Status
Owner	LIU-ext, Ekawati
Stakeholders	The business stakeholders involved in making, reviewing, and endorsing this decision. Type @ to mention people by name

Purpose

The purpose of this document is to define the conversion approach to create Material Listing and Exclusions in S/4 HANA.

Summarise how the data is currently utilized and set up in the legacy system/s and how object is intended to be represented in S/4, and any other relevant information

Conversion Scope

The scope of this document covers the approach for converting active Material Listing and Exclusions from Legacy Source Systems into S/4HANA following the Material Listing and Exclusions Master Data Design Standard.

From the current system landscape, Material Master 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:

All active Material Listing; valid to date beyond S/4 Go-Live date
All active Material Exclusions; valid to date beyond S/4 Go-Live date

The data from legacy system excludes:

Inactive Material Listing; valid to date before S/4 Go-Live date or the table not active anymore.
Inactive Material Exclusions; valid to date before S/4 Go-Live date or the table not active anymore.

List of source systems and approximate number of records

Source	Scope	Source Approx No. of Records	Target System	Target Approx No. of Records
WP2	Table: KOTG001 Listing/exclusion type - Customer - Material - Valid to - Valid From	5000	S/4 HANA	5000
WP2	Table: KOTG004 Listing/exclusion type - Sales Organization - Distribution Channel - Customer - Material - Valid to - Valid From	100	S/4 HANA	100
WP2	Table: KOTG903 Listing/exclusion type - X-distr.chain status - Valid to - Valid From	50	S/4 HANA	50
WP2	Table: KOTG906 Listing/exclusion type - Sales Organization - Customer - Material - Valid to - Valid From	120,000	S/4 HANA	120,000
WP2	Table: KOTG908 Listing/exclusion type - Sales Organization - Departure country - Valid to - Valid From	50	S/4 HANA	50
WP2	Table: KOTG909 Listing/exclusion type - Material - Destination Country - Region - Valid to - Valid From	3000	S/4 HANA	3000
WP2	Table: KOTG913 Listing/exclusion type - Sales Organization - Material - Customer - Valid to - Valid From	300	S/4 HANA	300
WP2	Table: KOTG962 Listing/exclusion type - Material - Destination Country - Valid to - Valid From	150	S/4 HANA	150
WP2	Table: KOTG964 Listing/exclusion type - Sales Organization - Material - Destination Country - Valid to - Valid From	80,000	S/4 HANA	80,000
PF2	Table: KOTG501 Listing/exclusion type - Destination Country - Material Group - Valid to - Valid From	14,000	S/4 HANA	14,000
PF2	Table: KOTG521 Listing/exclusion type - Destination Country - Region - Material - Valid to - Valid From	50	S/4 HANA	50
PF2	Table: KOTG903 List/excl. - Material - Plant - Ship-To Party - Valid to - Valid From	50	S/4 HANA	50
PF2	Table: KOTG904 List/excl. - Material - Plant - Sold-To Party - Valid to - Valid From	50	S/4 HANA	50
PF2	Table: KOTG906 Sales org. - Destination Country - Valid to - Valid From	100	S/4 HANA	100

Additional Information

Multi-language Requirement

Summarize Multi-language Requirement/s, if any

Document Management

Summarize Document Management requirement, if any

Legal Requirement

Summarize Legal Requirement/s, if any

Special Requirements

Specify any special requirements or considerations that may impact the data conversion process based on specific locations, regulatory compliance or system limitations. Clearly outline any regional or localization requirements such as country-specific data formats, legal reporting obligations or industry standards that must be adhered to (e.g., localization rules for countries like China).

If the data conversion involves third-party systems or external data sources, such as Icertis, describe any additional requirements related to data mapping, transformation logic, validation rules or security measures that must be followed.

Target Design

Material Listing and Exclusions Data strictly adheres to the Master Data Standard. The complete information of the tables and key fields that hold the Material Listing and Exclusions 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
MARA	MATNR	MATNR	Material Number	CHAR	18	Mandatory

Data Cleansing

All data cleansing should take place in the data source system as defined in this document, unless system limitations prevent it.

If data cleansing is managed outside of the source system (e.g. Syniti Migrate, 3rd Party Vendor, DCT), the necessary documentation must be produced and appended to this deliverable for sign-off.

