Modelling high‐tech product life cycles with short‐term demand information: a case study

Increasing competition and volatile conditions in high‐tech markets result in shortening product life cycles with non‐cyclic demand patterns. This study illustrates the use of a demand‐characterisation approach that models the underlying shape of product demands in these markets. In the approach, a Bayesian‐update procedure combines the demand projections obtained from historical data with the short‐term demand information provided from demand leading indicators. The goal of the Bayesian procedure is to improve the accuracy and reduce the variation of historical data‐based demand projections. This paper discusses the implementation experience of the proposed approach at a semiconductor‐manufacturing company; the key test results are presented using product families introduced over the last few years with a comparison to real‐world benchmark demand forecasts.