Even for early-stage companies, have a long-term business model

On May 19th, eShares held a presentation and discussion for the Bay Area CFO community. One of the speakers was Stephanie Gantos, the VP of Finance at Degreed. Degreed is a series B Saas company. Their product provides an educational platform for employees to learn new skills. Below is the video and transcript of her presentation.

More from the Summit:

To see Slack's Allen Shim in a fireside chat with eShare's CFO click here

To see Eileen Treanor's talk about Lever at our CFO Summit click here


I'm Stephanie Gantos, and I'm going to be talking about growth-stage and early-stage, so forecasting in a rapidly changing startup is our topic today. So to tell you a little bit about me, cause I'm gonna be pulling out a lot of my experience throughout the presentation, I'm currently the Head of Finance and Operations at Degreed. It is a Saas startup in the corporate learning and development space. And so, I joined right before series A, pre-revenue, pre-customers. We've since obviously raised our series A, raised our series B, and we're about to begin raising our series C. So a really rapidly growing startup. (To read more about funding click here)

Prior to that, I was a founding team member and Head of Finance Strategy at UniversityNow, also controller there, and I joined, obviously- a founding member- pre to any kind of money in the door. So pre-funding, I did the C, the A, B, C, and actually led us through an acquisition attempt there as well, ultimately was not successful, but that was in the most secondary education space, and that was a consumer model. And in between those two things, I actually consulted with early-stage startups building financial models for them and helping them kinda get out the door. And prior to coming out to Silicon Valley and doing all this, I worked in growth equity at a private equity firm.

So a lot of my experience is across business models, so Saas and consumer, across seed all the way to growth capital later, and then both as an operator and an investor. So, the problem that I'm going to address today is- or the challenge, really, that I'm gonna address today is on the one side, we do models and financial forecasting because we want visibility into our business. We want to be able to predict it, understand it, know when we are running out of cash, know when we need to pour in more cash to really drive up our revenue. It also helps us to be accountable, accountable to our board, kind of accountable to our stakeholders, and to really understand the business.

The flip-side of that is, you might be locking in this false precision because you're in a really early-stage, you're high-growth and you just don't know the variables that you're putting your model, and you're convinced this is where I'm gonna be in three and six months, but you really don't have the data to say that that's true. And you're also locking in this rigidity that now you have to do what the model says, because that's what I've told people we are doing, rather than being able to just stay really nimble and fit it quickly. And then, of course, the biggest reason you don't want to be doing it, is you don't want to do the wasted effort, right? You're very busy, possibly if you're like me, you're also handling people, operations, or legal, you don't want to be doing all these cycles on a model that you're ultimately just going to be continually rewriting because the inputs are bad.

So when I think about how much precision, you know, walking into a new company I want to put into the model, I think of two really big considerations. And one is the stakeholders, and second is the business. So when I think about the stakeholders, I walk in day one and I say, "Okay, what currently exists and how is it serving everybody, and who are the people that it needs to be serving?" So at Degreed when I walked in day one, I was given a shoebox, literally, of receipts. The CEO knew he needed to be keeping up, he didn't know what he would be doing with them. And so, every once in a while, they work with their bookkeeper, kinda do their annual financials. But I walked in midway through the year, and nothing had been touched in nine months.

So you have to understand, "Okay, so where are we right now, and where do we need to be? And who are you reporting to?" So at this point, is it just the CEO that needs to be understanding the model, or do you now have all these department heads that really need to be understanding what the financial plan is? Does your board expect to be inside the model? I've definitely had investors that want the model, want to be playing with the model. And then on the flip-side, venture investors usually are saying, "Tell me more about the market, where's your market analysis?" So understanding who those stakeholders are, and who wants to be consuming your financial plan. And then obviously understand what matters to them.

Now on the flip-side, the business considerations. So the first thing I take a look at is stepping in, where is the product? What are the goals, right? So are we still at an MVP state? If so, I'm not gonna spend my time really working on a revenue build, or having difficult, more complex, rather, like that. I'm going to really look at, probably, headcount. Because headcount is what's going to take us to getting to the MVP, that's going to allow us and then go raise the next seed. So I need to have the detail there to understand when we're running out of cash.

