The case for putting a cognitive scientist on your big data team

Data analytics needs more than logic to succeed.

Data is valuable only to the extent that people make it so, which means that a big data project succeeds to the extent that we understand the ways in which information is created and used by people. This is the argument presented by professors Donald A. Marchand and Joe Peppard, who suggest a new way of approaching data analytics by focusing on information exploration.

To really make the most of data analytics, professionals in the cognitive and behavioral sciences should work alongside professionals in engineering, math, computer science and business, Marchand and Peppard write in a post at Harvard Business Review.

"When working with big data sets, you can probably find statistically meaningful relationships between any variables you choose," the authors write. "What pulls you back to reality is knowledge of the business. The dilemma is that this knowledge can also limit your sphere of thinking."

The tax agency in Britain (Her Majesty's Revenue and Customs) has hired organizational psychologists to assist the analytics staff in interpreting data, so as not to be deceived by their own biases. The idea is that the analysts must understand how debtors and debt collectors think before they can leverage the data about them.

For more:
- see Marchand and Peppard's post at Harvard Business Review

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