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Imagine approving a critical supplier, only to discover duplicate records that hide compliance risks.

Or needing urgent spend analysis, but wrestling with inconsistent vendor names across five systems.

For procurement leaders in large enterprises, poor data inflates costs, slows processes, and exposes the organization to compliance failures.

Master Data Management (MDM) offers a solution to these and many other problems.

It transforms fragmented, unreliable data into a trusted strategic asset.

In this guide, we outline a clear, step-by-step process for successfully implementing MDM and unlocking enterprise-wide value.

1. Understand the Current State of Your Data

You wouldn’t build a house without first surveying the land.

Similarly, effective MDM starts with a deep, honest assessment of your existing data landscape.

In procurement, this means focusing intensely on your supplier and item master data.

So, start by mapping all locations where supplier data is stored, including:

• ERP systems
• Procurement platforms
• Spreadsheets
• Other tools

Then, conduct a thorough data audit to identify gaps, inconsistencies, and duplicates.

List all systems, inventory the key attributes (names, IDs, addresses, compliance statuses), and flag missing or conflicting data.

According to Gartner, poor data quality costs organizations an average of $12.9 million annually.

Illustration: Veridion / Data: Gartner

A significant portion of this loss is often due to sloppy procurement data practices.

The impact of poor data quality becomes even more tangible when seen through real-world disruptions. 

One of them occurred in 2023, when a massive air traffic disruption in the U.K. and Ireland was traced to incorrect data.

Source: The Guardian

According to reports, more than 2,000 flights were canceled, stranding hundreds of thousands of travelers and costing airlines approximately $126.5 million.

Examples like this underscore why assessing your own data—before any system changes—is critical to preventing costly disruptions. 

So how do you assess your current state?

Start by speaking with the people who actually use it:

• Procurement buyers
• Finance clerks
• IT staff
• Legal/compliance managers

These people know where the “pain points” are, and consulting them can answer the following questions:

• Is onboarding taking weeks?
• Are duplicate vendors causing payment errors?
• Is inconsistent classification hindering spend analysis?
• Are compliance checks manual and risky?

Collecting diverse perspectives will give you an exhaustive understanding of data usage and needs across the many parts of a complex enterprise. This cross-functional approach also prevents blind spots.

Based on the findings from your assessment and stakeholder input, crystallize your MDM goals and establish a clear roadmap for your MDM implementation.

Align your goals directly with procurement and business priorities (faster onboarding, better spend decisions, or compliance targets).

This will secure leadership buy-in and ensure the project delivers real value.

2. Build a Governance Structure

Once you have a complete picture of your current data, build a data governance framework to enforce consistent processes.

Data governance is the framework that defines how master data is created, maintained, accessed, and protected across its lifecycle.

It ensures that processes are consistent, responsibilities are clear, and data is managed as a shared business asset.

Without a strong governance foundation, even the best MDM tools will fail. Over time, data decays, inconsistencies reappear, and users return to manual workarounds.

McKinsey’s Master Data Management Survey found that the most prevalent issues in an organization’s data quality were incompleteness, inconsistency, and inaccuracy—problems that governance is designed to prevent.

Source: Veridion

Now, how can you actually build a governance structure?

Start by assembling a cross-functional data governance team, often called an MDM council. It should include procurement, finance, IT, and legal representatives.

These departments all contribute to and rely on supplier data, so their involvement is critical.

Once the team is in place, define clear roles and responsibilities to ensure accountability.

For instance, appoint:

• Data stewards responsible for daily data quality tasks (such as standardizing formats and running deduplication routines)
• Data owners who have ultimate authority over specific data domains (e.g., supplier master) and approve structural or policy changes

Next, define data policies that govern how supplier data is created, updated, and validated.

This includes:

• Standardized supplier onboarding workflows with required validations and approvals
• Rules for naming, classification, and deactivation of vendors
• Clear documentation of which fields are mandatory and how they must be formatted

Additionally, integrate your policies into automated workflows.

