Blocks caused by VAT ID validation
If a company name or address does not match its VAT ID, processes such as order creation may be blocked and corrections can become costly.
Service
Business Partner data cleansing for S/4HANA migration.
When VAT ID checks, address data and duplicate records do not align, SAP processes can face blocks, interruptions and manual rework. Escarion establishes central address, VAT ID and duplicate validation ahead of migration, helping you transfer clean, migration-ready Business Partner data to SAP S/4HANA for operational use.
Typical triggers
Why this needs attention early
Multiple source systems
ERP, accounting and CRM systems provide different spellings, outdated contacts and inconsistent field values.
Hidden duplicates
Duplicate Business Partners, delivery addresses and billing addresses may only become apparent during testing or live operation.
No golden record
Without defined golden record rules, new inconsistencies arise even after individual records have been corrected.
Requirements
What central Business Partner validation should cover
- Central consolidation from multiple source systems: customers, vendors and Business Partners
- Address validation for EU and non-EU addresses, including structural checks
- VAT ID validation through VIES, including name and address checks
- Duplicate detection and consolidation of inconsistent records
- Field validation and data hygiene, such as email addresses in phone number fields
- Relationships and company hierarchies: parent/subsidiary, roles and contacts
- A golden record for each Business Partner and a migration-ready target dataset for SAP S/4HANA
Fuzzy matching and duplicate analysis can be accelerated with our own AI application, Fuzzy Clean .
Our approach
A practical route to a clean target dataset
1. Data overview and rules
Together, we define source systems, data objects, required fields and blocking rules. This produces testable rules and clear priorities.
2. Consolidation and validation
Data is consolidated, cleansed and checked against external references, such as address validation services and VIES.
3. Golden record and handover
Duplicates are merged, relationships established and a migration-ready dataset provided for testing and cutover.
Contact
Contact us
Briefly describe your starting point: source systems, scope, blocking rules and schedule. We will respond with a concrete proposal for the approach and effort involved.