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 Forecast the Demand for Lifecycle Products

 

With this feature, you can forecast the demand for lifecycle products (for example, one-time-purchase products such as fashion, or consumer electronics such as mobile phones). Lifecycle products pose particular challenges to demand modeling and forecasting in that they exhibit strong lifecycle effects on the one hand, but have sparse historical sales data on the other hand.

Technical Details

Product feature is

New

Country Dependency

Valid for all countries

Software Component Version

RTLDDF 200

Application Component

CA-DDF-RT

Availability

SAP Customer Activity Repository 2.0 FP1

Effects on Customizing

  • A new model definition supporting lifecycle products has been added to the Assign Demand Model Definitions Customizing activity under Start of the navigation path Cross-Application Components Next navigation step Demand Data Foundation Next navigation step Modeling and Forecasting End of the navigation path. For more information, see the Customizing activity documentation (transaction SPRO).

  • Preprocessing has been enhanced to fill gaps in the historical sales data with zeros. This “zero sales inferencing” improves the modeling results.

    Note Note

    If you want to trace the changes during preprocessing, you can set this up in Customizing under Start of the navigation path Cross-Application Components Next navigation step Demand Data Foundation Next navigation step Modeling and Forecasting Next navigation step Define Modeling Control Settings End of the navigation path. For more information, see the Customizing activity documentation.

    End of the note.

  • The Calculate Hierarchical Priors service of the Schedule Model and Forecast function has been enhanced. You can now also generate hierarchical priors based on relationships between generic products and their variants. As before, you can find the results of the Calculate Hierarchical Priors service in the /DMF/UMD_PRI table.

    • Activation: No special activation is needed. Simply provide the data for your generic products and variants as you do with other master data.

    • Example:

      Product Type

      Table /DMF/PROD

      Example

      Generic product

      prod_type = 02

      Short sleeve shirt

      First variant of the generic product

      prod_type = 05

      generic_id: identifies the generic product with prod_type = 02

      Medium red short sleeve shirt

      Second variant of the generic product

      prod_type = 05

      generic_id: identifies the generic product with prod_type = 02

      Medium blue short sleeve shirt

    • Customizing: When configuring hierarchical priors, you can prioritize and weight the generic-product-variant relationships as you can with product hierarchies and location hierarchies. For this purpose, two weight parameters have been added to the /DMF/HPR_CTRL control table for hierarchical priors:

      Parameter

      Default

      Description

      HPR_WGT_GEN_VAR

      1

      Weight of your generic product and variant hierarchy against your product hierarchy

      HPR_WGT_PROD_DFLT

      1

      Weight of your default product hierarchy

      You can set these weights in the existing Configure Hierarchical Priors Customizing activity under Start of the navigation path Cross-Application Components Next navigation step Demand Data Foundation Next navigation step Modeling and Forecasting End of the navigation path. For more information, see the Customizing activity documentation.

See also