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Angel Investing Strategies, Part II: Leveraging Survivorship Bias for Smarter Investments
Improving Startup Survival Rates and Investment Outcomes
Introduction
Last week, we explored early-stage investing strategies and noted that blindly expecting a large portfolio to help you achieve market returns is not a great idea. In venture capital, the returns of individual outperformers can be orders of magnitude better than the average, making strategies aimed at achieving "average" or "market rate return" (such as the large portfolio theory) impractical to truly leverage as the number of invested companies increase.
We also emphasized that avoiding the "risk of ruin" is a key component of finding success in active investing. Given the low success rates of early stage investing, we are often taught to consider the money we invest as potentially going to zero. So assuming most of us don’t have infinite wealth, we need to ensure we have more companies survive and exit to keep playing the game of venture investing over a long enough period of time to run into a big winner.
And there may be some truth to that. When modeling returns for an 18 company portfolio, just a 10% decrease in write-offs lowers the requirement to reach 3.5X ROI from two “good exits” + 1 unicorn to five “good exits” and NO unicorns. (“good exits” = 8-10X gross return).
Now granted, driving any company to a financial exit is tough in itself. However, no longer needing to hit a unicorn as an absolute requirement for a decent venture portfolio opens up new options and possibilities for investors, especially when most healthcare exits occur at the $100M-$500M range.
And when we think about “survival”, while it might be tempting to blindly follow industry rhetoric around what makes startups successful and what doesn’t (we’ve written about that topic ourselves in our series on due diligence), we might benefit from borrowing a page from the concept of survivorship bias to try and lower failure rates.
What is Survivorship bias anyways?
For those that aren’t familiar with survivorship bias, here’s the story about WWII airplanes that’s best associated with this phenomenon, courtesy of chatgpt:
During World War II, military engineers faced a critical problem: how to reinforce their airplanes to reduce losses. Initially, they examined the planes that returned from missions, noting where they were most frequently hit by enemy fire. They planned to add armor to these heavily damaged areas.
However, a statistician named Abraham Wald pointed out a critical oversight. The bullet holes on the returning planes indicated areas that could sustain damage and still make it back. The planes that were shot down had likely been hit in other areas, such as the engines or the cockpit. Wald's insight was that the armor should be placed where the surviving planes had no damage, as these areas were critical to the planes' survival.
This story exemplifies survivorship bias: the error of focusing only on the successes (planes that returned) and ignoring the failures (planes that didn’t). By shifting their focus to the unseen data, the military was able to make better decisions and improve the survival rates of their aircraft.
Survivorship bias also shows up in serious disciplines such as scientific publications, and more humorous(?) cases such as cats falling from great heights.
Please don’t try this at home
Why look at early stage investing through a survivorship bias lens?
Finding the “next Uber” or “next Google” is a dream for any early stage investors, but if we’re here to play the long game, survivorship bias might offer us some wisdom:
Learning from Failures
Failure provides valuable lessons, but unless companies fail publicly, such as Babylon Health or Pear Therapeutics, most failed companies die a lonely death, often without sharing their stories (there used to be a great website that tracks startup failures which no longer exists). This lack of visibility into failure means that we can only primarily use successful companies as proxies for avoiding failure, just like the surviving bombers taught us where to reinforce subsequent airplanes to increase the odds of them returning from battle.
Understanding Success
While it is important to understand and learn from success factors, we must also assess whether these factors are sustainable and repeatable. Just because a particular strategy worked for one successful company does not guarantee it will work for others. Survivorship bias helps us question the generalizability of success factors. Are they truly replicable, or were they contingent on unique circumstances that might not be present in new ventures?
Avoiding Over-Optimism
Survivorship bias reminds us to temper our expectations. Focusing solely on the success stories can lead to over-optimism, making investors blind to the inherent risks and challenges of startup investing. By acknowledging the full spectrum of outcomes, including failures, we can develop a more realistic perspective. This balanced view helps in setting more achievable goals and prevents the trap of expecting every investment to be a home run.
Improving Portfolio Construction
Incorporating survivorship bias into our evaluation process can significantly enhance portfolio construction. Instead of spreading investments too thinly in hopes of hitting multiple unicorns, a more strategic approach can be taken. By identifying the critical factors that contribute to both success and failure, investors can make more informed decisions about which startups to support. This leads to a more robust and resilient portfolio, with a higher likelihood of containing companies that have a genuine chance of success.
Applying survivorship bias to startup success factors:
When evaluating venture-backed companies, traditional success factors often dominate the narrative. However, applying survivorship bias can reveal overlooked areas of strength that may be critical to a startup's survival and success. Here are some reasons to look for strength elsewhere:
Founding Team’s Background and Experience
Common Belief: Successful startups often have founders with prestigious backgrounds, such as Ivy League degrees or experience at top tech companies.
Survivorship Insight: Many failed startups also had similarly impressive founders. Instead, look for founders with resilience, a deep understanding of their industry, and a track record of overcoming adversity. Practical experience and a passion for the problem they are solving can be more indicative of potential success.
Rapid Growth and Scalability
Common Belief: High growth rates and the ability to scale quickly are seen as primary indicators of a startup’s potential.
Survivorship Insight: Rapid growth can sometimes mask underlying issues such as unsustainable business models or poor unit economics. When evaluating companies, focus on factors driving steady, sustainable growth and a clear path to profitability. Even at the pre-revenue stage, one can tell alot, especially in healthcare verticals, about the business viability through their understanding of their initial customer profile and go to market strategy.
High Profile Investors and Big Funding Rounds
Common Belief: Securing investment from top-tier venture capital firms is often seen as a validation of a startup’s potential.
Survivorship Insight: While prestigious investors can open doors, they don’t guarantee success. Many startups with significant funding still fail. Instead, assess how wisely the startup uses its funds. Look for prudent financial management and efficient capital allocation. Are the companies maximizing their dollars towards experimentation and improving their business viability?
Market Size and Opportunity
Common Belief: A large addressable market is often seen as a crucial factor for a startup’s potential to become a unicorn.
Survivorship Insight: Many startups in large markets still fail to capture significant market share. Evaluate the startup’s competitive differentiation, barriers to entry, and their ability to execute on their market strategy. Smaller, niche markets with less competition can sometimes offer better opportunities for startups to establish a strong foothold. As we like to say, “0% of a billion dollar market is worth 0 dollars”.
Conclusion
The goal for any early stage investor is to generate above average returns by hitting large winners. However, we believe that too much attention has been paid to hitting massive winners in an unsustainable way for smaller investors with a smaller approach, and there are underappreciated opportunities in decreasing startup failures.
By applying survivorship bias, investors can gain a more nuanced understanding of what truly drives startup success. This approach encourages looking beyond conventional success factors and identifying the underlying strengths that can sustain a startup through the challenges of growth and market competition.
What should investors do instead of spray and pray, and chasing the ghost of past success? Join us next week as we continue exploring strategies and concepts to help investors enhance their early stage investing experience.
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