When stopping production, the manufacturer has to decide on the lot size in the final production run to cover spare part demand during the end-of-life phase. This decision can be supported by forecasting how much demand is expected in the future. Forecasts can be obtained from the installed base of the product, that is, the number of products still in use. Consumer decisions on whether or not to repair a malfunctioning product depend on the specific product and spare part. Further, consumers may differ in their decisions, for example, for products with fast innovations and changing social trends. Consumer behavior can be accounted for by using appropriate types of installed base, for example, full installed base for cheap but essential spare parts of expensive products, and warranty installed base for expensive spare parts of products with short lifecycle. The paper presents a general methodology for installed base forecasting of end-of-life spare part demand and formulates research hypotheses on which of four installed base types performs best under which conditions. The methodology is illustrated by case studies for eighteen spare parts of six products from a consumer electronics company. The research hypotheses are supported in the majority of cases, and forecasts obtained from installed base are substantially better than simple black box forecasts. Incorporating past sales via installed base supports final production decisions to satisfy future consumer demand for spare parts.

Additional Metadata
Keywords Installed base forecast, end-of-life service, decision support, consumer goods, spare parts
Persistent URL hdl.handle.net/1765/79920
Series Econometric Institute Research Papers
Citation
Kim, T.Y, Dekker, R, & Heij, C. (2016). Spare part demand forecasting for consumer goods using installed base information (No. EI2016-11). Econometric Institute Research Papers. Retrieved from http://hdl.handle.net/1765/79920