Using analytics to inform category management and strategic sourcing

PurposeThe purpose of this paper is to show how data analytics can be used to identify areas of potential cost savings for category managers of installation-level services. Using integrated solid waste management (ISWM) as a test case, the authors also examine the impact of small business set-asides on price and contractor performance.Design/methodology/approachThe authors use data analytics, specifically sequential regression, the Wilcoxon rank-sum test and ordered logistic regression to investigate the influence of service- and contracting-related variables on price and contractor performance.FindingsThe authors find that service- and contracting-related variables influence price. Specifically, they identify that a service-related variable, number of containers, significantly affects price, and that two contracting-related variables, one type of small business set-aside and the number of offers received, also significantly affect price. The authors quantify the price premiums paid for using various types of small business set-asides.Research limitations/implicationsAlthough the findings were significant, the authors believe that the robustness of the conclusions could be enhanced if the Air Force captured more data. Additional observations would increase the generalizability of the results.Practical implicationsThis empirical experiment demonstrates that detailed analyses are required to gain insights into services’ price drivers to craft more appropriate category management strategies for installation-level services.Originality/valueThis empirical study shows how historical data can be used to assess price drivers of installation-level services. It is also one of the first to quantify the impact that small business set-asides have on price.