Characterization of demand for short life-cycle technology products

Most technology companies are experiencing highly volatile markets with increasingly short product life cycles due to rapid technological innovation and market competition. Current supply-demand planning systems remain ineffective in capturing short life-cycle nature of the products and high volatility in the markets. In this study, we propose an alternative demand-characterization approach that models life-cycle demand projections and incorporates advanced demand signals from leading-indicator products through a Bayesian update. The proposed approach describes life-cycle demand in scenarios and provides a means to reducing the variability in demand scenarios via leading-indicator products. Computational testing on real-world data sets from three semiconductor manufacturing companies suggests that the proposed approach is effective in capturing the life-cycle patterns of the products and the early demand signals and is capable of reducing the uncertainty in the demand forecasts by more than 20%.