Three takeaways #3 Startup valuation

Last month, I officially graduated from the Executive Master in M&A and Valuation program at the University of Groningen. This executive degree focuses on the full spectrum of the M&A process, including valuation. In the program, we have analyzed deals such as the merger between Ahold and Delhaize, discussed Heineken’s take-over of Asia Pacific Breweries and valued dozens of companies in all sorts of industries and throughout the life cycle. Many deals that we have covered throughout the program contained at least three extra zeros in deal value compared to the venture capital deals that I am working on on a daily basis. Much has been written about the topic of valuation for mature enterprises. Much less, however, has been written on the topic of valuation of startups. Here are three takeaways from my perspective as an early stage investor with an academic background in M&A and valuation.

1. Price ≠ value. Of course, as an entrepreneur, you are certain that the MRR you will be generating with your SaaS startup will exceed $ 100k 24 months from now. As you should be. If you don’t believe in it yourself, why should I? Reality check — it is highly unlikely that your business will play out exactly as planned. And that’s not a bad thing. As long as you measure what you’re doing, learn from it and constantly improve on it. But since there’s uncertainty involved in the development of your business, it is difficult to determine its value at an early stage. This is why price, and not so much value, is an important economic concept at the early stage. Platitude incoming: Price is what you pay, value is what you get <insert Warren Buffet here 😉>. Understanding the difference is key to investing. So next time you hear investors talking about “pricing a round”, now you know where that is coming from.
2. Understand your key value drivers. An understanding of the key value drivers of your business is critical not just for valuation purposes. It also tells me that you truly understand which levers you have that allow you to steer your business towards profitable growth. This is why your financial model should always tie into the key value drivers of your company. On an abstract level, key value drivers are your businesses most important factors that drive performance, such as growth, profitability and capital intensity. To give an example of value drivers not tying into financial models, I sometimes encounter business cases with hockeystick growth trajectories and little to no increase in investments. Growth does not come for free. It is the investments that should drive growth. Investors look into your value drivers to evaluate the investment opportunity. The key drivers are often contained within the metrics that they look at when evaluating your company.
3. Valuation for startups is very much an art. It is possible to apply theoretical models such as the DCF to a startup but if done, it is important to understand that you are calculating the value of the expected cash flows of a certain scenario. Now, recall the uncertainty I mentioned earlier. How likely is it that this exact scenario will play out? Exactly . To illustrate a mistake often made in using DCF valuations for startup valuation — I often encounter DCF models with high double digit discount rates to compensate for the uncertainty involved at this early stage. Theoretically, that’s not correct. The business risk of the cash flows should be incorporated into the cash flows and not in the discount rate. How to incorporate such risk into your valuation model? Easy — build different scenarios into your financial forecast and weigh them. And as far as multiples go, from an academic perspective, there is a lot to be critical about. For startups, defining the right peer group is incredibly difficult. I often see pre-revenue startups comparing their forward looking ARRs with those of public companies who already have billions in revenues. Don’t get me wrong, I like that they are trying to get a feeling about the potential value of their future company and are trying to substantiate their claims using data. It is just from a theoretical perspective that these claims are often not too hard to devaluate, pun intended.

That’s all for now 👋🏼.