The Nonstationary Staff-Planning Problem with Business Cycle and Learning Effects

Abstract

Managing highly skilled employees is extremely complex because of the need to balance the costs and time lags associated with their training against the need to meet demand as quickly as possible. Unlike previous approaches to this problem in the staffing literature, this paper develops an optimal staffing policy at the strategic level to cope with nonstationary stochastic demand for a staff characterized by unproductive apprentice employees and fully productive experienced employees. The paper then explores the implications of this policy in different industries, using empirical data. Aside from the optimal policy, this paper's primary results include: (1) demand volatility reduces average productivity, most especially under conditions of low (or slightly negative) growth and - nonintuitively - low employee turnover or knowledge obsolescence rates; (2) there is a trade-off between meeting demand and high productivity; (3) firms with longer business cycles should smooth their hiring and firing policies; and (4) firms in industries with longer training times should smooth their hiring and firing policies. The paper also explores the possible rewards from reducing training times and turnover rates. Finally, it discusses managerial implications and possible future directions in research.