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The Analyst Revolution report, which was a comprehensive study aimed at identifying costly inefficiencies and opportunities to maximize enterprise data analysts' productivity, has been officially published by dbt Labs, the leader in standards for AI-ready structured data. Going by the available details, this particular report was developed in close collaboration with The Harris Poll. More on the same would reveal how it reveals that organizations are losing 9.1 hours per analyst each week to inefficient workflows, totaling upto $21,613 per employee annually from a monetary standpoint.
Beyond that, the findings also reveal how organizations can seamlessly build a competitive advantage, transform analyst roles, and drive impact through investing in governed, AI-powered self-serve platforms.
“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.”
When we delve a little deeper into the given report, we begin with a piece of discovery that asserts that analysts spend no more than 22% of their days generating insights, with the remaining 78% devoted to tasks such as data preparation, validation, tool navigation, and other activities. As for why that is the case, 62% report feeling overwhelmed by the number of tools required to do their jobs. The average analyst essentially uses 5.4 platforms daily and switches between tools nearly six times per day, causing 65% of professionals to experience burnout.
Next, the survey found that most analysts (89%) have used tools that aren't approved because they can't access the data they need. You have to understand that, while 40% use personal API keys or free online tools to process organizational data, well over half (54 percent) admit to using AI tools like ChatGPT to analyze company data outside of approved systems. In case that wasn’t bad enough, 32% also admit to creating workarounds for bypass governance processes entirely, and an equal number use personal software or tools not approved by IT. Having said so, there remains an awareness regarding the detrimental nature of this approach, as 63% reported that working outside governed systems actually delays their projects and requires retroactive validation.
William Tsu, Senior Analytics Engineer at WHOOP, stated, "As our data needs evolve, empowering analysts with seamless self-exploration becomes increasingly critical." "dbt’s new analyst offerings enhance discoverability and enable faster, more intuitive, and governed self-service." Another interesting fact revealed by the dbt survey is that while 72% of data analysts state that their company is not investing enough in AI-powered platforms, 90% of them agree that they urgently require more effective tools to meet business needs. The aforementioned 90% have the intention of incorporating additional AI tools to assist with tasks like automated visualization (42%) and real-time data quality detection. In fact, analysts' wish lists include task automation powered by AI as the single most valuable platform feature. Moving on, it was found that 93% of analysts believed that an all-in-one platform would help them work more efficiently. On the other hand, 96% of analysts were found to be more likely to stay with companies that invest in workflow optimization. Against that, 85% said they would consider leaving employers who use outdated tools.
It is important to note, among other things, that the opinions of more than 510 data analysts, business analysts, quantitative analysts, data specialists, and data scientists working in industries such as finance, healthcare/pharmacy, and consumer packaged goods/retail, among others, were taken into account in this particular survey. Making this development even more important would be the fact that more than 80,000 data teams use dbt, including those at Siemens, Roche and Condé Nast, to support their operations.
Mark Porter, dbt Labs' CTO, stated, "It's clear that analysts want to work with data in a way that makes them more productive and also more fulfilled at work." “Analysts of today are often overwhelmed by manual, time-consuming tasks and are susceptible to being held up by engineers. 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.”
