Task Selection and Workload: A Focus on Completing Easy Tasks Hurts Long-Term Performance
How individuals manage, organize, and complete their tasks is central to operations management. Recent research in operations focuses on how under conditions of increasing workload individuals can decrease their service time, up to a point, in order to complete work more quickly. As the number of tasks increases, however, workers may also manage their workload by a different process—task selection. Drawing on research on workload, individual discretion, and behavioral decision-making, we theorize and then test that under conditions of increased workload, individuals may choose to complete easier tasks in order to manage their load. We label this behavior task completion preference (TCP). Using six years of data from a hospital emergency department, we find that physicians engage in TCP, with implications for their performance. Specifically, TCP helps physicians manage variance in service times; however, while it initially appears to improve shift-level throughput volume, after adjusting for the complexity of the work completed, TCP is related to worse throughput. Moreover, we find that engaging in easier tasks, as compared to hard ones, is related to lower learning in service times. We then turn to the lab to replicate conceptually the short-term task selection effect under increased workload and show that it occurs due to both fatigue and the sense of progress individuals get from task completion. These findings provide another mechanism for the workload-speedup effect from the literature. We also discuss implications for both research and the practice of operations in building systems to help people succeed.
Keywords: healthcare; knowledge work; discretion; Workload; Employees; Health Care and Treatment; Decision Making; Performance Effectiveness; Performance Productivity;
Citation:
KC, Diwas S., Bradley R. Staats, Maryam Kouchaki, and Francesca Gino. "Task Selection and Workload: A Focus on Completing Easy Tasks Hurts Long-Term Performance." Management Science 66, no. 10 (October 2020). View Details