20 Survivorship Bias Examples You Need to Know

We often look at successful people, companies, or strategies and think, “That’s the blueprint! I just need to copy what they did.” But what if we’re only seeing part of the picture? What if we’re ignoring a vast graveyard of failures that followed the exact same path?

This is the core idea behind survivorship bias. It’s a common thinking error where we focus on the things that “survived” a process and overlook those that didn’t, leading to potentially flawed conclusions.

Understanding survivorship bias is crucial because it affects our decisions in business, finance, health, and even everyday life. Recognizing it helps us make more informed choices by considering the whole story, not just the happy ending.

This article will break down survivorship bias in simple terms and explore 20 diverse examples to help you spot it in the wild.

What is Survivorship Bias?

Download the above infographic in PDF

Imagine you want to learn how to build a successful tech startup. You read biographies of Bill Gates, Steve Jobs, and Mark Zuckerberg. You notice they all dropped out of college. You might conclude that dropping out of college is a good strategy for tech success.

But wait! You’re only looking at the survivors – the tiny fraction of college dropouts who became billionaires. You’re completely ignoring the vast majority of people who dropped out and didn’t achieve massive success. That information is missing.

Survivorship bias is the logical error of concentrating on the people or things that made it past some selection process and overlooking those that did not, typically because of their lack of visibility.

Think of it like this:

• You only see the winners, not the losers.
• You only see the success stories, not the failures.
• You only see the things that lasted, not the things that broke or disappeared.

This missing information – the “silent evidence” – can lead us to overestimate the chances of success or misunderstand the actual reasons behind it. We draw conclusions from incomplete data.

Why is this dangerous?

• It gives us a distorted view of reality.
• It leads to poor decision-making.
• It makes us overconfident in strategies that might be riskier than they appear.
• It can cause us to misattribute success to the wrong factors.

Now, let’s dive into specific examples to see how this bias plays out.

20 Survivorship Bias Examples Explained

Download the above infographic in PDF

Here are 20 examples of survivorship bias across various fields, explained simply.

1. The WWII Bomber Planes (The Classic Example)

• Scenario: During World War II, the Allied forces wanted to add armor to their bomber planes to reduce losses. But armor is heavy – adding too much would make the planes inefficient. They needed to figure out the most critical areas to reinforce. They analyzed the planes that returned from missions, noting where they had bullet holes. The initial thought was to reinforce these damaged areas.
• The Bias: Statistician Abraham Wald pointed out the error. The military was only looking at the planes that survived. The bullet holes on the returning planes showed where a plane could be hit and still make it back. The truly critical areas were the ones with no bullet holes on the survivors – because planes hit in those areas (like the engines or cockpit) likely didn’t return at all. The missing data was the location of damage on the planes that were shot down.
• The Takeaway: Don’t just look at what survived; actively consider what might have caused failure. The most important information might be in the data you don’t have.

2. Billionaire College Dropouts

• Scenario: We hear stories about Bill Gates, Mark Zuckerberg, and Steve Jobs – all college dropouts who founded incredibly successful companies. This might lead some to believe dropping out of college is a viable path to riches.
• The Bias: We focus on the handful of famous, successful dropouts (the survivors). We ignore the millions of people who dropped out of college and did not become billionaires. The success rate for dropouts becoming tech billionaires is astronomically low. The “failure” data is missing from the popular narrative.
• The Takeaway: Extraordinary success stories are often outliers. Don’t base general life strategies on extreme exceptions without considering the base rates and the experiences of the vast majority.

3. “They Don’t Build Them Like They Used To” – Old Buildings

• Scenario: People often admire old buildings, remarking on their durability and craftsmanship compared to modern structures. “They don’t build them like they used to,” is a common phrase.
• The Bias: We only see the old buildings that survived. All the poorly constructed buildings from the same era collapsed, burned down, or were demolished long ago. We’re comparing the best-built survivors of the past with the average building of today. The buildings that didn’t last are the missing data.
• The Takeaway: Time acts as a filter. What remains from the past is often the most durable or lucky, not necessarily representative of the average quality of that era.

4. Mutual Fund Performance Reports

• Scenario: Investment companies often advertise the impressive track records of their mutual funds. You might see charts showing strong performance over the last 5, 10, or 20 years.
• The Bias: These reports often suffer from survivorship bias. Funds that performed poorly are often closed down or merged into other funds. The advertised track records typically only include the funds that survived (i.e., performed well enough to stay open). The poor performance of the failed funds is excluded, making the average performance look much better than it actually was across the entire original pool of funds.
• The Takeaway: Be skeptical of performance statistics, especially in finance. Ask if the data includes funds that no longer exist. Look for data sources that track all funds, including the failures.

