Purpose

The purpose of this document is to define the conversion approach to create Service Master records in S/4HANA. It follows the Procurement Master Data Design Standard and is based on data being migrated from legacy SAP ECC systems (PF2, WP2) into SAP S/4HANA.

The purpose of this document is to define the conversion approach to upload data in S/4 HANA.

---CHECKLIST---

• Logical Source and Target Systems are identified. 
• Processing Type is specified (i.e. Direct Input, BAPI, IDoc, Web Service, OData API, etc.)
• Standard or custom load program name/BAPI/IDoc is specified to support this functionality.
• Data Mapping is provided for mappings which are not obvious to a suitably-skilled and experienced developer
• All translation requirements are clearly defined (including data validation rules, data derivation/calculation and default values, if applicable)Input and/or Output file layouts are provided for all record types possible
• Transaction volume is specifiedExecution frequency is specifiedRestart/Recovery requirements have been defined
• Error handling requirements are specified, including alerting requirement and expected action on failure. 
• Application log requirement if applicable to be specified. 

--- Additional topics to check---

• Update the Data Volume with a actual figures
• Rules for Data Merging (all systems)
• Mapping Rules & Conversion Rules

Conversion Scope

Current Usage and Setup in Legacy Systems:

In the legacy SAP ECC systems (PF2 and WP2), Service Master records are maintained primarily to support procurement processes involving services. However, the level of data quality and consistency varies across systems. In some cases, key fields such as Service Descriptions, Units of Measure, or Valuation Classes may be incomplete or non-standardized. Additionally, the linkage between services and associated purchasing conditions is often loosely maintained or inconsistently applied.

Target Representation in SAP S/4HANA:

In S/4HANA, Service Master data will be created in alignment with the Procurement Master Data Design Standard. The objective is to ensure that services are structured, clean, and standardized across the entire enterprise. This includes enforcing harmonized naming conventions, classification, and valuation data to support downstream procurement and analytics processes. Where applicable, service hierarchies and pricing conditions will also be defined to enable integrated procurement planning and execution.

Additional Relevant Information:

• Service Master records in S/4HANA will be loaded using the SAP Migration Cockpit, based on validated and cleansed legacy extracts.

• Redundant or obsolete service entries will be excluded as part of the cleansing process.

• Each service entry will be reviewed and approved by the business before final load.

• The mapping of legacy keys to S/4-compatible structures (e.g., Service Type, Material Group) will be maintained for traceability.

The data from legacy system includes:

1. Service records marked as relevant for purchasing processes

2. Entries with valid service numbers and active status

3. Records linked to active cost centers or purchasing groups

4. Service descriptions maintained in English

The data from legacy system excludes:

1. Obsolete or blocked service records

2. Entries with missing mandatory fields (e.g., Unit of Measure, Valuation Class)

3. Test or dummy records (e.g., codes starting with “ZZZ”)

4. Services not linked to any purchasing documents or usage history

5. Duplicate entries identified through harmonization process

Additional Information

Multi-language Requirement

Texts associated multiple languages can be mainted a such (in case available on the source system)

Document Management

Legal Requirement

Minor effort is foreseen for some specific countries having specific taxations, the topic is limited to have the tax codes mapping (from Old to New tax code).

Special Requirements

Processing Type ETL: 

• Transformation (T): Syniti will be responsible for cleansing, transforming, and merging the data, as well as updating the staging areas of the SAP Migration Cockpit.

• Extraction (E): Data will be extracted from at least two source systems. This activity will be performed by Syniti.

• Loading (L): The final data load into the target SAP system will be carried out using the standard functionalities of the SAP Migration Cockpit.

Target Design

The technical design of the target for this conversion approach.

Data Cleansing

Conversion Process

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

Data Privacy and Sensitivity

Extraction

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

1. The data exists. connects to the source and loads the data into . 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 ; 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 . This is to be conducted using DCT (Data Collection Template) in

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

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 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
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

Configuration

Conversion Objects

Error Handling

Post-Load Validation

Project Team

Completeness

Accuracy

Business

Completeness

Accuracy

Key Assumptions

• Master Data Standard is up to date as on the date of documenting this conversion approach and data load.
• is in scope based on data design and any exception requested by business.

See also

Change log

Workflow history