Burn to Earn

It was one of those parties last weekend, where there are too many small groups of people chilling together; friends, friends of friends, and friends of friends of friends. The music was deafening, and the place was filled with innumerable loud sentences getting mixed in a giant loop around my head. “Valuation”, I heard someone use that word in a conversation. I ignored it and continued joining dots and making sense of a random story I was being told. “Valuation”, I heard it again.

It was Robin. I grabbed him by his shoulder and took him out. Probably too demanding given I’d been introduced to him all of five minutes ago. He had taken a few steps in establishing his company, CheatCode. “I need 20 million; how much stake would I have to offload?”, he asked. *facepalm* I need to know much more than knowing the name of the venture.

And there I was — valuing CheatCode. With established companies, there is a fair amount of confidence built around estimates. Historic trends around revenue streams are in place, the nature and dynamics of cost structures are known, and strategic direction can be built into models.

In the case of start-ups, it is a challenging process because of the absence of history, large operating losses at the time of the estimate, and more importantly, the lack of experience around knowing how much cost has to be incurred in order to generate a certain quantum of incremental revenue. When owners are asked about their sense of how things will evolve; it is natural for one to see exponential growth in revenue, and the belief that most costs that are bulky in nature would been incurred in the near future; making the path to sustainable profitable growth, a rather quick and easy one.

But, revenue growth and profitability can’t be delivered for free. Consequently, it is critical for one to build a system that recognises estimation errors. Let’s make it simpler, by taking CheatCode as an example.

Once detailed revenue and cost assumptions are in place, it helps to analyse the operating margins of more established companies in the business. This could be termed as the target margin, that the start-up would ideally reach when it is assumed to operate when established. With CheatCode, this seemed to be in place, with steady improvement in margins, and stability at ~25%, in line with established comparable companies.

Check #1 seems okay, but isn’t enough!

But, no, this was deceiving. There was inconsistency in the estimates. The model was factoring in expenses/reinvestments that were too little, for the expected revenue growth. How do you know this? And how do you correct this? A simple exercise to conduct is the calculation of the return on capital. This could then be compared to the industry average return on capital.

Check #2 highlights inconsistency that needs to be corrected

Clearly, we were expecting CheatCode to be an outlier. A simple reverse calculation, by keeping the return on capital capped at 30%, shows the amount of inconsistency in absolute terms. This can either stem out of [1] underestimation of costs, or [2] lesser reinvestment than what is required for the forecasted revenue growth.

Easy peasy lemon squeezy. Okay, that wasn’t required.

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