Gang Li, Bentley University
Joy Field, Boston College
Hongxun Jiang, Renmin University of China
Tian He, Renmin University of China
Youming Pang, Renmin University of China

Today’s service companies operate in a technology-oriented and knowledge-intensive environment while recruiting and training individuals from an increasingly diverse population. One of the resulting challenges is ensuring strategic alignment between their two key resources – technology and workforce – through the resource planning and allocation processes.  The traditional hierarchical decision approach to resource planning and allocation considers only technology planning as a strategic-level decision, with workforce recruiting and training planning as a subsequent tactical-level decision. However, two other decision approaches – joint and integrated – elevate workforce planning to the same strategic level as technology planning.  Thus, we investigate the impact of strategically aligning technology and workforce decisions through the comparison of joint and integrated models to each other and to a baseline hierarchical model in terms of total cost.  Numerical experiments are conducted to characterize key features of solutions provided by these approaches under conditions typically found in this type of service company. Our results show that the integrated model is lowest cost across all conditions.  This is because the integrated approach maintains a small but skilled workforce that can operate new and more advanced technology with higher capacity.  However, the cost performance of the joint model is very close to the integrated model under a number of conditions and is easier to implement computationally and managerially, making it a good choice in many environments.  Managerial insights derived from this study can serve as a valuable guide for choosing the proper decision approach for technology-oriented and knowledge-intensive service companies.


This article is forthcoming in: Li, G., J. Field, H. Jiang, T. He, and Y. Pang (2015). “Decision Models for Workforce and Technology Planning in Services,” Service Science.