Building a framework for determining the optimal supplier shipping performance

Abstract

Most companies aim for perfect on-time delivery from suppliers, since late deliveries can cause supply disruptions and raise the cost of inventory, transportation and coordination. But this assumes that companies do not incur expenses in increasing or maintaining supplier performance. Our thesis looks at the problem faced by those companies that do invest in suppliers to help them achieve a desired performance level. In these special cases, a perfect target may no longer yield the minimum cost incurred over a performance spectrum. Our thesis provides a framework that companies can use to determine an optimal target for timely deliveries by comparing the cost implications of different supplier performance levels. We pursue an empirical approach, using the data and metrics of an industrial equipment manufacturer that uses a hit-or-miss performance measure to evaluate on-time supplier deliveries. Within the scope of this performance management system, we determine the relevant cost categories. Using regression analysis, we create models projecting each category's expected behavior based on data we collect. Combining the models allows us to calculate a system optimal point at which the incremental cost of supplier development towards an improved performance target matches the benefit derived from avoided supply disruption. This performance target minimizes the total cost of the performance management system. While our framework is calibrated to a specific company, the models we create are general enough to be adapted by companies facing similar problems. By laying out our treatment of costs, we hope to make it feasible for other companies to calculate a target that makes sense: one that suppliers can achieve and purchasers can afford.