Risk Intelligence IV

Overcoming Biases

In a recent post, RISKVIEWS proposed that Risk Intelligence would overcome biases.  Here are some specifics…

Biases

  • Anchoring – too much reliance on first experience
  • Availability – overestimate likelihood of events that readily come to mind
  • Confirmation Bias – look for information that confirms bias
  • Endowment effect – overvalue what you already have
  • Framing effect – conclusion depends on how the question is phrased
  • Gambler’s Fallacy – Belief that future probabilities are impacted by past experience – reversion to mean
  • Hindsight bias – things seem to be predictable after they happen
  • Illusion of control – overestimate degree of control over events
  • Overconfidence – believe own answers are more correct
  • Status Quo bias – Expect things to stay the same
  • Survivorship bias – only look at the people who finished a process, not all who started
  • Ostrich Effect – Ignore negative information

Each of Education, Experience and Analysis should reduce all of these.

Experience should provide the feedback that most of these ideas are simply wrong.  The original work that started to identify these biases followed the standard psychology approach of excluding anyone with experience and would also prohibit anyone from trying any of the questions a second time.  So learning to identify and avoid these biases through experience has had limited testing.

Education for a risk manager should simply mention all of these biases directly and their adverse consequences.  Many risk managers receiving that education will ever after seek to avoid making those mistakes.

But some will be blinded by the perceptual biases and therefore resist abandoning their gut feel that actually follows the biases.

Analysis may provide the information to convince  some of these remaining holdouts.  Analysis, if done correctly, will follow the logic of economic rationality which is the metric that we used to identify the wrong decisions that were eventually aggregated as biases.

So there may still be some people who even in the face of:

  • Experience of less than optimal outcomes
  • Education that provides discussion and examples of the adverse impact of decision-making based upon the biases.
  • Analysis that provides numerical back-up for unbiased decision making

Will still want to trust their own gut to make decisions regarding risk.

You can probably weed out those folks in hiring.

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Explore posts in the same categories: Decision Makng, Enterprise Risk Management, Execution Risk, Risk Culture, Risk Learning

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