How Does Data-Driven Decision-Making Affect Firm Productivity and CEO Pay? Erik Brynjolfsson, MIT Sloan Lorin Hitt, Wharton, School, University of Pennsylvania Heekyung Kim, MIT Sloan September 15, 2010 Preliminary and Incomplete Draft For consideration at WISE 2010 Comments welcome. Please do not quote. Abstract While there is a great deal of anecdotal evidence that firms can boost their performance by adopting a data driven decision-making (DDD) approach, there is little data or systematic analysis of these claims themselves. We gather detailed information on the business practices and information technology investments of 165 large publicly traded firms and find that DDD can explain a 3-5% increase in their output and productivity, beyond what can be explained by traditional inputs and IT usage. Furthermore, firms with more DDD tend to have a higher degree of consistency in business practices across business units and geography and stronger linkages between business and technology. In addition, we find that DDD is correlated with a significant increase in CEO pay even after controlling for the average worker’s wage, suggesting that the data-driven decision-making may further widen the gap between top managers and average workers. Intriguingly, the quadratic effect of DDD is positive for CEO compensation, but not for firm productivity, echoing Rosen’s (1982) model of increasing rewards to “superstars”.