Purpose

The purpose of this document is to define the conversion approach to create Business Partners - General in S/4 HANA.

In SAP ECC, customer and vendor master data are maintained separately as distinct entities. Customers are managed through Customer Master Data, while vendors are handled via Vendor Master Data. These records store essential details such as company name, address, payment terms, and tax information.
In SAP S/4HANA, the Business Partner (BP) concept replaces the traditional customer and vendor master data approach. The BP model integrates both customer and vendor roles into a single entity, simplifying data management and ensuring consistency across different business functions

Conversion Scope

The scope of this document covers the approach for converting active Customer Master Data General and Vendor Master General from Legacy Source Systems into S/4HANA Business Partner (BP) General (Role 000000) Master Data Design Standard. 

Customer Master Data - General Information

The data from legacy system includes:

1. Customer with AR Balance under the company codes within S4 Hana implementation scope.
2. or (Customer doesn't have central deletion indicator AND Customer has sales transaction within the sales organizations in scope), e.g., the customer is used as any partner function in the sales document, such as sales order, delivery or billing.
3. or (Customer doesn't have central deletion indicator and customer has financial posting under the company codes within S4 Hana implementation scope)
4. or Customer is part of Customer Hierarchy Higher Node, and the sales area data is part of the sales areas within migration scope
5. or there is customer consignment stock and the plant for the consignment stock is within S4 Hana implementation scope. 
6. or (Customer is created within 2 year and there is no central block) and it has sales view within sales organization in scope
7. or (Customer is created within 2 year and there is no central block) and it has company code view within company code in scope
8. or 

The data from legacy system excludes:

1. Customer has central deletion indicator and without AR/AP Balance under the company codes within S4 Hana implementation scope.
2. Customer is used exclusively by entities not in scope, such as Oil & Gas and Aroma.

Vendor Master Data - General Information

The data from legacy system includes:

The data from legacy system excludes:

 List of source systems and approximate number of records 

Additional Information

Multi-language Requirement

The customer and vendor general data may contain international address. Therefore, the conversion will also need to support the multi-language address.  Below languages (International versions) are supported. 

Document Management

It is possible the customer has attachment in the legacy system. The migration of attachment will be captured in conversion spec CNV-3004 - Attachment for customer master data. 

Legal Requirement

CMMC 2.0 is a mandatory DoD cybersecurity certification for contractors handling Controlled Unclassified Information (CUI) and Federal Contract Information (FCI). CUI includes sensitive technical data (e.g., design specs, system info) related to U.S. military and space applications. The Composites Business handles CUI and is therefore within CMMC scope. Without certification, the business risks disqualification from existing and future DoD programs.
It is mandatory to implement CMMC-compliant systems and processes to for all the organizations that are dealing with CUI.

Therefore, there will be one SAP instance specifically for CUI related entities. As Synithi is not CUI certified partner, the migration for CUI related entities will be covered by US based data consultant using separate tools.

Special Requirements

If the data conversion involves third-party systems or external data sources, such as Icertis, describe any additional requirements related to data mapping, transformation logic, validation rules or security measures that must be followed.

Due to compliance requirement, there will be one SAP instance for Rest of the World, one for China and one for CUI.

1. For entities in China, the data will be loaded into SAP China instance while the entire migration process will remain the same as rest of the world.
2. For entities which will reside in CUI, the migration will be handled by US based data consultant. 

Customer Master Data - General Information

 - To identify the record is for SAP China Instance, it will use below logic. 

1. The customer has sales area data or company code data in below entities. 
2. If the customer is used in both China entities and ROW, then the general data needs to be created in both SAP China and ROW instances.

 - To identify the record is for SAP CUI Instance, it will use below logic. 

1. The customer has sales area data or company code data in below entities. 
2. If the customer is used in both CUI entities and ROW, then the general data needs to be created in both SAP CUI and ROW instances.

In the meantime, for WP2/PF2 customer master general data, it is possible they are both coming from the same MDM PRS system, therefore, a de-duplication or reconciliation needs to be performed based on below logic. 

1. In PF2, it will have the relationship that KNA1-ZZR_KUNNR_RCS (RCS Customer code) = WP2, KNA1-KUNNR, then it refers to the same customer. 
2. In WP2, it will have the relationship that KNA1-ZZR_KUNNR_PRS (PRS Customer code)= PF2, KNA1-KUNNR, then it refers to the same customer. 

