Organizations and individuals are notoriously poor at judging the
likelihood of uncertain events. Predictions are often colored by the
forecaster’s understanding of basic statistical arguments,
susceptibility to cognitive biases, desire to influence others’
thinking, and concerns about reputation. Indeed, predictions are often
intentionally vague to maximize wiggle room should they prove flawed.
But getting judgments wrong can of course have serious consequences. On
the basis of research involving 25,000 forecasters and a million
predictions, the authors identified a set of practices that can improve
companies’ prediction capability: providing training in the basics of
statistics and biases; assembling teams of forecasters to debate and
refine predictions; and tracking performance and giving rapid feedback.
To improve prediction capability, companies should keep real-time
accounts of how their top teams make judgments, including underlying
assumptions, data sources, external events, and so on. Keys to success
include requiring frequent, precise predictions and measuring prediction
accuracy for comparison. [ABSTRACT FROM AUTHOR]