When analytics teams operate in silos, organizations miss out on efficiency, alignment, and strategic insight. At a major food distributor, fragmented analytics efforts were creating duplicated work, inconsistent metrics, and confusion about which reports to trust. Teams spent more time reconciling numbers than using them to drive decisions.

Seeing the need for change, I led the integration of analytics functions into a unified, enterprise-wide operating model. As a first step, I formed a cross-functional council of data leaders across sales, operations, and finance. This group established clear ownership of critical metrics, fostering accountability and reducing conflicting definitions that had previously slowed decisions.

To support this ownership model, I led the development of the organization’s first enterprise data catalog. This catalog documented both technical and business definitions for key metrics such as on-time delivery and gross margin, creating a single source of truth accessible across teams.

In parallel, I rationalized the Power BI reporting landscape. By analyzing usage patterns, documenting ownership, and retiring reports with no documented use, we significantly reduced unnecessary maintenance work. Analysts regained time to focus on higher-value insights instead of managing redundant reports.

To strengthen communication and governance, I introduced an enterprise-wide release notes repository. This tool automatically alerted analysts when updates were made to data assets – including reports, semantic models, and data flows – and included important metadata to support efficient change management.

Building a stronger analytics community was equally important. I established a Power BI community of practice with quarterly training sessions and designed a course to prepare analysts for the Power BI Data Analyst certification exam. This empowered analysts with new skills while reinforcing standards and best practices.

The results were transformative. Definitions were aligned, confidence in reporting grew, and issue resolution times for critical data elements like gross margin decreased significantly. For the first time, the organization had truly enterprise-wide reporting, backed by clear ownership and data quality accountability across domains. Analytics evolved from isolated teams into a strategic partner, delivering faster, more impactful insights that moved the business forward.