EXPRESS: Algorithmic Supervisor and Employee Performance

In this paper, we explore the impact of implementing an algorithmic supervisor, a data analytics tool that offers real-time feedback to employees, on their overall performance. We collaborate with a leading service company that initiated the transition from human supervisors to an algorithmic supervisor for managing call agents in their outbound call center on September 18, 2019. We collect data for 220,085 calls over a span of 6 months—that is, 3 months before and 3 months after the introduction of the algorithmic supervisor. We find that the introduction of the algorithmic supervisor improved the agents’ service quality in terms of customer satisfaction; however, this came at the expense of quantity as fewer customers were served. In particular, the adoption of the algorithmic supervisor resulted in a 15.80% reduction in the number of served customers, accompanied by a 14.91% increase in the number of satisfied customers. Moreover, our study uncovers a gender-related dimension to the impact of the algorithmic supervisor. Before its adoption, male agents outperformed their female counterparts. However, after its adoption, female agents exhibited an 11.52% increase in the number of served customers, and a remarkable 14.00% increase in the number of satisfied customers as compared to their male counterparts. Our results suggest that the adoption of the algorithmic supervisor strikes a new economic balance between service quality and service quantity and generates a social impact in differently affecting service performance of female and male employees.