Business Requirement
Accounts Receivable Aging is a standard reporting capability in SAP S/4HANA Public Cloud. It helps users review customer balances, what is due, what is overdue, and how long receivables have been outstanding. The standard AR Aging report provides this information through configurable aging periods.
However, the client's requirement went beyond the standard aging information. They wanted to see additional customer, credit, payment, and receivables-related information alongside the aging data, allowing the relevant business information to be reviewed together within the same reporting scenario.
These details were not available in the standard AR Aging data. Therefore, an extension was required to enrich the existing aging information without creating a separate solution for the aging functionality itself.
Solution Approach
The solution uses the standard AR Aging data as the foundation and extends it with the additional fields required by the client.
A custom CDS view was created using the standard AR Aging data as its primary source. Through associations with the relevant data sources, the view adds Sales Employee, Customer Credit Limit, Payment Terms, Journal Entry details, Customer Country/Region, Business Partner identification, and Billing Document reference.
The extended CDS view was then used to build the analytical layer. An analytical cube was created from the extended data, followed by an analytical query using the Custom Analytical Queries and Services app. The query was exposed through OData V2 for consumption by the reporting applications.
This approach keeps the standard AR Aging data at the core while providing a structured way to add information that is not available in the standard scenario.
Standard AR Aging Report
Solution Approach
Extending the AR Aging Data for Analytical Reporting
The standard AR Aging report uses SAP's delivered CDS view, I_ARAgingGridGenLedgerCube, as its underlying data source for aging information. This was used as the starting point for the extension.
A custom CDS view was created using this data source and connected through associations to the relevant sources for the additional business information. This brings the required attributes together with the receivables data in a single CDS view, making the extended data available for the analytical layer.
The custom CDS view was then used to create an analytical cube, which acts as the structured data layer for the extended information, defining the data that can be used for analysis, including the available measures and dimensions.
An analytical query was then created on the cube using the Custom Analytical Queries and Services app. The query defines which data and dimensions are exposed to the report and how they can be analyzed, turning the cube's data into a dataset that can be consumed by the reporting applications.
The query was exposed through OData V2 and managed through Manage KPIs and Reports, making it available through the Fiori Launchpad for consumption by the required applications.
Custom CDS View
Reporting Experience
1. Analytical List Page (ALP) — Interactive Analysis
The Analytical List Page provides an interactive view through tables and graphical views. The information can be filtered, sorted, and arranged for analysis across dimensions such as Customer, Journal Entry, Country/Region, and Credit Limit.
2. Web Dynpro — Statement-Style View
The Web Dynpro report presents the same information in a more structured, graphical, and statement-style format. It brings together outstanding documents, due dates, aging information, and the extended fields to provide a detailed view of the customer's receivables position.
Analytical List Page (ALP) — Interactive Analysis
Web Dynpro — Statement-Style View
Aging and Due-Date Handling
The extension continues to use the Future Due Interval and Overdue Interval available in the AR Aging reporting scenario. No separate aging calculation was introduced.
The intervals can be configured according to the reporting requirement. The testing configuration used 30, 60, and 90 days for future due periods, followed by 30, 60, 90, 120, 150, and 180 days for overdue periods.Business Benefits
- Builds on Standard SAP Data: Extends the existing AR Aging model instead of maintaining a separate aging dataset.
- Enriches the Existing Aging View: Allows additional business information required for a reporting scenario to be brought into the same analytical model.
- Creates a Reusable Analytical Layer: The extended dataset can support multiple applications without maintaining separate data logic for each one.
- Provides Two Reporting Views: The same extended AR Aging data can be consumed through ALP for interactive analysis or Web Dynpro for a structured statement-style view.
Conclusion
The solution demonstrates that when standard AR Aging does not provide all the information required for a business scenario, the capability can be extended without recreating the aging functionality itself. By enriching the existing data and carrying it through the analytical layer, the additional requirements can be addressed within the same SAP framework.
The resulting model also provides a consistent base for different ways of consuming the data, allowing the same extended information to support both interactive analysis and a structured statement-style view. This makes the approach practical for extending standard SAP capabilities while keeping the solution focused and maintainable.
