In a well-run distribution center, data is everywhere. Warehouse management systems track transactions. Timekeeping systems record labor hours. Dashboards measure throughput, utilization, and performance against plan. Yet, many operations still struggle to answer a deceptively simple question: Why does performance sometimes fall short of expectations?

This challenge was at the heart of a recent proof-of-concept at Schneider Electric’s Athens Distribution Center (DC), where teams worked with Leela AI to explore how vision-based operations data could help uncover hidden sources of waste, validate process assumptions, and improve performance.

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