Most orgs don’t have a data problem—they have a decision problem. This executive memo reveals why dashboards and training won’t fix culture, and what leaders must do differently to turn data into real decisions.
Most AI efforts fail not because of bad tech, but because of bad design. This article reframes AI as an organizational challenge, not just a data science project. Learn what business leaders must rethink to turn AI from a pilot into a competitive advantage.
Think your org is data-informed? Think again. Most companies are still making bad decisions—just with dashboards attached. Discover why traditional data literacy fails—and what it really takes to build a culture where data drives action.
The paper provides a comprehensive analysis of the potential benefits and risks of enabling business teams to conduct decentralized self-service analytics. It concludes that while empowering business users with analytics capabilities can provide faster insights and greater autonomy, a lack of governance can lead to inaccurate analysis and security issues. The paper recommends a balanced approach of phased adoption tied to analytics maturity assessments, strong data governance, positioning IT as an enabling partner, and instilling an enterprise-wide data-driven culture. It highlights that realizing the promise of self-service analytics requires developing analytical capabilities across business and IT, securing executive sponsorship and nurturing partnerships through cross-functional governance and collaboration. With concerted effort across people, process, technology, and culture dimensions, organizations can unlock significant upside from self-service analytics while mitigating risks.
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