Selecting competing technologies is a costly process, particularly for new technologies where little historical precedent exists in terms of development cost and effort, schedule, and probability of success. Convening a board of "experts" is the standard practice, with the individuals being the aggregators of all data, information, and knowledge that diffuse up from the ranks below. Information aggregation for each individual becomes a very inefficient process: information is incomplete and filtered; data must be collected, compiled, evaluated and communicated; information overload taxes a person's limited time and bandwidth; and individuals cannot be expected to be versed in all subject matter disciplines needed for a complete systems analysis. The hope is that the group as a whole - though limited in its number and imperfect in its aggregate knowledge - will adequately and equitably cover the entire evaluation and selection criteria trade space. Tall order. Prediction markets can be used as an effective and efficient means for aggregating the collective wisdom of all individuals. Prediction markets are futures markets where options are written on future events. The price of the option at any time is indicative of the probability that the event will be true at the option expiration date. Markets, being a very efficient means of quantifying value, can thus be used to assess relative importance, that is, the relative probability of success between competing technologies. It is a "Wisdom of Crowds" approach that addresses the notion that no one knows everything, everyone knows something . Prediction markets put into practice a means to quantify the collective belief carried by the idea that everyone knows something. This paper examines the use of prediction markets for use in selecting competing technologies.
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