dbt Labs and The Harris Poll’s Analyst Revolution report reveals tool sprawl and inefficient workarounds drain productivity, while analysts seek AI platform investment
dbt Labs, the leader in standards for AI-ready structured data, published its Analyst Revolution report, a comprehensive study uncovering costly inefficiencies and opportunities to maximize productivity in the work of enterprise data analysts. Developed in partnership with The Harris Poll, the report reveals that organizations are losing 9.1 hours per analyst each week to inefficient workflows, equating to $21,613 per employee annually. The findings also reveal how organizations can build a competitive advantage, transform analyst roles and drive impact through investing in governed, AI-powered self-serve platforms.
Excessive admin work drives inefficienciesÂ
According to the report, data analysts are consumed by administrative and low-value tasks, hampering their ability to deliver strategic insights. Analysts spend, on average, only 22% of their day generating insights, with the remaining 78% consumed by data preparation, validation, tool navigation, and other tasks.
For many, the source of this inefficiency is tool overload; 62% report feeling overwhelmed by the number of tools required to do their jobs. The average analyst uses 5.4 platforms daily and switches between tools nearly six times per day. And as a result, 65% experience burnout.
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Technology bottlenecks lead to shadow IT
Due to these inefficiencies, analysts create workarounds that expose their organizations to governance, compliance, and security risks. Most (89%) analysts have experienced limitations in available data tools or data access, driving many to use unapproved tools. More than half (54%) admit to using AI tools like ChatGPT to analyze company data outside of approved systems, while 40% use personal API keys or free online tools to process organizational data.
Concerningly, 32% admit to creating workarounds to bypass governance processes entirely, and an equal number use personal software or tools not approved by IT. Many admit this is counterproductive, with 63% reporting that working outside governed systems actually delays their projects and requires retroactive validation.
“The number of professionals working around governance systems is alarming, but it’s a clear sign for leaders that data teams need better technology that enables them to streamline and accelerate their work,” said Libby Rodney, Chief Strategy Officer at The Harris Poll. “The onus is now on leaders to implement solutions that will reduce friction and boost agility.”
AI tools are in demand
The findings reveal a key gap in AI adoption. While 72% of data analysts report their organization isn’t investing enough in AI-powered platforms, 90% agree they desperately need more efficient tools to meet business demands.
Data analysts are also optimistic about increasing their AI usage, with 90% hopeful to incorporate more AI tools into their workflows to support tasks like real-time data quality detection (42%) and automated visualization (40%). In fact, AI-powered task automation ranks as the single most valuable platform feature on analysts’ wish lists.
“It’s clear that analysts want to work with data in a way that makes them more productive, but also more fulfilled at work,” said Mark Porter, CTO of dbt Labs. “Today’s analysts are drowning in manual, labor-intensive tasks and can be bottlenecked by engineering counterparts. AI can bridge that gap if it’s properly integrated into governed workflows. The companies that provide unified platforms will create a symbiotic relationship where AI reduces time-consuming work and frees analysts to deliver the strategic insights that drive the business forward, ultimately boosting morale and personal fulfillment.”
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Top tools are key to talent retention and productivity
Modern tools have become a make-or-break when it comes to talent retention — 93% of analysts believe an all-in-one platform would increase their productivity. Nearly all analysts surveyed (96%) are more likely to stay with employers who invest in workflow optimization, and 85% saying they would consider leaving employers who use outdated tools.
Analysts who gain access to better platforms with self-service capabilities expect significantly better outcomes: 47% anticipate an improved ability to develop more impactful insights and 43% expect significant improvements in data quality and consistency.
“As our data needs evolve, empowering analysts with seamless self-exploration becomes increasingly critical,” said William Tsu, Senior Analytics Engineer at WHOOP. “dbt’s new analyst offerings enhance discoverability and enable faster, more intuitive, and governed self-service.”
