Status
Owner	SUSANTO-ext, William
Stakeholders	GERVAIS, Pascal

Purpose

The purpose of this document is to define the conversion approach to create 1041 Inspection Plan Conversion Specification Document in S/4 HANA.

Inspection Plans are a core component of SAP Quality Management (QM) that define how materials are inspected, including inspection characteristics, sampling procedures, and inspection methods. An inspection plan contains detailed steps for quality checks and ensures that inspections are carried out in a standardized, repeatable, and compliant manner for specific materials, plants, and usage scenarios.

In SAP S/4HANA, the structure and usage of inspection plans remain largely consistent with SAP ECC, typically organized by key combinations such as material/plant, material group/plant, or multiple materials assigned to the same inspection plan via task lists. Inspection plans may also be linked to specific usage types (e.g., goods receipt, in-process inspection, final inspection) and can be maintained with reference to alternative groupings for flexibility.

In SAP ECC, aside from the standard structures, there may be inspection plans with additional variants such as multiple alternative plans for the same material/plant combination, inspection plans assigned to multiple task list groups, or plans that use reference materials. In some legacy systems, plans may also include non-standard fields or custom enhancements (pending MDS review) that will require evaluation before conversion.

This conversion aims to migrate active and relevant inspection plan master data, including associated operations, inspection characteristics, sampling procedures, and inspection methods, from existing ECC systems into S/4HANA. The migration will apply 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_INSPECTIONPLAN_CREATE), IDOCs, or direct table loads where applicable, ensuring data consistency and compliance with S/4HANA requirements

Conversion Scope

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

From the current system landscape, Inspection Plan 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:

1. Data not older than 3 years of usage
2. Data  not flagged for deletion
3. Data that has material / plant relationship and material is active
4. Data is relevant for migration according with the Material/Plant mapping match with MARC table (ToBe)

The data from legacy system excludes:

1. Data older than 3 years
2. Data flagged for deletion
3. Data that has material / plant relationship and material is not active or falged for deletion
4. Data that is not material / plant relevant according to the latest MARC table definition

List of source systems and approximate number of records

Source	Scope	Source Approx No. of Records	Target System	Target Approx No. of Records
PF2/WP2	Inspection Plan will be extracted from PF2 and WP2	PF2 = 8129 records WP2 = 37451 records	S/4 HANA	13209 records
DCT	Material with Plant and Inspection type combination which do not have data existing from PF2 and WP2	TBD	S/4 HANA	TBD

Additional Information

Multi-language Requirement

Not applicable

Document Management

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

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)

