The Concept Of Aggregates In APO 

ERP in SAP ==> SAP APO

What are Aggregates in the context of APO? What are their uses?

Normally the data's were stored at lower level (detail), so aggregates are nothing but storing the data at aggregate level to improve the performance of planning.

The data is always at location product level if its SNP on the other hand the data is always stored at CVC level if its DP.

These are the consolidated values of the lower level detail for the defined key figures, as standard there are quite a few aggregates for an SNP planning area:

  • 9AAC (9AACTNAME)
  • 9AACPR (9AACTNAME, 9APPMNAME)
  • 9ALA (9ATRNAME)
  • 9ALO (9ALOCNO)
  • 9ALORE (9ALOCNO, 9ARNAME)
  • 9AMA (9AMATNR)
  • 9AMALA (9AMATNR, 9ATRNAME)
  • 9AMALARE (9AMATNR, 9ARNAME, 9ATRNAME)
  • 9AMALO (9ALOCNO, 9AMATNR)
  • 9AMALORE (9ALOCNO, 9AMATNR, 9ARNAME)
  • 9AMAPR (9AMATNR, 9APPMNAME)
  • 9AMARE (9AMATNR, 9ARNAME)
  • 9APR (9APPMNAME)
  • 9ARE (9ARNAME)
  • 9AREPR (9APPMNAME, 9ARNAME)
In transaction /sapapo/msdp_admin if you look at the detail of the planning area you will see on the tab "Key Figure Assignment" the aggregates associated with that planning area and the key figures assigned to the aggregate.

An APO aggregate contains a subset of the characteristics in the master planning object structure. 

The creation and use of aggregates is optional. The data is always saved on the lowest level of detail. If aggregates exist, the system saves the planning data on the defined aggregate levels as well as on the lowest level of detail. The data is saved twice, but consistently; that is, the sum of the details equals the aggregate value. 

The aggregates in APO are not the same as those in the Business Information Warehouse (BW), but they have the same purpose: to speed up data access and therefore increase performance. SAP recommends that you use aggregates in Demand Planning and Supply Network Planning

For example you are having Product Group -- P

Having Product as P1, P2, P3

Your forecast data for month 092008 for product 

P1 is 200

P2 is 300

P3 is 500

Then forecast data for product group P is for month 092008 is 1000.

Aggregation is the summation at group level.

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