Key Takeaways
An MDM framework is essential for structuring master data management (MDM) efforts, defining roles, processes and technology to ensure data consistency and usability.
A well-planned MDM framework enhances operational efficiency, improves collaboration and enables better decision making through unified and high-quality data.
Successful implementation requires stakeholder alignment, integration with broader data governance strategies and clear documentation to maintain continuity.
A detailed plan is the key to any successful project, and that’s no different when it comes to your master data management (MDM) initiative. An MDM framework provides the blueprint for building a successful initial MDM project and serves as a guide for expanding into further domains across the organization. In this article, we’ll explore what a master data management framework is, why you should build one and how to do it.
The State of Master Data Management (MDM) 2025
What is a Master Data Management Framework?
A master data management (MDM) framework consists of the people, processes and technologies that support an organization’s overall MDM strategy. Organizations build frameworks that serve their data needs and technological maturity, making each one different at inception and ready to evolve with the needs and direction of the business. Because it ultimately defines how an organization will operationalize MDM, an MDM framework is an important component of a successful MDM strategy.
The MDM framework also covers four major data processes:
- Integration: Deciding which business systems and software feed data to and/or pull data from golden records
- Management: Choosing critical data domains and defining audit, reporting and expansion cycles
- Storage: Locating where the golden record data will rest and under what conditions the records are updated, audited and purged (see implementation styles)
- Access: Determining which employee roles have administrative, edit or read-only access to the golden record, and under what conditions those access levels change
Each of these data processes may require several steps within the framework, but not all organizations will use the same steps. Working with an experienced MDM provider to define those steps may help clarify an organization’s individual framework.
How is an MDM Framework Different Than a Data Governance Framework?
Data governance frameworks manage the entire data lifecycle — including master data management — while MDM frameworks manage just the corner of data that contributes to and works from master data. A robust data governance framework would pay special attention to MDM in addition to other data governance concerns like security, reporting and regulatory compliance.
Why Build an MDM Framework?
An MDM framework — sometimes also called an operating model — defines how your MDM initiative will be implemented. It defines what the business can expect to receive and what’s expected of the business to achieve that. This is important because MDM frameworks help manage expectations around what MDM will and won’t do.
A successful MDM program promises to unify business systems, improve collaboration across teams and speed up internal processes. These results, in turn, drive greater business outcomes, like increasing revenue, identifying opportunities for cross and upselling, optimizing vendor management and improving the customer experience.
The Importance of Framework Planning
That sounds great, but without devoting the time and effort to drawing up a workable and complete MDM framework document, you risk not realizing the full potential of MDM and possibly even losing out on some of these benefits.
A successful project requires preparation and buy-in — two things the framework planning process can provide. The framework planning process requires discussions with stakeholders from across the business to understand priorities and needs. It outlines the known contingencies to keep in mind during data matching and cleansing and defines how to approach new difficulties.
A master data management framework may include directives for each of these stages in the MDM lifecycle:
- Data Collection: Integrating data from various source systems
- Data Matching and Cleansing: Matching, merging, deduplicating and cleansing data
- Data Storage: Deciding whether golden records will live in the MDM system itself, in a data warehouse or somewhere else
- Data Delivery: Providing access to or copies of golden record data to end users and downstream systems
- Data Security: Protecting golden record data from exposure, deletion or inadvertent edits
- Data Governance: Defining and defending standards and processes for audit, access and deletion
The comprehensive nature of the MDM framework improves outcomes and ensures success across technical and business teams.
Master Data Management Framework Examples
For a successful first project, choose a single data domain, define stakeholders and outcomes and build a framework that meets those needs. These are some example frameworks to guide your thinking.
