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Proxies for Cash Flow: ACV
In November of last year, I wrote about how EBITDA multiples were dead. My point was not that EBITDA multiples were literally no longer going to be a thing, but rather that the using EBITDA to generate a valuation for a company was not as broadly applicable as it had once been. More importantly, for several subsets of industries, there were going to be better ways to asses a company’s future cash flows. I briefly touched on the idea that if you didn’t use EBITDA, surely there had to be a replacement metric to be the one metric to rule them all, right?
Not exactly. There are a variety of metrics to review for certain companies to better understand cash flow, but no single silver bullet.
Before we dive into what some of the metrics are, let’s quickly remember what makes EBITDA such a compelling metric and why I would spend my time mentioning it in another blog if it were dead. It is a proxy for cash flow. It’s something that you can review and get a good idea for what sort of cash is capable of flowing into an owner’s coffers under the right set of circumstances. It is not an exact replica of cash flow, however. Like the name suggests, cash flow is a fluid thing, so it’s hard to pin it down with an actual metric without running into some time sensitivity bias issues. Instead, we should use a variety of metrics to get a closer approximation of what’s going on within a company’s cash flow situation.
You might be thinking - well why don’t I look at a company’s Statement of Cash Flows - why do I need a proxy? First, a cash flow statement generally doesn’t capture a company's entire picture. It frequently misses on important items, such as investments into intangible assets, heavy spending on growth initiatives that have a longer payback period, and maintenance vs. growth capex considerations. These considerations might be minimal for a lot of stable, mature cash-flowing entities, but it falls short for startups, high-growth software companies, and a variety of other entities.
As a well-known big-time software boy (BTSWB™), I spend most of my time thinking about how to evaluate a software startups cash flow situation or potential situation. For most software startups, EBITDA and Cash Flow statements are not super helpful. The market (with some notable exceptions) rewards fast growing SaaS solutions because of the nature of their margins in the long term (and frankly because of the incredible secular tailwinds they have ridden for several decades). As a result, it’s important to analyze companies in this space with a new set of cash flow proxies. There are some folks who think that the best way is to simply review either ARR (annual recurring revenue), revenue, growth rate, or all three combined. However, I feel that is a gross oversimplification, and there are several others that demand special attention.
Recently, I have spent a lot of time thinking about Average Contract Value or Annual Contract Value (ACV) and its uses as a cash flow proxy. While it might not jump off the page as a good proxy for cash flow at first blush, it does help understand cash flow potential better than you might imagine.
ACV is the calculation of determining how much revenue a typical SaaS contract will bring in in a 12 month period for a given company. The simplest way to calculate it is to take the total ARR figure and divide by the total number of customers on contract in a given period. There is more nuance to its calculation depending on how contracts are set up (if there are any additional kickers for usage, etc.), but that’s the general idea.
While this doesn’t really represent any form of bottom line cash flow, it can be a good indicator of a company’s ability to translate ARR into margin. If ACV is high (for instance, above $50K), that means that the typical structure of a software organization will better support the gross and net margin of the entity. Which is to say, the typical overhead involved in running a SaaS business (sales team, software engineers, etc.) will be more than paid for assuming the company generates enough scale. As a result, it can be inferred that the company will have a higher cash flow situation with each incremental contract.
There are a lot of qualifiers around what a “high ACV” really is, depending on business model, go-to-market motion, and a host of other considerations. The generally accepted $50K as being a baseline for ACV for SaaS businesses leans heavily into the notion that the sales organization for said SaaS business will be a traditional sales & commission structure, where you have a bunch of sales people out there selling and upselling the product. These folks are highly commissionable and require a certain amount traction and revenue to clear their overhead.
On the other hand, the distribution model for many SaaS businesses looks a little different that the typical enterprise sales organization. For a company that has developed a solid foundation of product-led growth, it’s not unreasonable to think that ACV can be a little lower. This is because the product is doing a lot of the selling and distribution on its own and is less reliant upon a full sales organization to make that happen.
[If you want a deeper explainer on product-led growth, there are a handful of resources I can point you in the direction of. A more recent case study would be Zoom, which has a relatively low ACV, but extremely profitable business model. Its sales staff is tiny compared to most public SaaS companies.]
ACV is also limited based on the stage of the Company. A lot of Seed and Series A stage startups are doing everything they can just to get their products into the hands of their customers to better test their product-market fit and potential, and, as a result, the contracts aren’t necessarily fully mature. As a result, the ACV might be artificially low for a variety of reasons. While I don’t necessarily recommend selling your product at a discount just to get it into customers hands, if you feel confident that what you are building is going to be so valuable that you will control the pricing dynamic moving forward, it’s not the worst strategy. What’s critically important, however, is to make sure you can show evidence that your product can be upsold and that your retention rate moves in the right direction.
There is a flip side of ACV as well. It’s possible that a very large ACV will raise questions about sales cycle. Most enterprise SaaS investors want to see market penetration and growth overtime (the old adage of triple, triple, double, double growth is still a decent proxy for what folks are looking for at seed stage). Having a super long sales cycle can be an indicator that this growth will be hard to come by. It’s great to go elephant hunting for your product, and having a big name on your logo list can show strong signs of market acceptance and product-market fit, but it’s also important to keep in mind that you need medium wins as much as you need big wins. Hunting a bunch of antelope while simultaneously looking for elephants can be an efficient way to show growth and market acceptance simultaneously (easier said than done, of course). Just make sure the antelope you are chasing after are worth the squeeze as well.
Large ACV can also raise questions about how big a market truly is. If there are only extremely large players in a space, that can be a sign of maybe not a huge market opportunity. For example, if you are selling something only into State Governments, there are only 50 potential targets. So you might get a large contract from Utah, but if you have been rejected by California and West Virginia, that might be a sign that your product is not as scalable as you might think. There are examples of small customer counts that still have large market, with one of the best Case Studies being Veeva Systems. While this is a fairly minor concern, it is one to keep in mind.
Overall, ACV, like most startup metrics, has plenty of solid uses. It also has a fair amount of flaws - anything that reviews a data set purely through a mean calculation has a lot of potential for data manipulation or misreading. It’s a good tool to have in your tool kit and can tell you a lot about early stage SaaS companies as well as fully-baked public software companies as well. Like most tools, it’s all about how you use it.