5. Successful Startup Advice

• Scenario: Entrepreneurs read countless articles and books featuring advice from founders of “unicorn” startups (companies valued over $1 billion). They try to emulate their strategies, work habits, and funding approaches.
• The Bias: The advice comes exclusively from the tiny percentage of startups that achieved massive success. It ignores the 90%+ of startups that fail, even if they followed similar advice or worked just as hard. The stories of failed founders, whose strategies didn’t work out, are rarely highlighted.
• The Takeaway: Success involves many factors, including luck, timing, and market factors and conditions, not just the founder’s actions. Advice from survivors might highlight necessary conditions, but not sufficient ones. Seek out “post-mortem” analyses of failed startups too.

6. “Secrets” of Long-Lived People

• Scenario: News articles often feature interviews with centenarians (people over 100) asking for their secrets to longevity. They might say things like “eating chocolate every day” or “drinking a little whiskey.”
• The Bias: We’re only interviewing the people who survived to an old age despite (or perhaps unrelated to) their specific habits. We don’t hear from all the people who had similar habits but died much younger due to genetics, accidents, or other health issues. Maybe the chocolate-eater just had great genes.
• The Takeaway: Correlation doesn’t equal causation. Anecdotes from survivors aren’t reliable evidence for health strategies. Rely on broad scientific studies, not just stories from outliers.

7. Online Reviews

• Scenario: When looking up a product, restaurant, or service online, you often see reviews that are either glowing (5 stars) or terrible (1 star), with fewer reviews in the middle.
• The Bias: People are more motivated to leave a review when they have a very strong reaction – either extreme satisfaction or extreme dissatisfaction. Moderately satisfied customers (the likely majority) often don’t bother leaving a review. The “surviving” reviews represent the extremes, not necessarily the average experience.
• The Takeaway: Be aware that online reviews can be skewed. Look for the overall volume of reviews and try to read a range, paying attention to patterns in moderate reviews if available.

8. Historical Accounts Written by “Victors”

• Scenario: Much of recorded history focuses on the achievements and perspectives of winning empires, successful rulers, or dominant cultures.
• The Bias: History is often written by the survivors or victors. The perspectives, stories, and even existence of defeated peoples, failed movements, or lost cultures are often underrepresented or completely missing. We get a skewed view based on who had the power to record and preserve their story.
• The Takeaway: Seek out diverse historical sources and perspectives, including those from marginalized or defeated groups, to get a more complete picture of the past. Be critical of dominant narratives.

9. Music Industry “One-Hit Wonders” vs. Legends

• Scenario: We remember legendary bands and artists with long, successful careers. We might analyze their music, marketing, and evolution to understand musical success. We also remember “one-hit wonders” as curious anomalies.
• The Bias: We focus on the artists who achieved some level of fame (the survivors in the public eye). We completely forget the thousands upon thousands of talented musicians and bands who never got a record deal, whose albums flopped instantly, or who played in obscurity their whole lives. The definition of “survivor” here is even just reaching public awareness, let alone lasting success.
• The Takeaway: The music industry is incredibly competitive. Focusing only on famous artists gives a misleading impression of the odds and requirements for success.

10. Self-Help Book Authors

• Scenario: Self-help books promising wealth, happiness, or productivity are often written by people who have achieved remarkable success in those areas. They detail their methods and mindsets.
• The Bias: The authors are the “survivors” who made their methods work (or believe their methods were the key reason). We don’t hear from the countless people who read the same books, applied the same techniques, and saw no significant results. The failures of the method are invisible.
• The Takeaway: Be critical of self-help advice. What worked for one person (the author) might not work for everyone due to different circumstances, luck, or inherent abilities. Look for evidence beyond the author’s own story.

11. Studying Tame vs. Wild Animals

• Scenario: Researchers studying animal behavior might find it easier to observe animals in captivity or those that have become habituated to humans.
• The Bias: The behavior of captive or tame animals (the “survivors” of the capture or habituation process) may not accurately represent the behavior of their counterparts in the wild. Wild animals might be more cautious, aggressive, or exhibit different social structures. Conclusions drawn only from the accessible group might be flawed.
• The Takeaway: Be mindful of the sample population in any study. Ensure it’s representative of the group you want to understand. Results from captive animals may not generalize to wild populations.

