Key Figure settings for temprature in DP planning area

[Former Member]

These documents explains one of the approach to get correct temperature values in monthly and weekly planning books.

Applies to: Industries which have implemented “SAP SCM-Demand planning” (Release version from 4.1…).

Author: G.K.Radhakrishnan

G.K.Radhakrishnan (APICS-CPIM ), is working as a SAP APO-DP consultant in Accenture has a consulting experience of more than three years with a domain experience of 7years in supply chain.

Introduction: Temperature can be a variable in MLR forecast models in many industries such as beverages.The sales of soft drinks increases in summer as the  temperature goes up and it reduces in winter months .So it is important to get correct temperature values in both monthly view and weekly views to generate the forecast

Key Figure settings

Below link provides all the details of  aggregation and disaggregation of each key figure are defined by its calculation type and its time-based disaggregation type.

http://help.sap.com/saphelp_scm70/helpdata/en/47/d12b801fb26c68e10000000a42189b/frameset.htm

As shown below if we use temperature  with calculation type S and Time based disaggregation P  then the results are incorrect in monthly view if we get data in weeks.

Temperature is updated at weekly level and weekly view is shown below

Temperature is shown in technical buckets below

Temperature is shown in Monthly view below.As seen it  got added up and now it is not possible to run MLR in monthly view

One possible solution is to use the below settings

After making these changes if we reload data at weekly level then the results are below

Advantages of this approach

Temperature  will be correct in monthly view and weekly view.This gives user the flexibility to run MLR forecast at both monthly and weekly level.

Limitations of this approach

Historical temperature and future temperatures( predictions from weather department) should be  available for all the weeks with no missing data at all the locations.Else monthly numbers will be incorrect.

The approach will only show correct values if temperature is seen in location or at a drill down but  it will be incorrect at aggregated level .

For example if we have a Region with two locations L1 and L2 .Location L1 has 3 CVC for Product P1,P2,P3 and Location L2 has two products P1 and P2