| Status | Revision in Progress |
|---|---|
| Owner | |
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.
This Conversion Specification does not include the WPX system (CUI Objects).
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:
Active Inspection Methods used within the last four (4) years in inspection plans or master inspection characteristics or Master recipe.
Inspection Methods without deletion flag.
- Consider inspection methods only with being created & released status for migration(LOEKZ = 1, 2)
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).
Inspection Methods referenced in active MICs or inspection plans.
The data from legacy system excludes:
Inactive Inspection Methods not used in more than four (4) years.
Inspection Methods marked for deletion.
- Inspection methods other than released , being created status.
Inspection Methods belonging to deleted plants (per To-Be Plant mapping).
Obsolete or duplicate Inspection Methods that are no longer relevant
Relevancy rule
- Active Inspection Methods used within the last four (4) years in inspection plans or master inspection characteristics or Master recipe.
Derive the last 4 years of Inspection plans or MICs from rules provided in respective CS, after that follow the below logics to get the list of Inspection methods.
(PLMK-QMTB_WERKS = QMTB-WERKS AND PLMK-PMETHOD = QMTB-PMTNR AND PLMK-PLNTY IN ('Q', '2') )
OR
(QPMZ-WERKPM = QMTB-WERKS AND QMPZ-PMETHOD = QMTB-PMTNR)
2. Inspection Methods without deletion flag. QMTB-LOEKZ <> '4'(Deletion flag)
3. Consider inspection methods only with released or being created status for migration. QMTB-LOEKZ = '2'(Released) or QMTB-LOEKZ '1'(Being created)
| Source | Scope | Source Approx No. of Records | Target System | Target Approx No. of Records |
|---|---|---|---|---|
| PF2/WP2 | Inspection Methods will be extracted from PF2 and WP2 | PF2 = 153 WP2 = 479 | S/4 HANA | 632 records |
Additional Information
Multi-language Requirement
Inspection Method description will be maintained in English by default.
Since multi-language support is available for Inspection Method, 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 Inspection Method.
Document Management
Migration required if documents are identified. The conversion scope is limited to the migration of Inspection Method object. No 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.
| Table | Field | Data Element | Field Description | Data Type | Length | Requirement |
| QMTB | WERKS | Q_METH_PLANT | For inspection methods this plant is the planning plant, in which the inspection method was created in QM. | CHAR | 4 | R |
| QMTB | PMTNR | QPMETHODE | Name that uniquely identifies an inspection method within a plant. An inspection method describes how to inspect an inspection characteristic. We can assign an inspection method to a master inspection characteristic or directly to an inspection characteristic in an inspection plan. | CHAR | 8 | R |
| QMTB | VERSION | QVERSNRPM | Version Number for inspection Method | CHAR | 6 | S |
| QMTB | GUELTIGAB | DATUV | Specifies the start date for the validity period of the Inspection Method | DATS | 8 | R |
| QMTB | LOEKZ | QLOESCHKZ | Indicates the processing status of the master record; for example, created, released, blocked, marked for deletion. | CHAR | 1 | C |
| QMTB | SORTFELD | QSORTFELD | This field uses the search help to make it easier to find master data records. | CHAR | 40 | C |
| DRAD | DOKAR | DOKAR | Part of the document key, which categorizes documents according to their distinguishing features and the organizational procedures which result from them. | CHAR | 3 | C |
| DRAD | DOKTL | DOKTL | Section of a document which is maintained as an independent document. Design departments, for example, can use document parts to divide up large documents such as design drawings into pages. | CHAR | 3 | C |
| DRAD | DOKVR | DOKVR | Number which identifies the version of a document. | CHAR | 2 | C |
| DRAD | DOKNR | DOKNR | Document Number | CHAR | 25 | C |
| QMTB | DUMMY10 | This field is used to store information only. The system does not use the contents of this field. Its only purpose is to provide a place to store information that is relevant to an object, such as an inspection method or a master inspection characteristic. | CHAR | 10 | C | |
| QMTB | DUMMY20 | This field is used to store information only. The system does not use the contents of this field. Its only purpose is to provide a place to store information that is relevant to an object, such as an inspection method or a master inspection characteristic. | CHAR | 20 | C | |