Another thing to take into account is, where are you in the business model stage? So how have you figured out our monetization strategy? So when I walked into Degreed, which is now a large enterprise SAS business, we were actually still a consumer business. So we thought we were going to monetize off of this big premium platform and do consumers, so luckily, understanding that, I didn't build a model yet that was making these assumptions around the revenue. I just said, "Let's focus on the product and how we're gonna make more in there." So if you're figuring out your business model, you shouldn't be layering too much detail yet.

Now, the flip-side is, once you've moved on to having a repeatable business model, so as you move from your series A to your B, and to your B to your C, you should be having a repeatable business model. You should understand that, "As I pour in money into marketing, this is the result that's going to be coming out of it." And it should be starting to to be on repeat like that. At that point, you have the detail and the data to really be making a more precise model.

Now, the last point is even if you are really early-staged, if your business model is complex you need to be having a more precise model from day one. And what I mean by that is, are you capital intensive? So are you maybe in hardware, do you have inventory, things like that. Say that you need to move from more complex model day one, because you're going to be turning this through a lot of cash, and so you need to know where that's coming in and going out. An example of that is Degreed, very simple Saas enterprise, repeatable revenue- recurring revenue. So, pretty simple model day one, versus UniversityNow was a service business. So we had teachers, we had books, we had students, so really just day one it had to be a more complex model.

So, you know, adding all of this together, what this is really saying is, you just have to look at your business within the context of your business. I can't tell you that seed-stage, you know, or series H can be a simple model every single time, you need to just take a look at these considerations. Are you still early stage? Do you have customers yet, or just a few customers? Are you still experimenting with your monetization strategy, and your business model? And how capital intensive are you? So as you begin to move towards later stage, and having many customers, needs becoming more complex, not just focusing on cash, but really focusing on the financials as well.

If you have a lot of stakeholders, so maybe now you have a bank involved. I typically put venture down on a business fairly early, so that usually gets a bank involved, which is then going to give you financial covenants. So now you do need a more precise model, 'cause you need to know that you're not going to trip those up. Capital intensive, we spoke about, and then repeatable business model. Once you have that, you're really going to have the data that allows you to really build a robust model.

So in conclusion, the more complex your business and stakeholders, the faster your forecast needs to gain complexity and precision. In general, I will do a major model rewrite about three times, and like I said, this is typical for me personally from seed-stage to kind of growth. When I first come in, day one, is my first rewrite. And I look at what the CEO's done, it's probably in a Google doc, even Google Excel, which have no idea how those things run, have to just completely put it in the real Excel, and I start off with that.

And then the year one, year two, I'm understanding the business. Now I'm in it day in, day out, we're understanding it, we're understanding our headcount. Now we may have a monetization strategy. So typically I actually scrap that original model completely, and we do a massive rewrite at that point, 'cause now we know what really the business is. And then the third massive rewrite of the model is really when we are now. We may have hired just a detailed FP&A individual, someone who does- done this at a previous company, big company, lives and dies by FP&A. We have the chart of accounts really well defined, so he's going to take that and he's gonna plan it by departmental budget, and that's kind of the last major rewrite of the model that gets us from the seed-stage onto the growth-stage.

The one thing to always keep in mind as you're choosing the level of precision you want in your model, is whatever level you go with, you are accountable to that. So if you're going to keep it high-level, that's fine, but if you start putting in details and layering the details, you are now accountable to that. And the most important thing, too, is that you'll know when you need to start adding details, and really adding precision, if you weren't missing your forecast. You can never be surprised, you can never make your stakeholders surprised. The entire purpose of your financial forecast is so that you are running the business, and you are staying on top of and ahead of the business. So if you are not doing that, then you are missing too much detail on your model, and you need to start rewriting it and adding in those depths and those layers. And that's it, thanks.



Jesse Klein

Jesse Klein

Jesse was born and raised in the Bay Area. She crossed the country to go to the University of Michigan before heading back to her roots in San Francisco at eShares.