How AI Helped a Retailer Prevent Stockouts
A national retailer combined optimization modeling with large language models to address the issue.
Supply chain leaders have long utilized optimization to make sense of complexity, from network design to replenishment, as mathematical models promise clarity in uncertain situations.
However, while these models excel at generating optimal solutions, they often fail to communicate them effectively, leading to a communication gap.
When the plan cannot be explained, it will not be adopted.
This paradox results in companies investing heavily in optimization engines, yet the resulting plans are frequently reworked, delayed, or ignored, with planners creating "shadow" spreadsheets and executives requesting simplified summaries that lack nuance and confidence.
In 2024, a national hardlines retailer directly addressed this problem.
Author's summary: AI helps retailer prevent stockouts by optimizing supply chain.