| Status | Pending Stakeholder Review |
| Owner | |
| Stakeholders |
Purpose
This document outlines the Syensqo-wide approach to data migration and readiness to move to SAP S/4HANA. It establishes a strategic and operational framework to ensure data is clean, reliable, structured and available at go-live.
The objectives are:
To plan, govern and control data migration activities from legacy systems to the SAP S/4HANA platform.
To define scope, dependencies, roles, risks and timelines aligned with cutover planning.
To ensure business engagement and ownership in all data quality and validation activities.
To meet global regulatory, operational and integration requirements with third-party systems.
To institutionalize data quality and governance practices that extend beyond go-live.
Background
The migration to SAP S/4HANA is a core enabler of business transformation and digital integration across Syensqo operations. Accurate and high-quality data is critical for the success of this initiative as it directly impacts core business processes, user adoption, reporting accuracy and legal compliance.
This data approach takes into consideration the need to:
Harmonize disparate legacy system data models into a unified global standard.
Ensure operational continuity during cutover by preloading critical data and validating business readiness.
Enable phased go-lives while managing cross-system data dependencies.
Use repeatable and scalable tools and methods that support global harmonization efforts.
Key steps include:
Inventory and classification of all data objects
Definition of transformation rules and mappings
Execution of data profiling, cleansing and enrichment
Mock load cycles for reconciliation and process testing
Final cutover execution with validation and audit trails
Data Migration Scope
The scope of data migration for this global ERP transformation encompasses all essential master data, open transactional data and selected historical records required to ensure business continuity, legal compliance and readiness at the point of cutover. Data will be migrated from multiple SAP ECC source systems, legacy third-party applications and local tools into a harmonized SAP S/4HANA environment.
Data Sources
Data Targets
Data Dependencies
The data dependencies diagram will be used to ensure Syensqo's data migration timeline remains achievable, dependent object loads may begin once the corresponding predecessor objects have been technically loaded with 100% success and have passed initial data verification. This approach supports timely execution across all load waves and has been designed to balance efficiency with data integrity.
Link - Data Dependencies Diagram
Data Migration Process
Data Extraction
Data extraction from Syensqo legacy systems is performed using Syniti Migrate, a tool designed specifically to streamline and automate the end-to-end data extraction process. This tool has been selected to align with Syensqo’s objective of reducing manual effort, increasing traceability, and accelerating migration readiness.
The adoption of Syniti Migrate offers the following advantages:
Minimizes dependency on legacy system owners by automating data pulls, reducing manual handovers and time-intensive coordination.
Enables both full and delta extractions, supporting iterative load cycles and ensuring data accuracy across multiple mock migrations.
Supports scheduled or on-demand extraction, allowing flexibility to align with validation cycles, mock cutovers and business availability.
Requires minimal to no custom development within the legacy systems, preserving system stability and reducing the risk of disruptions during the extraction phase.
This tool-driven approach has been integral in maintaining data integrity, auditability and repeatability across Syensqo’s global migration waves.
Data Transformation
Data Load
Special Requirements
Team and Deliverables
Functional Team
Deliverables
Roles
Data Team
Deliverables
Roles
Business Team
Deliverables
Roles
Third Party Vendor
Deliverables
Roles
Assumptions
Data Migration Risks & Issues
| Risk/Issue | Mitigation Action |
|---|---|
Data Validation Process
Pre-Load Validation
Post-Load Validation
Data Privacy
Change log
Workflow history
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