Leaders Make the Case for Well-Managed Data

We Asked: Should Better Data Management Be a Strategic Priority?

In our digital economy, data is everywhere — but not always useful. Organizations are overwhelmed by incomplete, inconsistent, and siloed data that makes decision-making harder, not easier. Industry and enterprise leaders are struggling to convert this chaos into clarity amid an uncertain, volatile business climate.  

Many of them are seeking answers in master data. They're also recognising the value of master data management (MDM) — a strategic approach to governing data assets. In 2025, to learn more about how global data leaders are handling their current challenges, Dun & Bradstreet commissioned Forrester Consulting to survey over 300 of them. We asked about how they’re currently managing their data and how their data management partners are helping them reach their goals.

Let’s explore four key takeaways from the research. 

1. The Data Problem Is Bigger Than You Think 

The organizations surveyed are managing data from an average of more than 30 internal and 32 external data sources. That’s a staggering amount of data flowing in from CRMs, ERPs, marketing platforms, third-party vendors, and more. While many companies strive to be “data-driven,” this reality could cause an organization to be “data-overwhelmed.” 

This flood of information creates a paradox: the more data organizations collect, the harder it becomes to use effectively. One in three decision-makers surveyed say they have too much data; can’t easily find or access it; or don’t even know where to start analysing data.

Respondents were candid when reporting the consequences of poor data management. Over half of the survey respondents say they have experienced privacy or security lapses because of inadequate data management practices. Meanwhile, 40% have faced regulatory violations or damaged reputations. Other reported issues included delayed product launches (46%), missed growth opportunities (45%), and difficulty detecting business risks (33%).

Disconnected data also diminishes the value of advanced technologies like AI and machine learning. These tools rely on clean, structured data to function properly. Without it, even the most sophisticated algorithms can produce misleading results.

The consequences of poor data management are far-reaching. These aren’t just technical issues — they’re strategic risks that can impact customer trust, competitive ability, and many other business goals. 

2. Master Data Management Is the Foundation for Clarity 

Master data is the consistent, trusted core of your business information — think customer records, financials, supplier data, and more. When managed well, it becomes the single source of truth that supports everything from efficient operations to strategic growth. Survey respondents seem to understand this; about half reported that they already use MDM, and another 40% plan to start within a year. 

The strong data foundation created by MDM is especially critical in industries with strict regulatory requirements. For example, survey respondents from the financial services and/or banking industry were more likely than others to implement MDM, with an impressive 94% reporting that they are either actively using it or plan to implement it within 12 months.  

MDM isn’t just a tech tool; it helps ensure that everyone in the company uses the same accurate data, cutting down on mistakes and extra work. Whether you're launching a product, entering a new market, or facing a compliance check, reliable data is key to success.

Moreover, MDM supports the ability to scale and grow. As companies expand and adopt new technologies, a strong data foundation ensures that new systems can integrate smoothly without introducing new inconsistencies. 

It also plays a pivotal role in digital transformation. Many organizations are investing in automation, AI, and real-time analytics — but these initiatives can’t succeed without high-quality, well-governed data. The survey responses reinforce this theme; 70% of respondents agree that better data management would make it easier to launch digital transformation programs.  

3. Better Data Management Drives Real Business Impact 

The benefits of effective data management go far beyond IT. The study found that investments in better data management could greatly improve many areas of business operations.  

• 71% of respondents expect better customer experiences, driven by more personalized and timely interactions. 

• 70% anticipate more actionable business decisions, thanks to improved data visibility and accuracy. 

• 68% foresee more efficient business processes and employee experiences, as teams spend less time searching for or cleaning data. 

• 66% believe better data management would help them comply with regulations and protect their brand, lowering the risk of fines or losing public trust.

Yet, despite these expected benefits, over 25% of leaders surveyed say they can’t fully trust their data sources. This trust gap highlights the ongoing need for stronger governance, better tools, and a cultural shift toward data accountability. 

Data quality issues also have a direct impact on innovation. Nearly 30% of leaders surveyed report that poor-quality data has caused problems with AI initiatives. When data can’t be trusted, it undermines the very technologies designed to give businesses a competitive edge. 

In addition, poor data management can interfere with market expansion and the ability to respond to customer needs in real time. These missed opportunities can have a significant impact on revenue and long-term growth. 

4. Data Management Partners Can Make the Difference 

Managing data effectively isn’t something most organizations can do alone. That’s why over 90% of respondents already work with a data management partner, and they’re seeing real results. 

These partnerships are not just about outsourcing — they’re about advancing the key business targets of growth, risk management, and cost control. The right partner brings expertise, tools, and frameworks that help organizations move faster and smarter. 

Here’s what leaders look for in a partner: 

• Data quality and integrity as a top priority, ensuring that insights are based on accurate, consistent information. 

• Advanced tools like AI and machine learning to refine insights and automate processes. 

• Support for innovation, scalability, and compliance, helping organizations adapt to changing business needs and regulatory landscapes. 

Beyond technology, partners also bring strategic value. They help organizations align data initiatives with business goals, streamline operations, and unlock new opportunities for growth. 

The study found that organizations working with data partners reported better efficiency, agility, and time to market. These partners help simplify the management of fragmented data and enable faster, more confident decision-making. 

Three Steps to Smarter Data Management 

To move forward, organizations should focus on: 

• Adopting master data solutions to establish trusted systems of record. These solutions provide the backbone for consistent, high-quality data across the enterprise. 

• Prioritising data governance to ensure integrity, security, and consistency. Strong governance frameworks help mitigate risk and build trust in data-driven decisions. 

• Leveraging expert partners to improve integration, usability, and insights. A good partner can help you navigate complexity, implement best practices, and accelerate time to value. 

These steps are not just best practices — they’re becoming business imperatives. As data continues to grow in volume and importance, organizations that fail to manage it effectively will fall behind. 

To grow your business, improve customer experiences, or meet regulations, you need relevant, consistent data. With the right tools and partners, you can turn your data into a powerful asset. Companies that manage their data well will outperform their competition in trust, agility, and performance.