Thursday, April 10, 2014

Crowdsourcing and Prediction Markets
While researching our Prediction Markets brief, several articles included crowdsourcing in the same vein.  Crowd sourcing argues that “that a diverse collection of independently deciding individuals is likely to make certain types of decisions and predictions better than individuals or even experts, draws many parallels with statistical sampling.[1] During our research, many of the articles combined prediction markets and crowdsourcing to the point where I am not sure that the authors thought there was a difference.  The main difference is treating the probability in market predictions the same as a security in the stock market. One definition also states that crowdsourcing should come from opinions outside your immediate organization instead of inside.  However, the discussion below draws no difference between the two.  Both are beneficial.
Crowdsourcing became popular to the mainstream around the same time as when James Surowiecki penned his book, Wisdom of Crowds.  In it, he describes several factors for tapping the collective intelligence in an organization.  Jaya and I briefly covered these key factors during the brief, but I wanted to highlight them in a bit more detail because without them, your market or the question your are posing to your selected group will be doomed to fail.
Diversity is paramount.  Knowledge and perspective will smooth out your data (the law of large numbers).  Many examples of government projects include countless groups inside the government as well as private sector companies that are involved in the same project.  Each group will have different perspectives and knowledge about the project.  When performing your crowdsourcing or prediction market the aggregation of the different points of view in the market far outweigh the IQ or expertise of a single person.
The other key component is the Independence of opinion.  With the goal of obtaining different opinions form your group, group think acts as a detriment to the end goal.  This is another example of why the C-suite personnel or the public manager herself miss the mark on the deadline of a project.  Their judgment is clouded from their colleague’s opinions of the project. 
Crowdsourcing could prevent this because it allows the public manager to see a different perspective on the project.  Instead of being surprised that the project missed the deadline, she can have an the crowds viewpoint on the projected outcome far before the deadline date to see what the bottleneck is in the process. Has anyone experienced this for themselves or seen a manager surprised when he/she missed the due date for a project?



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