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Status

  Approved

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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.

SystemUse
Mappy SpPMappy application is used to improve commercial data accuracy
Material CenterMaterialCenter is a web application for materials data management.
SAP MDM-MDGSAP 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 WorkflowHomemade ABAP application for automating vendors creation in the ERP
SAP PF1 - PRSSAP ERP PF1 - Data - Master Data module of SAP ECC
CRMApplication 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.


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.

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.

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




Integration and Compatibility

(plus)Pro

(minus)Con

(plus)Pro

(plus)Pro

(plus)Pro

(minus)Con

Flexibility

(plus)Pro

(minus)Con

(minus)Con

(plus)Pro

(plus)Pro

Complexity and Maintenance(plus)Pro(minus)Con(minus)Con
Data Quality and Consistency


Implementation and Cost


Responsiveness and Agility


Scalability


Suitability for Critical vs. Non-Critical Data


See also


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Change log

Version Published Changed By Comment
CURRENT (v. 10) Sept 11, 2024 19:57 NARAHARI-ext, Bhargavi
v. 28 Sept 11, 2024 19:51 NARAHARI-ext, Bhargavi
v. 27 Sept 11, 2024 18:59 NARAHARI-ext, Bhargavi
v. 26 Sept 11, 2024 17:00 NARAHARI-ext, Bhargavi
v. 25 Sept 11, 2024 16:48 NARAHARI-ext, Bhargavi
v. 24 Sept 10, 2024 11:50 NARAHARI-ext, Bhargavi
v. 23 Sept 10, 2024 11:39 NARAHARI-ext, Bhargavi
v. 22 Sept 09, 2024 10:24 WENNINGER-ext, Sascha
v. 21 Sept 05, 2024 12:20 NARAHARI-ext, Bhargavi
v. 20 Sept 05, 2024 11:16 NARAHARI-ext, Bhargavi

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