Purpose

The purpose of this document is to define the conversion approach to create 1057 - QM Master Inspection Characteristics in S/4 HANA.

Master Inspection Characteristics are a fundamental element of SAP Quality Management (QM) used to define the parameters, specifications, and methods for quality inspections. MICs provide a standardized definition of what is to be inspected and how it should be measured, ensuring uniformity and consistency across inspection plans and quality processes. MICs can be maintained as Quantitative (numeric specifications such as measurement ranges and tolerances) or Qualitative (descriptive specifications such as defect classes or codes).

In SAP S/4HANA, the structure and usage of MICs remain consistent with SAP ECC, typically defined by key combinations such as plant, characteristic name, and characteristic type. MICs may include additional settings such as selected sets for qualitative characteristics, catalog assignments, default inspection methods, target values, upper and lower specification limits, and sampling procedures.

In SAP ECC, aside from the standard MIC structures, there may be additional configurations, such as plant-independent characteristics, characteristics linked to custom catalogs, or MICs with special control indicators and custom fields. Certain legacy systems may also include MICs with obsolete catalog references, inactive units of measure, or unused selected sets (pending MDS review), which must be validated before conversion.

This conversion aims to migrate active and relevant MIC records, along with their associated control indicators, selected sets, catalog assignments, default inspection methods, and specification limits, from existing ECC systems into S/4HANA. The migration will apply 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_INSPOPER_RECORDRESULTS for linking to inspection operations, or QS21 transaction for creation), IDOCs, or direct table loads where applicable, ensuring data integrity, compliance, and reusability across inspection plans.

Conversion Scope

The scope of this document covers the approach for converting active Master Inspection Characteristic (MIC) from Legacy Source Systems into S/4HANA following the Master Inspection Characteristic Master Data Design Standard.

The data from legacy system includes:

1. Active MICs used within the last three (3) years in inspection plans or inspection lots.

2. MICs without deletion flag.

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

4. MICs referenced in active inspection plans, sampling procedures, or inspection methods.

5. MICs with valid configuration, including:
   • Inspection Plan
   • Sampling Procedure
   • Inspection Method
6. MICs with complete multilingual descriptions (short texts and, if available, long texts) in required business languages.

The data from legacy system excludes:

1. Inactive MICs not used in inspection plan for more than three (3) years.

2. MICs marked for deletion in ECC.

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

4. Obsolete or duplicate MICs that are no longer relevant, such as:

   • MIC replaced by harmonized corporate standards

   • Local variations with identical configuration
   • Test or training MICs not intended for productive use
5. MICs with invalid references, such as:
   • Links to deleted Sampling Procedures
   • Links to inactive or obsolete Inspection Methods
6. MICs with incomplete setup, including:

   • Missing UoM or decimal places for quantitative MICs

   • Missing catalog/code group for qualitative MICs

   • Missing description in mandatory languages

Additional Information

Multi-language Requirement

Master Inspection Characteristic description will be maintained in English by default.

Since multi-language support is available for Master Inspection Characteristic, users logging in with a different language will see the description displayed in their logon language, provided that the corresponding language key has been maintained in the on Characteristic.

Document Management

Not applicable

Legal Requirement

Not applicable

Special Requirements

Not applicable

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:

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)

Master Inspection Characteristic 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