Productivity Analysis in Services Using Timing Studies

Abstract

We develop a novel empirical approach to analyze workforce productivity in service systems via timing studies – detailed time-stamped data recording relevant activities performed by the employees processing service requests. Our econometric approach, which is based on models from survival analysis, takes advantage of the detailed information provided by timing study data to capture the time-varying factors that affect productivity, such as the workload level, switching among different tasks and temporary work-relief from breaks during the working shift. We apply our framework in an information technology service delivery system and use the estimated results to evaluate alternative designs of the service system in terms of workforce productivity. Specifically, our methodology can inform decisions regarding workload allocation, routing, prioritization, and working schedule design in a service system.

Keywords: Service Operations, Applied Econometrics, Empirical Research, Behavioral Operations, OM Practice