12. Medical Treatment Studies (Ignoring Dropouts)

• Scenario: A study reports a high success rate for a new medical treatment based on the outcomes of patients who completed the trial.
• The Bias: If patients who experienced severe side effects or found the treatment ineffective dropped out of the study, they might be excluded from the final analysis. The results then only reflect the “survivors” who tolerated the treatment and potentially responded well. This inflates the perceived effectiveness and safety.
• The Takeaway: When evaluating medical studies, look at how dropouts were handled (intention-to-treat analysis is often better). High dropout rates can be a red flag.

13. Job Search Advice from the Employed

• Scenario: People seeking jobs often get advice from friends, family, or mentors who are currently employed. This advice might focus on specific resume techniques, interview strategies, or networking approaches that “worked for them.”
• The Bias: The advice comes from the “survivors” – those who successfully landed a job. It doesn’t account for the experiences of those who used the same techniques but are still unemployed, perhaps due to market conditions, industry shifts, or other factors beyond their control. The advice might be outdated or context-specific.
• The Takeaway: While advice from employed individuals can be helpful, recognize its limitations. The job market is dynamic. Seek diverse perspectives, including insights from career services or industry reports on current trends.

14. Ancient Philosophies and Texts

• Scenario: We study the works of Plato, Aristotle, Confucius, or Seneca – philosophers whose ideas have endured for centuries. We might assume their ideas represent the pinnacle of ancient thought.
• The Bias: We only have access to the texts and philosophies that survived. Countless other thinkers, schools of thought, and manuscripts have been lost to time due to wars, fires, neglect, or suppression. What we study is a curated collection shaped by historical accidents and the preferences of those who preserved the texts.
• The Takeaway: Appreciate the surviving texts, but acknowledge they represent only a fraction of the intellectual output of their time. Recognize the role of chance and power in determining which ideas endure.

15. “Hustle Culture” Glorification

• Scenario: Social media is full of entrepreneurs glorifying extreme work hours (“hustle culture”) as the key to success, often showcasing luxurious lifestyles as the result.
• The Bias: We see the posts from the small minority who “made it” while working relentlessly. We don’t see the masses who followed the same path and suffered burnout, mental health issues, failed businesses, or damaged relationships without achieving similar success. The negative outcomes and failures are largely invisible.
• The Takeaway: Be wary of narratives that glorify extreme work habits. Sustainable success often involves balance. The costs of “hustle culture” are often hidden by survivorship bias.

16. Relationship Advice from Long-Married Couples

• Scenario: People often seek relationship advice from couples who have been married for decades, assuming they hold the secrets to lasting love.
• The Bias: We’re only hearing from the couples whose relationships survived. We don’t get relationship advice from the (often much larger) group whose marriages ended in divorce, even if they started with similar hopes and strategies. Furthermore, some long marriages might endure due to social pressure, financial dependence, or inertia, not necessarily because they are happy or healthy.
• The Takeaway: While long-term couples may offer valuable insights, their experience isn’t universal. Relationship success is complex. Consider advice from therapists and researchers who study broad patterns in both successful and failed relationships.

17. Website Design Trends

• Scenario: A web designer notices several successful websites are using a particular design trend (e.g., minimalist navigation, large hero images). They decide to implement this trend on their client’s site, assuming it contributes to success.
• The Bias: The designer is only looking at successful websites (survivors). They don’t see potentially hundreds of failed websites that used the exact same design trend. The success of the observed websites might be due to other factors (brand reputation, marketing budget, product quality), and the design trend might be irrelevant or even detrimental.
• The Takeaway: Don’t blindly copy trends from successful examples. Analyze why something might be working in its specific context. Consider A/B testing design elements rather than assuming correlation equals causation.

18. Diet and Fitness Success Stories

• Scenario: Advertisements for diet plans or fitness programs prominently feature “before and after” photos and testimonials from people who achieved dramatic results.
• The Bias: We only see the “survivors” – the individuals who successfully completed the program and achieved significant results, often due to exceptional dedication, favorable genetics, or specific circumstances. We don’t see the (likely much larger) group of customers who bought the program but didn’t stick with it, saw minimal results, or even regained the weight later. The failure or non-response data is missing.
• The Takeaway: Be skeptical of miracle results. Look for programs backed by robust scientific evidence and consider typical results rather than just the best-case scenarios presented in marketing.

