Optimized staffing between product lines for a technical support center

Abstract

Technical support for products after the sale is commonplace in today’s businesses. Original Equipment Manufacturers (OEMs) provide technical support to their dealer channel for resolution of complex product issues. Technical support staffing levels can vary by product type, product complexity, and production volumes, and case volumes. This research seeks a better understanding of appropriate staffing levels between three product lines for one OEM. The objective of this paper is to develop a model for monthly and weekly average case volumes for the three product lines, based off of historical case volume data. This data is used to predict a product line’s (platform’s) workload based off the month of the year. The output of each platform’s monthly case volume is then used in an optimization model to determine optimal staffing levels for each platform, based off the time of the year. The models developed for each platform use a linear relationship which regresses workload on a set of binary variable for the months of the year. Each of the models developed provided statistically significant coefficients for months which contain the platform’s highest workload. The outputs from these models are used in a mixed integer nonlinear programming optimization model to determine staff level of full time equivalent (FTE) employees at each platform. Each of the three scenarios utilized in this research provide similar trends and staffing levels for each of the three product lines. Results of this research are of interest for the management of technical support staffing.