 Vendor Master Data - General Information

*please indicate how S2P will identify the SAP China Instances.

Target Design

The technical design of the target for this conversion approach. 

Data Cleansing

All data cleansing should take place in the data source system as defined in this document, unless system limitations prevent it.

Customer Master Data - General Information

Vendor Master Data - General Information

Conversion Process 

The high-level process is represented by the diagram below:

The ETL (Extract, Transform, Load) process is a structured approach to data migration and management, ensuring high-quality data is seamlessly transferred across systems. Here’s a breakdown of its key components:
1. Extraction
The process begins with extracting metadata and raw data from source systems, such as Syensqo ECC system (i.e., WP2/PF2) periodically. The extracted data is then staged for transformation.

2. Transformation
Once extracted, the data undergoes cleansing, consolidation, and governance. This step ensures data integrity, consistency, and compliance with business rules. The transformation process includes:
- Data validation to remove inconsistencies.
- Standardization to align formats across datasets.
- Business rule application to refine data for operational use.

3. Loading
The transformed data is then loaded into the target S4 Hana system. 

Data Privacy and Sensitivity

Extraction

Extract data from a source into Syniti Migrate. There are 2 possibilities:

1. The data exists. Syniti Migrate connects to the source and loads the data into Syniti Migrate. There are 3 methods:
   1. Perform full data extraction from relevant tables in the source system(s).
   2. Perform extraction through the application layer.
   3. Only if Syniti Migrate cannot connect to the source, data is loaded to the repository from the provided source system extract/report.
2. The data does not exist (or cannot be converted from its current state).  The data is manually collected by the business directly in Syniti Migrate. This is to be conducted using DCT (Data Collection Template) in Syniti Migrate

The agreed Relevancy criteria is applied to the extracted records to identify the records that are applicable for the Target loads

Extraction Run Sheet

Selection Screen

Data Collection Template (DCT)

DCT Rules

Customer Master Data - General Information

 Vendor Master Data - General Information

Extraction Dependencies

Transformation

The Target fields are mapped to the applicable Legacy field that will be its source, this is a 3-way activity involving the Business, Functional team and Data team.  This identifies the transformation activity required to allow Syniti Migrate to make the data Target ready:

1. Perform value mapping and data transformation rules.
   1. Legacy values are mapped to the to-be values (this could include a default value)
   2. Values are transformed according to the rules defined in Syniti Migrate
2. Prepare target-ready data in the structure and format that is required for loading via prescribed Load Tool.  This step also produces the load data ready for business to perform Pre-load Data Validation

Transformation Run Sheet

Transformation Rules

Transformation Mapping

Transformation Dependencies

Pre-Load Validation

Project Team

Completeness

Accuracy

Business

Completeness

Accuracy

Load

The load process includes:

1. Execute the automated data load into target system using load tool or product the load file if the load must be done manually
2. Once the data is loaded to the target system, it will be extracted and prepared for Post Load Data Validation

Load Run Sheet

Load Phase and Dependencies

The Business Partner General will be loaded in the pre-cutover period.

Before loading, it will have dependency on the configuration. The configuration needs to be transported into the respective system first, including the manual configuration such as the BP number range set up.

Configuration

 Conversion Objects

Error Handling

Post-Load Validation

Project Team

Completeness

Accuracy

Business

Post-load validation is a critical step in data migration, ensuring that transferred data is accurate, complete, and functional within the target system.

1. Ensuring Data Integrity
After migration, data must be consistent with its original structure. Post-load validation checks for missing records, incorrect mappings, and formatting errors to prevent discrepancies.
2. Business Continuity
Faulty data can disrupt operations, leading to financial losses and inefficiencies. Validating post-load data ensures that applications function as expected, preventing downtime.
3. Error Detection and Resolution
By validating data post-migration, businesses can detect anomalies early, reducing the cost and effort required for corrections

Completeness

Accuracy

Key Assumptions

• BP Master Data Standard is up to date as on the date of documenting this conversion approach and data load. 
• BP General (Role 000000) is in scope
• There will only be SAP instance, one for ROW, and one for China only

Change log

Workflow history