Crowdsourcing data analysis–and everything else

A few weeks ago, I wMartin-Dec-2010rote about a troubling finding questioning the objectivity of the traditional market research. A team of scientists from Imperial College London conducted a study on how marketing managers choose products and services. The study showed that the more managers were trying to “put themselves in the customers’ shoes” (supposedly to understand their “needs”), the more they used their personal preferences to predict what customers really want. Moreover, in so doing, marketing managers tended to ignore available market research data. Taking to the extreme, the study implies that the products created based on market research reflect not the customer needs but rather personal preferences of marketing researchers. As a solution to this problem, the authors of the study suggested relying on team decision-making instead of individual opinions.

I believe that we need to take a more dramatic step and start replacing the traditional market research with crowdsourcing. Instead of relying on the opinion of a single individual–or even a group of individuals–marketing should switch to on-line customer forums.

A recent piece of evidence now indicates that even data analysis, a process supposed to result in “objective” answers, is plagued with individual biases. A 65-person-strong international author consortium conducted an experiment in which 61 analysts organized in 29 teams were offered exactly the same set of data. Yet, by choosing different variables to look at and employing different statistical tools, the teams came up with wildly different interpretations. That implies that any interpretation based on data analysis conducted by a single individual or a small team can hardly be trusted. The authors of the study directly call for applying crowdsourcing approaches to data analytics. In their own words:

“Crowdsourcing analytics represents a new way of doing science; a data set is made publicly available and scientists at first analyze separately and then work together to reach a conclusion while making subjectivity and ambiguity transparent.”

 I couldn’t agree more. The “wisdom of crowds” approach should be expanded to all areas of business and social activities. Research, market and otherwise, is the next, but not last, stop.

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About Eugene Ivanov

Eugene Ivanov is the Founder of (WoC)2, an innovation consultancy that helps organizations extract maximum value from the wisdom of crowds by coordinated use of internal and external crowdsourcing.
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2 Responses to Crowdsourcing data analysis–and everything else

  1. Len Bisson says:

    Crowdsourcing is an interesting strategy that has worked in many areas and I think you are correct that it would lead to more valuable data analysis as well. If the analytics are left to individuals or small teams, individual biases would likely have a large impact on the results. The “wisdom of crowds” would take care of some of this bias but care would be needed to make sure “group think” doesn’t creep in. I have noticed that in the case of online forums there are a very vocal minority that drive the discussions. The real value would come from finding a way to engage the lurkers.

  2. Dear Len,

    Thank you very much for your comment. There are many ways to avoid the destructive effect of the vocal minority. One way is actually not to have a “discussion.” You state your problem, you define success criteria and then you collect–separately–contributions of each individual member of the “crowd.” This is how, for example, open innovation services providers, such as InnoCentive and NineSigma, operate.


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