Manufacturing Productivity with Worker Turnover
86 Pages Posted: 25 Sep 2018
Date Written: September 11, 2018
Once endemic in early manufacturing, high worker turnover has re-emerged as a challenge for modern manufacturers. A long-standing literature suggests or presumes that standardizing practices and deskilling assembly tasks shield manufacturing productivity against turnover. We investigate this persistent common wisdom using a uniquely rich dataset drawn from China-based FATP (final assembly, testing, and packaging) facilities that produce millions of units of consumer electronic goods per week yet exhibit high worker turnover exceeding 300% annually. Combining data on weekly rolling-horizon production plans, 52,214 workers' compensations and assignments, and production lines' volumes and yields, we find that worker turnover significantly impacts productivity, conservatively incurring $103-146 million in material costs alone over the production life cycle of a single device model absent active mitigation by the firm. Turnover disrupts critical workflows and relationships, which are often neglected even as firms track individual employee performance with increasingly granularity. To study managerial prescriptions, we extend the classical production planning problem to include endogenous worker turnover as an Experience-Based Equilibrium. Advances in approximate dynamic programming and reinforcement learning are applied to estimate and simulate our model. We find that well-calibrated increases to worker compensation reduce the manufacturer's labor-inclusive, variable production costs by about 5%, or $135 million. The wage increase improves workforce and yield stability and reduces underage costs, which are incurred from lost sales when missing production targets.
Keywords: Data-driven workforce planning, Empirical operations management, Employee turnover, Experience-Based Equilibrium, Production planning, Productivity, Stochastic optimization, Structural estimation
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