Manufacturing Productivity with Worker Turnover
69 Pages Posted: 25 Sep 2018 Last revised: 24 May 2022
Date Written: May 23, 2022
Abstract
To maximize productivity, manufacturers must organize and equip their workforces to efficiently handle variable workloads. Their success depends on their ability to assign experienced and skilled workers to specialized tasks and coordinate work on production lines. Worker turnover may disrupt such efforts. We use staffing, productivity, and pay data from within a major consumer electronics manufacturer's supply chain to study how firms should manage worker turnover and its effects using production decisions, wages, and inventory. We find that worker turnover impedes coordination between assembly line co-workers by weakening knowledge sharing and relationships. Publicly available unit-cost estimates imply that worker turnover accounts for $206--274 million in added direct expenses alone from defectively assembled units failing the firm's stringent quality control. To evaluate managerial alternatives, we structurally estimate a dynamic equilibrium model (Experience-Based Equilibrium, Fershtman and Pakes 2012) encompassing (1) workers' endogenous turnover decisions and (2) the firm's weekly planning of its production scheduling and staffing in response. In counterfactual analyses, a less turnover-prone, hence more productive, workforce significantly benefits the firm, reducing its variable production costs by 4.5%, or an estimated $928 million for the studied product. Such benefits justify paying higher efficiency wages even to less skilled workforces; further, interestingly, rational inventory management policies incentivize self-interested firms to reduce, rather than tolerate, turnover.
Keywords: Data-driven workforce planning, Empirical operations management, Employee turnover, Experience-Based Equilibrium, Production planning, Productivity, Reinforcement learning, Stochastic optimization, Structural estimation
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