Workload, Time Use and Efficiency

Abstract: Existing empirical research suggests worker output and workload are positively correlated, but how the two are related is not yet well understood. We study how workload affects performance outcomes and how workers adjust labor input and organize tasks in response to workload. We do so using a dynamic multi-tasking model with labor-leisure and quality-quantity choices in which the production environment allows for efficiencies of scale. We find that in heterogeneous contexts, where there is more learning within projects than within the same step across projects, it is optimal to work sequentially, completing one project before starting the next. In contrast, in homogeneous contexts, in which learning within the same step across projects is relatively stronger, it is optimal to work in batches, completing the same step across projects. Output increases with workload in either context, but while timeliness may decrease in heterogeneous contexts, quality and timeliness are expected to increase in homogeneous contexts because higher workload increases the efficiency of batch work. We provide empirical evidence of the theoretical predictions using detailed workload, productivity, time and internet use data of insurance claims examiners across two departments that handle heterogeneous and homogeneous claims respectively, and who face plausibly exogenous variation in workload. We show evidence consistent with examiners working sequentially in the heterogeneous context and working in batches in the homogeneous context. A one standard deviation increase in workload increases output by 2.8% in the heterogeneous context and 9.3% in the homogeneous context, while tardiness decreases and quality increases in the latter context only.