Purpose

The purpose of this document is to define the conversion approach to create Materials - Sales view with sales long text 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 Master Sales View including the sales long text from Legacy Source Systems into S/4 HANA following the Material Sales View Master Data Design Standard. 

From the current system landscape, Material Master data exists separately in the legacy systems (WP2 and PF2), with potential discrepancies in both organizations. Harmonization and validation are required to ensure accurate and consolidated data in S/4HANA. While WP2 and PF2 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. Material without sales view block: X-distr.chain status OR DChain-spec. status are blank or 63 (Available for Sale) AND Material has sales transactions within the sales organizations in scope for the last 5 years, e.g. sales order, delivery or billing.
2. Or Material without sales view block: X-distr.chain status OR DChain-spec. status are blank or 63 (Available for Sale) AND Material does not have sales transactions within the sales organizations in scope for the last 5 years, e.g. sales order, delivery or billing AND Material has stock within the sales organization in scope. 

The data from legacy system excludes:

1. Material with sales view block: X-distr.chain status OR DChain-spec. status are not blank or not 63 (Available for Sale) 

List of source systems and approximate number of records

*MVKE Sales Organization X 3 Distribution Channel

Additional Information

Multi-language Requirement

Not Applicable

Document Management

Not Applicable

Legal Requirement

As per US Department of Defence (DOD) a Cybersecurity Maturity Model Certification/ CMMC 2.0 is a mandatory certification for all contractors handling Controlled Unclassified Information (CUI) and Federal Contract Information (FCI). CUI includes sensitive technical data (e.g., design specs, system info) related to U.S. military and space applications. The Composites Business handles CUI and is therefore within CMMC scope. Without certification, the business risks disqualification from existing and future DoD programs.
It is mandatory to implement CMMC-compliant systems and processes to for all the organizations that are dealing with CUI.

Therefore, there will be one SAP instance specifically for CUI related entities. The migration for CUI related entities will be covered by US based data consultant using separate tools.

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.

Materials - Sales View with Sales Long Text

A. Different SAP Instance Migration Approach

Due to compliance requirement, there will be one SAP instance for Rest of the World (ROW), one for China and one for CUI.

1. For entities in China, the data will be loaded into SAP China instance while the entire migration process will remain the same as rest of the world.
2. For entities which will reside in CUI, the migration will be handled by US based data consultant. 

Please refer to the link for the entity mapping for each instance. In case the data object is applicable for multiples instances, what business rule to follow?

 - To identify the record is for SAP ROW Instance, it will use below logic. 

1. The Material has sales organization data in below entities. 
2. If the Material is used in both ROW entities and others, then the Sales View data needs to be created in both SAP ROW and others instances.

- To identify the record is for SAP China Instance, it will use below logic. 

1. The Material has sales organization data in below entities. 
2. If the Material is used in both China entities and others, then the Sales View data needs to be created in both SAP China and other instances.

 - To identify the record is for SAP CUI Instance, it will use below logic. 

1. The Material has sales organization data in below entities. 
2. If the Material is used in both CUI entities and others, then the Sales View data needs to be created in both SAP CUI and other instances.

Target Design

Materials - Sales View with Sales Long Text Data strictly adheres to the Master Data Standard. The complete information of the key fields that hold the Materials - Sales View with Sales Long Text information follows the Master Data Standard document.

The technical design of the target for this conversion approach.

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.

Conversion Process

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

Summarize High-Level Process. Include diagrams, where applicable. Include information supporting details of Extract, Transform and Load specific to the Data Object

Data Privacy and Sensitivity

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

Selection Screen

Data Collection Template (DCT)

Materials - Sales view with sales long text DCT Rules

Extraction Dependencies

List the steps that need to occur before extraction can commence

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

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

The Materials – Sales views with sales long text will be loaded in the pre-cutover period.

Before loading, it will have dependency on the configuration and 2019 - Materials-Basic View(required Material Types-ROH/FERT/HALB/SRV/DIEN/ZDIE/Packaging/Spares). The configuration needs to be transported into the respective system first, including the manual configuration such as the number range set up. And 2019 Materials-Basic View(required Material Types-ROH/FERT/HALB/SRV/DIEN/ZDIE/Packaging/Spares) have to be uploaded into the respective system first.

Configuration

List the Configurations required before loading can commence

Conversion Objects

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

Post-Load Validation

Project Team

Completeness

Accuracy

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

Accuracy

Key Assumptions

• Master Data Standard is up to date as on the date of documenting this conversion approach and data load.
• Materials - Sales Views with sales long text 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

Workflow history