Your peers in business intelligence are facing a contradiction. Massive volumes of data are pouring into dashboards, yet the people making decisions are overwhelmed. What used to be a data analyst’s careful query is now an automated suggestion; what used to be a meeting between analysts and
For years, companies have poured resources into business intelligence platforms, convinced that better dashboards would unlock better decision-making. But the uncomfortable truth is that BI doesn’t fail because of technology. It fails because of the people using it. Behind every metric, KPI, or
When enterprise teams discuss improving their business intelligence, the conversation often begins with tools: upgrading dashboards, layering predictive models, and automating reports. But beneath the surface of this endless stack expansion lies an issue more fundamental than any technical gap.
Everyone claims to be data-driven. From enterprise resource planning exports and customer relationship management dashboards to ESG metrics and sales forecasts—Business Intelligence teams are swimming in data. But in reality, most BI initiatives struggle because people can’t align fast enough to
Business Intelligence (BI) allows companies to minimize risks and surprises, which is a major advantage. Missed earnings, regulatory enquiries, and the like; usually result from unpreparedness or the inability to recognize red flags. Due to this fact, a significant portion of BI tools seems to aim
You can run the best models on pristine datasets. Still, a messy dashboard shuts the whole thing down. If it’s cluttered, hard to read, or built around developer logic instead of user needs, expect drop-off. Business Intelligence lives or dies by the experience. A dashboard isn't just a reporting
