TY  - CHAP
AB  - A company is developing a new product and wants an accurate estimate of the investment's ROI. For that the money in-flows and out-flows for the project have to be forecasted. And to develop those forecasts, the resulting product's life cycle must first be forecasted.In this chapter, we are considering a real company. The company was in the process of developing a new product – a special purpose computer. In June of a year, the company wished to predict the product's future life cycle before the product had been fully developed. The product would be introduced into the market in January of the following year. However, to predict the locus of a product's future life cycle before the product has been fully developed is known to be very difficult.This chapter presents a method for predicting a new brand's life cycle trajectory from its beginning to its end before the brand is introduced into the markets. The chapter also presents a combination of two methods to use current information to revise the entire predicted trajectory so it comes closer and closer to the true life cycle trajectory. The true trajectory is not known till the product is pulled from the market. The two methods are the Delphi method and Kalman filtering tracking method.The company, which this application originates with, and the problem we discuss are real. However, we are prepared to identify neither the company nor the product. This chapter discusses the approach, but the data and the time scale have been masked, so that no identification from the data is possible.
VL  - 7
SN  - 978-0-85724-201-3, 978-0-85724-202-0/1477-4070
DO  - 10.1108/S1477-4070(2010)0000007011
UR  - https://doi.org/10.1108/S1477-4070(2010)0000007011
AU  - Waage Frenck
ED  - Kenneth D. Lawrence
ED  - Ronald K. Klimberg
PY  - 2010
Y1  - 2010/01/01
TI  - Predicting a new brand's life cycle trajectory
T2  - Advances in Business and Management Forecasting
T3  - Advances in Business and Management Forecasting
PB  - Emerald Group Publishing Limited
SP  - 121
EP  - 134
Y2  - 2024/04/18
ER  -