A product's lifecycle consists of different phases: launch, growth, maturity, and discontinuation. In this process, you model the launch, growth and discontinuation phases.
SAP provides several tools with which you can model a product’s lifecycle in Demand Planning. These functions apply equally well to other characteristics. For instance, if you are introducing an existing product into another location, you can use like profiles to use the historical data from the current locations to create a forecast and then use a phase-in profile to reduce the forecast for the introductory period.
In Release 4.0 lifecycle planning is fully integrated with the Interchangeability suite of functions. For more details see Product Interchangeability in Demand Planning.
Lifecycle planning is integrated with univariate forecasting, causal analysis and composite forecasting.
Lifecycle planning in SAP APO consists of two functions, like modeling and phase-in/phase-out modeling. Each of these functions is available for forecasting both at detail level and aggregate level.
When you start to create forecasts for new characteristic values combinations there is generally no historical data on which to base the forecast for this combination. (You could also use the realignment function to copy data from another characteristic values combination, but this would result in an unnecessary increase of redundant data in the system.) With like modeling one of the characteristic values is replaced by one or more other values. This results in new combination for which historical data is available. Consequently this system can then carry out a forecast.
The demand for an object (usually a product or product group) in the initial and final phases of its lifecycle is generally different to that in the maturity phase. In the initial phase the demand increases from period to period, whereas towards the end of the lifecycle the demand drops off. However a statistical forecast based on the situation in the maturity period cannot predict such a behavior. In phase-in/out modeling the result from the statistical forecast is multiplied by a time-dependent factor to produce the actual forecast. The time-dependent factor is stored in a phase-in/out profile. In general in phase-in profiles the factor increases with time, while in the case of phase-out profiles it decreases.
For more information, see Phase-In/Phase-Out Modeling.
Aggregated lifecycle planning is an option that allows you to carry out a forecast using lifecycle planning at aggregate level, that is for a selection in which at least one of the characteristics of the basic settings has had no value(s) assigned.
For more information, see Aggregated Lifecycle Planning with Like Modeling and Aggregated Lifecycle Planning with Phase-In/Out Modeling.