2009 Wagner Prize Finalist - Intel Corporation

Extending Bass for Improved New Product Forecasting at Intel

Forecasting demand for new products is increasingly difficult as the technology treadmill drives product lifecycles shorter and shorter. We present a model that perpetually reduces forecast variance as new market information is acquired over time. Our model extends Bass's idea of product diffusion to a more comprehensive theoretical setting using the notion of demand-leading indicators in a Bayesian framework. Successful implementation at Intel demonstrates not only improvement in time/efforts but also reduction in forecast errors that leads to significant cost savings.