Coaching practices for How to Avoid Single Story Bias
Describe almost anything you are working through and IX Coach finds the practices whose real-world fit is closest. For How to Avoid Single Story Bias, these are the strongest matches in the current practice library.
Does this sound like the set of challenges you might be facing?
- I’ve decided the lesson from this success is “focus narrow” or “go big”
- My whole feed and reading list is wall-to-wall success stories
- I build my whole sense of what’ll happen out of the specifics of this one case and never once ask how often this kind of thing actually turns out that way to begin with.
- I’ve got this clean, satisfying explanation for why it all went the way it did, and it feels airtight
- I’m sure about my read on this, but I only ever notice the things that confirm what I already think
Practices that may help
- Steelman the strategy opposite to the successful one
Before adopting a lesson from a success story, build the best possible case for the opposite approach.
Survivorship Bias: Learning from What You Can’t See - Audit whether your information sources systematically favor survivors
Check whether the media, advice, and communities you consume are filtered toward successes.
Survivorship Bias: Learning from What You Can’t See - Anchor on base rates before adding details
Start with how common the outcome is in the relevant population, then update — don’t start with the story.
The Conjunction Fallacy — When "More Details" Feels More Likely - Identify what the narrative leaves out
After hearing or constructing a causal story, deliberately list the facts it doesn’t explain.
The Narrative Fallacy: Why We Can’t Stop Making Stories - Notice which data you selected — and which you ignored
Your conclusions are built on a sample of the available data — ask what the sample excluded.
The Ladder of Inference - Include a trusted other in high-stakes AARs
Self-conducted AARs have blind spots; a peer or coach who was not inside the event sees the causal story differently.
After-Action Review: The US Army’s Tool for Continuous Learning - Hold multiple maps simultaneously
For complex situations, develop two or three competing models and check which fits better.
The Map Is Not the Territory - Actively seek disconfirming cases
When researching base rates, specifically look for cases where things went badly — failure cases are underrepresented in natural memory.
The Outside View - The Narrative Fallacy: Why We Can’t Stop Making Stories
The narrative fallacy, named by Nassim Taleb in The Black Swan, is the tendency to construct coherent, causal stories from sequences of events — and then to mistake the story for the underlying reality. Narratives feel explanatory because they are causal and emotionally coherent, but they systematically underweight randomness, omit disconfirming details, and create false predictability. The bias is real and well-grounded theoretically; its practical importance is high wherever decisions depend on forecasting or learning from the past. - Check the outside view before trusting the inside view
Ask how similar situations have gone before trusting your story about this specific situation.
Thinking in Bets
Related concerns
- Survivorship Bias Learning From What You Can T See During Conflict
Survivorship bias is the error of drawing conclusions only from the cases that made it through a filter — winners, survivors, visible successes — while the failures that never appear are silently excluded. The clearest historical example is Abraham Wald’s WWII aircraft study: the military wanted to armor the bullet holes they saw on returning planes; Wald showed they should armor where they saw no damage, because planes hit there didn’t return.
- Cpt No Narrative
The protagonist (you, your customer, your team) should be different at the end than at the beginning.
Structure the story as a transformation, not a summary
- Data Selection Bias
Your conclusions are built on a sample of the available data — ask what the sample excluded.
Notice which data you selected — and which you ignored
- Extract Lessons From Success
Deliberately collect, read, and learn from failure case studies in your domain.
Build a personal library of failure post-mortems
- How Many Tried Survivorship
Look for the people who tried the same thing and didn’t make it through.
Actively seek out the failures you aren’t seeing
- How To Check Survivorship Bias
Survivorship bias is the error of drawing conclusions only from the cases that made it through a filter — winners, survivors, visible successes — while the failures that never appear are silently excluded. The clearest historical example is Abraham Wald’s WWII aircraft study: the military wanted to armor the bullet holes they saw on returning planes; Wald showed they should armor where they saw no damage, because planes hit there didn’t return.
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