Webinar: D&B and Forrester Discuss Mastering Data Management

Our recent webinar, “Mastering Data Management: How Leaders Are Driving Growth, Efficiency, and AI Readiness,” kicked off with a poll question for the audience: What is your top priority when it comes to data management in 2025?

The top response, from 50% of the attending audience, was “improving data quality and trust.” Which came as no surprise to the featured speakers — Dun & Bradstreet’s Senior Vice President of Customer Solutions & Success Elizabeth Barrette, and Forrester Senior Analyst Jayesh Chaurasia.

“Trust in data is obviously top of mind. It’s a requirement now,” said Barrette.

From there, Barrette and Chaurasia dug into the topic of why master data management (MDM) has become a strategic necessity, and how it serves as a prerequisite for enterprises pursuing AI readiness and business growth.

Why MDM Is Foundational, Not Optional

The conversation began with a clear message: trusted, high-quality data is the foundation for everything from operational efficiency to advanced analytics and AI readiness.

Within enterprises today, organizations are juggling dozens of internal and external data sources. This typically creates silos, inconsistencies, and trust issues that hinder decision-making and stall innovation. Chaurasia pointed to the recent commissioned study conducted by Forrester Consulting on behalf of Dun & Bradstreet, “Mastering Data Management: Why Leaders Are Prioritizing Data Management for Better Performance and Growth.” The organizations surveyed for that study were managing, on average, more than 30 internal and 32 external data sources.

The sheer volume of data impedes efforts to strengthen governance and improve data reliability. So organizations are left with fragmented, disconnected data that teams are reluctant to utilize as they should. These organizations will find themselves struggling to move faster or make confident decisions.

As Barrette put it, “The companies we see getting it right are the ones treating master data as a strategic asset. They’re using it to unify disconnected systems and lay the groundwork for AI and smarter growth. They’re seeing quality data as a key component to anything they’re going to do moving forward.”

Chaurasia noted that he sees a shift in the broader perception of MDM: it’s evolved from a “back-office, data hygiene or IT initiative” to a business-critical function. It’s not just a deduplication and record-matching activity anymore; beyond operational efficiency, it’s fundamental for AI adoption and digital transformation milestones such as cloud migration.

Insights From the Study

The study featured in the webinar was based on a survey of 304 global decision-makers responsible for data management strategy. The results highlight both progress and continuing challenges:

• MDM Tops the Data Priority List

63% of respondents said MDM was their number one data goal for the next 12 months.

• Data Distrust Persists

Over 25% of respondents admitted that they can’t trust their data sources —underscoring that many lack foundational data governance practices today.

• Missed Opportunities Are Real

41% of respondents said that poor data quality cost them business opportunities, while 28% said that it had undermined their AI initiatives.

As Barrette commented, “When your data is clean, connected, and governed, and teams are spending less time questioning it, they’re able to deliver more revenue. They’re spending more time doing their job, versus cleaning data.”

Tips for Successful MDM Implementation

Chaurasia and Barrette discussed ways that organizations could overcome obstacles to implementing MDM and justify the business case. Despite the clear benefits, many organizations face hurdles such as budget constraints, lack of internal alignment, and confusion about whether existing tools offer similar capabilities.

The presenters recommended starting with a phased approach:

• Begin with high-value use cases like entity resolution or improving one domain at a time.
• Measure and communicate impact using KPIs and dashboards to demonstrate ROI.
• Leverage external partners to bring objectivity, expertise, and speed — especially when internal disagreements or resource limitations slow progress.

“MDM success is built in stages. Prove the value early — then scale,” said Chaurasia.

Why Third-Party Data Partners Matter

One of the most compelling parts of the webinar focused on the role of external partners in accelerating data management success. While internal teams often have deep knowledge of their systems, they can be constrained by limited budgets, competing goals, and even office politics. External partners bring objectivity and specific expertise that help organizations move faster and with greater confidence.

“External data partners may seem like an extra expense, but more often than not, they’re a difference maker,” said Barrette.

 “A good third party can help mediate internal issues when teams disagree on priorities or approaches,” Chaurasia commented. “They also bring scale and speed to your data strategy and implementation. They have specialized tools and frameworks which they’ve used in multiple places for success.”

Barrette explained that an external partner “isn’t here to override your data. We’re here as a gut check, a second set of eyes to help you assess where you stand and move forward with clarity.”

Beyond advisory support, external partners often provide clean, consistent data that can serve as a trusted foundation for internal systems. This accelerates progress toward unified views of customers, suppliers, and products — critical for AI readiness and advanced analytics. In short, partnering with experts doesn’t replace internal teams; it amplifies their impact.

Watch the Webinar

Watch the full webinar recording to hear all the insights, research findings, and practical MDM implementation tips.