Location Data for Commercial Food Supplier
| Problem | A commercial food supplier to restaurants hopes to consolidate systems, improve delivery times and streamline warehousing after acquiring a competitor. |
|---|---|
| Process | The supplier needs to collect location data from sales, vendor, warehousing and delivery systems to deduplicate and standardize the location data across the redundant systems and make that data available for use by all teams. |
| Benefits | By creating golden record location data across the company, the supplier can successfully build more efficient routes that shorten shipping times from the warehouse or pick-ups from vendors. The sales team can identify new sales prospects along those routes, expanding the company’s reach. |
Product for Dropship Ecommerce Company
| Problem | A dropship ecommerce company needs to make sense of product listings across multiple ecommerce platforms, including their own website and large online retailers. |
|---|---|
| Process | The ecommerce company collects product description, pricing, weights and inventory data from warehouse, shipping, sales and CRM systems, as well as across all online retail outlets. |
| Benefits | By standardizing product information, the team can improve search results with optimized descriptions, decrease inventory on-hand according to sales rates, improve shipping efficiency and pricing due to weight or frequency discounts and decrease shipping incomplete orders that require double shipping. |
Assets for Regional Medical Group
| Problem | A regional medical group with several locations has seen an increase in asset maintenance spend, and the company finds many of its digital tools have not received preventative maintenance. |
|---|---|
| Process | The medical group collects asset data from mobile device management, IT systems, contracts, scheduling and maintenance control. This data may include serial numbers, date of acquisition, maintenance records and connected systems. The golden record data is stored in a centralized source that connects to IT, finance and scheduling applications. |
| Benefits | The medical group can move from reactive to preventative maintenance schedules, decreasing time and revenue lost to assets out of order. The finance team has access to detailed financial reports and accurate depreciation schedules and can advise on appropriate procedures for repair or replacement. In addition, the group will reduce device loss due to turnover, as HR can access device assignments during offboarding processes. |
Best Practices for Developing an MDM Framework
While there’s no one-size-fits-all approach to developing an MDM framework, there are general best practices you can follow that are relevant regardless of the use case. In “3 Essentials for Starting and Supporting Master Data Management,” Gartner analysts Sally Parker and Simon Walker lay out the six steps Gartner takes to developing MDM frameworks (MDM operating models):
- Scope: Align MDM goals with data and business strategies and define how MDM will support key business functions
- Metrics: Determine how you’ll measure the efficacy or business value of your MDM program
- Governance: Implement a data governance program, which includes creating data governance policies and determining data stewardship roles
- Organization and Roles: Decide who is responsible for the different aspects of the MDM program, establish training and change management programs and build collaboration and trust between IT and business teams
- Process: Establish processes for managing data quality, integrating data across systems and creating workflows for creating new records, data validation and other tasks
- Technology: Choose an MDM platform based on the needs you’ve identified in steps one through five
Benefits of Using a Master Data Management Framework
When building an MDM framework, the team creates a plan of attack, ensures integration with existing organization-wide data efforts, defines plans for continuity should team members leave and identifies metrics that signal the success of the project. These plans provide guideposts and touchpoints to assure team members and organizational stakeholders despite the inevitable project difficulties.
Plan of Attack
An MDM framework acts as a blueprint for building the initial MDM project. The framework should name stakeholders (or their roles), data domains, available and potential technology resources and funding. The planning document then acts as a touchpoint during the inevitable scope creep conversations.
Integration with Broader Data Efforts
An existing, well-architected data governance framework can provide some guidance on the structure and needs of the business when writing the MDM framework. And if data governance or other data planning documents do not exist, the MDM framework documentation can work as a catalyst for the creation of similar documents. Either way, the MDM framework enumerates the ways golden record management works within the greater organizational data landscape.
Continuity Planning
Like any critical corporate project, master data management projects have timelines that may extend beyond the tenure of individual team members. Documentation that includes project objectives, goals and detailed steps fills the critical gaps that employee attrition can leave behind. It’s always easier to read the documentation than it is to contact a retiree in his new RV.
Success Metrics
Whether the first MDM project is wildly successful or takes a couple of reworkings to see results, the framework holds the team to a set of planned goals and the indicators of success. By referencing these metrics, the MDM project stakeholders can check progress regularly, double-down on processes that work or make incremental changes toward success. Without the framework’s roadmap and goal, the data effort is susceptible to tangents, scope creep or project failure.
Explore Profisee Professional Services
Share
