Coaching practices for Durability Bias Correction

Describe almost anything you are working through and IX Coach finds the practices whose real-world fit is closest. For Durability Bias Correction, these are the strongest matches in the current practice library.

Does this sound like the set of challenges you might be facing?

• I catch myself shaving down the estimate I’m about to present
• The mistakes that mortify me most are the ones I was dead certain about and turned out flat wrong
• I’ve decided the lesson from this success is “focus narrow” or “go big”
• I had one unusually bad stretch, then I changed something, and now things are better
• One thing happened that fits what I suspected and now I’m treating it as settled

Practices that may help

1. Survivorship Bias: Learning from What You Can’t See
   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.
2. Distinguish cognitive optimism bias from strategic misrepresentation
   Recognize that some forecast inflation is genuine bias and some is deliberate spin — they require different fixes.
   Reference Class Forecasting
3. Prioritize items you were confidently wrong about
   Items you felt sure about but got wrong are retained especially well after correction — target these deliberately.
   Errorful Learning: Why Making Mistakes Strengthens Memory
4. 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
5. Base-Rate Neglect: Why We Ignore the Odds
   Base-rate neglect is the tendency to underweight or ignore prior probabilities (how often things happen in general) when vivid, specific information is available. Identified by Kahneman and Tversky, it is one of the most robustly replicated biases in judgment research, and it leads to systematic overconfidence in predictions about specific cases. Correcting it requires actively looking up or estimating base rates before evaluating individual information.
6. Expect regression to the mean in extreme outcomes
   Unusually good or bad performance tends to be followed by more average performance — not because of what you did.
   Base-Rate Neglect: Why We Ignore the Odds
7. Update beliefs by degrees, not wholesale
   Treat new information as evidence that shifts probabilities, not as proof that changes everything.
   Base-Rate Neglect: Why We Ignore the Odds
8. Recognize when contrast is being used on you
   Awareness of the contrast principle is the antidote — evaluate options against an independent standard, not the presented sequence.
   The Contrast Principle, Made Practical
9. Receive corrective feedback promptly after a test attempt
   For error-based learning to work, feedback must follow the error — delay weakens the effect and risks embedding the wrong answer.
   Errorful Learning: Why Making Mistakes Strengthens Memory
10. Anchor on the base rate before adding inside-view details
    Start your forecast from the class median, then adjust — do not start from your narrative and adjust to the base rate.
    Reference Class Forecasting

Describe your situation in your own words to search the complete practice library.