Demand for spare parts is often difficult to forecast using historical data only. In this paper, we give an overview of installed based information and provide several ways in which installed base forecasting can be used. We discuss cases of installed based forecasting at four companies and list the issues involved. Moreover, we provide some models to assess the value of installed base information and conclude that forecasts of spare parts demand and return can be made considerably more timely and accurate by using installed base information
