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Status

  Revision in Progress

Owner
Stakeholders

Purpose

The purpose of this document is to define the conversion approach to create Batches with Classification Data in S/4 HANA.

Batches are used extensively used in Syensqo Legacy System and used for below purposes.: 

Quality Control

  • Each batch can be tested and its quality attributes recorded. SAP enables linking quality results to specific batches, ensuring only compliant products are shipped.

Inventory Management

  • Batches help manage inventory by expiration date, production date, or quality status.
  • Enables First-Expired-First-Out (FEFO) or First-In-First-Out (FIFO) inventory strategies.

Production Efficiency

  • Batches allow for detailed production planning and tracking.


Conversion Scope

The scope of this document covers the approach for converting active Batches & Classification Data from Legacy Source Systems into S/4HANA following the 
Master Data Design Standard.


The data from legacy system includes:

  1. Batches in Stock

The data from legacy system excludes:


List of source systems and approximate number of records
SourceScope

Source Approx No. of Records

Target SystemTarget Approx

No. of Records

PF2Batches in Stock


WP2Batches in Stock












Additional Information

Multi-language Requirement

NA

Document Management

NA

Legal Requirement

NA

Special Requirements

NA

NA




Target Design

The technical design of the target for this conversion approach.

TableFieldData ElementField DescriptionData TypeLengthRequirement
MCHAHSDATHSDATDate of Manufacture of the batch
MCHAVFDATVFDATShelf Life Expiration Date of the batch


MCHAVERABVERABBatch available from date


MARAIPRKZIPRKZPeriod indicator


MCHAZUSCHZUSCHUnrestricted or Restricted


MCHAZAEDTZAEDTDate of last status change


MCHAQNDATQNDATDate of next inspection


MCH1LVORMLVORMDeletion flag at client level


MCHALVORMLVORMDeltion flag at plant level


MCHAZFDATZFDATDate of certification


MCHALIFNRLIFNRSupplier number


MCHALICHALICHASupplier batch


MCHALWEDTLWEDTDate of last goods receipt


MCHAHERKLHERKLBatch country of origin


MCHAHERKRHERKRRegion of origin


MCHAMTVERMTVERGrouping of materials with similar instrastat requriements


MCHAFVDT1FVDT1Date for free use


MCHAFVDT2FVDT2Date for free use


MCHAFVDT3FVDT3Date for free use


MCHAFVDT4FVDT4Date for free use


MCHAFVDT5FVDT5Date for free use


MCHAFVDT6FVDT6Date for free use


AUSPATWRTATWRTValue for each characteristic of class


MARAMHDRZMHDRZCalculated remaining Shelf Life


MARAMHDHBMHDHBTotal shelf life


MARAIPRKZIPRKZPeriod indicator from material


MARARDMHDRDMHDRounding rule



Data Cleansing

IDCriticalityError Message/Report DescriptionRuleOutputSource System


























Conversion Process

The high-level process is represented by the diagram below:


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

Req #Requirement DescriptionTeam Responsible













Selection Screen

Selection Ref ScreenParameter NameSelection TypeRequirementValue to be entered/set





















Data Collection Template (DCT)

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

DCT Rules

Field NameField DescriptionRule












Extraction Dependencies

Item #Step DescriptionTeam Responsible













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

Item #Step DescriptionTeam Responsible













Transformation Rules

Rule #Source systemSource TableSource FieldSource DescriptionTarget SystemTarget TableTarget FieldTarget DescriptionTransformation Logic









































Transformation Mapping

Mapping Table NameMapping Table Description








Transformation Dependencies

List the steps that need to occur before transformation can commence
Item #Step DescriptionTeam Responsible













Pre-Load Validation

Project Team

Completeness

TaskAction





Accuracy

TaskAction





Business

Completeness

TaskAction





Accuracy

TaskAction





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 DescriptionTeam Responsible













Load Phase and Dependencies

Configuration

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

Error TypeError DescriptionAction Taken










Post-Load Validation

Project Team

Completeness

TaskAction





Accuracy

TaskAction





Business

Completeness

TaskAction





Accuracy

TaskAction





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

Version Published Changed By Comment
CURRENT (v. 2) Apr 29, 2026 17:10 RAYUDU-ext, Narasimha Kumar CR0436
v. 21 Apr 29, 2026 11:26 RAYUDU-ext, Narasimha Kumar
v. 20 Dec 12, 2025 13:34 RAYUDU-ext, Narasimha Kumar
v. 19 Oct 14, 2025 14:32 RAYUDU-ext, Narasimha Kumar
v. 18 Oct 14, 2025 14:28 RAYUDU-ext, Narasimha Kumar
v. 17 Oct 14, 2025 14:05 RAYUDU-ext, Narasimha Kumar
v. 16 Oct 14, 2025 14:05 RAYUDU-ext, Narasimha Kumar Rework Syniti
v. 15 Oct 10, 2025 15:53 RAYUDU-ext, Narasimha Kumar
v. 14 Oct 10, 2025 15:43 RAYUDU-ext, Narasimha Kumar
v. 13 Oct 10, 2025 15:40 RAYUDU-ext, Narasimha Kumar

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