Manufacturing Productivity with Worker Turnover

68 Pages Posted: 25 Sep 2018 Last revised: 2 Sep 2021

See all articles by Ken Moon

Ken Moon

University of Pennsylvania - The Wharton School

Patrick Bergemann

University of Chicago - Booth School of Business

Daniel Brown

University of California, Berkeley

Andrew Chen

Apple Inc.

James Chu

Stanford University, Department of Sociology, Students; Stanford University - Freeman Spogli Institute for International Studies

Ellen Eisen

University of California, Berkeley

Gregory Fischer

London School of Economics & Political Science (LSE)

Prashant Kumar Loyalka

Stanford University - Freeman Spogli Institute for International Studies

Sungmin Rho

Graduate Institute of International and Development Studies (IHEID)

Joshua Cohen

Apple University

Date Written: September 1, 2021

Abstract

Today's most sophisticated manufacturers produce immense quantities of complex goods in rapid response to fast-evolving near-term demand. To maintain high productivity under such circumstances, they schedule and staff large bodies of workers to efficiently dispatch highly variable workloads. Their success depends on managing the assignment of experience and skills to specialized tasks and effectively coordinating work on production lines. Worker turnover may disrupt such productivity, and we study the manufacturer's problem of controlling turnover and its effects. We collect data regarding production schedules, staffing, productivity, and pay from within the supply chain of a major consumer electronics manufacturer. Studying 52,214 China-based workers manufacturing millions of devices weekly, we find that worker turnover adversely affects the ability to coordinate by weakening knowledge-sharing and relationships among assembly line co-workers. Using publicly available cost information, we estimate a cost impact of $206-274M in units failing stringent quality control alone. We solve the manufacturer's problem of production planning which embeds flexibility in scheduling and staffing and structurally models workers' turnover decisions in dynamic equilibrium. Our counterfactual analyses predict significant gains from a less turnover-prone, hence more productive, workforce. Increasing wages by 10% reduces the manufacturer's variable production costs by an estimated 4.5%, or $928M for the product we study. Intuition suggests that by building inventories to buffer against variability in workforce productivity, firms may ignore turnover. We instead find that using inventories in production planning can keep workforce utilization high, hence raising the marginal returns to productivity and motivating self-interested firms to retain workers.

Keywords: Data-driven workforce planning, Empirical operations management, Employee turnover, Experience-Based Equilibrium, Production planning, Productivity, Stochastic optimization, Structural estimation

Suggested Citation

Moon, Ken and Bergemann, Patrick and Brown, Daniel and Chen, Andrew and Chu, James and Eisen, Ellen and Fischer, Gregory and Loyalka, Prashant and Rho, Sungmin and Cohen, Joshua, Manufacturing Productivity with Worker Turnover (September 1, 2021). Available at SSRN: https://ssrn.com/abstract=3248075 or http://dx.doi.org/10.2139/ssrn.3248075

Ken Moon (Contact Author)

University of Pennsylvania - The Wharton School ( email )

Jon M. Huntsman Hall
3730 Walnut St.
Philadelphia, PA 19104-6365
United States

Patrick Bergemann

University of Chicago - Booth School of Business

Daniel Brown

University of California, Berkeley

Andrew Chen

Apple Inc.

James Chu

Stanford University, Department of Sociology, Students ( email )

Stanford
United States

Stanford University - Freeman Spogli Institute for International Studies ( email )

Stanford, CA 94305
United States

Ellen Eisen

University of California, Berkeley

Gregory Fischer

London School of Economics & Political Science (LSE)

Houghton Street
London, WC2A 2AE
United Kingdom

Prashant Loyalka

Stanford University - Freeman Spogli Institute for International Studies ( email )

Stanford, CA 94305
United States

Sungmin Rho

Graduate Institute of International and Development Studies (IHEID) ( email )

PO Box 136
Geneva, CH-1211
Switzerland

Joshua Cohen

Apple University ( email )

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