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  <title>Superforecasting</title>
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  <place>
   <placeTerm type="text">Boston</placeTerm>
   <publisher>Harvard Business School Publications</publisher>
   <dateIssued>May 2016</dateIssued>
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  <extent>p. 72 - 78</extent>
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 <note>Organizations and individuals are notoriously poor at judging the &#13;
likelihood of uncertain events. Predictions are often colored by the &#13;
forecaster’s understanding of basic statistical arguments, &#13;
susceptibility to cognitive biases, desire to influence others’ &#13;
thinking, and concerns about reputation. Indeed, predictions are often &#13;
intentionally vague to maximize wiggle room should they prove flawed. &#13;
But getting judgments wrong can of course have serious consequences. On &#13;
the basis of research involving 25,000 forecasters and a million &#13;
predictions, the authors identified a set of practices that can improve &#13;
companies’ prediction capability: providing training in the basics of &#13;
statistics and biases; assembling teams of forecasters to debate and &#13;
refine predictions; and tracking performance and giving rapid feedback. &#13;
To improve prediction capability, companies should keep real-time &#13;
accounts of how their top teams make judgments, including underlying &#13;
assumptions, data sources, external events, and so on. Keys to success &#13;
include requiring frequent, precise predictions and measuring prediction&#13;
 accuracy for comparison. [ABSTRACT FROM AUTHOR]&lt;br&gt;&lt;br&gt;</note>
 <note type="statement of responsibility"></note>
 <classification></classification>
 <identifier type="isbn">00178012</identifier>
 <location>
  <physicalLocation>Perpustakaan - Sekolah Tinggi Manajemen PPM Pusat Informasi Manajemen</physicalLocation>
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