Determining an optimal margin of error for supply chain audits

Unsaleables are products that need to be removed from the primary distribution channel for a variety of reasons including being damaged in the supply chain or reaching the end of their useful life before being sold. One approach for processing unsaleables is the development of Adjustable Rate Policies (ARP) whereby manufacturers establish reimbursement rates for damaged and expired product based on data collected from supply chain audits. A prerequisite for developing equitable reimbursement rates is the need for representative audits of the supply chain which in turn depend on the development of proper sampling plans. Given the need to obtain a representative sample in order to establish accurate reimbursement rates and critical flaws in the conventional sampling methodology, the purpose of this research is to propose a new methodology for determining the sample size for conducting supply chain audits and compare the proposed method to other methods. The results of the study consistently support the value of optimally determining the margin of error based on contextual factors such as sales volume, unit cost, and unit sampling costs.