Survivorship bias is all around us, yet many of us do not notice it shaping how we see success and failure in life. Survivorship bias happens when we only look at people or things that have survived or succeeded, while ignoring those that failed or disappeared. This common mistake can give us a false idea of what it really takes to succeed, because we forget about all the examples that did not make it.
Being aware of survivorship bias is important if we want to make smarter decisions in business, health, and even our personal lives. By learning to spot this bias, we can avoid drawing the wrong conclusions based on incomplete information and better understand the true reasons behind success and failure.
Key Takeaways
- Survivorship bias results from focusing on successes and ignoring failures.
- It can mislead our decisions in work, finance, and health.
- Knowing about this bias helps us make more informed choices.
Defining Survivorship Bias
Survivorship bias causes us to focus on people or things that succeeded while ignoring those that did not. This can affect how we interpret results, make decisions, or understand success and failure.
Origins of the Term
The term "survivorship bias" comes from studies of groups where only the successful or surviving members are visible to researchers. One famous example is from World War II.
During the war, analysts studied damage to aircraft that returned from battles to decide where to add more armour. However, this approach ignored the planes that did not come back. These missing planes held critical data about what areas needed the most protection.
This sort of bias is not new. We see it in fields like finance, science, and medicine. Anytime we only study the winners or survivors of a group, our view gets distorted. The term reminds us to look for missing data when analysing results.
Difference Between Survivorship and Survivor Bias
"Survivorship bias" and "survivor bias" are often used in similar ways but have slight differences. Survivorship bias is the more common phrase and means focusing on individuals, teams, or companies that made it past a certain point, while not considering those that didn’t.
Survivor bias is sometimes used for personal or psychological situations, where we may focus on a surviving person’s story. In both cases, the main problem is ignoring failures, which can lead us to wrong conclusions.
For example, studying only successful businesses gives us an incomplete idea of what it takes to thrive. We miss lessons from the many companies that failed but never get noticed.
Incomplete Data and Hidden Failures
Incomplete data is at the heart of survivorship bias. When we look only at survivors, our data set leaves out those who didn’t make it. This missing information changes the results in ways we might not notice.
Hidden failures can completely change what we learn from a situation. Ignoring failed experiments, businesses, or products risks repeating the same mistakes.
We need to remind ourselves to ask, “What is missing from this picture?” Without data on failures, our understanding of any field—from science to sports—remains limited.
Tables, lists, or other visual aids can help us compare survivors with non-survivors to see the difference and fill in knowledge gaps.
Historic Examples and the World War II Aircraft Case
Survivorship bias has shaped important moments in history. Through looking at overlooked data, people have been able to make smarter decisions, especially during times of conflict and change.
Abraham Wald and Aircraft Analysis
In World War II, Allied forces faced heavy losses as their planes returned from combat with visible bullet holes. Statisticians, including Abraham Wald, were asked where extra armour should go to protect aircraft.
Wald realised the key information came from the planes that did not return. The bullet holes on returning aircraft showed where planes could be hit and still make it home. Areas with little or no damage, on the other hand, often meant a direct hit there caused the plane to be lost entirely.
Wald recommended reinforcing the parts with little damage on returning planes, like the engines and cockpit. His insight prevented wasted resources and improved survival rates for pilots. His work is now a classic example of how survivorship bias can lead us to ignore failures if we only look at successes.
Lessons from World War II
The World War II aircraft case teaches us the danger of focusing only on survivors. Generals and engineers almost made a costly error by planning to reinforce the areas with the most visible bullet damage.
By looking only at the planes that returned, they ignored the data from the lost planes, whose weaknesses were in other parts. Wald’s analysis taught us to ask which missing information could be vital.
This example shows how survivorship bias can cloud thinking in high-stakes situations. It’s a lesson in the value of considering unseen failures, not just visible success.
Other Historical Applications
We find survivorship bias in many other historical settings. In business, we often hear stories about start-ups that made it big, but not about those that failed and disappeared quietly.
In science and exploration, famous successes are studied and written about, but lessons from failed projects are often lost. This can lead to repeating mistakes and ignoring useful warnings from the past.
Economics, finance, and even stories about inventors are affected by this bias. When we only focus on enduring examples, we miss the full picture and risk drawing the wrong conclusions.
Impact of Survivorship Bias on Decision-Making
Survivorship bias often leads us to focus only on the visible successes while ignoring hidden failures. This distorts our judgement, resulting in poor choices based on incomplete information.
