Case Study: Kroger uncovers 1.2M units of unfulfilled demand with Lumi AI

Kroger Uncovers Millions of Units in Unfulfilled Demand Using Lumi

Kroger, one of the largest retail companies in the United States, faced a challenge in its supply chain. Their existing tools could not effectively analyze the vast volume of daily store orders versus distribution shipments (OvS) at scale. This inability forced teams to rely on high-level summaries and manual workarounds, which delayed the identification of unresolved out-of-stocks and hidden demand.

Using Lumi's chat-based analytics interface, Kroger rapidly pinpointed high-impact exceptions in its supply chain without manual reporting. The solution from Lumi analyzed over 511,000 item-store combinations and identified 1.2 million units of unfulfilled demand. This cut the issue resolution time from days to just minutes, allowing Kroger to quickly address significant vendor-distribution center gaps.

Kroger

Lyle O’Banion

Demand Planning