During a recent holiday I was reading an economic history book, “The ascent of money” by Niall Ferguson (by the way, strongly recommended if you want to put the current economic crisis into some kind of historic perspective) when I found these definitions of “heuristic biases” (skewed modes of thinking or learning).
Though the author was referring in his text to skewed ways of evaluating financial risk, I immediately found a clear link to our experience as operation excellence consultants related to the way people understood and utilized data in projects.
This is Dr. Ferguson´s classification. I hope you enjoy it
- Availability bias causes us to base decisions on data that is more readily available than the data we really need
- Hindsight bias causes us to attach higher probabilities to events after they have happened than we did before they happened
- The problem of induction which leads us to formulate general rules on the basis of insufficient information
- The fallacy of conjunction which means that we tend to overestimate the probability of simultaneous occurrance of multiple events of very high probability compared to the probability of ocurrance of only one of multiple events of low probability
- Confirmation bias which inclines us to look for confirming evidence of an initial hypothesis rather than evidence that would disprove it
- Contamination effects, whereby we allow irrelevant but proximate information to influence decisions
- The affect heuristic whereby preconceived value judgements interfere with assessment of things
- The failure of invariance that leads to risk aversion for events leading to positive outcomes while risk seeking for negative ones.
- Scope neglect which prevents us from adjusting our efforts and actions to the relative importance or magnitude of an issue
- Overconfidence in calibration which leads us to overestimate the confidence intervals within which our estimates will be robust
- Bystander apathy which inclines us to abdicate individual responsibility when in a group