Table	Field	Data Element	Field Description	Data Type	Length	Requirement
PLKO	PLNTY	PLNTY	Task List Type (Q = Inspection Plan)	CHAR	1	Mandatory
PLKO	PLNNR	PLNNR	Task List Group	CHAR	8	Mandatory
PLKO	PLNAL	PLNAL	Group Counter (alternative)	CHAR	2	Mandatory
PLKO	WERKS	WERKS_D	Plant	CHAR	4	Mandatory
PLKO	DATUV	DATUV	Valid-From Date	DATS	8	Mandatory
PLKO	VERWE	VERWE	Task List Usage (e.g., 1/5/9 – confirm in T416)	CHAR	3	Mandatory
PLKO	STATU	STATU	Task List Status (e.g., Released)	CHAR	1	Mandatory for load (set to released if required)
PLKO	KTEXT	KTEXT	Header Description	CHAR	40	Recommended
PLKO	LOEKZ	LOEKZ	Deletion Indicator	CHAR	1	Optional (leave blank for active)
PLKO	KLART	KLART	Class Type (if classification used)	CHAR	3	Optional
PLKO	KZKUP	KZKUP	Reference Indicator (Header)	CHAR	1	Optional
PLPO	PLNKN	PLNKN	Node Number (internal op ID)	NUMC	8	Mandatory
PLPO	VORNR	VORNR	Operation Number (sequence)	CHAR	4	Mandatory
PLPO	LTXA1	LTXA1	Operation Short Text	CHAR	40	Mandatory
PLPO	STEUS	STEUS	Control Key	CHAR	4	Mandatory (drives QM/confirmation behavior)
PLPO	ARBID	ARBID	Work Center (internal ID)	NUMC	8	Mandatory (or map via ARBPL/CRHD)
PLPO	WERKS	WERKS_D	Plant (Work Center Plant)	CHAR	4	Mandatory
PLPO	BMSCH	BMSCH	Base Quantity (for std values)	QUAN	13	Recommended
PLPO	VGW01	VGWRT	Standard Value 1 (e.g., Setup/Inspect time)	DEC	7	Optional
PLPO	VGE01	VGWTS	Unit for Standard Value 1	UNIT	3	Optional
PLPO	VGW02	VGWRT	Standard Value 2	DEC	7	Optional
PLPO	VGE02	VGWTS	Unit for Standard Value 2	UNIT	3	Optional
PLPO	KAPAZ	KAPAZ	Capacity Category (if used)	CHAR	3	Optional
PLPO	ARBPL	ARBPL	Work Center (external key, if you load views)	CHAR	8	Optional (derived from ARBID)
PLPO	LOEKZ	LOEKZ	Deletion Indicator (Operation)	CHAR	1	Optional
PLMK	MERKNR	MERKNR	Characteristic Number (in plan)	NUMC	4	Mandatory
PLMK	KURZTEXT	KURZTEXT	Char. Short Text	CHAR	40	Mandatory
PLMK	VORGLFNR	VORGLFNR	Op Link (operation sequence number)	NUMC	4	Mandatory (links to PLPO)
PLMK	KZREF	KZREF	Reference to Master Insp. Char. (MIC)	CHAR	1	Mandatory if using MIC
PLMK	VERWMERKM	VERWMERKM	MIC Name (Referenced Char.)	CHAR	18	Mandatory if using MIC
PLMK	VERSION	VERSION	MIC Version	NUMC	2	Mandatory if using MIC versioning
PLMK	PRUEFUMF	PRUEFUMF	Inspection Scope / Sample Procedure Link	CHAR	4	Optional (if using sampling procedures)
PLMK	STICHPRVER	STICHPRVER	Sampling Procedure	CHAR	8	Optional
PLMK	KATALGART	KATALGART	Catalog Type (for qualitative)	CHAR	3	Optional/Required for qualitative
PLMK	CODEGRP	CODEGRP	Code Group (qualitative)	CHAR	8	Optional/Required for qualitative
PLMK	AUSWMENGE	AUSWMENGE	Selected Set (qualitative)	CHAR	8	Optional
PLMK	PRUEFME	MSEHI	Unit of Measure (quantitative)	UNIT	3	Required for quantitative
PLMK	TOLKZ	TOLKZ	Tolerance Indicator	CHAR	1	Optional (quantitative)
PLMK	MWERTS	MWERTS	Target Value	DEC	15	Optional (quantitative)
PLMK	MWERTU	MWERTU	Lower Spec Limit	DEC	15	Optional/Required per spec rule
PLMK	MWERTO	MWERTO	Upper Spec Limit	DEC	15	Optional/Required per spec rule
PLMK	PRFGEB	PRFGEB	Inspection Method Assignment	CHAR	12	Optional
PLMK	PRFGVER	PRFGVER	Inspection Method Version	NUMC	2	Optional
PLMK	ANZST	ANZST	No. of Single Values / Samples	NUMC	3	Optional
PLMK	LOEKZ	LOEKZ	Deletion Indicator (Characteristic)	CHAR	1	Optional
MAPL	MATNR	MATNR	Material	CHAR	40	Mandatory (if plan is material-assigned)
MAPL	WERKS	WERKS_D	Plant	CHAR	4	Mandatory
MAPL	PLNTY	PLNTY	Task List Type	CHAR	1	Mandatory
MAPL	PLNNR	PLNNR	Task List Group	CHAR	8	Mandatory
MAPL	PLNAL	PLNAL	Group Counter	CHAR	2	Mandatory
MAPL	DATUV	DATUV	Valid-From Date	DATS	8	Mandatory
MAPL	LOEKZ	LOEKZ	Deletion Indicator	CHAR	1	Optional

Data Cleansing

ID	Criticality	Error Message/Report Description	Rule	Output	Source System
2009-001	C1	Invalid or inactive Material Assignment in Inspection Plan	Inspection plan (MAPL) is assigned to a material/plant that does not exist or is inactive in Material Master (MARA/MARC).	Material Master	PF2/WP2
1006-001	C1	Invalid or inactive Work Center linked to Operation	Operation (PLPO) assigned to a Work Center (CRHD) that does not exist or is flagged for deletion.	Work Center	PF2/WP2
1041-001	C1	Inspection Plan not released	Header (PLKO-STATU) not set to “Released” (status = 4). Only released plans are migrated.	Inspection Plan Header	PF2/WP2
1041-002	C1	Invalid Usage assignment	Inspection plan header (PLKO-VERWE) has an invalid or non-configured Task List Usage.	Usage	PF2/WP2
1041-003	C1	Missing or invalid Group Counter	Inspection plan (PLKO-PLNAL) is blank, duplicated, or inconsistent with group.	Plan Counter	PF2/WP2
1057-001	C1	Invalid Inspection Characteristic	Plan characteristic (PLMK) references a Master Inspection Characteristic (QPMK) that does not exist, is inactive, or marked for deletion.	Master Insp. Characteristic	PF2/WP2
1057-002	C1	Inconsistent Quantitative/Qualitative Settings	Plan characteristic (PLMK-QUALI) is inconsistent with assigned MIC type (quantitative/qualitative).	Characteristic	PF2/WP2
1064-001	C1	Missing Sampling Procedure	Plan characteristic (PLMK-STICHPRVER) references a Sampling Procedure (QDSV) that does not exist or is obsolete.	Sampling Procedure	PF2/WP2
1043-001	C1	Missing or Invalid Inspection Method	Plan characteristic (PLMK-PRFGEB) references an Inspection Method (QMTB) that does not exist, is obsolete, or not valid for plant.	Inspection Method	PF2/WP2
1057-003	C1	Duplicate Inspection Characteristics	Inspection plan contains duplicate operation/characteristic entries (same VORNR + MERKNR).	Inspection Plan Operations/Characteristics	PF2/WP2
1041-004	C1	Invalid Validity Date	Valid-From date (PLKO-DATUV) is in the future or overlaps inconsistently with other plans for same material/usage.	Inspection Plan Header	PF2/WP2
1041-005	C1	Obsolete Inspection Plan	Header marked with deletion flag (PLKO-LOEKZ = X). Exclude from migration.	Inspection Plan Header	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 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

