Building operational excellence in a multi-node supply chain

Abstract

This thesis shows how a combination of macro-economic, business, and organizational factors can lead a well-run company to adopt a "launch-and-expedite" behavior with detrimental effects on operational efficiency. It also demonstrates how it is possible, for an organization that finds itself in such a state, to apply basic operations principles and a data driven approach to systematically get out of the "launch-and-expedite" mode. The thesis presents a method to characterize a real, functioning supply chain in the context of changing conditions and in the absence of perfect data. It shows the analysis, recommendations, and results from a particular supply chain case study at Agilent Technologies, Inc. The project first analyzes and maps the current supply chain to characterize demand and supply variability. A selected menu of operational building blocks is then recommended to improve overall supply chain performance by reducing the internal bullwhip effect and improving on-time delivery. The recommendations are implemented in a successful pilot study and key operational metrics are recorded such as supply chain inventory, on-time delivery, variability of lead-time, and number of expedite/schedule change requests.

(cont.) The particular organizational context of the project and its affect is also considered. Although this thesis provides a case study of the Colorado Springs Technical Center operations and supply chain, results and lessons learned are applicable to other component suppliers or component buyers within multi-node supply chains, particularly those in the capital equipment business.