Flawed Strategies and Cognitive Pitfalls
When we only notice the winners, we miss out on vital lessons from those who did not succeed. This can cause us to copy risky or untested methods, thinking they guarantee success. For example, many people study the habits of successful entrepreneurs, believing these methods alone lead to wealth. We overlook the many who followed the same steps but failed.
Survivorship bias encourages confirmation bias, where we seek information that supports what we already believe. This makes our decision-making less reliable. We may wrongly assume our chances of success are higher than they truly are because we do not consider the full range of possible outcomes.
| Cognitive Pitfalls | Description |
|---|---|
| Confirmation bias | Seeking only supportive evidence |
| Overconfidence | Believing odds are better than reality |
| Risk blindness | Ignoring challenges faced by failures |
Real-Life Implications in Daily Choices
We see survivorship bias in everyday life. For instance, fitness trends often highlight dramatic transformations, but fail to mention those who saw little or no results despite similar effort. This misleads us about what is truly effective.
In financial decisions, people may invest in stocks based on companies that succeeded, ignoring how many similar firms did not survive. This can lead to poor investment strategies.
Students might choose schools or courses by looking only at famous graduates. We miss how many did not achieve the same outcomes. Survivorship bias can also affect health choices, business plans, or job searches.
To avoid these pitfalls, we need to look for data on both success and failure, not just the easy-to-spot winners.
Survivorship Bias in Business, Finance, and Entrepreneurship
Survivorship bias leads us to miss important information by focusing only on winners and overlooking those who did not succeed. This skews our understanding of risk, reward, and what it really takes to thrive.
Overstated Success Stories
We often hear about companies and individuals that achieved great success, such as well-known entrepreneurs Mark Zuckerberg, Steve Jobs, and Bill Gates. These stories are shared everywhere, creating the impression that success is common and follows certain clear steps.
However, most businesses and start-ups do not survive in the long run. By only looking at those who 'made it', we underestimate how hard it is to succeed. When failed ventures are ignored, the risks faced by new businesses get downplayed.
Survivorship bias can even affect studies and guidance about starting a business. If we focus on famous cases, we can be misled about what strategies usually work, causing us to overestimate our chances of making it big.
Mutual Fund and Company Performance
In finance, survivorship bias often appears in studies of investment funds or company performance. For instance, when measuring mutual fund results, only those funds still running are sometimes included in the analysis.
This can make average returns look higher than they actually are. Failed funds, which often lost money, are left out of the data. The result is that investors see a misleading picture of how well funds perform.
If we want a true, fair comparison, we should include both surviving and failed funds and companies in our reviews. Ignoring those that closed down can distort statistics and influence our financial decisions in the wrong way.
Entrepreneurs and the College Dropout Narrative
The idea that dropping out of college leads to major business success is popular. Stories about Mark Zuckerberg, Steve Jobs, and Bill Gates make this seem like a proven path to wealth.
What we often forget is that thousands of people leave university but never become successful entrepreneurs. The odds of building a company like Facebook or Microsoft are extremely low.
Key problems with the dropout myth:
- It highlights rare success stories
- It ignores countless failures
- It oversimplifies the road to business achievements
By only shining a spotlight on these rare winners, we get an incomplete view of the risks involved in leaving education to pursue entrepreneurship.
Effects in Health, Science, and Other Sectors
Survivorship bias influences how we interpret data, make decisions, and create policies. Ignoring those who do not succeed, or whose experiences go unrecorded, can lead to incorrect conclusions in medicine, engineering, and many other fields.
Medical Research and Treatment Outcomes
In medical studies, we often focus on patients who have recovered or survived, leaving out those who did not respond to treatment or dropped out of trials. This can make new treatments appear more effective than they actually are. For example, public health policies may overestimate a drug’s benefits if they only consider survivors.
Clinical trials for diseases like cancer and mental illness sometimes highlight the progress of those who do well. As a result, doctors and researchers may not see the full range of side effects or the actual risk of failure. Policies based only on successful outcomes can cause resources to be allocated to less effective treatments, while better options are overlooked.
Key Impacts:
- Skewed data in scientific literature
- Misleading treatment success rates
- Policies that do not help everyone in need
Product and Building Longevity
In the fields of engineering and architecture, we often hear about structures and machines that have lasted for decades. The products that failed early are usually forgotten. This bias can make us believe that certain designs or brands are more reliable than they truly are.
When we only study the buildings still standing or the machines still running, we miss important data about what causes failures. As a result, we might continue building to older standards that only appear successful because their failures are hidden or ignored.