ID	Criticality	Error Message/Report Description	Rule	Output	Source System
		Set valid to date to before or after S/4 Go-Live date	Validate if the table combination is still in scope or not

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:

Extraction
The process begins with extracting metadata and raw data from source systems, such as the Syensqo ECC system (i.e., WP2/PF2) periodically. The extracted data is then staged for transformation.
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.
Loading
The transformed data is then loaded into the target S4 Hana system.

SyWay Project > CNV-2001 Material Listing and Exclusions > image-2025-6-11_17-35-12.png

Data Privacy and Sensitivity

Summarize Data Privacy and Sensitivity Requirements, if any

Extraction

Extract data from a source into Syniti Migrate. There are 2 possibilities:

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.
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
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

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

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 Listing and Exclusions 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:

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
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
MAP_VKORG	Sales Organization Mapping
MAP_VTWEG	Distribution Channel Mapping SyWay - Sales Area.pptx --> All the actual distribution channels and divisions won't exist in the to-be solution Check current Dist.Ch. and discuss with Functional team and how to do the mapping
MAP_MSTAV	Material Status - Sales Mapping MSTAV - Cross Distribution Chain is used in WQ2 Exclusions (code: 05 and 11) Check the configuration in ECC for 05 and 11 and the mapping to S/4 HANA. Discuss with the Functional team if the material master for these 2 codes will be migrated to S/4?
MAP_WERKS	Plant Mapping WERKS - Plant Share the same mapping table with S2P. To check with Jasleen Madhok, John Hancock, Angelo Buosi
MAP_MATKL	Material Group Mapping
MAP_ALAND	Country Mapping
MAP_MATNR	Material Mapping
MAP_REGIO	Region Mapping
MAP_KUNNR	Customer Mapping Covers mapping for ALL customers, incl.: KUNAG Sold-to KUNWE Ship-to
MAP_KSCHL	Listing/exclusion type

Transformation Dependencies

List the steps that need to occur before transformation can commence

Item #	Step Description	Team Responsible
1	Source Data Integrity - Ensure extracted data is complete, accurate, and consistent. - Validate that data types and formats align with transformation requirements.	Syniti
2	Referential Integrity - Ensure dependent records are transformed together or in advance	Syniti
3	Transformation Logic and Mapping - Define data mapping rules between source and target schemas.	Data Team
4	Performance and Scalability Considerations - Optimize transformation processes for large datasets. - Ensure system resources can handle transformation workloads	Syniti
5	Logging and Error Handling - Maintain detailed logs of transformation activities. - Define error-handling procedures for failed transformations	Syniti

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
Verify Record Count	Business Data Owner/s to verify that the total number of relevant records from the DCT is equal to the total number of records in the Preload and Load Sheets.

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

Identify the phase as to “when” the load for this object will occur. <Pre-Cutover, Cutover, Post Cutover> and list the steps that need to occur before the load can commence

The Material Listing and Exclusions will be loaded in the pre-cutover 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
1	Listing/ Exclusion Table
2	Listing/ Exclusion Access Sequence
3	Listing/ Exclusion Type
4	Listing/ Exclusion Procedure
5	Country Code (Departure and Destination Country)
6	Region
7	Material Group
8	Sales Organization
9	Distribution Channel
10	Plant
11	Cross-Distribution-Chain Material Status (X-distr.chain status)

Conversion Objects

Object #	Preceding Object Conversion Approach
3003	Business Partners - Customer (Sales and Service) - FLCU01
2003	Materials - Sales view with sales long text

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
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
title	specific details of what and how the task needs to be performed e.g. which reports are being used etc.

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.
Material Listing and Exclusions is in scope based on data design and any exception requested by business.

Any additional key assumptions.

Purpose

Conversion Scope

Additional Information

Multi-language Requirement

Document Management

Legal Requirement

Special Requirements

Target Design

Data Cleansing

Conversion Process

Data Privacy and Sensitivity

Extraction

Extraction Run Sheet

Selection Screen

Data Collection Template (DCT)

Extraction Dependencies

Transformation

Transformation Run Sheet

Transformation Mapping

Transformation Dependencies

Pre-Load Validation

Project Team

Completeness

Accuracy

Business

Completeness

Accuracy

Load

Load Run Sheet

Configuration

Conversion Objects

Error Handling

Post-Load Validation

Project Team

Completeness

Accuracy

Business

Completeness

Accuracy

Key Assumptions

See also

Change log

Workflow history