- Statistics about successful companies can seem very exciting. However, most companies aren’t successful. That means those statistics don’t represent a “normal” outcome. They represent an unlikely outcome.
- That’s basically what survival bias is – having data that only selects from (or biases towards) successful outcomes.
- If you fail to spot data with survival bias, you may be given unrealistic expectations for how well an investment is likely to go.
- These mistaken expectations can lead us to take on more risk than we realize and jeopardize returns and investment objectives.
Startup Investing
There are a lot of reasons to be excited about equity crowdfunding and the increased accessibility of investing in private companies.
One, it provides avenues for impact investing. A collection of retail investors can turn many small capital contributions into significant support for a founder, business, mission, or problem that needs solving.
Two, more avenues for raising funds also means that a more diverse range of founders and companies have a shot at getting consideration for investment.
Three, companies that allow their customers and audience to invest through “community rounds” can add an entirely new dimension to the relationship with their most dedicated customers and community members.
Four, it allows smaller investors to get in early at lower valuations. This opens up the possibility for a level of returns that is extremely difficult to impossible to get in the public markets.
However, it’s this fourth item where care is needed.
Setting The Trap
One of the most famous startup investing stories is Airbnb. For the few venture firms that backed the company during its seed round, their returns upon Airbnb’s IPO were simply eye-popping.
If you had invested $1000 when Y-Combinator did, it’d be worth nearly $5 million.
Benzinga
Putting $1000 into a good idea, waiting 10 years, and cashing that in for $5M basically sounds like the dream for any investor, especially for anyone hoping to get rich moderately quickly.
With that kind of return, you can be wrong 99% of the time and still have a nice return. Investing $1M and having $999,000 of them be complete duds but having one turn into $5M is still a 5X. Not bad! Right?
Well, here’s the thing.
We can pretty much say for sure that isn’t going to happen for anything you’re investing in.
A rush of objections might be forming already – but why? It’s happened before. It’s actually happened plenty of times. All the early investors in major companies like Airbnb made huge profits!
Which brings us to survivorship bias.
Survivorship Bias
Put most simply, survival bias results in an incorrect expectation of what the realistic potential outcomes of something are.
Expectations are skewed because we unintentionally make our assessments with a biased sample of data. Those that “survive” are more likely to be noticed or included and thus have a disproportionate effect on how we view things.
Let’s try a sports metaphor.
Let’s assume the statement “Any Quarterback that plays in the NFL for more than 10 years is basically a lock to get into the Hall of Fame” is true for this example.
So, does that mean the Hall of Fame criteria is basically just a count of how many years you played in one or more games? That a player that plays in one game a year for 10 years would be a likely candidate?
Something is clearly wrong here.
The issue is that the statement is true because it inherently filters out many players. Think about it – how hard is it to be on an NFL team for even one season?
Only the best players in the world can compete for those limited roster spots. Then how hard is it to do that consistently for years at a time? Many players that have one or two good seasons disappear from the professional levels, unable to consistently execute at that caliber.
That means to be able to play in the NFL for 10 years, you actually have to be among the best players in the world for that entire time. So, our original statement sneakily speaks of only a small, elite fraction of athletes in the sport.
Imagine if we had instead said “Any Quarterback that can be among the best in the world at the position and consistently hold their own against professional competition for 10 years is almost a lock for the Hall of Fame.”
Now, that doesn’t sound so crazy, does it?
How Does This Relate To Investing?
Now, consider the following illustrative statements, while thinking about survivorship bias:
- “The average exit valuations for companies in our industry are between 8-12X yearly revenue.”
- “Investors that got in during the seed round of companies that eventually IPO’ed saw an average gain of 25,000%.”
When you see them, they sound very enticing. It feels like you’re setting yourself up for a really big win. You’ve found an amazing opportunity.
And maybe you have. But, statements like these are misleading your expectations with their survival bias.
Sure, maybe companies in that industry do tend to get acquired for that much. However, what percentage of startups actually have enough of a product and business fit to get acquired in the first place?
This is an illustrative example, so we can’t really investigate, but I feel fairly confident saying that it’s a whole lot less than 50%. Maybe less than 10%. Imagine seeing this instead:
“There’s a 90% chance this turns into nothing, and a 10% chance we can exit for around 10X our revenue. Even then, that’s only a nice return if we can substantially grow revenue over the next few years.”
I bet you’d think a lot more before making an investment if you saw this version instead of the original.
Conclusion
It’s great that we continue to see a democratization of access across alternatives, including investing in startups and private companies.
However, while there is great potential upside, it’s important to remember that many of the facts and figures about potential exits and returns are laden with survivorship bias.
It’s important to realize that and to have grounded expectations about the risks and rewards (or probable lack thereof) when making investment decisions. Otherwise, it’s easy to get overly excited and make a poor decision based on unrealistic and improbable expectations.
