The Financial Data Quality check within SAP Readiness Check has been enhanced and extended to provide further insights. This new version of the Financial Data Quality check includes the ability to analyze asset accounting data, in addition to general ledger data. As with general ledger data inconsistencies, it is critical to identify and resolve asset account inconsistencies before or as part of a conversion project to SAP S/4HANA.
In addition to the support of an additional area of finance, the Financial Data Quality check tile and detail pages have been enhanced to clearly display the findings from the analysis. Grouped by finance area, the detail view includes:
◉ Identification of inconsistency hotspots by company code and fiscal year
◉ Grouping of inconsistencies by message type
◉ Classification of inconsistency message types to assist with remediating inconsistencies
◉ Summary of key facts and figures for each finance area
Overview
The overview of the Financial Data Quality check displays the number of inconsistent documents and distinct inconsistency types for general ledger and the number of inconsistent assets and distinct inconsistency types for asset accounting. On the right-hand side, the inconsistency types are categorized in
A: Standard automated correction available
B: Manual correction available
C: Contact SAP Support
D: System-specific correction required
to give a better indication on the required efforts for resolving the issues.
Detail View for General Ledger
General Ledger is a comprehensive view of external accounting. Including and collecting all business transactions for primary postings and settlements from Management Accounting into a system that is integrated into your business ensures that accounting is complete and reconciled at all times.
In the detail view of the Financial Data Quality check, a new dropdown menu allows you to navigate between the different detail pages.
Inconsistencies
The data displayed in the Inconsistencies section is based on the results of the FIN_CORR_RECONCILE analysis in your system. It is important to highlight that the Financial Data Quality checks are client specific. This means that all analysis results belong to a specific system client. The underlying reconciliation check is the main source of the financial data quality analysis, performing various consistency checks against the General Ledger module in your system. It is crucial to carefully analyze and resolve identified issues prior to (or as part of) the SAP S/4HANA conversion project. Please note that, when estimating the resolution effort for the identified inconsistencies, you should refer to the number of different inconsistency types, rather than the total number of inconsistencies.
Documents
This section contains an overview of identified documents and open items by fiscal year and company code. The number of open items in financial documents per fiscal year and company code may reflect unfinished business transactions. To see a detailed overview, use the Export to Spreadsheet function on the top of the table on the Documents and Open Items tab. The top 10 financial documents based on the total number of financial documents are listed in the table below.
Documents view:
Facts and Figures
This section contains information about factors that usually influence the required effort, duration, and cost for the data cleansing. Resolving these issues can lead to a significant financial data reduction and, as a result, improve your system’s performance.
Detail View for Asset Accounting
Asset Accounting is a subledger accounting module in Financial Accounting in which the business transactions for fixed assets are entered.
Inconsistencies
The data displayed in this section is based on the results of the FIN_AA_CORR_RECON analysis in your system. The underlying reconciliation check is one of the main sources of the financial data quality analysis, performing various consistency checks against the Asset Accounting module in your system. Once again, it is important to highlight that the Financial Data Quality checks are client specific. This means that all analysis results belong to a specific system client. It is crucial to carefully analyze and resolve identified issues prior to (or as part of) the SAP S/4HANA conversion project. Please note that, when estimating the resolution effort for the identified inconsistencies, you should refer to the number of different inconsistency types, rather than the total number of inconsistencies. For more information about the identified inconsistency types, refer to SAP Note 3038014.
Assets
This section contains an overview of the identified main assets by company code. To see a detailed overview, use the Export to Spreadsheet function on the top of the table on the Assets tab. The top 10 assets based on the total number of assets are listed in the table below.
Facts and Figures
This section contains information about factors that usually influence the required effort, duration, and cost for the data cleansing. Resolving these issues can lead to a significant financial data reduction and, as a result, improve your system’s performance.
Data Collection for Financial Data Quality Check in SAP Readiness Check
To prepare the data collection for Financial Data Quality in SAP Readiness Check, follow the description in SAP Note 2972792 – Financial Data Quality: Trigger Data Collection Reports to Check Your Financial Data Quality and to Enable the Financial Data Quality Check in SAP Readiness Check.
The Financial Data Quality (FDQ) analysis cross-references records spanning the financial data model that exists in SAP ERP 6.0 (It is valid for systems with SAP_APPL 600 to 616 or SAP_FIN 617 to 618). Depending on the volume of financial data, there is the potential for this check to run longer than other checks. If necessary, it is possible to schedule the Financial Data Quality check in isolation from the rest of the SAP Readiness Check data collectors.
The exact duration depends on the number of financial records in the system being analyzed. By default, the number of work processes allocated to this analysis is limited (as the priority with SAP Readiness Check is to avoid resource contention with productive operations) but can be adapted manually as described in the SAP Note.
If run separately, the collected data archive can be uploaded to an existing SAP Readiness Check analysis.
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