Judah Taub is Managing Partner at Hetz Ventures, a top seed stage VC based in Tel Aviv. He lectures on time-management & creative thinking.
In his book, Black Swan, Nassim Taleb demonstrates how in numerous industries, building on the average or the mean is essentially pointless.
He uses two scenarios to illustrate this point. In the first, imagine 100 people are in a room, and I tell you the mean height is 1.8 meters. Now you pick one at random. What would you guess the person’s height? Knowing the average is certainly helpful here, and even if you happened to pick the tallest or shortest person, you are unlikely to be far off.
Now in the second scenario, imagine I told you that 100 people had provided the amount of their net worth, and the mean is $100,000. But if this random assortment happens to include Bill Gates and you pick him, you’d be off by something like 1,000,000,000%.
As Taleb explains, in too many cases—from climate to the stock market—averages or means miss the point.
Averages As It Relates To Startups
But a scenario we are much more likely to encounter than hidden billionaires is working with and investing in startups. I find that, too often, startup investors and founders tend to rely on averages. For example, we may ask ourselves questions like: “What does an average customer pay for a typical product like this?” “What will the average lifetime value of a customer be?” “What will the average discount be in this vertical?”
I think it’s funny that so many do this when we know that the venture power law suggests a small number of startups can generate significant returns, benefiting all the other startups in a particular fund; these startups continue to perform far from the “average” on each of their metrics.
Simply put, if you pitch that your startup will perform anywhere within the range of average, it is probably doomed to fail. It’s the outlier startups that fall outside of the norm and defy statistical expectations.
There are many examples of metrics and factors that fit this rule; here are three that stand out.
Customer Acquisition Cost (CAC) And Annual Contract Value (ACV)
Investors often hear grandiose pitches about how revolutionary a given product could be. At the end of the pitch, they will often ask how much a customer will pay for this product. The response is often something along the lines of: “Well, like most DevOps tools in this space, we should price it at $10 a head” or “Like most cybersecurity products, we think $30,000 for a midsize organization is fair.”
But actually, what we see again and again is that the very best products inherently create a larger willingness to pay and typically require less to acquire initial customers.
How Critical Is Your Product
This is a follow-up to the previous point, but it is one that allows startups to test where they are on the priority scale. Today, most enterprises are cutting costs, especially around third-party applications. I hear plans ranging from cutting 10% to 50% of the tool budget.
Too often, startups interpret this to mean that they need to cut their prices to keep their customers. While this may sound true since, on average, they are right, in practice, they are mostly wrong. Just like when running your household expenses, when you need to cut back, it is the “nice-to-have” expenses that receive the 80% to 100% cut, while the “must-have” expenses likely won’t be affected at all.
As a side note, this is what I see happening today in most startups trying to cut costs. Rather than announcing a 20% salary reduction across the firm, startups are letting go of those that they can’t afford to operate without.
Startup Growth Trajectory
There’s a classic table I often see that shows how fast a startup needs to grow to be in the top quartile, depending on which growth stage it is. These types of tables are popular as they are easy to produce and intuitive to digest. However, I believe that they are flawed, for they are averaging numbers again and again.
Look at the very best startups, and you will see alternative phenomena such as a network effect that kicks in after hitting a critical mass, negative churn as upsells outstrip customers leaving or economics of scale that actually make it easier as you get bigger rather than harder.
Another way to see this? Think differently about startup investing. In stock picking, sometimes getting the broader industry right (such as investing in airlines) is more important than a particular stock (such as British Airways). If you get the big picture right, the rest should fall into place.
I find that in startup investing, the opposite is true. It is infinitely more important to pick the winning startup. Unfortunately, averages in our ecosystem do not count for much.
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