Date of this Version
We analyze a large, detailed operational data set from a restaurant chain to shed new light on how workload (defined as the number of tables or diners that a server simultaneously handles) affects servers' performance (measured as sales and meal duration). We use an exogenous shock—the implementation of labor scheduling software—and time-lagged instrumental variables to disentangle the endogeneity between demand and supply in this setting. We show that servers strive to maximize sales and speed efforts simultaneously, depending on the relative values of sales and speed. As a result, we find that, when the overall workload is small, servers expend more and more sales efforts with the increase in workload at a cost of slower service speed. However, above a certain workload threshold, servers start to reduce their sales efforts and work more promptly with the further rise in workload. In the focal restaurant chain, we find that this saturation point is currently not reached and, counterintuitively, the chain can reduce the staffing level and achieve both significantly higher sales (an estimated 3% increase) and lower labor costs (an estimated 17% decrease).
Originally published in Management Science © 2014 INFORMS
This is a pre-publication version. The final version is available at http://dx.doi.org/10.1287/mnsc.2014.1950
econometrics, empirical study on staffing, worker productivity, business analytics, restaurant operations, behavioral operations management, quality/speed trade-off
Tan, T. F., & Netessine, S. (2014). When Does the Devil Make Work? An Empirical Study of the Impact of Workload on Worker Productivity. Management Science, 60 (6), 1574-1593. http://dx.doi.org/10.1287/mnsc.2014.1950
Business Administration, Management, and Operations Commons, Business Analytics Commons, Business and Corporate Communications Commons, Business Intelligence Commons, Human Resources Management Commons, Labor Relations Commons, Management Information Systems Commons, Operations and Supply Chain Management Commons, Organizational Behavior and Theory Commons, Strategic Management Policy Commons
Date Posted:09 July 2018
This document has been peer reviewed.