“Big Data” Shines New Light on Less Pay for Women

Data mining has come to the study of gender inequality. For more than 30 years, researchers have studied causes of inequality—almost entirely focused on individual attributes and attitudes toward women. These still matter, but a new field called “people analytics” exposes discriminatory organizational practices that were not uncovered.

A case in point is a large-data crunch by Prof. Janice Fanning Madden of the Wharton School (Penn). Her research finds that female stockbrokers in two of the largest U.S. brokerage firms made less money than their male counterparts because they were given worse-performing accounts to start with.