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

If applicable, this section will give the details on any selection screen parameters, including the parameter type, that are required to be entered to ensure consistent data extracts.

Selection Ref Screen	Parameter Name	Selection Type	Requirement	Value to be entered/set
Not applicable

Data Collection Template (DCT)

Target Ready Data Collection Template will be created for Data Object data with exception of some fields which require transformation as mentioned in the transformation rule.

<Object> DCT Rules

Field Name	Field Description	Rule
		Pending MDS and number of data in source system

Extraction Dependencies

List the steps that need to occur before extraction can commence

Item #	Step Description	Team Responsible
1	Source System Availability Ensure that the source database or application is accessible. Confirm that necessary credentials and permissions are granted	Syensqo IT
2	Data Structure Identify relationships between tables, views, and stored procedures.	Syniti
3	Referential Integrity Ensure dependent records are extracted together.	Syniti
4	Extraction Methodology Define whether extraction is full, incremental, or delta-based. Establish batch processing schedules for large datasets.	Syniti
5	Performance and Scalability Considerations Optimize extraction queries to prevent system overload. Ensure network bandwidth supports data transfer volumes.	Syniti
6	Security and Compliance Adhere to regulatory standards for sensitive information if applicable	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 Syniti Migrate 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 Syniti Migrate
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

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

Transformation Mapping

Use the exact name and reference this section in the “Transformation rules” above

Mapping Table Name	Mapping Table Description

Transformation Dependencies

List the steps that need to occur before transformation can commence

Item #	Step Description	Team Responsible

Pre-Load Validation

Project Team

The following pre-load validations will be performed by the Project Team.

Completeness

Task	Action
Compare Data Counts	Verify row counts between source and target databases. Identify missing or duplicated records.
Validate the mandatory fields	Validate there is value for all the mandatory fields
Validate Primary Keys and Unique Constraints	Check for duplicate or missing primary key values. Ensure unique constraints are maintained.
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	Compare field values across systems Validate data formats and structures

Business

The following pre-load validations will be performed by the business.

Completeness

Task	Action
Compare Data Count	Verify row counts between source and target databases. Identify missing or duplicated records.
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:

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

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 Material Listing and Exclusions 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

List the Configurations required before loading can commence

Item #	Configuration Item

Conversion Objects

Object #	Preceding Object Conversion Approach
	list the exact title of the conversion object of only the immediate predecessor – this will then confirm the DDD (Data Dependency Diagram)

Error Handling

The table below depicts some possible system errors for this data object during data load. All data load error is to be logged as defect and managed within the Defect Management

Error Type	Error Description	Action Taken
Configuration / Data Transformation	The value XXX for field XXX doesn't exist	Check the mapping/ conversion is done properly in the loading file Validate the target value is configured/ transported in the target system Reach out to function team to validate the configuration
Configuration	There is mandatory field XXX missing	Validate MDS if the fields are set as mandatory Validate if there is value in the pre-loading file Validate if the configuration for the mandatory fields are done properly

Post-Load Validation

Project Team

The following post-load validations will be performed by the Project Team.

Completeness

Task	Action
Validate Record count in the backend	Validate all tables with prefix “KOTG” has the same records as the loading file
Display Records	Pick up a few random Material Listing or Material Exclusions, and run t-code: VB03 to validate the Material Listing and Exclusions can be displayed without any error.
Perform Source-to-Target Comparisons	Validate that migrated data matches source records. Check for discrepancies in numerical values, text fields, and timestamps

Accuracy

Task	Action
Execute Sample Queries and Reports	Run queries to validate business logic. Generate reports to compare expected vs. actual results
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	Validate that migrated data matches source records. Check for discrepancies in numerical values, text fields, and timestamps
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 Plan is in scope based on data design and any exception requested by business.

Any additional key assumptions.

See also

Insert links and references to other documents which are relevant when trying to understand this decision and its implications. Other decisions are often impacted, so it's good to list them here with links. Attachments are also possible but dangerous as they are static documents and not updated by their authors.

Change log

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