The challenges of pre-launch forecasting of adoption time series for new durable products - Karima Dyussekeneva (International Journal of Forecasting, 2014)
The successful introduction of new durable products plays an important part in helpingcompanies to stay ahead of their competitors. Decisions relating to these products can beimproved by the availability of reliable pre-launch forecasts of their adoption time series.However, producing such forecasts is a difficult, complex and challenging task, mainly becauseof the non-availability of past time series data relating to the product, and the multiplefactors that can affect adoptions, such as customer heterogeneity, macroeconomicconditions following the product launch, and technological developments which may leadto the product’s premature obsolescence. This paper provides a critical review of the literatureto examine what it can tell us about the relative effectiveness of three fundamental approachesto filling the data void : (i) management judgment, (ii) the analysis of judgmentsby potential customers, and (iii) formal models of the diffusion process. It then shows thatthe task of producing pre-launch time series forecasts of adoption levels involves a set ofsub-tasks, which all involve either quantitative estimation or choice, and argues that thedifferent natures of these tasks mean that the forecasts are unlikely to be accurate if a singlemethod is employed. Nevertheless, formal models should be at the core of the forecastingprocess, rather than unstructured judgment. Gaps in the literature are identified, and thepaper concludes by suggesting a research agenda so as to indicate where future researchefforts might be employed most profitably.