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Managers are trained to trust experts. Yet, if they are allowed to ''bet'' on the information that''s available to them, crowds of even relatively uninformed observers often arrive at better decisions than experts. By bringing many different perspectives to bear on a problem and allowing participants to learn from each other''s assessments, so-called ''prediction markets'' can significantly reduce margins of decision-making error. Many early attempts to use prediction markets in a corporate context - to predict the likely success of new products for example - were not successful however. This is because the markets themselves were not designed well. For example, they didn''t involve enough people, or they involved the wrong people, or they failed to create the right incentives for those taking part. Learning from these experiences, it is possible to identify some basic rules for the successful deployment of prediction markets in a corporate context. Given the careful application of these rules prediction markets can and should become part of a firms'' forecasting tool kit.