Scenario analysis of demand in a technology market using leading indicators

This paper proposes an approach to analyzing demand scenarios in technology -driven markets where product demands are volatile, but follow a few identi fiable lifecycle patterns, After examining a large amount of semiconductor data, we found that not only can products be clustered by lifecycle pattern s, but in each cluster there exists a leading indicator product that provid es advanced indication of changes in demand trends, Motivated by this findi ng, we propose a scenario analysis structure in the context of stochastic p rogramming. Specifically, the demand model that results from this approach provides a mechanism for building a scenario tree for semiconductor demand, Using the Bass growth model and a Bayesian update structure, the approach streamlines scenario analysis by focusing on parametric changes of the dema nd growth model over time, The Bayesian structure allows expert judgment to be incorporated into scenario generation while the Bass growth model allow s an efficient representation of time varying demands. Further, by adjustin g a likelihood threshold, the method generates scenario trees of different sizes and accuracy, This structure provides a practical scenario analysis m ethod for manufacturing demand in a technology market. We demonstrate the a pplicability of this method using real semiconductor data.