Optimizing the Labor Strategy of a Professional Service Firm

Abstract

A professional service firm often faces challenges in matching its available workforce with the demands for service delivery. In this paper, we coin the labor strategy optimization (LSO) problem to prescribe an optimal staffing plan for meeting the target revenues of a professional service firm. It simultaneously optimizes the capacity, capability, location, and flexibility of a firm's workforce at the strategic level. Our modeling framework captures the richness and complexity of a general service transformation process. Mathematical programming based models are developed for both the deterministic and stochastic versions of the problem. A prototype of the LSO technology was implemented at the former HP Consulting & Integration organization. Through a comprehensive computational study, managerial insights are drawn and discussed about the optimal labor strategy under various supply-side risks and uncertainties. The optimal labor strategy provides a cost effective and reliable basis for more detailed workforce optimization concerning scheduling and assignment decisions. Our study also offers a data-driven approach to take advantage of large amount of disparate data, from different organizations and geographical locations of a firm, for improving the workforce planning decisions.