Purpose

The purpose of this document is to define the conversion approach to migrate Business Partners - Prospect (BUP002) in S/4 HANA.

In Salesforce, a Prospect is typically used to track potential customers who have shown interest but have not yet been qualified as quotations or sales order. They may include essential details like company information, interaction history, and engagement level.

In SAP S/4HANA, the Prospect is intended to be represented similarly. Prospects are classified as BP (Business Partners) under the Customer category, with attributes that allow future conversion into full-fledged customers. 

Conversion Scope

The scope of this document covers the approach for converting active Prospect from Legacy Source Systems into S/4HANA following the Business Partners - Prospect (BUP002) Master Data Design Standard.

The data from legacy system includes:

1. Under the Salesforce Account object, the Partner Type is Prospect and there is no deletion indicator for the account.
2. The Account Organization is SCO (Syensqo).
3. For prospect created for more than 2 years, there is usage for the prospect within the 2 years, e.g., there are visit reports, leads or sales opportunities created. 
4. For prospect created within 2 years, it is not in any blocked status
5. The prospect is for GBU within scope. 

The data from legacy system excludes:

Additional Information

Multi-language Requirement

The prospect may contain local language. Therefore, the conversion will also need to support the multi-language address.  Below languages (International versions) are supported based on KDD055 - Multiple Language Support. 

It will support 4 Core Languages (English, French, Italian and Mandarin).

Document Management

N/A.

Legal Requirement

CMMC 2.0 is a mandatory DoD cybersecurity certification for 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.

Special Requirements

Due to compliance requirement, there will be three SAP instances, one for Rest of the World (ROW), one for China and one for CUI. Prospect will be migrated into all three SAP instances.

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:

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 CRM system (i.e., iCare/CoreCRM) 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 S4 Hana system. 

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 . 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.

For SAP CUI related entities, it will be alternative extraction process and the data will be stored in approved tools.

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

Workflow history