How AI Helped a Retailer Prevent Stockouts
A national retailer combined optimization modeling with large language models to address supply chain complexity.
Supply chain leaders have long used optimization to make sense of complexity, from network design to replenishment, as mathematical models provide clarity in uncertain situations.
However, these models often struggle to communicate their solutions effectively, leading to a communication gap between optimization software outputs and planners who must execute the plans.
As a result, companies invest heavily in optimization engines, but the resulting plans are often reworked, delayed, or ignored, with planners relying on "shadow" spreadsheets and executives requesting simplified summaries that lack nuance and confidence.
In 2024, a national hardlines retailer tackled this problem directly by leveraging AI.
The optimization software outputs do little to reassure a planner, who must execute the plan. When the plan cannot be explained, it will not be adopted.
Author's summary: AI helps retailer optimize supply chain.