Managing Demand for Short Life-Cycle Products Using Leading Indicators—November 21
AUSTIN, TEXAS—November 17, 2008
S. David Wu, Lehigh University
Friday, November 21, 2008
Over the past decade, the pace of technology innovation and new product introduction has increased significantly. Successful firms must be able to manage multiple dimensions of risks during the rapid innovation cycle. For instance, when introducing a new product, the transition from one generation to another must be carefully managed to mitigate undesirable market impact, while significant capital investment is committed in ramping up capacity.
In this talk, we will discuss demand management issues identified when working with several major U.S. semiconductor companies. We developed a methodology that identifies leading indicators of demand trends. The core technique is a statistical method that examines the demand pattern of a given group of products and identifies leading indicators that demonstrate patterns that predict the demand characteristics for the entire group. Coupled with technology diffusion models, we demonstrate the use of leading indicators as a variance reduction technique that improves the accuracy of demand forecasting methods. The method has been tested at four semiconductor companies, and is currently going through full-scale implementation.
Dr. S. David Wu is Dean of the Rossin College of Engineering and Applied Science at Lehigh University, where he holds the Lee A. Iacocca Chair Professorship. He is co-founder of the CVCR: Center for Value Chain Research and the Manufacturing Logistics Institute at Lehigh University.
Professor Wu's research interests are in the areas of operations research, optimization, and game theory, with applications in semiconductor planning and operations and supply chain coordination. He has published extensively in these and related areas in journals such as Operations Research, Management Science, IEEE Transactions, and Naval Research Logistics, with over eighty articles in archival publications.
Professor Wu's research has been supported by NSF, DOD, SRC, ISMI, Sandia National Laboratory, and various industrial firms such as Intel, Lucent Technologies, Agere Systems, HP, GM, and IBM. Professor Wu's work in the semiconductor industry has been widely recognized and cited, with various press coverage. A fellow of IIE, Dr. Wu was a department editor of the IIE Transactions and he served on the editorial boards of IEEE Transactions, M&SOM, and Journal of Manufacturing Systems. He is a frequent referee for journals such as Management Science, Operations Research, European Journal of Operations Research, and Naval Research Logistics.
Handbook of Quantitative Supply Chain Analysis, a book Wu co-edited with David Simchi-Levi and Max Shen, was published by Springer. The book is among the best sellers in the International Series of Operations Research and Management Science, edited by F.S. Hillier.
Professor Wu was a visiting professor at the University of Pennsylvania and the Hong Kong University of Science and Technology.