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.

【書誌情報】

ページ数：8ページ

サイズ：A4

商品番号：HBSP-R1605E

発行日：2016/5/1

登録日：2016/5/12