Big Data and Hiring

The article “Big Data and the Hourly Workforce” (see Slashdot comments) repeats the known story that Big Data is being used by companies to improve their product.  It is used by Target to target customers (by, for example, identifying pregnant women), by the Center for Disease Control to identify outbreaks, to predicted box office hits from Twitter, and by political campaigns to target the right voters with the right message.  The article implies that Big Data algorithms identify patterns in the data which companies can exploit.

But then the article gets into application of Big Data to the hourly work force. Companies are focusing on improving worker retention, worker productivity, customer satisfaction, and average revenue per sale.  Big Data is being used to increase each of these metrics five to twenty-five percent.  As in baseball (Moneyball), some of the old rules of thumb like excluding “job hoppers” or even those with an old criminal history are being rejected by the data in favor of machine learning features like distance from work or the Meyers Briggs personality classification which are supported by the data.