Purpose

The purpose of this document is to define the conversion approach to create Material Master-General Plant Data / S.Loc Data in S/4 HANA.

The General Plant Data/Storage view is one of the key views in the Material Master. It contains information about a material that is specific to a particular plant and storage location. This view is essential for plant-level operations and inventory management. Currently, in both ECC systems PF2 and WP2, materials are extended to specific plants and their respective storage locations. Source and Target structures mapping are provided below.

Conversion Scope

The scope of this document covers the approach for converting active Material Master-General Plant Data / S.Loc Data from Legacy Source Systems into S/4HANA following the DD-FUN-050 Master Data Standard - Material General Plant and Storage Data Master Data Design Standard.

As per KDD011 - Material Master Numbering Alignment All Syensqo's materials (finished, semi-finished, raw materials, spares etc.) will be represented by a unique material master number which will be assigned from a new number range

The data from legacy system includes:

1. Materials which are created from Past 3 Years
2. Materials with Maintenance Status (MARA-PSTAT = L)
3. Materials without Deletion Flag (MARC-LVORM = NO)
4. Materials with Plant Specific Status (MMSTA=NULL)

The data from legacy system excludes:

1. To Be Confirmed

Additional Information

Multi-language Requirement

As per KDD055 - Multi-Language Support there are 8 languages in scope: English, French, Italian and Mandarin and Brazilian Portuguese, German, Spanish and Thai.

Legacy text for applicable records at Plant level are in-scope for Migration to support system functionalities (If anything is getting printed on output documents then the Text would be in scope

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

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

Selection Screen

Data Collection Template (DCT)

DCT Rules

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

Configuration

Conversion Objects

Error Handling

Post-Load Validation

Project Team

Completeness

Accuracy

Business

Completeness

Accuracy

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