Data governance, especially within the context of Master Data Management, has become increasingly vital in recent years. As businesses realize the value of maintaining clean, consistent data—driving greater efficiency across departments like procurement, supply chain, maintenance, and product teams—and recognizing the high costs of frequent data cleaning, the demand for robust data governance practices has soared. To achieve this, companies leveraging SAP MDG can implement a variety of master data governance strategies.
As a leader in ERP solutions, especially for asset-intensive industries, SAP has developed its own data governance product to support multi-domain master data management initiatives
This product is called SAP MDG, which stands for Master Data Governance.
As a result, both the practice of managing master data within SAP and the product itself are typically referred to as SAP MDG.
Related Article: How to Manage SAP MDM
What is SAP MDG & What Does it Do?
As mentioned earlier, MDG is part of a comprehensive Data Management suite, which is licensed and sold separately via the SAP store.
This solution supports all types of master data and comes with built-in features for data deduplication, compliance, approvals, replication, and standardization.
MDG can be deployed on SAP ECC, S/4HANA, or as a cloud-based solution.
Interested users can explore free trials or demos of certain MDG cloud versions via SAP’s Business Technology Platform.
Pricing varies based on the specific implementation, whether it's for materials, suppliers, customers, finance, or multiple domains.
Centralized Data Governance
One of the key advantages of SAP MDG is its ability to integrate and unify data across large, complex enterprises. These organizations often manage multiple supply chains, distribution centers, manufacturing plants, and facilities.
Many companies operate on different SAP instances or entirely separate ERP systems such as Oracle Cloud or Microsoft Dynamics. SAP MDG seamlessly integrates with these systems, offering a consolidated, unified view of organizational data.
This unified view empowers companies to make more informed strategic decisions across departments. For example, they can extend spare parts inventory across multiple plants, consolidate suppliers for the same parts or products to improve negotiation power, and analyze customer consumption patterns globally, regardless of the source system.
Compliance & Workflows
SAP MDG facilitates the creation of complex workflows and approval processes, reinforcing data stewardship standards. These workflows and sub-workflows ensure accountability and transparency in the creation and update of data across the organizational hierarchy.
For example, in managing supplier master data, a procurement team steward might initiate a request to onboard a new supplier for maintenance spare parts. The workflow can be designed such that a maintenance engineer first submits the request for the spare part, which is then reviewed by the data steward for approval, followed by additional reviews and approvals from the heads of Maintenance and Procurement.
MDG supports the design of workflows that can range from simple to highly complex, ensuring that compliance and approval processes are strictly enforced through technology-driven solutions.
Data Normalization
Data normalization is a key component of effective master data governance. SAP MDG utilizes rule-based normalization through Business Framework Plus to systematically organize raw, unstructured data from descriptions and free-text fields.
These rules enable the software to process data in bulk, standardizing and correcting errors at the point of entry. For instance, it can automatically convert values like “US” or “USA” into “United States of America.”
In the same way, SAP MDG standardizes units of measure, currency formats, and naming conventions using a centralized framework and set of rules.
This structured approach is critical for automating processes and consistently applying business rules, making it a fundamental element of any robust master data governance solution.
Furthermore, MDG integrates seamlessly with SAP Data Services to enhance advanced data cleansing and quality control tasks, including name parsing, address standardization, phone number formatting, and more.
Bulk Processing & Uploads
While not directly tied to governance, this feature provides valuable functionality by enabling the retrospective processing of legacy data records and values.
Updates can be carried out using CSV, XML files, or via SAP Data Services, as previously discussed.
A key limitation, however, is the lack of comprehensive mechanisms for enriching data from external sources, along with the absence of industry-specific training within the software. This gap often leads to increased manual effort from data stewards and ERP maintenance teams.
Data Deduplication
Much like Moresco' data cleansing services for MRO parts through Assure, SAP MDG also performs data de-duplication in two stages.
The first stage focuses on removing duplicate records by comparing standard fields, such as description, record ID, manufacturer name, or part number.
The second stage employs a scoring system that assesses potential duplicates by analyzing overlapping attributes like units of measure and utilizes fuzzy logic to flag likely duplicates for further manual review.
Consolidation of Records
MDG also aggregates data from multiple source systems, documents, and files, utilizing its built-in matching and merging logic to deliver a more complete and refined view of organizational data.
This process can be executed in batches or continuously via ongoing data integration.
Enforces Validation Rules
The software enables the configuration of validation rules for different types of master data. This includes setting parameters for "mandatory fields," "character length limits," "alphanumeric or date formats," and more.
These validations guarantee that data is entered only after passing essential quality checks. With MDG's flexible rule configuration, data stewardship becomes significantly easier.
Executing Master Data Governance in SAP Systems
While SAP MDG has proven to be a strong solution—particularly given its launch in 2011—it does have some notable limitations.
Furthermore, updates targeting features and performance improvements have been somewhat limited, with recent enhancements in embedded AI often lacking practical, real-world relevance.
In more than 70% of our projects, we advise supplementing SAP MDG with additional bolt-on solutions that offer modern features tailored to specific industry use cases.
In the upcoming sections, we will explore data governance capabilities, from basic to advanced, compare how SAP MDG meets these requirements, and highlight potential alternative solutions.
Limitations of MDG & Alternatives
The introduction of SAP MDG in 2011 marked a pivotal milestone in ERP data management. However, as with any long-standing product, its limitations have become more evident over time.