You might configure your system so that every new supplier record triggers checks (like verifying the legal entity or tax ID) and routes through a multi-step approval chain.

Automation will save you time and reduce the risk of errors.

Overall, a well-defined governance structure with codified roles, documented policies, data quality standards, and approval processes creates the discipline needed to maintain high-quality data long after the initial MDM rollout.

It also transforms MDM into a shared responsibility, ensuring that procurement and business teams own the integrity of the data they depend on.

3. Select a Suitable MDM Platform

With governance in place, the next step is selecting an MDM platform that supports your data strategy and brings your policies to life.

The MDM platform enables you to apply standards, manage data across systems, and maintain a consistent single source of truth—when paired with strong governance and integration.

But how to select the right one?

By checking if it has these features:

Source: Veridion

Start by evaluating platforms based on their ability to scale with your organization.

The solution should handle large volumes of supplier records and support future growth across other domains, such as products or locations, if needed.

Look for built-in features like automated validation, record matching, deduplication, and data consolidation.

These features will help enforce data quality standards without manual intervention.

The platform should also have smooth bidirectional integration with your critical source systems, such as ERP, CRM, and procurement tools, to ensure real-time data flow rather than creating more silos.

On top of that, consider your preferred deployment model.

Do you prefer a cloud-based hub, which offers faster deployment and elastic capacity, or an on-premises platform, which comes with more control?

Then weigh the total cost of ownership, such as licensing and long-term maintenance.

The chosen platform should reinforce your governance model rather than forcing you to change processes. Ensure it supports the defined roles, workflows, and approval mechanisms.

Also, look for ways to augment your master data with trusted external sources. 

Maintaining accurate, comprehensive supplier data internally is challenging, especially across a global supplier base.

This is where Veridion comes in. 

Veridion provides an AI-powered data enrichment service that integrates directly into your MDM system.

Source: Veridion

We provide a weekly-updated global supplier database with over 220 data attributes, including firmographics, financials, ESG scores, and more.

Source: Veridion

Integrating this rich data into your MDM means vendor profiles are automatically augmented and verified without manual research.

It also ensures that critical information, such as business status, financial health, or location details, is always current.

The result is a continuously refreshed set of supplier records that improves segmentation, risk-scoring, and compliance checks.

By combining an MDM platform with live data enrichment, you reduce duplicate effort and ensure the system always has the latest, most reliable vendor data.

Source: Veridion

Lastly, the platform should offer a user-friendly interface for business users, especially your procurement team.

It should be intuitive enough to allow daily tasks to be completed without constant IT support and flexible enough to provide role-based views tailored to each function.

Selecting a platform that seamlessly integrates with your ecosystem, empowers business users, and leverages external enrichment sources like Veridion is key to achieving high-quality, actionable supplier master data.

4. Prepare the Data for Migration

Now that you’ve selected a platform, it’s time to tackle the data itself.

This phase is about cleansing, harmonizing, and preparing data for its new life in the MDM hub.

This is often the most labor-intensive step.

Done properly, it ensures data quality, accuracy, and consistency. Done poorly, it simply moves bad data into a new system.

Jonathan Block, former VP at Sirius Decisions Research (now part of Forrester), explains:

Illustration: Veridion / Data: Reltio

So, to save money in the future, ensure you thoroughly clean your data before loading it into your new MDM.

You can do it following these five steps:

Source: Veridion

Begin by collecting all supplier records from across your organization—ERP systems, procurement tools, CRM platforms, and spreadsheets—and load them into a staging area.

Use data profiling to deeply analyze source data for duplicates, errors, anomalies, missing values, and format inconsistencies.

Correct mismatches—for example, different address formats or misspelled names—and remove or merge duplicate entries.

Next, standardize formats. Ensure tax IDs, country names, and address fields follow one consistent format (e.g., addresses using postal standards, phone numbers in E.164 format, standardized commodity codes like UNSPSC).

It is also important to check data against internal rules (governance policies) and external sources (e.g., validating Tax IDs or DUNS numbers via APIs).

