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  <title>Oracles :</title>
  <subTitle>how prediction markets turn employees into visionaries</subTitle>
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  <namePart>Thompson, Donald N.</namePart>
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   <placeTerm type="text">Boston, Massachusetts</placeTerm>
   <publisher>Harvard Business Review</publisher>
   <dateIssued>2012</dateIssued>
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  <languageTerm type="code">en</languageTerm>
  <languageTerm type="text">English</languageTerm>
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  <extent>261p. ill., index. ; 24 cm.</extent>
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 <note>Why Prediction Markets Are Good for Business&#13;
&#13;
From selecting the lead actress in a Broadway musical, to predicting a crucial delay in the delivery of Boeing’s 787 Dreamliner months before the CEO knew about it, to accurately forecasting US presidential elections—prediction markets have realized some amazing successes by aggregating the wisdom of crowds.&#13;
&#13;
Until now, the potential for this unique approach has remained merely an interesting curiosity. But a handful of innovative organizations—GE, Google, Motorola, Microsoft, Eli Lily, even the CIA—has successfully tapped employee insights to change how business gets done.&#13;
&#13;
In Oracles, Don Thompson explains how these and other firms use prediction markets to make better decisions, describing what could be the origins of a social revolution. Thompson shows how prediction markets can:&#13;
&#13;
 draw on the hidden knowledge of every employee&#13;
 tap the “intellectual bandwidth” of retired employees&#13;
 replace surveys&#13;
 substitute for endless meetings&#13;
&#13;
By showing successes and failures of real organizations, and identifying the common roadblocks they’ve overcome, Oracles offers a guide to begin testing expertise against the collective wisdom of employees and the market—all to the benefit of their bottom line.&#13;
</note>
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 <subject authority="">
  <topic>Strategic planning</topic>
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 <subject authority="">
  <topic>Decision Making</topic>
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 <subject authority="">
  <topic>Business forecasting</topic>
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 <subject authority="">
  <topic>Organizational behaviour</topic>
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 <classification>ADF/ADBE</classification>
 <identifier type="isbn">9781422183175</identifier>
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