Dun & Bradstreet Report Reveals Latest Data Trends Across Organizations

With the high volume of data being generated by businesses and the sharing of common processes, every role at an organization can play a role in data management. However, there is often misalignment between enterprise functions, and this leads to delays or failures of data initiatives. This “disconnect” can also lead to redundant efforts and costly mistakes.

Dun & Bradstreet aims to provide insights into the changing attitudes about data health and data management across organizations. This year’s annual B2B data survey and report by Dun & Bradstreet has a broader audience including key decision-makers. The focus of this year’s report is to shed light on why diverse attitudes about data exist among different company functions, and what threats they may pose to business growth.

Based on the findings of the report, there is agreement across companies that the primary benefits to greater investment in data quality include lack of results and ROI proof; low confidence in the usefulness of data quality investments; lack of executive recognition that data is a necessity; and better returns on investment in other company initiatives.

However, despite the challenges, 70 percent of respondents shared that their organization has increased investment in data quality initiatives in the past 12 months, and they expect the investment to continue increasing through the end of 2024.

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The survey also highlights that the opinions about data and benefits are linked to three main business objectives: company growth, protection from risk, and creation of business efficiencies. While a high percentage of respondents (81 percent) believe that the primary role of data is to help businesses grow, far fewer believe their current data can achieve that objective.

The report shows that despite the enormous potential of AI to support business objectives, organizations are slow to implement it. Surprisingly, only 25 percent of respondents shared that their organization has rolled out a budget plan for AI and data management initiatives. According to the respondents, the three biggest hurdles to AI deployment include incompatibility with existing systems, high costs, and data privacy and security concerns.

According to Dun & Bradstreet, master data management (MDM) could help overcome some of these challenges. MDM refers to creating a unified master data discipline that provides consistent, accurate, and complete data across the enterprise. It helps eliminate data silos to help build trust and drive performance. MDM also helps accelerate time to value, reduce time to deployment, and improve decision-making.

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The most authoritative and truest version of data, referred to as the “golden record” in the report, is a great enabler of achieving business outcomes, such as more effective marketing campaigns, improved customer relationship management, and streamlined business operations.

The implementation of the golden record is often hindered by differences in the definition of what the golden record means. This is not surprising as different disciplines within an organization have their own unique needs for data.

Taking the concept of the ideal state for data further, the report recommends organizations to aim for a “multifaceted golden record” that accommodates diverse versions of the truth. This helps capture the full richness of data and ensures all use cases are appropriately represented by the data.

As AI and other technologies continue to evolve at a rapid rate, organizations also need to adapt to the changes. Based on the findings of the report, organizations that are quick to implement a master data management strategy will be well-positioned to increase data quality, improve processes, and achieve their business outcomes.

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