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.

This Conversion Specification does not include the WPX system (CUI Objects).

Conversion Scope

The scope of this document covers the approach for converting active Conversion Specification CNV-1057 Master Inspection Characteristic (MIC) from Legacy Source Systems into S/4HANA following the Master Inspection Characteristic Master Data Design Standard MDS-1057. 

From the current landscape, MIC data exists in legacy quality management systems (e.g., PF2 and WP2). Harmonization and validation are required to ensure accurate and consolidated MIC data in S/4HANA. While PF2 and WP2 serve as source systems, extensive mapping and transformation logic will be applied to ensure clean, relevant, and standardized data is migrated.

1. Active MIC records that meet the Material Relevancy Criteria (aligned with valid Material Master Basic Data View, QM View, QM Inspection Plan and Master Recipe) and are used in valid inspection processes within the last four (4) years.

2. MICs without deletion flags, ensuring only valid and relevant characteristics are migrated.

3. MICs assigned to in-scope plants or inspection plans based on the To-Be Plant Mapping.

4. MICs linked to valid inspection types and usage (e.g., 01, 04, 09) to ensure functional integration with quality processes in the target system.

5. MICs with valid catalog assignments (e.g., defect class, code group, selected set) and valid control indicators.

6. MICs referenced in sampling procedures or inspection plans to ensure inspection process continuity in the target environment.

The data from legacy system excludes:

1. Inactive or obsolete MICs that are not used in inspection plans or linked processes within the last four (4) years.

2. MICs marked for deletion in the legacy system.

3. MICs assigned to plants that are out of scope, based on the To-Be Plant Mapping in Enterprise Structure Catalog worksheet "30. Plants"

4. Invalid or incomplete catalog assignments, missing required control indicators, or unsupported settings in S/4HANA.

Relevancy rule

1. Material/Plant with history and active usage
   Materials must be defined at both global level (MARA) and plant level (MARC) with valid status and assignment to active in-scope plants. Only materials with active QM View are considered relevant. In addition, QM View relevancy must aligned with Material Master Basic Views (CNV-2019) to ensure consistent dependency with MARA-level relevancy. Usage confirmation may also include inspection lots (QALS) within the last four (4) years where applicable.
2. Active Inspection Types
   Only materials with at least one valid and active inspection type (e.g., 01, 02, 03, 04, 05, 06, 08, 10, 11, 12, 17) maintained in QMAT and linked to relevant plants will be considered in scope.
3. Inspection Setup with Valid Usage 
   Inspection types must be relevant to in-scope Syensqo business processes (e.g., Goods Receipt, In-Process, Delivery). Materials without any active inspection usage in the last four (4) years will be excluded.

4. Plant-Specific Validation
   Materials with QM View will be checked against active plant mappings (To-Be Plant Definition) to ensure that only valid, active plants are considered for migration.

Material/Plant active with four (4) years inspection usage history ➝ validates active QM View (QMAT) with at least one valid inspection type (e.g., 01, 04, 09) ➝ confirms Control Key, Certificate Type, and Q-Score alignment with configuration ➝ ensures accurate integration with incoming inspection and quality processes in S/4HANA.

Plant Merging

Plants will be harmonized based on the To-Be Plant Mapping. As some legacy plants will be merged into one target plant, QM Views will be reassigned accordingly to ensure data consistency and alignment with the new plant structure in SAP S/4HANA.

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

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. 

Data Privacy and Sensitivity

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)

The Data Collection Template (DCT) will not be applicable in this case. If there is a need to create a new Master Data (MD) for Material BOM object, the business must perform this activity in the source system. The newly created object will then be captured and migrated as part of the standard migration process.

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

Pre-Cutover

Configuration

Conversion Objects

Error Handling

Post-Load Validation

Project Team

Completeness

Accuracy

Business

Completeness

Accuracy

Key Assumptions

• Master Data Standard (MDS) is up to date as of the date of documenting this conversion approach and Master Inspection Characteristic data load.

• Data cleansing activities have been completed to ensure only active, valid, and relevant Master Inspection Characteristics are migrated. Characteristics marked for deletion or obsolete records are excluded.

• Required configuration elements such as Catalogs, Selected Sets, Code Groups, Control Indicators, and Authorization Groups are already in place in the target S/4HANA system prior to migration.

• All Units of Measure (UoM) used in quantitative characteristics are harmonized between source and target systems to ensure data consistency during migration.

• Plant master data and organizational mapping are completed prior to Master Inspection Characteristic load to ensure proper assignment.

• Number ranges for characteristic identifiers are preconfigured in S/4HANA and internal numbering will be applied during migration unless otherwise specified.

• Only fields required for QM inspection processing, quality planning, and execution are in scope for migration. Legacy-specific or unused fields will not be migrated.

• Enrichment activities (such as missing control indicators, invalid UoM, or obsolete characteristics) are handled outside of the automated migration process and may require business sign-off.

• Dependencies such as catalog entries, selected sets, and reference data are assumed to be loaded and validated prior to characteristic migration.

• Any exceptions to these assumptions (e.g., manual updates to control indicators or special characteristic types) will be managed through a formal exception process.

See also

CNV-2009 Material Master QM view

CNV-1064 QM Sampling Procedure

CNV-1043 QM Inspection Methods

CNV-1041 QM Inspection Plan

CNV-1047 Batch Characteristics of Class Type: 023

Change log

Workflow history