Understanding the Plan Data Scope

[Susanne_Helbig]

Introduction

This blog post explains how the Plan Data Scope works. After reading it, you will understand the logic behind it, how it helps you avoid accidentally overwriting data, and what outcomes you can expect, as well as its limitations.

The plan data scope logic is applied to Import Financial Plan Data, Manage Financial Plan Data Jobs for SAP Analytics Cloud Integration, SAP Analytics Cloud Legacy Export functionality and works the same for those apps.

Let us explore the plan data scope using the Import Financial Plan Data app in a simple scenario for cost center planning, whereas the X in the CSV file sets the Plan Data Scope.
This is similar to the Scope settings in Manage Financial Plan Data Jobs for SAP Analytics Cloud Integration and SAP Analytics Cloud Legacy Export functionality.

Example Scenarios

Example 1: Initial Import
In the example provided, you intend to import four plan data records. Since this is the first time the application is being used, no records are present in the database. This means four new records will be incorporated from the CSV file, as shown in the following screens:

After importing the plan data, you then see a success message that allows you to run the Display Financial Plan Data report directly. This report displays the plan data on the corresponding accounts, indicating that the outcome is as expected.

Example 2: Correcting Data
Suppose you notice that one of the amounts in your file was incorrect. To correct this, simply change the amount from 100 to 150 USD, and import the file again. The import process informs you that the existing plan data will be adapted within the plan data scope and that four records will be incorporated from the CSV file.

After the successful import, the Display Financial Plan Data report shows the corrected amount of 150 USD.

Example 3: Adding Missing Accounts
In another example, you may have forgotten to upload the plan data for a specific account. In this case, you merely need to reimport the file, including the new account.

The system notifies you that the existing plan data will be adapted within the plan data scope and that five records will be incorporated from the CSV file.
Consequently, the Display Financial Plan Data report now displays the plan data for the missing account as well.

Example 4: Handling Complex Scenarios
Let us now examine how the system handles more complex scenarios or repetitive imports.
To reverse specific records before importing a new CSV file, the system creates a logical query based on the dimensions included in the file. Dimensions marked with an X in row #3 are concatenated with AND, while the different members in this column are concatenated with OR. For dimensions without an X, the members are not specified, so records for all members of that dimension are reversed.

Note:
This may reverse data values for which there is no corresponding row in the source file because the selection defined by the plan data scope reverses all values for which the following is true, for example:
Plan Category = "PLN"
AND General Ledger Fiscal Year = "2025"
AND Posting Period = "011"
AND Company Code = "1710"
AND (Cost Center = "0017101101" OR Cost Center = "0017101201")

In example 3, you mistakenly planned on cost center 17101201, which should not have been planned on. The data you imported in this file is incorrect, and now you wish to send only three records instead of five.
To correct this, you reimport the file with these three records, but you leave the X for the cost center dimension in the file.

This action results in the reversal of the records meeting the following criteria:
Plan Category = "PLN"
AND General Ledger Fiscal Year = "2025"
AND Posting Period = "011"
AND Company Code = "1710"
AND Cost Center = "0017101101"

The erroneous cost center data remains unchanged, so the incorrect data for cost center 17101201 is still present in the system after this import.

To correct the erroneous data, you need to remove the X from the cost center column.

This action results in the reversal of the records meeting the following criteria:
Plan Category = "PLN"
AND General Ledger Fiscal Year = "2025"
AND Posting Period = "011"
AND Company Code = "1710"

This sets the records for cost centers not specified in the CSV file to zero.

Example 5: Updating and Adding Records
In this last example, you want to correct one existing record for 2025 from 150 USD to 200 USD and add new records for 2026.

Let’s assume that the data in your system looks as follows:

By importing the CSV file as shown above, the system reverses the plan records for both cost centers and both years. Note, however, that even records that were not part of the uploaded CSV file are also reversed because of the following criteria:
Plan Category = "PLN"
AND (General Ledger Fiscal Year = "2025" OR General Ledger Fiscal Year = "2026")
AND Posting Period = "011"
AND Company Code = "1710"
AND (Cost Center = "0017101101" OR Cost Center ="0017101201")

To resolve this, you need to split your data into two upload files.

One CSV file contains the record that needs to be corrected and where the X is set for all dimensions, including the G/L account.

This changes the amount from 150 USD to 200 USD, while all other records remain unchanged.

The second file contains the new records for 2026, where you don’t need to set the X for the G/L account dimension.

After both CSV files have been uploaded, the data in your system looks as follows:

Summary:

Dimension in scope:
During import, the system matches the specified dimensions and reverses existing records that align with the imported values. If the import contains fewer records than what is currently in the target, only the matching records are affected. The rest remains unchanged.

Dimension not in scope:
During import, the system assumes that all members of that dimension are included, which means it will reverse all existing records for that dimension even if they are not explicitly part of the import. This can result in data being set to zero for any members not included in the import.

Note that the time dimension is mandatory in the Plan Data Scope to avoid accidental reversal of data from previous planning cycles.

Keep in mind that the fewer dimensions you include in the plan data scope, the more records will be set to zero. To minimize the risk of unintentional data loss, consider adding more dimensions to the plan data scope and separating the uploaded data accordingly.

This means that the combination of Plan Data Scope and imported data defines which entries in the target will be updated. Note it is not possible to delete data using these apps, only setting the values to zero in the target is possible.