Data preparation also involves creating a “golden record”—a single, authoritative view that combines data from all sources for each supplier entity.

As McKinsey explains:

“An MDM “golden record” is a repository that holds the most accurate information available in the organization’s data ecosystem. For example, a golden record of client data is a single, trusted source of truth that can be used by marketing and sales representatives to analyze customer preferences, trends, and behaviors; improve customer segmentation; offer personalized products and services; and increase cross-sales, interactions, customer experiences, and retention.”

To build your golden record, merge data from every business unit into the master record and update it as more accurate info becomes available.

For example, if the purchasing team has a bank account for Supplier X and the finance team has updated contact info, both sets should converge in the golden record.

Before migrating all data, conduct a pilot migration. 

Select a limited and representative data set—perhaps by geography, supplier type, or category—and test the process end to end.

Apply your golden record logic, validate results, and refine rules based on the findings.

After the pilot is successful, execute the full migration.

Ensure that validation checks are in place during and after migration to detect any data quality issues.

Maintain detailed audit trails that log every change made throughout the process for full traceability and compliance.

This phase transforms raw, disparate data into a cleansed, unified asset.

The “golden record” for each supplier becomes the single point of truth used across the enterprise.

5. Drive Adoption through Training

The MDM system is live, the golden records shine… but if your procurement team doesn’t use it effectively, the initiative fails.

Adoption is where the theoretical benefits become tangible business value.

Without it, even the best-designed MDM initiatives will fall short.

According to McKinsey, 70% of change programs fail, mainly due to resistance from employees and a lack of support from management.

Illustration: Veridion / Data: McKinsey

To ensure your MDM is part of the successful 30%, develop comprehensive training programs and communication plans tailored to your teams, educating them on MDM and data principles, processes, and tools.

By equipping your MDM users with vital skills and knowledge to effectively interact with the system, you’ll be maximizing its value and minimizing resistance to change.

Conduct hands-on workshops or webinars showing users how to enter or update supplier data under the new governance rules.

In the process, highlight the benefits, such as faster onboarding and fewer errors, so people see why it matters and understand the value of their contributions to the organization’s data management efforts.

Show procurement teams how MDM makes their jobs easier and more impactful through:

• Faster supplier searches
• Reduced onboarding times
• Confidence in compliance checks
• Better spend insights
• Less time reconciling data

This is vital because training is not just “how to click buttons,” it is “why data quality matters to your job.”

As Juan Carlos Ribot, Plan Data and Analytics Senior Analyst at Johnson & Johnson, puts it:

Illustration: Veridion / Data: LinkedIn

It also helps to appoint enthusiastic and respected individuals in each department to be your MDM champions. 

Empower them to be first-line support, promote MDM best practices, gather feedback, and act as advocates.

Moreover, establish feedback loops where users can report data issues or suggest improvements.

This could involve simple channels, such as a dedicated email or a form in the MDM portal, allowing users to report data issues, suggest improvements, or ask questions. Regularly review feedback with the governance council and act on it promptly.

It’s also important to measure adoption and data quality with clear metrics.

Track the following metrics:

• The percentage of complete supplier profiles (e.g., valid tax IDs, bank details, addresses)
• Time-to-onboard new suppliers
• Data quality indicators

You should also set specific goals, such as achieving 95% profile completeness or reducing onboarding time by 30%.

Importantly, keep people engaged. Plan regular data audits, refresher training, and success story sharing.

MDM is not a one-time implementation but a long-term discipline. Reinforcing training and adjusting governance practices over time helps maintain data integrity as your supply base evolves.

Conclusion

Master Data Management implementation is a big undertaking that demands cross-functional commitment and strategic focus.

By following these five steps, you create a strong foundation for accurate supplier data.

The payoff is clear:

Procurement teams can onboard suppliers faster, make smarter sourcing decisions, and stay compliant.

Implement this systematic approach today, and you’ll turn master data management into a strategic asset for your company.