The science of startup valuation
- June 23, 2022
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“It’s more of an art than a science.”
You’ve probably heard this phrase more often in relation to cooking, from a friend or relative explaining their mixed results with a specific recipe. The implication is that precision and calculation are less important than sensation and intuition.
The same logic is often applied to the evaluation of early-stage startups. The predictions are unreliable, the roadmap contains important assumptions, and the founding team has yet to be really tested. Investors will speak in vague terms about valuation at this stage, which is often a combination of rudimentary Excel and “gut feeling”.
The interesting thing about the cooking analogy is that as you increase your skill, less is true. Any self-respecting chef can talk about the Maillard reaction, the role of protein-binding and leavening agents, or even the angle of radial slices to get uniformly sized onion segments.
Just because the process is qualitative does not mean the methodology is unscientific.
The same can be said for evaluating startups, especially in the early stages, where the focus is on qualitative data.
Potential and ambition
There are two sides to evaluating a startup: potential and ambition.
The potential of a startup is measured with qualitative methodologies such as a scorecard and checklist. They look at everything from the founders themselves to the strength of their intellectual property and the market in which they operate.
What is the industry growth rate? What is the region’s startup survival rate? They provide insight into the theoretical capability of the startup, which is crucial because talking to investors about expectations for the future means first agreeing with the present.
The second step is to measure the startup’s ambition with quantitative methodologies focused on revenue forecasting, such as discounted cash flow. You focus on what the founding team aims to achieve – not capability – which is important for two main reasons:
1. Not everyone wants to build a unicorn in five years. Some startups have the potential for this kind of scale if the money is invested in growth, but not every founding team wants that future. Many are looking for steady growth in a niche market, less dilution and a more predictable future.
2. Some founders think they can build a unicorn, but all they have are horse parts. If projections show $300 million after four years, does that correspond to industry growth? Can they win in a competitive market with no intellectual property advantage or gain confidence in a technical market without experienced founders?
It is through a rigorous and methodological approach of qualitative and quantitative data that you can reconcile the potential and ambition of a startup to arrive at an evaluation. This type of process, done correctly, also has the benefit of eliminating the many biases that easily creep into these decisions under the guise of a “sixth sense”.
In later stages, the focus shifts from qualitative to quantitative measures. Instead of “potential and ambition”, the two sides of the assessment can be thought of as “assets and expectations”.
Think of evaluation like baking: if you’re trying to produce the best slice of bread on the market, you need to make sure your ingredients are of the best quality and your technique and timing are accurate. One is qualitative, the other is quantitative. Properly addressed, both are scientific. Fundamentally, they are reproducible, reliable, and reasonable.