Purpose

The purpose of this document is to define the conversion approach for Quota Arrangements to be uploaded into SAP S/4HANA as part of the Procurement Data Migration. Quota Arrangements are used to determine the distribution of procurement quantities across multiple sources of supply, providing control over vendor sourcing allocations.

---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 specified Execution frequency is specified Restart/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

This conversion approach covers active and relevant Quota Arrangements maintained at the material, plant, and source (vendor or source list) level. Records from legacy ECC systems (e.g., PF2, WP2) will be extracted, validated, transformed, and loaded into the S/4HANA system.

Only quota entries linked to valid material and vendor combinations and with an active allocation percentage will be considered in scope. Obsolete, deleted, or inactive quota records will be excluded. The harmonization process will align multiple legacy records into a consistent target format.

The data from legacy system includes:

1. - Materials that are in scope for conversion
2. Vendors that are valid and active in the target system
3. Quota Arrangements with non-zero quota % and valid plant/material/vendor combinations
4. Entries with recent procurement activity (last 3–5 years)

The data from legacy system excludes:

1. Entries marked for deletion (QMAT-LOEKZ)
2. Obsolete vendors or materials not migrated
3. Quotas with zero allocation or expired validity period

Additional Information

Multi-language Requirement

Document Management

Legal Requirement

Special Requirements

Target Design

Quota Arrangement will be loaded into SAP S/4HANA using standard structures:

• Table: QMAT (Quota Arrangement by Material)
• Fields: MATNR, WERKS, LIFNR, KNTTP, KZUST, ANZQU, DATBI, DATAB, etc.
• The data must match the material master, vendor master, and source list configurations. 

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 will involve harmonizing supplier codes, plant IDs, and units of measure across systems. Where multiple legacy entries exist for the same material/plant, the most recent or business-prioritized record will be retained.

Quota percentage (ANZQU) will be recalculated if source values are inconsistent or incomplete. Date fields will be reformatted to YYYYMMDD and adjusted to cover valid procurement windows.

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