19. Cats Falling From High Buildings (“Feline High-Rise Syndrome”)

• Scenario: Studies in the past noted that cats falling from greater heights (e.g., above 7 stories) sometimes had fewer severe injuries than those falling from intermediate heights. Some speculated that cats reach terminal velocity and relax, leading to better landings.
• The Bias: The data came from cats brought into veterinary clinics. Cats falling from extreme heights might be more likely to die instantly and therefore never make it to the vet. The data pool primarily included the “survivors.” Cats falling from intermediate heights might be more likely to be injured but survive, thus making up a larger portion of the treated cases. The missing data was the cats that died on impact.
• The Takeaway: Consider how the data was collected. If the collection method systematically excludes certain outcomes (like immediate fatalities), the conclusions drawn from the surviving data can be highly misleading.

20. Studying Elite Athletes

• Scenario: Coaches and aspiring athletes often study the training regimens, diets, and techniques of Olympic champions or top professional players to learn how to achieve peak performance.
• The Bias: They are focusing only on the tiny fraction of athletes who reached the absolute elite level (the survivors). They ignore the thousands of athletes who trained just as hard, followed similar programs, made similar sacrifices, but didn’t achieve the same level of success due to genetics, injury, slightly less talent, bad luck, or other factors.
• The Takeaway: While learning from the best is valuable, recognize that mimicking their path doesn’t guarantee similar results. Factors beyond trainable skills and effort play a significant role in reaching the highest levels of competition. Focus on principles of good training, but tailor them to individual needs and potential.

How to Spot and Avoid Survivorship Bias

Download the above infographic in PDF

Now that you’ve seen the examples, how can you train yourself to recognize and counter this bias in your own thinking? Here are some practical strategies:

1. Actively Seek Out Failure Stories: Don’t just read success stories. Look for post-mortems, analyses of failures, and stories of projects or companies that didn’t make it. What went wrong? What lessons were learned? Websites like Autopsy.io (for startups) or simply searching for “[Industry] failures” can be insightful.
2. Question the “Secrets to Success”: Be skeptical of simple formulas or “secrets” derived solely from observing winners. Success is usually complex and multi-faceted. Ask: What other factors might be at play? Was luck involved? What were the starting conditions?
3. Look for the Base Rate: Before jumping to conclusions based on survivors, ask: How many started? What percentage actually succeeded? If 1,000 companies try a strategy and only 2 succeed, focusing on those 2 gives a very different picture than knowing the 0.2% success rate.
4. Consider the “Invisible Graveyard”: Always ask: What am I not seeing? Who or what failed? Why did they fail? What data is missing from this picture? Try to imagine the characteristics of those who didn’t survive the selection process.
5. Be Wary of Filtered Data: Recognize that performance charts, historical records, and even news reports can be filtered. Ask how the data was collected and whether anything was excluded (like closed funds, demolished buildings, or study dropouts).
6. Distinguish Correlation from Causation: Just because survivors share a trait doesn’t mean that trait caused their survival. The WWII planes weren’t surviving because they were hit in certain areas; they survived despite being hit there.
7. Think Probabilistically: Instead of seeing things in black and white (success/failure), think in terms of probabilities and distributions. Success often lies at the tail end of a distribution.
8. Diversify Your Information Sources: Don’t rely solely on survivor accounts. Read critical analyses, academic studies, different types of data reports, and perspectives from different angles.

Conclusion: Seeing the Whole Picture

Survivorship bias is a subtle but powerful force that shapes our perception of the world. By focusing only on the winners, the success stories, and the things that last, we get an incomplete and often dangerously misleading picture. We might copy strategies that are far riskier than they appear, misunderstand cause and effect, or chase unrealistic goals based on outlier examples.

From the battle-scarred planes of WWII to the gloss of successful startups and the wisdom of the ancients, survivorship bias is everywhere. But by understanding what it is and consciously looking for the “silent evidence” – the failures, the dropouts, the missing pieces – we can start to correct for it.

The goal isn’t to be cynical, but to be realistic. It’s about making decisions based on a fuller understanding of reality, acknowledging the role of failure, chance, and hidden factors. By asking “What am I not seeing?” and actively seeking out the stories of those who didn’t make it, we can develop a clearer, more critical, and ultimately more helpful view of the world. Keep these 20 survivorship bias examples in mind, and you’ll start seeing this cognitive shortcut everywhere – empowering you to make better judgments in all areas of your life.