| QMTB | DUMMY40 | This field is used to store information only. The system does not use the contents of this field. Its only purpose is to provide a place to store information that is relevant to an object, such as an inspection method or a master inspection characteristic. | CHAR | 40 | C | |
| QMTT | WERKS | Q_METH_PLANT | For inspection methods this plant is the planning plant, in which the inspection method was created in QM. | CHAR | 4 | R |
| QMTT | PMTNR | QPMETHODE | Name that uniquely identifies an inspection method within a plant. An inspection method describes how to inspect an inspection characteristic. We can assign an inspection method to a master inspection characteristic or directly to an inspection characteristic in an inspection plan. | CHAR | 8 | R |
| QMTT | VERSION | QVERSNRPM_TXT | Version Number for inspection Method | CHAR | 6 | S |
| QMTT | SPRACHE | SPRAS | The language key for the inspection method text. | CHAR | 1 | R |
| QMTT | KURZTEXT | QKURZTEXT | Text up to 40 characters in length that describes the Inspection Method | CHAR | 40 | C |
Data Cleansing
| ID | Criticality | Error Message/Report Description | Rule | Output | Source System |
| 1043_001 | C1 | Method not released or obsolete | Method record is flagged for deletion (QMTB-LOEKZ) or has status that is not active. Only active methods should be migrated. | Inspection Method | PF2/WP2 |
| 1043_002 | C1 | Invalid Validity Date | Valid-from date (QMTB-GUELTIGAB) is in the future. | Validity Dates | PF2/WP2 |
| 1043_003 | C1 | Missing Short Text | Method description (QMTT-KURZTEXT) is missing | Method Text | PF2/WP2 |
| 1043_004 | C1 | Orphaned Method Reference | Inspection plan characteristic (PLMK) references an inspection method (QMTB) that does not exist or is inactive. | Inspection Plan Link | PF2/WP2 |
| 1043_005 | C2 | Duplicate Methods | Multiple active inspection methods exist with the same Plant + Method ID + Version combination. | Inspection Method | PF2/WP2 |
| 1043_006 | C2 | Missing Long Texts | Method flagged for long text (QMTT-LTEXTKZ) but no lont is text maintained. | Long Text | PF2/WP2 |
| 1043_007 | C2 | Invalid Inspector Qualification | Method requires inspector qualification (QMTB-PRFQL) not available in customizing (TQ11). | Qualification | PF2/WP2 |
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
Not applicableExtraction
Extract data from a source into . There are 2 possibilities:
- The data exists. connects to the source and loads the data into . There are 3 methods:
- Perform full data extraction from relevant tables in the source system(s).
- Perform extraction through the application layer.
- Only if ; cannot connect to the source, data is loaded to the repository from the provided source system extract/report.
- 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
| Req # | Requirement Description | Team Responsible |
|---|---|---|
| Extraction Scope Definition | - Identify the source systems and databases involved. - Define the data objects (tables, fields, records) to be extracted. - Establish business rules for data selection. | Syniti / LTC Data team |
| Extraction Methodology | - Specify the extraction approach (full, incremental, or delta extraction). - Determine the tools and technologies used. - Define data filtering criteria to exclude irrelevant records. | Syniti |
| Extraction Execution Plan | - Establish execution timelines and batch processing schedules. - Assign responsibilities for extraction monitoring. - Document dependencies on other migration tasks. | Syniti |
| Data Quality and Validation | - Define error handling mechanisms for extraction failures. | Syniti |
Selection Screen
| Selection Ref Screen | Parameter Name | Selection Type | Requirement | Value to be entered/set |
|---|---|---|---|---|
| Not applicable | ||||
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 Inspection Methods 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
| 1 | Source System Availability
| Syensqo IT |
| 2 | Data Structure
| Syniti |
| 3 | Referential Integrity
| Syniti |
| 4 | Extraction Methodology
| Syniti |
| 5 | Performance and Scalability Considerations
| Syniti |
| 6 | Security and Compliance
| Syniti |
| 7 | Data cleansing of legacy Material Master - QM View with assigned inspection type data must be completed. If standardization within the DCT begins using relevant data from PF2 and WP2 before the cleansing is finalized, it is understood that the business will take due diligence to ensure any subsequent delta cleansing is verified and aligned within the DCT. | Business |
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:
- Perform value mapping and data transformation rules.
