Skip to main content

Boost Data Quality for SAP S/4HANA: The Role of Customer Vendor Integration (SAP CVI)

Product Manager
Black and gold marble for CVI blog article

In today's SAP landscape, one of the most pressing concerns for companies is the transition to the latest ERP generation, SAP S/4HANA. However, before crossing the finish line, there are essential tasks that must be completed. One such task involves the establishment of SAP Business Partners as the central repository for master data, encompassing both natural individuals and legal entities with whom a company maintains business relationships. 

As we approach the end of 2030, SAP users are required to migrate to SAP S/4HANA, as legacy system support will cease. The new data model within SAP S/4HANA necessitates the consolidation of existing entities like 'Debtor,' 'Creditor,' and 'Business Partner' into a centralized Business Partner data repository. This underscores the mandatory nature of Customer Vendor Integration (SAP CVI) as a vital step in preparing for data migration. It presents a prime opportunity to scrutinize your own data, as data quality is paramount for a seamless migration.


What exactly is the SAP Business Partner?  

By making the Business Partner the central master data object, SAP is instigating a profound transformation in the data structure of the ERP system. In previous iterations, separate data silos existed for customers, suppliers, and employees. SAP S/4HANA is designed to facilitate a higher degree of process automation, necessitating a closer integration of various roles, given the frequent overlaps—for instance, a company can simultaneously function as a supplier and a customer. The SAP Business Partner ensures data consistency by assigning the relevant roles of customer and/or supplier to the same master data object.  


What is Customer Vendor Integration (CVI) and why is it necessary?   

The transition to SAP Business Partner must occur prior to the S/4HANA conversion within the ERP system. The mechanism that connects the SAP Business Partner with debtor and/or creditor master data is known as Customer-Vendor Integration (CVI). During the initial transition, the Business Partner is established through CVI. During ongoing operations, CVI maintains the synchronization of fundamental data between the Business Partner and customer/supplier records.

In SAP S/4HANA, the Business Partner assumes the role of the primary master data object. This implies that basic data is managed within the Business Partner and subsequently shared with customer and supplier objects. However, companies still have the flexibility, within the ERP system, to maintain customers and suppliers separately, while the Business Partner operates in the background.  

The conversion of data from debtors, creditors, and neutral business partners in legacy systems to the new data model is a complex endeavor. Data quality is a pivotal factor, and individual customizations only compound the intricacy, as additional fields and their contents must be considered. Furthermore, the migration of all creditors and debtors is not a matter of choice; it is mandatory. There is no workaround—the vehicle for data conversion is Customer Vendor Integration (SAP CVI). 


The crucial role of data quality and recommended actions

Before embarking on the consolidation of your customers' and suppliers' data into the new model, it is imperative to focus on data quality. Neglecting this aspect can result in the "garbage in, garbage out" scenario or even disruptions during the migration process. For instance, it is critical to verify the accuracy of postal data.  

Data cleansing represents a significant component of the transition, with a clear distinction between obligatory and discretionary tasks. Addressing data inconsistencies is obligatory to enable the technical creation of Business Partners. While additional checks, such as duplicate identification and address validation, are not mandatory, they are strongly recommended to initiate the Business Partner era with genuinely clean data.  

Clean data is an indispensable prerequisite for user acceptance of the SAP Business Partner. The search for duplicates in customer and supplier data should extend beyond individual datasets to encompass a cross-data set examination. Only by doing so can you pinpoint instances where connections between customers and suppliers are absent, potentially leading to adverse outcomes for the SAP Business Partner. A proliferation of duplicates post-transition can impede business operations and erode enthusiasm for adapting to the new data structure.  

This is where the CDQ Suite for Business Partners comes into play.  


CDQ Suite for Business Partners  

Our Data Quality Services  enable quick identification and assessment of critical data errors. These checks, with over 2500 data quality rules today, can be customized and extended as needed.  

With the help of our Cleansing Services, trusted business partner data can be enriched, and erroneous entries can be corrected. We utilize over 70 sources for Identity Resolution, in addition to CDQ-managed reference data.  

Furthermore, addresses can be improved to the required quality with address validation and cleansing. Last, but not least should duplicates be identified and removed early in the migration process, which we facilitate with our Deduplication Services.  


CDQ recommended approach  

Step 1: Preliminary Assessment  

  • Identify the scope and objectives of the S/4HANA migration project, including the business partners whose data needs to be migrated.  
  • Assemble a dedicated team that includes data experts, business analysts, and SAP specialists.  
  • Set up a Change Management Process to ensure that any changes to data are carefully managed and documented throughout the migration process.  


