Purpose

The purpose of this document is to define the conversion approach to create Inspection Methods in S/4HANA.

Inspection Methods are master data objects in SAP Quality Management (QM) that describe how inspections are to be carried out. They specify the procedure, tools, or references to be used for measuring or evaluating inspection characteristics, and can include documents such as test instructions, work instructions, or external references. This feature ensures standardized execution of quality inspections across plants, materials, and processes.

In SAP S/4HANA, the structure and usage of inspection methods remain consistent with SAP ECC. Inspection methods are typically created at the plant level and assigned to master inspection characteristics (MICs) or directly to inspection plan characteristics. Methods may also include language-dependent descriptions, versioning, validity dates, and document references.

In SAP ECC, aside from the standard structure of inspection method master data (method number, version, plant, and description), additional combinations may exist, such as methods assigned to specific catalogs, methods linked to custom documentation, or methods maintained with plant-independent validity. Some legacy ECC systems may also contain methods with non-standard extensions or inactive versions that need to be reviewed and cleansed (pending MDS).

This conversion aims to migrate active and relevant inspection method records 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_INSPECTIONMETHOD_CREATE), IDOCs, or direct table loads where applicable, ensuring consistency, compliance, and reusability in quality processes.

Conversion Scope

The scope of this document covers the approach for converting active 1043 Inspection Methods from Legacy Source Systems into S/4HANA following the Inspection Method Master Data Design Standard.

The data from legacy system includes:

1. Active Inspection Methods used within the last three (3) years in inspection plans or master inspection characteristics.

2. Inspection Methods without deletion flag.

3. Plant-specific and global Inspection Methods that will be migrated to the To-Be Plant Mapping (taking into consideration the To-Be definition of Plants).

4. Inspection Methods referenced in active MICs or inspection plans.

The data from legacy system excludes:

1. Inactive Inspection Methods not used in more than three (3) years.

2. Inspection Methods marked for deletion.

3. Inspection Methods belonging to deleted plants (per To-Be Plant mapping).

4. Obsolete or duplicate Inspection Methods that are no longer relevant (e.g., replaced by harmonized corporate standards).

Additional Information

Multi-language Requirement

Not applicable

Document Management

None identified. The conversion scope is limited to the migration of Inspection Method object. No document attachments, images, or supporting files are included.

Legal Requirement

Not applicable

Special Requirements

Not applicable

Target Design

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

The technical design of the target for this conversion approach.

Data Cleansing

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. 

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