Sullexis successfully assisted the a Major Chemicals manufacturer in addressing data quality challenges and aligning critical data across key systems, ultimately enhancing business processes and ensuring data accuracy and compliance.
A client recently acquired a large chemicals manufacturer and underwent a data migration program, integrating raw, intermediate, and finished materials data into the common systems for engineering, manufacturing, and product safety functions. However, data quality and validation activities were overlooked during migration, resulting in misaligned and incomplete data. These issues had a significant impact on essential business activities, particularly the creation of Safety Data Sheets.
The client needed assistance in understanding the current data landscape and formulating a data remediation plan to ensure the accurate and aligned representation of critical data across key systems, including Product Lifecycle Management (PLM), Bill of Materials (BOM), and Health, Safety, and Environment (HSE) systems.
Sullexis provided strategic direction and collaborated with the client to create a comprehensive data remediation plan, which included the following components:
- Business and Data Alignment Rules: Defined clean and aligned material data rules across the key systems, establishing a standardized framework for data integrity.
- Certified Material Data Methodology: Introduced a methodology to define and track the journey towards certified material data, ensuring data accuracy and reliability.
- Roles and Responsibilities: Outlined key roles and responsibilities for stakeholders involved in the certification journey, promoting accountability and efficiency.
- Organizational Change Management: Developed a plan to manage organizational change effectively, ensuring successful execution of the data cleanup initiative.
The development and implementation of the data remediation plan resulted in several benefits for the client:
- Clear Path Forward: Stakeholders gained clarity on the roadmap for cleaning up and certifying materials data, ensuring data accuracy and compliance.
- Repeatable Framework: The established framework served as a repeatable model for cleaning up materials data in other regions or business units, enhancing data consistency.
- Foundation for Sustainment: The plan provided a strong foundation for measuring the sustainability of data quality following the cleanup, promoting long-term data integrity.