t realize I have my test environments on 24 7. If I shut those off on the nights and weekends, I can save 30% of my cloud. Yet that little bit of, uh, health is all they really need. And then we give them some white papers and things on how to do that.
Glenn Hopper :
And with the compute growing so much right now with everything around generative ai, and you, you know, every day there’s, you’re hearing about how many more billions of dollars are being spent on, on new data centers, and, you know, we’ve been digitizing everything in our lives for the last 30 years. Um, so I’m wondering if you’re already seeing, or what do you think the impact on cloud hosting and, and this could be everything from, from Snowflake, AWS just, you know, all all the, the cloud expenses. How much is, are you seeing already or do you think that the, the, the cloud storage is gonna grow based on this new tech round of, of generative ai?
Damon Fletcher:
Well, I can see from my cust, uh, just from the, the small amount of customers we have, several of them are AI first companies, and so they are experiencing sharp increases because they’re buying more expensive, or they’re, you know, renting more expensive compute types than they had traditionally. We had a small startup that was very tiny. It ended up going out of business, but they, they were renting machine for $35 a day that they had turned on for six months. And, and they didn’t realize they had, uh, for an AI experiment that they had left on. Um, so that was like $12,000 a year savings on one seat of Caliper. We helped them find, so I think it’s one where they’re renting more expensive machines. They’re, you know, the compute is, you know, a lot of times I’m helping customers with, um, you know, they’re, they’re wanting, they’re doing like single tenant SaaS where they’re standing up environments on behalf of individual customers, and I’m helping them with like, well, you’re charging a million dollars for this customer, but it’s costing you 1.6 million. So helping them understand their margins on, uh, on particular customer relationships. From all that experience, all I’m seeing is dramatic increases. And so this is an kind of an exciting time to be in this market because, you know, it’s, and I think that’s why the cost management kind of tooling kind of category is expected to rise, you know, the TAM is supposed to get so big is because there’s so much spend going in this area, and there’s very little tools to help you manage, you know, the, this kind of consumption based pricing.
Glenn Hopper :
Very interesting. So yeah, it, it does seem like your, your timing is very good as you’re kind of riding the wave of this, uh, you know, when just when you thought it, it couldn’t get any <laugh>, the, the growth couldn’t get any faster. Now here we’ve got the past couple of years where, uh, we’re actually right, you guys kind of caught the wave right at the front of it, and, uh, yeah. So hopefully that, uh, continues to do well for you, for someone just starting out, uh, or just a finance professional, uh, who’s starting to realize, okay, I’ve got <laugh>, I’ve gotta get up to speed on the integration of, of AI and data analytics into the roles for, at an individual level. What advice would you, would you give them?
Damon Fletcher:
You know, make sure you understand kind of the, the latest technologies and how that’s evolving. I mean, there’s been so much change just in the time <laugh>, when I was, when I first started at Tableau, we were competing against companies like Qlik and MicroStrategy <laugh>, now they’re a Bitcoin company, and now all, you know, people were doing data cataloging and things like that. And then now everything’s moved to either Snowflake or Databricks. And so it’s kind of deeply understanding kind of the, the trends in the industry. Obviously there’s some really powerful companies that are helping comp, you know, helping organizations. The the two best in that are, are kind of databricks and, and Snowflake around getting data ready for analysis and providing, you know, some basic AI tooling to be able to analyze that. Um, and then, uh, you know, from a, you know, career, you know, progression standpoint, I think it’s important that, like I said earlier, uh, that you really define what’s important for your organization and that’s gonna set you up to be kind of a kind of a thought leader in your organization. If you can provide, you know, a point of view on what are the insights that you think are gonna, you know, best drive the, the business outcomes of the company, and investing the time to really think through that and interviewing different parts of the business and understanding those, uh, kind of those, those drivers, I think you’re gonna, you know, you set yourself up for, instead of just the kind of report, the news type accountant, um, you’ll be a trusted business advisor to the, you know, the rest of the organization.
Glenn Hopper :
Absolutely. Really, really good advice. Alright. All right. Well, we’re at the time of the show where we’ve got two questions that, uh, that we ask every guest. It’s always, uh, fun to see what, what kind of answers we get here. So the first one is, what’s something that not many people know about you? Maybe something they couldn’t find just by Googling you real quick?