Technical Know-how
Managing large datasets spread across various silos is always challenging. One common criticism of SAP MDG, however, is that its complexity often surpasses what is truly needed.
As a result, many organizations are forced to employ dedicated SAP data governance specialists to effectively manage MDG workflows and day-to-day operations.
The availability of numerous paid SAP MDG training courses underscores the demand for professionals capable of navigating this intricate software—software that could be designed to be much more intuitive and user-friendly.
Integrations with Non-SAP Systems
While SAP MDG offers seamless and flexible integration with other SAP systems by default, connecting with non-SAP systems usually requires custom development and significant technical expertise.
Given that large organizations often use multiple ERP systems across different regions and departments, the need for custom integrations can become a significant challenge.
Limited Coverage for All Master Data Domains
SAP MDG is highly effective in managing key master data domains such as Materials, Business Partners, Customers, and Finance. However, its support for other domains like Employees and Equipment remains limited.
Moreover, industries such as retail, energy, healthcare, and mining often require substantial customizations, which can make it challenging to sustain effective governance initiatives.
Lacks Built-in Enrichment Methods
A major challenge in Master Data Management is handling incomplete or limited information.
Many MDM solutions tackle this issue by leveraging AI-driven processes or maintaining structured, proprietary databases within their platforms.
Several tools also pull data from verified sources like supplier websites and PDFs, with some even identifying obsolete supplier parts and suggesting suitable alternatives.
However, when it comes to customer master data, especially for B2B companies, integration with business intelligence platforms like ZoomInfo or Dun & Bradstreet remains relatively limited.
Limited AI Functionalities
Numerous industries and fields stand to gain immensely from the transformative power of Artificial Intelligence.
One such area is data management, where AI’s influence is particularly profound. From data normalization and enrichment to governance and integration, the potential is vast — and here at Moresco, we are already experiencing these advancements firsthand.
In late 2024, SAP MDG introduced an AI assistant (source), marking a notable step forward. However, its full impact on managing master data is yet to be realized in practice.
Assure© for Master Data Governance
Many organizations provide SAP master data management solutions compatible with SAP ERP systems. One such solution is Moresco’ Assure, which seamlessly integrates with SAP MDG, offering a holistic approach to master data governance. This enables enterprises across industries to effectively manage and maintain their ERP data, reducing data quality issues and minimizing the need for frequent data cleansing.
Assure can either function as a bolt-on solution alongside MDG or be deployed independently with popular ERP platforms like S/4HANA, ECC, Oracle JD Edwards, and Microsoft Dynamics.
This solution is specifically tailored for enterprises in manufacturing or production-heavy industries such as Oil, Gas & Energy, Mining & Metals, Building Materials, and Chemical Manufacturing.
Below, we will dive into some of Assure’s key features, practical applications, and the challenges it solves — many of which SAP MDG alone may not fully address or may find too complex.
Industry-Specific Context
Assure is specifically designed and expertly trained for MRO data governance, with a focus on spare parts, materials, supplier, and equipment data used in asset-heavy industries — particularly in sectors like energy, mining, chemicals, and building materials.
Equipped with industry-specific modifiers, business rules, and integrations with third-party data, Assure ensures that the data processed is far more accurate and "complete" — even before it enters the ERP system.
Check out our client use cases below to see how effective data governance practices lead to more structured, enriched, and dependable data.
Governance with Embedded AI
Assure is an AI-powered data governance platform, with its core processes and functionalities driven by artificial intelligence and machine learning.
By integrating advanced capabilities like autonomous web scraping, OCR-based data extraction, and pre-trained industry models, Assure enables fast, accurate, and highly reliable data processing.
Continuous Learning
As an AI-powered platform, Assure enables any incorrectly processed data to be corrected and re-trained during the human review phase.
The built-in generative AI models are designed to learn from these corrections, reducing the likelihood of similar errors in the future.
Seamless Integration
One of the primary limitations of SAP MDG, as previously noted, is its limited integration capabilities with non-ERP systems. This has remained a significant challenge for large enterprises, where intricate supply chains depend on multiple ERP systems and versions to fulfill varying functional and regional demands.
Unlike SAP MDG, Assure provides a completely no-code experience. Even the most complex processing tasks and workflows are intuitive and easy to manage, without needing any technical skills or programming knowledge.
While having a basic understanding of the data is helpful, it’s generally not a limitation. Most users already have a solid grasp of the context and meaning behind the data they work with.
No-Code & User-Intuitive
Unlike SAP MDG, Assure offers fully no-code workflows and operations. Even the most complex tasks and processes are intuitive, requiring no technical expertise or programming knowledge.
While a basic understanding of the data is beneficial, it’s usually not a barrier—users typically already understand the context and significance of the data they are working with.
Conclusion
In conclusion, while SAP MDG offers strong master data governance capabilities, its complexity, limited integration options, and absence of built-in enrichment features can present significant challenges for many organizations.
Among the various master data governance solutions, Assure by Moresco emerges as a more advanced and user-friendly choice—particularly for asset-intensive industries like oil, gas, and mining. Powered by AI and machine learning, Assure ensures seamless integration, offers no-code workflows, and provides industry-specific data enrichment, making it both efficient and easy to use.
Its ability to streamline data governance while requiring minimal technical expertise sets it apart as a versatile, future-ready solution for modern enterprises.
