With environmental, social, and governance (ESG) initiatives becoming more important for companies, our customer, one of Greater China region’s top convenience store chains, has been seeking a solution to reduce food waste (currently over $3.5 million USD per year). Doing so will allow them to not only realize substantial operating savings, but also support corporate sustainability goals.
In this post, we focus on forecasting demand of freshly prepared food by retail convenience stores. Our customer sells ready-to-eat food items with a short shelf life—typically 2–3 days. They faced two challenges: how to reduce food waste, and how to manage forecast models for over 10,000 SKUs and thousands of stores efficiently and at scale.
With Amazon Forecast, and support from the AWS ProServe team and AWS Machine Learning Solutions Lab, our customer—with limited internal data scientists—now has state-of-the-art forecasting capabilities. Within a few months, this forecasting solution has helped them reduce

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