Optimal resource action planning analytics for services delivery using hiring, contracting & cross-training of various skills

Abstract

We address the problem of optimal resource action planning, which is faced by firms in the services business in the context of planning delivery of services with an expected demand outlook for various skills. Firms have the option of cross-training a chosen number of resource-units from a primary skill type into secondary skills, tertiary skills, and so on. They have the option of further hiring and increasing the system availability of any chosen skill type. They also have the option of contracting out a required amount of any chosen skill type. We address the problem of identifying the optimal set of planned resource control actions, in terms of both the timing and extent of hiring, cross-training, and contracting combination, so that they are well positioned to meet the actual demand. We present a mathematical model that can be described in terms of a constrained network flow and map it to a mixed integer linear programming formulation. The model considers practical constraints such as minimum residence time that a resource unit needs to spend in a skill-type into which it gets cross-trained or hired, minimum acceptable contracting duration for a contracted skill type, first order and higher orders of cross-training for a skill type, with lead-times, logical business rules associated with cross-training transfer sequences, as well as firm-specific targets on service levels and resource utilization, in determining the optimal resource action plan. © 2008 IEEE.