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

Option C - Separate master data governance process and system for specific master data objects, which involves using separate master data governance systems tailored to specific master data objects, is recommended for Syensqo due to its flexibility, targeted governance, and adaptability to diverse business needs. Here’s a detailed expansion on why this option is preferred:

• Customized Governance and Flexibility: Option C allows Syensqo to tailor governance processes to the specific needs of each master data object. Critical data can be managed centrally with strict controls, while less critical or localized data can be governed by systems that best suit their unique requirements, providing a balanced and adaptable approach.

• Enhanced Responsiveness and Agility: By using separate systems, Syensqo can quickly adjust governance processes to respond to changing business needs or regulatory requirements ex: ITAR

• Optimized Resource Allocation and Cost Control: This approach enables efficient use of resources by centralizing governance only for high-priority data and allowing localized management for less critical data. It avoids unnecessary overhead and allows strategic investment in systems that align best with specific data governance needs.
• Scalability and Future-Proofing: Option C provides scalability and the ability to adapt as Syensqo grows or evolves. New systems can be added for emerging data types or business requirements without disrupting the existing governance structure, making it a flexible and future-ready solution.

Next Steps during the detailed design phase:

• Determine and confirm the tier mapping for the master data objects - Link
• Tool determination for each key master data and the dependent objects

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.

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

• Master data standards will be available and will be the input to the governance rules required for each Master Data Object
• Centralized and Standardized Data will be available: Data will be cleansed as per the Master data standards for all the objects when we go live

Constraints

None identified

Impacts

Governance Organisation: There will be a central organisation set-up which will manage and monitor the master data standards and the maintain the master data for Tier 1 objects. The same team will be responsible to govern all the master data that is created in the system. Three will be local master data maintenance teams for maintaining Tier 2 and 3 master data

Integration with the Downstream systems: Downstream systems which integrate with the existing master data solutions will have to change the integrations to the new system

Training: Training will be conducted to the entire organisation on the process to request for master data 

Business Rules

Will be determined as part of the detailed design

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

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.

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

Evaluation

Outline why you selected a position. The best format could be a pro/con table (sample below), but is up to you as the author. You must consider complexity, feasibility, cost/effort to implement, but also ongoing operational impact and cost. You must consider the program principles and explain any deviations in detail. This is probably as important as the decision itself.

	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	SAP solution supports only limited master data objects ex: Business Partners, materials and finance objects.  Any other master data needs to be implemented as a custom object	No system out in the Market which supports all the master data objects. Some customisation required to support all the relevant master data objects	Best of breed solutions to support the critical master data objects of Syensqo
Integration and Compatibility	Easy integration to SAP Landscape Very few out of the box integrations available. Rest needs to be custom built	Easy integration to SAP Landscape as majority of the best of breed MDM solutions support SAP integrations Custom integrations still required for some of the bespoke objects	Easy integration to SAP Landscape as supported solutions are selected
Flexibility	Moderately flexible as most of the objects are custom	Least flexible as most of the objects are custom	Highly flexible as each of the Master data object and its dependent objects can be customised as per the requirements Ex: Customisation can be done based on various requirements like ITAR
Complexity and Maintenance	Complex system for configuration (BRF+ rulesets) and maintenance	Complex system for configuration and maintenance as one system supports all the master data objects	Least complex in terms of the master data processes Complex maintenance in terms of the number of bespoke processes for the master data objects
Implementation and Cost	Complex implementation and expensive licenses Based on SAP's feedback customer typically implement 5-10 master data objects	Relatively less complex implementation as one governance process	Complex implementation as multiple governance processes
Scalability	Scalability is difficult as a lot of objects are custom built	Scalable across various systems and data types	Scalability tailored per system
Suitability for Critical vs. Non-Critical Data	Best suited for critical data in SAP; less efficient for non-critical.	Suitable for both, adaptable to specific data needs.	Optimizes by centralizing critical data and localizing non-critical data.

See also

Insert links and references to other documents which are relevant when trying to understand this decision and its implications. Other decisions are often impacted, so it's good to list them here with links. Attachments are also possible but dangerous as they are static documents and not updated by their authors.

Change log

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