- Legacy values are mapped to the to-be values (this could include a default value)
- Values are transformed according to the rules defined in
- 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
| Item # | Step Description | Team Responsible |
|---|---|---|
1 | Transformation Scope Definition - Identify the source and target data structures. - Define business rules for data standardization. - Establish data cleansing requirements to remove inconsistencies. | Data Team |
2 | Data Mapping and Standardization - Align source fields with target fields. - Ensure unit consistency (e.g., currency, measurement units) | Data Team |
3 | Business Rule Application - Implement data enrichment/collection if applicable - Apply conditional transformations based on predefined logic/business rules | Data Team |
4 | Transformation Execution Plan - Define batch processing schedules. - Assign responsibilities for monitoring execution. - Establish error-handling mechanisms | Syniti |
Transformation Rules
| Rule # | Source system | Source Table | Source Field | Source Description | Target System | Target Table | Target Field | Target Description | Transformation Logic |
|---|---|---|---|---|---|---|---|---|---|
| 1 | PF2/WP2 | QMTB | WERKS | Plant | S/4 HANA | QMTB | WERKS | Plant | R. Xref from Legacy to S4 SpP and P&C will use one central plant (for each of them) to store all QM Master Data, then assign them to plant/materials across the world. Composite will store QM Master Data independently plant by plant. A dedicated Plant per GBU will be created in order to maintain all the QM Master Data within it and to be used for the specific GBU when needed. |
| 2 | PF2/WP2 | QMTB | PMTNR | Inspection Method | S/4 HANA | QMTB | PMTNR | Inspection Method | R. Copy from source system |
| 3 | PF2/WP2 | QMTB | VERSION | Version | S/4 HANA | QMTB | VERSION | Version | S.Internal |
| 4 | PF2/WP2 | QMTB | GUELTIGAB | Valid-From Date | S/4 HANA | QMTB | GUELTIGAB | Valid-From Date | R.Copy from Source system. Keep the ECC start date as the S/4 effective-from date |
| 5 | PF2/WP2 | QMTB | LOEKZ | Status | S/4 HANA | QMTB | LOEKZ | Status | C. Copy from Source system. |
| 6 | PF2/WP2 | QMTB | SORTFELD | Search Field | S/4 HANA | QMTB | SORTFELD | Search Field | C. Copy from source system |
| 7 | PF2/WP2 | DRAD | DOKAR | linked Document Type | S/4 HANA | DRAD | DOKAR | linked Document Type | C. Copy from source system |
| 8 | PF2/WP2 | DRAD | DOKTL | Document Part | S/4 HANA | DRAD | DOKTL | Document Part | C. Copy from source system |
| 9 | PF2/WP2 | DRAD | DOKVR | Document Version | S/4 HANA | DRAD | DOKVR | Document Version | C. Internal |
| 10 | PF2/WPF2 | DRAD | DOKNR | Document Number | S/4 HANA | DRADD | DOKNR | Document Number | C. Copy from source system (DRAD-DOKOB=QMTBDOC) |
| 11 | PF2/WP2 | QMTB | DUMMY10 | Info field 1 | S/4 HANA | QMTB | DUMMY10 | Info field 1 | C. Copy from source system |
| 12 | PF2/WP2 | QMTB | DUMMY20 | Info field 2 | S/4 HANA | QMTB | DUMMY20 | Info field 2 | C. Copy from source system |
| 13 | PF2/WP2 | QMTB | DUMMY40 | Info field 3 | S/4 HANA | QMTB | DUMMY40 | Info field 3 | C. Copy from source system |
| 14 | PF2/WP2 | QMTT | WERKS | Plant | S/4 HANA | QMTT | WERKS | Plant | R. Xref from Legacy to S4 SpP and P&C will use one central plant (for each of them) to store all QM Master Data, then assign them to plant/materials across the world. Composite will store QM Master Data independently plant by plant. A dedicated Plant per GBU will be created in order to maintain all the QM Master Data within it and to be used for the specific GBU when needed. |
| 15 | PF2/WP2 | QMTT | PMTNR | Inspection Method | S/4 HANA | QMTT | PMTNR | Inspection Method | R. Copy from source system |
| 16 | PF2/WP2 | QMTT | VERSION | Version | S/4 HANA | QMTT | VERSION | Version | S.Internal |
| 17 | PF2/WP2 | QMTT | SPRACHE | Language | S/4 HANA | QMTT | SPRACHE | Language | R. Copy from source system |
| 18 | PF2/WP2 | QMTT | KURZTEXT | Short Text | S/4 HANA | QMTT | KURZTEXT | Short Text | C. Copy from source system |
