The task and temporal microstructure of productivity

Sustaining workers' productivity is critical to organizations' operational success. Yet, comparatively little attention has been given to how managers can effectively allocate work across tasks and time to improve workers' performance. In this paper, we use the learning curve framework to investigate how productivity varies within task and within time (i.e., over the course of a day) in contexts where work is repetitive in nature. We introduce the concept of a restart effect - task and temporal disruptions that stimulate worker productivity - as a means of addressing challenges of repetitive work. For our empirical analyses, we use two and a half years of transaction data from a Japanese bank's home loan application processing line, totaling nearly six hundred thousand observations of individuals completing work at a given step in the process. We find that productivity on the current task is most impacted by experience on the same day, but the benefits of such experience decrease with time. Additionally, we find evidence for beneficial effects of both task change and start-of-day restarts on worker productivity. Together, these results offer insight into the underlying structure of productivity and suggest new ways to improve performance through the effective allocation of work.