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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