Measuring the impact of part‐time workers in service organizations

In the last twenty years we have seen a significant increase in interest by practicing managers and academic researchers in the labor/staff scheduling decision. In particular, service firm managers have focused their attention on improving the productivity of their labor intensive operations by an increased use of part‐time personnel. These actions have been motivated by the presence of significant variations in hourly and daily work loads faced by these firms and the desire to provide flexibility to adequately match staff capacity with customer demand. The past employment practice of using full‐time staff causes significant idle capacity to exist in many firms, reducing productivity. The significant increased use of part‐time staff has allowed today's managers to correct this situation by reducing the amount of idle labor capacity, thus reducing operating cost. Academic researchers have also investigated the labor scheduling problem during the past two decades. They have analyzed and evaluated mathematical algorithms, optimal and heuristic, to efficiently solve the staff tour scheduling problem. Some of this work has eventually found applicability in a number of service firms. However, most of these studies have focused on the scheduling of full‐time staff to meet varying daily and hourly work load shifts and little insight has been attained in understanding a number of trade‐off issues in this area. In this paper we investigate the complex issue of the trade‐off between full‐time and part‐time staff and develop a relative “measure of flexibility” for using part‐time individuals. First, we demonstrate, as might be expected, how greater flexibility reduces idle labor capacity. Second, we define and test what is “scheduling flexibility,” as measured by work‐hours‐per‐day and work‐days‐per‐week. Third, we document the marginal reduction in labor hours scheduled attainable with increased flexibility, using actual operating data from a lockbox department in a large Chicago commercial bank. And fourth, we demonstrate the cost implications of using part‐time staff by employing operating data from the wire transfer department of a New York commercial bank, where we examine the problem using cost data as a basis for comparing the relative impact of various labor scheduling decisions and flexibility. We illustrate the common trade‐offs that must be evaluated due to various labor costs, turnover rates, full and part‐time personnel hours and differing productivity rates among various categories of personnel. Our approach illustrates the type of analysis that should be conducted by practicing managers to adequately evaluate the trade‐offs for the staffing decision when using both full and part‐time personnel.