Booking Values on Leaf vs. Parent Members 

Learn how SAP Analytics Cloud handles data entry at leaf and parent levels, and how disaggregation works when booking values to parent members in planning models.
Beginner
June 22, 2025

In SAP Analytics Cloud (SAC), planning models store data at the most granular level—known as leaf members. When entering or adjusting data in planning tables, understanding how SAC handles leaf vs. parent members is key to maintaining data accuracy and leveraging SAC’s disaggregation engine. 

What Are Leaf and Parent Members?

Leaf Member – The lowest level in a dimension hierarchy. Data is stored here. 

Parent Member – A higher-level aggregate based on its child (leaf) members. Cannot directly store raw data but reflects the sum or calculation of its children. 

Example

  • In a regional sales hierarchy, “Vancouver” and “Toronto” are leaf members, while the parent “Canada” aggregates their totals.

Booking Data to Leaf Members

  • Direct entry to leaf members is straightforward. 
  • The values entered are stored directly in the model without any redistribution. 
  • Ideal for precise planning inputs at the most detailed level. 

How to do it:

1

Open the planning story and select the table. 

2

Filter to display leaf members (if needed). 

3

Enter your planning values directly into the editable cells. 

Booking Data to Parent Members (Disaggregation)

When you enter values at a parent level, SAC automatically disaggregates the value down to its child members using predefined rules or proportions based on existing data. 

Disaggregation Logic:

  • Equal split across children if no prior data exists 
  • Proportional distribution based on historical or related values if available 

Example

If “Marketing Expenses” is the parent of three subcategories and you enter 300 at the parent level: 

  • With no existing values in the subcategories, each one receives 100. 
  • If the subcategories already have values of 50, 100, and 150, SAC allocates the 300 proportionally according to those amounts. 

Best Practices for Disaggregation

  • Use disaggregation only when necessary → Prevents accidental data overrides 
  •  Review disaggregated values after input → Ensures outcomes align with business intent 
  •  Lock specific members before disaggregating → Maintains data integrity and prevents unwanted changes 

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