| Status | Approved |
| Owner | |
| Stakeholders |
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.
| System | Use |
|---|---|
| Mappy SpP | Mappy application is used to improve commercial data accuracy |
| Material Center | MaterialCenter is a web application for materials data management. |
| SAP MDM-MDG | SAP Master Data Governance is a solution allowing to define, enforce, monitor and improve master data management in a hybrid landscape. Solvay is using it for Finished Product mgt for few businesses (it is not a global implementation). |
| Vendor Workflow | Homemade ABAP application for automating vendors creation in the ERP |
| SAP PF1 - PRS | SAP ERP PF1 - Data - Master Data module of SAP ECC |
| CRM | Application for maintaining prospects and customers |
Approach
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.
A list of all the tiers based on the current data objects is here
Assumptions
Constraints
Impacts
Business Rules
Options considered
Following are the Options considered for implementing a master data system
Option A: Single / central SAP master data governance system (MDG)
This option involves utilizing SAP Master Data Governance (MDG) as the primary system for managing master data across the organization. SAP MDG is an integrated solution within the SAP environment, designed to centralize master data management and governance, ensuring consistency, accuracy, and compliance. SAP MDG helps streamline the processes for creating, updating, and maintaining master data, providing a robust platform for data governance that aligns with SAP standards and best practices.
MDG has 2 flavours classic and cloud ready. Both of these can co-exist and doesn't need any additional licences than the MDG licenses.
Classic MDG: As part of the classic MDG the following objects are supported. Note that EAM and Retail are supported by partner extension (Utopia).
Cloud Ready MDG: This is an attempt from SAP to harmonise MDG, MDG for S/4 HANA public cloud and MDG in BTP. Supports Fiori UI and uses BTP as the workflow layer. Uses BRF+ for master data rules configuration. It is a very recent product and supports only some roles of Business partner at the moment. Material support is planned in the next release in 2025, and no roadmap confirmed beyond that.
For the sake of evaluation this option considers adopting the master data objects available as part of the cloud ready MDG and the rest via Classic MDG.
As a part of this option
| Tier | Approach | Examples |
|---|---|---|
| Tier 1 Data | Implement the master data governance in SAP MDG. For the objects that are not available custom development required | Material Master General View BOM's |
| Tier 2 Data | Governance workflows and reports custom developed in SAP MDG | Material Master QM view |
| Tier 3 Data | Governance and maintenance managed locally - System to be determined by the local team | TM - Transportation Zones |
Option B: Single / Central master data governance system
This option involves using an external, non-SAP system as the centralized master data governance solution. The chosen system could be a specialized master data management (MDM) platform or another enterprise solution that is capable of integrating with various systems across the organization. The external system would serve as the single source of truth for all master data, centralizing governance and ensuring data consistency, quality, and accessibility across multiple platforms and applications within the organization.
| Tier | Approach | Examples |
|---|---|---|
| Tier 1 Data | Implement the master data governance in a Master data management tool | Material Master General View BOM's |
| Tier 2 Data | Governance workflows and reports custom developed in SAP MDG | Material Master QM view |
| Tier 3 Data | Governance and maintenance managed locally - System to be determined by the local team | TM - Transportation Zones |
Below are some of the master data tools available in the market and a detailed analysis with tool selection will be done during detailed design.
Option C: Separate master data governance process and system for specific master data objects
This option proposes the use of separate master data governance systems tailored to specific master data objects or business needs. Instead of a single, centralized system, different master data objects would be managed by dedicated systems that are best suited to their unique requirements. Critical data objects may have their own centralized governance system, while less critical or more localized data could be managed by different systems that cater specifically to regional or departmental needs. This decentralized approach allows for greater flexibility and customization, enabling each system to be optimized for its particular data governance requirements while ensuring that the organization can effectively manage diverse data needs across various areas.
Following is the implementation approach
| Tier | Approach | Examples | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Tier 1 Data | For a master data object and the corresponding dependent objects, implement a master data governance process and tools that will best cater to that master data object |
| |||||||||
| Tier 2 Data | Governance workflows and reports custom developed in the tool chosen | Material Master QM view | |||||||||
| Tier 3 Data | Governance and maintenance managed in the tool chosen | TM - Transportation Zones |
Evaluation
Option A: Single / central SAP master data governance system (MDG) | Option B: Single / Central master data governance system | Option C: Separate master data governance process and system for specific master data objects | |
|---|---|---|---|
| Fit for Purpose |
Any other master data needs to be implemented as a custom object Tier 1 Object Support: Partial Tier 2 Object Support: Custom Tier 3: Object Support: Custom |
Tier 1 Object Support: Partial Tier 2 Object Support: Partial Tier 3: Object Support: Partial |
Tier 1 Object Support: Complete Tier 2 Object Support: Complete Tier 3: Object Support: Custom |
| Integration and Compatibility |
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| Flexibility |
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| Complexity and Maintenance |
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| Data Quality and Consistency | |||
| Implementation and Cost | |||
| Responsiveness and Agility | |||
| Scalability | |||
| Suitability for Critical vs. Non-Critical Data |
See also
Change log
Workflow history
| Title | Last Updated By | Updated | Status | |
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