Step 2: Duplicate Identification and Consolidation  

  • Utilize our CDQ Deduplication Services to identify duplicate records within the existing data.  
  • Consolidate duplicate records to create a single, accurate representation of each business partner.  

Ein Bild, das Text, Screenshot, Schrift, Karte Menü enthält.

Automatisch generierte Beschreibung


Step 3: Data Quality Assessment  

  • Assess the quality of the data by identifing critical data defects, such as missing information, incorrect tax identifiers, and discrepancies in naming conventions. 

Ein Bild, das Text, Zahl, Software, Screenshot enthält.

Automatisch generierte Beschreibung


Step 4: Prioritize Data Clean-up  

  • Based on the data quality assessment, prioritize countries or regions with the most records, the highest number of data defects, and the most critical issues.  
  • Develop a prioritization matrix to determine which areas require immediate attention.  

Ein Bild, das Screenshot, Diagramm enthält.

Automatisch generierte Beschreibung


Step 5: Enrich and cleanse Data  

  • Use the CDQ Services to enrich business partner data by adding missing information, such as tax identifiers.  
  • Standardize names and other data elements to ensure consistency and compliance with SAP S/4HANA requirements.  
  • Identify records representing business partners that are no longer active due to factors like legal address changes, mergers, or acquisitions.  
  • Archive or retire inactive business partner records as appropriate.

Ein Bild, das Text, Screenshot, Software, Zahl enthält.

Automatisch generierte Beschreibung


Step 6: Address Standardization  

  • Cleanse and standardize addresses with the CDQ services, thus ensuring accuracy and consistency in the data.  
  • Verify that all addresses meet the format requirements of SAP S/4HANA.  


Ein Bild, das Text, Karte, Screenshot enthält.

Automatisch generierte Beschreibung


Step 7: Data Validation and Testing  

  • Conduct thorough data validation and testing to ensure that the cleaned and enriched data aligns with the SAP S/4HANA system's requirements.  
  • Perform data migration dry-runs and test data scenarios to identify and resolve any issues before the actual migration.  


Step 8: Documentation and Training  

  • Document the entire data quality process, including how the CDQ services were used, data cleaning procedures, and validation results.  
  • Train the relevant personnel on how to maintain data quality in the SAP S/4HANA system after the migration.  


Step 9: Ongoing Data Governance  

  • Establish ongoing data governance practices and responsibilities to ensure that data quality is maintained post-migration.  
  • Regularly monitor and audit data to catch and correct issues as they arise. We enable automated update alerts in case any business partner changed in a connected data source, e.g. business registers  


Step 10: Go-Live and Post-Migration Support  

  • Execute the SAP S/4HANA migration according to the established plan.  
  • Provide post-migration support to address any unforeseen data quality issues that may arise during the transition.  


Step 11: Continuous Improvement  

  • Continuously monitor data quality in SAP S/4HANA and refine data governance processes as needed to maintain high-quality data proactively. 


CVI Do’s and Don’ts

  1. Understand the Importance of SAP Business Partners: Recognize the significance of SAP Business Partners. encompassing both individuals and legal entities with whom your company maintains business relationships.  
  2. Prepare for SAP S/4HANA Migration: Plan ahead for the migration to SAP S/4HANA, as legacy system support will cease, and it's crucial to be prepared for this transition.  
  3. Implement Customer Vendor Integration (SAP CVI): Understand that the SAP CVI is a vital part in preparing for data migration to SAP S/4HANA, as it connects SAP Business Partners with debtor and creditor master data.  
  4. Prioritize Data Quality: Focus on data quality before migrating to SAP S/4HANA. Ensure accuracy and consistency in your data, including verifying postal data and addressing data inconsistencies.  
  5. Consider Data Cleansing: Perform data cleansing to address data inconsistencies, identify duplicates, and validate addresses. While some checks are obligatory, others, like duplicate identification and address validation, are strongly recommended.  
  6. Use Data Quality Services: Consider using Data Quality Services like the CDQ Suite for Business Partners to identify and assess critical data errors, enrich trusted business partner data, and identify and remove duplicates early in the migration process.  






Get our e-mail!

On the way to SAP S/4HANA: migration scenarios supported by Data Quality

Transitioning to SAP S/4HANA is a significant step for any organization looking to modernize its enterprise resource planning (ERP) system. Let's explore three…

CDQ and SAP: the master data automation dream team

In collaboration with SAP, we are dedicated to advancing automation in master data management (MDM), building upon two foundational pillars: cutting-edge…

Better data - unchanged process: Data Quality made easy

It is common sense: Data quality is a key factor for the success of any business that relies on efficient processes, data-driven decision making, analytics, or…