Technology

A recent survey by Gartner, Inc. has found that 30% of chief data and analytics officers (CDAOs) identify the inability to measure data, analytics, and artificial intelligence (AI) impact on business outcomes as their top challenge.

The annual Gartner Chief Data & Analytics Officer Agenda Survey, conducted between September and November 2024, gathered insights from 504 data and analytics executives worldwide. The findings highlight a significant gap in defining and tracking business impact metrics for data-driven initiatives.

Michael Gabbard, Senior Director Analyst at Gartner, emphasized the growing emphasis on data value but noted that few organizations can substantiate its impact. “There is a massive value vibe around data, where many organizations talk about the value of data and desire to be data-driven, but few can substantiate it. Often, organizations that regularly align with data themes outperform their peers,” he said.

More than 90% of surveyed CDAOs reported that value- and outcome-focused areas have become their primary focus over the past 12 to 18 months. However, only 22% of organizations have defined, tracked, and communicated business impact metrics for most of their data and analytics (D&A) use cases.

Gabbard highlighted the need for a stronger D&A strategy, stating, “Organizations are increasingly prioritizing the development of a robust D&A strategy to enhance decision-making and operational efficiency. CDAOs must accelerate data-driven and decision-centric visions by spotting key trends early and making proactive, informed choices.”

The survey also found that 91% of CDAOs consider creating an actionable D&A strategy a primary responsibility. However, more than one-third do not view establishing and evolving the operating model as a priority. “There is a perennial gap between planning and execution for D&A leaders,” Gabbard added.

Gartner clients can access more insights in reports such as “2025 CDAO Primer: Lead a World-Class Data and Analytics Organization” and “Ignition Guide to Build a Data and Analytics Strategy in the Age of AI.”

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