Examples:
- Celebrated historic buildings while failed ones are erased from records
- Emphasis on legacy products, overlooking design flaws that led to early failures
- Standards based on visible success, not the full range of outcomes
Other Fields Affected by the Bias
Survivorship bias is not just a problem in health and engineering; it affects many industries. In business, we often hear stories from successful entrepreneurs but rarely from those who did not make it. This gives a false sense of how easy or likely success is.
In employment, focusing on traits of promoted workers can ignore how much luck or outside factors helped. In education, we sometimes study top-performing schools, without seeing the struggles elsewhere.
Sector Examples:
- Business: Overvaluing popular strategies and ignoring those that failed
- Workplace: Misjudging what behaviours lead to promotion or recognition
- Education: Missed lessons from students or schools that drop out early
We need to be aware of survivorship bias so that our decisions and policies are based on complete, not just successful, data.
Recognising and Avoiding Survivorship Bias
When we make decisions, survivorship bias can lead us to focus too much on winners and miss lessons from failures. To make sound choices, we should use specific methods to spot this bias and address it with clear steps.
Strategies to Mitigate the Bias
We can reduce survivorship bias by first acknowledging that it exists. Acting as if it cannot affect us is a mistake. Instead, we should actively seek information about failures, not just successes.
It is helpful to use checklists or decision guides that prompt us to ask, “What didn’t work, and why?” We can also discuss our decisions with people who have different points of view or more experience, as they might spot bias we miss.
Including case studies of both success and failure gives us a better picture for our decision-making. Trying to adopt a “lessons learned” approach can turn past failures into useful guides.
Analysing Comprehensive Data Sets
To avoid survivorship bias, we need to examine complete data, not just examples of success. When possible, we should collect data on all attempts, not only those that worked out.
For example, studying all businesses in an industry, instead of just those that survived, helps us see patterns that lead to failure as well as success. This can highlight warning signs we might otherwise miss.
Using tables or charts to compare outcomes for both successes and failures makes it easier to spot trends. For instance:
| Group | Number Started | Number Succeeded | Number Failed |
|---|---|---|---|
| Tech Start-ups | 1000 | 100 | 900 |
| Restaurants | 800 | 120 | 680 |
Being mindful that incomplete data skews our perspective can help us catch mistakes before we make big decisions.
Promoting Balanced Perspectives
We should encourage ourselves and our teams to value stories of failure alongside stories of success. By sharing information about what went wrong, we build a more realistic view.
Inviting feedback from people who were not among the “survivors” in a group—such as those who left a job or stopped a project—broadens our understanding.
Regular training or workshops can help embed this thinking into company culture.
By promoting a balanced approach, we avoid overestimating the chances of future success, which leads to better, more informed decision-making.
Frequently Asked Questions
We examine how survivorship bias shows up in different areas. These include history, science, psychology, family life, and the media.
What are some classic examples of survivorship bias?
We often hear stories about businesses that succeeded during hard times. People may assume following their path guarantees success, but they rarely see or study the many businesses that failed.
Another classic example comes from wartime, when damaged planes that returned were studied, while those that did not return were ignored, leading to wrong conclusions.
How did Abraham Wald's work contribute to our understanding of survivorship bias?
During World War II, Abraham Wald studied bullet holes in returning aircraft. He realised that only the surviving planes were being examined.
Wald advised reinforcing armour where planes returning had the least damage, not the most. His insight helped prevent survivorship bias and saved many lives.
Can you explain the role of survivorship bias in psychological research?
In psychology, we may only look at participants who complete a study. If we ignore those who dropped out or failed, our results can be misleading.
This bias makes treatments or interventions seem more effective than they really are, as failures are overlooked.
What is meant by 'reverse survivorship bias'?
Reverse survivorship bias is when we pay more attention to failures instead of successes.
Here, we might focus too much on negative outcomes or problems, missing important lessons from those who succeeded.
In what way does survivorship bias affect parental decision-making?
Parents sometimes see only the positive outcomes of certain parenting choices in other families. They may ignore unsuccessful cases because they are less visible.
This can lead parents to follow trends or advice based only on examples of apparent success, rather than the full range of outcomes.
How is survivorship bias recognised in discussions about transgender experiences?
Stories about transgender people often highlight those who are thriving or accepted. We hear less about those facing ongoing challenges or discrimination.
This can give a false sense of how easy transition or life as a transgender person can be, hiding the struggles that many still experience.
