Issue

Managing master data is vital from a business perspective because it ensures accuracy, enhances efficiency, supports compliance, improves customer experience, and drives financial performance. By implementing effective master data management practices, organizations can achieve reliable data, streamlined operations, and better decision-making, all of which contribute to long-term success of ERP Implementation.

As a part of ERP Rebuild program, there is an opportunity to implement a master data solution, and this document is to evaluate the options for the same.

Recommendation

Background & Context

Managing master data is critically important from a business perspective for several reasons, all of which contribute to the efficiency, effectiveness, and success of organizational operations. Here’s why effective master data management (MDM) is crucial:

• Ensures Data Accuracy and Consistency by enabling single source of truth and reducing any errors
• Enhances Operational Efficiency by enabling streamlined processes and automation
• Improves Decision-Making by providing reliable insights and a unified view of data
• Supports Regulatory Compliance by enabling audit trails and implementing data privacy and security
• Facilitates Integration and Interoperability
• Drives Financial Performance by cost reduction due to data errors, redundancies, and inefficiencies
• Mitigates Risks by reducing the likelihood of errors that can lead to financial losses, legal issues, or operational failures.
• Supports Scalability and Growth by providing the framework to scale data management practices efficiently and supporting the integration of new systems and data sources while maintaining data quality.
• Enhances Competitive Advantage by enabling strategic insights and agility to respond quickly to market changes, customer demands, and emerging opportunities.

Syensqo currently utilizes various disjointed systems for creating, maintaining, and governing master data. This fragmented approach poses significant challenges to data quality, consistency, and governance. Following are some of the key systems that are used for master data maintenance. Apart from the below, there are multiple other homegrown and 3rd party applications where some of the master data is maintained and governed. 

Note that the below list of systems and the governance process is only for a subset of master data objects and there are many master data objects where there is no central system nor governance implemented.

Assumptions

Constraints

Impacts

Business Rules

Options considered

To fulfill Syensqo’s master data governance requirements, it is proposed to divide the master data into three tiers:

Tier 1: Critical Master Data Objects
This tier includes master data objects that are essential to Syensqo’s key processes and must be managed centrally to ensure consistency and reliability. These data objects are crucial for the smooth operation of critical business functions and require strict governance and oversight. Any master data object shared across regions also falls into this tier to maintain data integrity and uniformity across all areas of the organization.

Tier 2: Important Master Data Objects
This tier encompasses master data objects that, while important to Syensqo, are not as critical as Tier 1 objects. These objects require centralized governance to ensure adherence to company-wide standards and policies, but their maintenance can be performed locally. This allows for flexibility in data management while ensuring alignment with the organization’s overall data governance framework.

Tier 3: Localized Master Data Objects
This tier consists of master data objects that are specific to individual regions, countries, or plants and are tailored to meet the unique needs of each location. These objects are not critical to the key processes of Syensqo and therefore do not require centralized governance. They will be managed and governed locally, providing flexibility and customization based on regional requirements with minimal central oversight.

Following are the Options considered for implementing a master data system

Option 1: Single / central master data governance (MDG) system for all master data objects

Option 2: Separate master data governance process and system for specific master data objects

Option A: Single / central SAP master data governance system (MDG)

As a part of this option, a single master data governance system is implemented to manage and govern all the master data objects. 

Option B: Single / Central master data governance system 

As a part of this option master data is grouped into tiers and the tool and process is dependent on each tier.

Tier 1 Master Data: 

Option C: Separate master data governance process and system for specific master data objects

Option D: 

Evaluation

	Option A	Option B	Option C	Option D
Criterion 1	Pro Con	Pro Pro	Pro Con	Pro Con
Criterion 2	Pro Con	Con	Pro Pro	Con Con
Criterion 3	Pro	Con	Con	Pro

See also

Change log

Workflow history