| 19 | PF2/WP2 | STXH | TDOBJECT | Text Object | S/4HANA | STXH | TDOBJECT | Text Object | Default to"QPMETHODE" |
| 20 | PF2/WP2 | STXH | TDNAME | Text Name | S/4HANA | STXH | TDNAME | Text Name | The STXH table data will be migrated as-is from the current system to S/4HANA, with no modifications, ensuring consistency and traceability of existing records. TDNAME = MANDT+ WERKS + PMTNR + VERSION + SPRACHE(Language) |
| 21 | PF2/WP2 | STXH | TDID | Text ID | S/4HANA | STXH | TDID | Text ID | The STXH table data will be migrated as-is from the current system to S/4HANA, with no modifications, ensuring consistency and traceability of existing records. Default to 'QMTT' |
| 22 | PF2/WP2 | STXH | TDSPRAS | Language Key | S/4HANA | STXH | TDSPRAS | Language Key | The STXH table data will be migrated as-is from the current system to S/4HANA, with no modifications, ensuring consistency and traceability of existing records. |
| 23 | PF2/WP2 | STXH | TDVERSION | Version Number of Text | S/4HANA | STXH | TDVERSION | Version Number of Text | The STXH table data will be migrated as-is from the current system to S/4HANA, with no modifications, ensuring consistency and traceability of existing records. |
| 24 | PF2/WP2 | STXH | TDLOCK | Lock Indicator for Text | S/4HANA | STXH | TDLOCK | Lock Indicator for Text | The STXH table data will be migrated as-is from the current system to S/4HANA, with no modifications, ensuring consistency and traceability of existing records. |
| 25 | PF2/WP2 | STXL | CLUSTD | Text Line (Compressed) | S/4HANA | STXL | CLUSTD | Text Line (Compressed) | The STXL table data will be migrated as-is from the current system to S/4HANA, with no modifications, ensuring consistency and traceability of existing records. |
| 26 | PF2/WP2 | STXL | TDOBJECT | Text Object (Reference from STXH) | S/4HANA | STXL | TDOBJECT | Text Object | Default to"QPMETHODE" |
| 27 | PF2/WP2 | STXL | TDNAME | Text Name | S/4HANA | STXL | TDNAME | Text Name | The STXH table data will be migrated as-is from the current system to S/4HANA, with no modifications, ensuring consistency and traceability of existing records. TDNAME = MANDT+ WERKS + PMTNR + VERSION + SPRACHE(Language) |
| 28 | PF2/WP2 | STXL | TDSPO | Text Line Sequence | S/4HANA | STXL | TDID | Text ID | The STXH table data will be migrated as-is from the current system to S/4HANA, with no modifications, ensuring consistency and traceability of existing records. |
Transformation Mapping
| Mapping Table Name | Mapping Table Description |
|---|---|
| Plant | Mapping of legacy Plants to To-Be Plants in S/4HANA |
Transformation Dependencies
List the steps that need to occur before transformation can commence| Item # | Step Description | Team Responsible |
|---|---|---|
1 | Value Mappings are according to the latest design - <List of Value Mappings> | SyWay Data Team |
Pre-Load Validation
Project Team
Completeness
| Task | Action |
|---|---|
Compare Data Counts |
|
Validate the mandatory fields | Validate there is value for all the mandatory fields |
Validate Primary Keys and Unique Constraints |
|
Test Referential Integrity | Confirm dependent records exist in related tables |
Accuracy
| Task | Action |
|---|---|
Validate the transformation | Validate the fields which require transformation have the value after transformation instead of the original field value |
Check Data Consistency |
|
Business
Completeness
| Task | Action |
|---|---|
Compare Data Count |
|
| Review populated templates for missing or incorrect values | Use checklists to verify completeness and correctness before submission |
Accuracy
| Task | Action |
|---|---|
Conversion Accuracy | Business Data Owner/s to verify that all the data in the load table/file is accurate as per endorsed transformation/ mapping rules (and signed-off DCT data). |
Load
The load process includes:
- Execute the automated data load into target system using load tool or product the load file if the load must be done manually
- Once the data is loaded to the target system, it will be extracted and prepared for Post Load Data Validation
