Learning from the Missing Voices
In the world of decision-making, what you don’t see often matters more than what you do. Survivorship Bias is the tendency to focus only on the people or things that made it past a selection process—and ignore those that didn’t—thereby distorting the full picture and leading to flawed conclusions.
This model is a foundational warning to any executive, strategist, or investor: beware the narrative told only by the winners. Because the losers often have the most valuable lessons.
What Is Survivorship Bias?
Survivorship Bias occurs when we draw conclusions based on the visible successes, while failing to consider the silent majority who failed and disappeared from view.
Think of entrepreneurs idolizing unicorn startups without studying the thousands of failed companies with the same ideas. Or investors analyzing the “Top 10 Performing Funds” without factoring in the countless funds that quietly shut down before making the list.
It’s like looking at a battlefield and only seeing the soldiers who returned—not realizing the real story is with those who never made it back.
A Classic Case: WWII Planes
During World War II, the Allies analyzed returning fighter planes to see where they should reinforce armor. The initial idea was to strengthen the parts with the most bullet holes—wings and fuselage.
But statistician Abraham Wald proposed the opposite. The returning planes survived despite those hits. The real issue lay in the missing planes—the ones that didn’t return—likely hit in other critical areas like the engines.
This is Survivorship Bias in action. It’s not just about what’s in front of you. It’s about what’s not.
Executive Relevance: The Risk of Studying Only Success
In business, this bias creeps in constantly:
- In Hiring: Modeling your leadership hiring process after just the top performers may ignore those who should have succeeded but were lost due to systemic blind spots.
- In Strategy: Benchmarking only high-performing companies may cause you to imitate surface-level traits, while missing foundational differences in market conditions, luck, timing, or risk tolerance.
- In Transformation: Quoting “best practices” without understanding the graveyard of initiatives that used the same methods and failed is a shortcut to repeating history.
Survivorship Bias and Modern Investing
Survivorship Bias also distorts performance metrics in markets. Mutual funds that perform poorly often close or merge into others. But when you scan a database of active funds, all you see are the survivors, making historical returns look rosier than reality.
If you’re assessing managers, strategies, or even stock performance, this bias can inflate your optimism and blind you to risk.
How to Think Clearly: Practical Guardrails
- Ask: Who’s Missing?
Before drawing conclusions, deliberately ask: “Who didn’t make it into this dataset, and why?” - Study Failures Intentionally
Build failure analysis into your decision-making process. There’s often more wisdom in why startups fail than in why they succeed. - Widen the Sample Size
Include a broader range of inputs when evaluating performance. Look at closed funds, scrapped products, and unsuccessful launches to get a full picture. - Normalize for Selection Bias
When benchmarking or forecasting, adjust your expectations to account for how many others tried and failed.
Closing Reflection: Learning from the Invisible
Great decision-makers understand that history isn’t just written by the victors—it’s written about the victors. The stories we tell often exclude the vast, quiet majority who didn’t make it.
True wisdom comes from looking beyond the polished success stories and learning from the overlooked, the forgotten, and the fallen.
Executives who master this lens are less likely to be fooled by vanity metrics, hollow benchmarks, and seductive outliers. They build strategies rooted in the whole truth—not just the part that made it out alive.
Missed out on the over all series?
Murray Slatter
Strategy, Growth, and Transformation Consultant: Book time to meet with me here!
