Kroger Uncovers Millions of Units in Unfulfilled Demand Using Lumi

Introduction

Store Order vs. Distribution Shipment (OvS) is a critical supply chain metric at Kroger, measuring how well shipments align with store demand.

Problem

Kroger manages over 511K item–store and 1.8K vendor–DC combinations daily. Existing tools can’t analyze OvS at scale, forcing high-level summaries and manual workarounds, driving unresolved out-of-stocks. Identifying these trends required time-consuming manual analysis, delaying visibility into key opportunities.

Approach

With Lumi’s chat-based analytics interface, Kroger rapidly identified vendors with the largest gaps between their global OvS across all distribution centers (DCs) and local OvS at individual DC, filtering for vendor-DC pairs with material demand and unfulfilled units to surface only high-impact exceptions—all without manual reporting or complex SQL queries.

Impact

After analyzing 8 weeks’ worth of OvS data, Lumi flagged 46 vendor–DC combinations with significant OvS drops, representing 1.2M units of unfulfilled demand and cutting issue resolution time from days to minutes.

This approach demonstrated how AI-driven analytics can move beyond static reporting to deliver  speed, and operational insights across complex supply chains.