Performance Metrics in Downstream Supply Chain

In a downstream supply chain (DSC), consisting of manufacturers, transportation, distribution, and retail members, end customers expect timely, reliable and quality delivery of the right amount of products at low cost. The manufacturer, in its attempt to deliver the product through the DSC, however, must balance customer expectation with profitability. This balance can be achieved through a mix of strategies. One DSC strategy tool, the SCOR model, integrates and continuously improves the performance of the various DSC activities. The SCOR model metric system is considered a breakthrough given its standardized approach to assessment across organizations and industry types. The top tier of the SCOR metric system evaluates the overall strategic organizational activities in a supply chain context. These top tier metric system elements consist of: delivery reliability, flexibility and responsiveness, cost, and assets. These metrics follow the standard as recommended by Schneiderman (1996) who stated that a metric system should contain no more than five top tier metrics given that a large number diffuses the focus of the stregic activities. Schneiderman further suggests that this first tier metric system should consist of 1) internal process and 2) external results performance. The SCOR model activities fit these internal and external schemas well. For the SCOR model to work among the DSC members, these measurements, though, must be standardized among DSC members (Lambert and Pohlen, 2001). The use of a DSC metrics system leads to synergies of performance among supply chain members that facilitate the measure of total supply chain performance as opposed to isolated functional "silo" measures (Hausman, 2003). We have purposely chosen performance metrics as the standard of evaluation as opposed to the terms "performance measurement" and "performance measure." The term "performance measure" carries a connotational definition that is vague, historical, and diffused (Neely, 1999). Schneiderman (1996) stated that measures and metrics differ in the following way: measures consist of the broad set of infinite forms of evaluating a firm's process whereas metrics are a subset of the few measures actually useful to improve a company's efforts. Metrics should be monotonic, that is, improvements in metrics must lead to improvement in shareholder wealth. Gunasekaran, Patel and Tirtiroglu (2001) discussed the problem of these terms in their study of the literature and stated, "Quite often, companies have a large number of performance measures to which they keep adding based on suggestions from employees and consultants, and fail to realize that performance measurement can be better addressed using a few good metrics (p. 72)."