Purpose

The purpose of this document is to define the conversion approach to create Conversion Specification Document CNV-2009 Material Master – QM View in S/4HANA.

The QM View in the Material Master contains quality-related settings that control how a material is handled in Quality Management processes. These settings include inspection types (e.g., goods receipt, in-process, delivery), quality control keys, certificate requirements, preferred inspection plans or material specifications, and the status of quality management activation for the material. Maintaining the QM View ensures that materials are consistently subjected to the correct inspection processes during procurement, production, and sales.

In SAP S/4HANA, the structure and usage of the Material Master QM View remain consistent with SAP ECC. The QM View is defined by material (MARA-MATNR), plant (MARC-WERKS), and the associated quality-related fields. These include inspection setup (QMAT), inspection types (QMAT-ART), active status, and assignment of task lists or material specifications.

In SAP ECC, aside from the standard fields, additional legacy configurations may exist, such as:

• Materials with inactive or obsolete inspection types still marked in the QM View.
• Materials assigned to inspection types without corresponding inspection plans or specifications.
• Redundant or duplicate plant-level QM settings for the same material.
• Materials with blocked or obsolete quality control keys.
  These cases will need to be validated and cleansed as part of the Master Data Services (MDS) process prior to migration.

This conversion aims to migrate active and relevant Material Master QM View data from existing ECC systems into S/4HANA by applying the required transformation logic using Syniti as the data migration and transformation platform. The converted records will be loaded into the target S/4HANA system using standard SAP mechanisms such as BAPIs (e.g., BAPI_OBJCL_CREATE or BAPI_MATERIAL_SAVEDATA), IDOCs, or direct table loads where applicable, ensuring that all materials in scope have consistent and accurate QM-related setup in the target system.

Conversion Scope

The scope of this document covers the approach for converting active Material Master – QM View data from Legacy Source Systems into S/4HANA following the Material Master QM View Design Standard.

From the current system landscape, Material Master QM View data exists separately in the legacy systems (PF2 and WP2), with potential discrepancies in both systems. Harmonization and validation are required to ensure accurate and consolidated data in S/4HANA. While PF2 and WP2 serve as source systems, extensive mapping and transformation logic will be necessary to produce properly formatted load templates in line with the target design.

The data from legacy system includes: Final relevancy rule pending MDS

1. Active Material Master QM Views that are in use within the last three (3) years in inspection lots, quality certificates, or inspection plans.

2. QM Views without Deletion Flag, i.e., not blocked or obsolete.

3. QM Views assigned to plants that are in-scope for S/4HANA migration, based on the To-Be Plant Mapping.

4. Materials with at least one valid inspection type (e.g., 01, 04, 09) configured and active in the QM View.

5. Materials where control key, inspection setup, and certificate requirements are consistent with S/4HANA target design.

The data from legacy system excludes:

1. Inactive QM Views for materials not used in inspection lots or quality processes for more than three (3) years.

2. QM Views marked for deletion or with inspection types blocked in ECC.

3. QM Views belonging to plants that are out of scope or deleted as per To-Be Plant Mapping.

4. Obsolete inspection types or settings that are not supported in S/4HANA.

5. Duplicate or conflicting QM Views for the same material/plant combination, where only one harmonized record should remain.

Relevancy rule

1. Material/Plant with history and active production usage – Materials must be defined at global (MARA) and plant level (MARC) with valid status and assignment to active plants in scope.

2. BOMs linked to active materials – Only BOMs associated with materials that have valid production usage (Usage = 1 “Production”) and are actively used in production within the last three (3) years will be considered.

3. Production Versions referencing BOMs – Production Versions must exist and be valid, linking BOMs with corresponding Routings/Master Recipes at the plant level to ensure continuity of manufacturing execution.

4. Component materials – All components within the BOM must be valid, active materials in the Material Master and not marked for deletion.

5. Plant-specific validation – BOMs will be checked against active plant mappings (per To-Be Plant definition) to ensure only relevant BOMs are migrated.

Material/Plant Active with three years production usage history ➡ defines Active BOMs (Usage = 1 “Production”) by Plant ➡ validates Production Versions ➡ ensures accurate mapping of dependent Routings/Master Recipes.

Plant Merging

Plants will be harmonized based on the To-Be Plant Mapping. As some legacy plants will be merged into one target plant, BOMs will be reassigned accordingly. Plant transformation will be managed through a mapping table maintained in Syniti to ensure consistent alignment with the To-Be Plant structure.

List of source systems and approximate number of records

Additional Information

Multi-language Requirement

Not applicable

Document Management

Not applicable

Legal Requirement

Not applicable

Special Requirements

Not applicable

Target Design

Inspection Plan strictly adheres to the Master Data Standard. The complete information of the tables and key fields that hold the Inspection Plan information follows the Master Data Standard document.

The technical design of the target for this conversion approach (pending MDS)

Data Cleansing

All data cleansing activities must be performed in the source systems (e.g., PF2, WP2) wherever possible, following the rules and criteria defined in this document. The objective is to ensure that only valid, active, and relevant master data is migrated to S/4HANA, while obsolete, redundant, or inconsistent records are excluded.

If certain data cleansing activities cannot be executed directly in the source systems due to system limitations, they may be managed externally (e.g., using Syniti Migrate, 3rd Party Vendor tools, or DCT processes). In such cases, proper documentation of the cleansing activity must be maintained and appended to this deliverable to support review, validation, and sign-off by stakeholders.

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 S/4HANA system. 

For sites that are not on SAP-PF2 and WP2 systems, collection will be done manually in the data collection template.

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

Data Privacy and Sensitivity

Not applicable

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)

Extraction Dependencies

Before data extraction can commence, several prerequisite steps and conditions must be met to ensure a smooth and accurate extraction process. These dependencies involve confirming system readiness, validating data structures, and ensuring that appropriate access rights and credentials are in place.

Each step must be clearly defined, assigned to responsible teams, and completed prior to extraction activities. Proper coordination across stakeholders is required to mitigate risks and avoid delays in the migration timeline.

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