Damon Fletcher:
I love being on a sports field. I help, you know, I coach, uh, multiple teams. So I coach, uh, high school baseball age, uh, kids, and I coach my daughter’s fast pitch team. And so you, on the weekends, uh, and nights you can find me on a, on a field somewhere, uh, almost every night of the week. So, uh, that’s a lot of fun and, and something kind of invest in kind of mentoring, uh, you know, young, young kids and, you know, helping them prepare to be, uh, kind of better athletes.
Glenn Hopper :
That’s awesome, man. And, and travel ball, that’s a, that’s a pretty, uh, <laugh>, that’s a pretty serious commitment, right? <laugh>
Damon Fletcher:
Yeah, it’s, it’s, uh, yeah, it, it is a, you know, a lot of, a lot of work, but I, you know, I, I enjoy it. And, you know, really the most important thing is I enjoy kinda getting the, you know, seeing the kids grow from year to year and, and I improving their skills.
Glenn Hopper :
Alright, and our last question here, so you’ve been a bit removed from it and you were, you were a Tableau guy obviously, and, um, but you’re also a finance guy at heart, and, uh, we ask all of our, all of our guests, we, what is your favorite Excel function and why
Damon Fletcher:
<laugh>? Uh, well, I was pretty good at the short Excel shortcuts. You know, I’ve, I’ve completely transitioned to Google Sheets at this point in my career, just, uh, after I started at Salesforce, they were, they were a big Google shop. And so, you know, I think the, you know, when I try to open up Excel, I, I still have trouble now with the, uh, with, with being such a transitioning to the cloud. And so, you know, one of the things I, I guess I really liked about, you know, that transition and is just, you know, having, you know, documents available at all times, whether you’re on your phone or your, uh, your computer or, or maybe another computer. Um, and so the sharing functionality of, of Google Sheets is something i i, I love. Uh, but yeah, I was, uh, I, I can, I can work pretty quick with the Excel shortcuts. In the old days, uh, people were like, what, what did you just do with all those shortcuts? <laugh>, I’m, uh, I’m able to move things around and, and, uh, without having to, without having to kind of go in and use a, use a mouse or anything like that. Um, but, uh, my days of doing pivot tables are, are long gone. I’m, uh, I would struggle yeah, these days with one of my career.
Glenn Hopper :
Yeah, no, I’m in, I’m in the same boat where I, you know, I used to be so proud of just how quickly I’m, I, I was one of the guys that had my mouse, you know, uh, the, the cord tied a little noose on it and hung the mouse, uh, on my thing. I was like, we’re no mouse here. We’re gonna <laugh> do everything through, uh, through shortcuts. And now I, I don’t, I open it up and I’m like, I’m not even understanding the formulas that are in the cells anymore. It’s just you get removed from it and you, uh, I tried to, I went back a few years ago and got a, uh, an FMVA certification just to get back into Excel. And of course, if you’re not using it every day though, at that level, you know, you’re getting using it more as a tool that’s being presented to you rather than building the model. So I do miss that a bit, but I’m, I’m right there with you <laugh>. Yeah.
Damon Fletcher:
Yeah. I think, uh, you know, I think when you is, when you, especially when you’re a Tableau, you, you tend to, you know, rely more heavily on kind of your analytics software than your Excel to do most analysis. So, um, I think, um, uh, I’ve got completely away from it at this point in my career. But, um, I do, uh, I, I do have a big budget document from my small startup and, uh, kinda update that on a monthly basis. And, and, uh, I love the love the ability to, to share and, and how quickly things can, information can move around these days compared to the, you know, the old days of when I first started my career.
Glenn Hopper :
So. Well, Damon, I really appreciate you coming on the show. Just one last question and know, I know you mentioned it earlier and we’ll put it in the show notes too, but if our listeners, uh, want to, uh, wanna, uh, get in touch with you, learn, uh, more about you and what you’re, what you’re doing at Caliper, um, how, how can they do that?
Damon Fletcher:
Yeah, so it’s Caliper Software, a ai, you can do a free trial of the product, you can contact us through the website. So again, caliper software ai. Alright,
Glenn Hopper :
I appreciate it. Thanks for coming on. Thank you.