Load Run Sheet
| Item # | Step Description | Team Responsible |
|---|---|---|
1 | Load Scope Definition - Identify the target system and database structure. - Define data objects (tables, fields, records) to be loaded. - Establish business rules for data validation. | Data team |
2 | Load Methodology - Specify the loading tools and technologies (Migration Cockpit, LSMW, custom loading program). | Syniti |
3 | Data Quality and Validation - Ensure data integrity checks (null values, duplicates, format validation). - Perform pre-load validations to verify completeness. - Define error handling mechanisms for load failures | Syniti |
4 | Load Execution Plan - Establish execution timelines and batch processing schedules. - Assign responsibilities for monitoring execution. - Document dependencies on other migration tasks | Syniti |
5 | Logging and Reporting - Maintain detailed logs of loading activities. - Generate summary reports on loaded data volume and quality. - Define escalation procedures for errors | Syniti |
Load Phase and Dependencies
The Inspection Methods will be loaded in the pre-cutover (PreCutover 4 phase) period.
Before loading, it will have dependency on the following configuration and data objects in the S/4 HANA.
Configuration
| Item # | Configuration Item |
|---|---|
| 1 | MARA - General Material Data |
| 2 | MARC - Material Plant data |
| 3 | T001W - Plants/Branches |
Conversion Objects
| Object # | Preceding Object Conversion Approach |
|---|---|
| 2009 | Material Master (QM View must exist before Inspection methods) |
Error Handling
| Error Type | Error Description | Action Taken |
|---|---|---|
| 1 | Material Master (QM View) does not exist for the plant/material combination | Ensure that the Material Master with QM View is created and valid before plan migration |
Post-Load Validation
Project Team
Completeness
| Task | Action |
|---|---|
Validate Record count in the backend | Validate all tables with prefix “QMTB” has the same records as the loading file |
Display Records | Pick up a few random Inspection Methods, and run t-code: QS33 to validate the Material Listing and Exclusions can be displayed without any error. |
Perform Source-to-Target Comparisons |
|
Accuracy
| Task | Action |
|---|---|
Execute Sample Queries and Reports |
|
Conduct Post-Migration Reconciliation | Generate reports comparing pre- and post-migration data. |
Business
Post-load validation is a critical step in data migration, ensuring that transferred data is accurate, complete, and functional within the target system.
1. Ensuring Data Integrity
After migration, data must be consistent with its original structure. Post-load validation checks for missing records, incorrect mappings, and formatting errors to prevent discrepancies.
2. Business Continuity
Faulty data can disrupt operations, leading to financial losses and inefficiencies. Validating post-load data ensures that applications function as expected, preventing downtime.
3. Error Detection and Resolution
By validating data post-migration, businesses can detect anomalies early, reducing the cost and effort required for corrections
Completeness
| Task | Action |
|---|---|
| Perform Source-to-Target Comparisons |
|
| Conduct Post-Migration Reconciliation | Go through reports comparing pre- and post-migration data. |
Accuracy
| Task | Action |
|---|---|
Perform Manual Testing | Conduct manual spot-checks for additional assurance. |
Key Assumptions
- Master Data Standard is up to date as on the date of documenting this conversion approach and data load.
- Inspection Methods is in scope based on data design and any exception requested by business.
- Data cleansing has met the required percentage threshold for the specified mock cycle and all preparation activities have been completed.
- Data entries in DCT are target-ready data unless a specific transformation rule is stated for that field in the transformation rules.
See also
Change log
Workflow history
| Title | Last Updated By | Updated | Status | |
|---|---|---|---|---|
| There are no pages at the moment. | ||||
