Little Teams, Big Data: Big Data Provides New Opportunities for Teams Theory

Over the past 25 years, industrial and organizational (I-O) psychologists have made great strides forward in the area of teams research. They have developed and tested meso-level theories that explain and predict the behavior of individuals in teams and teams operating within and across organizations. The continued contributions of I-O psychologists to theory and research on teams require us to address the challenges—several of which were well described in the focal article (Guzzo, Fink, King, Tonidandel, & Landis, 2015 )—and embrace the opportunities that are being ushered in by big and broad data streams (Hendler, 2013 ). We suggest that a principal unique value add of the I-O psychologist to the basic scientific endeavor of understanding small teams comes in the form of theory —theories that explain why, when, how, and to what end individuals form relationships needed for teams to function in unison toward the accomplishment of collective goals. Some have argued that the big data revolution means “the end of theory,” suggesting petabyte data render theoretical models obsolete (Anderson, 2008 ). On the contrary, we submit that big-data enabled social science holds the promise of rapid progress in social science theory, particularly in the area of teams.