McDonald's China optimized its network, saving $63.75M on supply chain.

McDonald's China, the region's second-largest franchise, planned to open about 1,000 new restaurants a year. Its supply chain had to expand distribution to keep every store stocked, but adding warehouses and trucks one at a time was costly and inefficient.

In partnership with Xiahui Logistics and Optimization Analytics Technology (OAT), the company built a supply-chain network-planning solution using operations research. It evaluates the full network — suppliers, distribution centers, store demand and transport routes — and returns the optimal configuration.

The work saved $63.75 million in supply-chain investment and $8.9 million in annual transportation costs. By 2028 McDonald's China aimed to grow toward 10,000 stores, and the tools were built to keep re-optimizing the network as that expansion continued.

Optimize the network as one problem, not store by store

Store growth made the old, locally-planned network expensive and slow

Modeling suppliers, hubs and stores together reveals lower-cost configurations

Freshness constraints were incorporated rather than ignored

A network optimizer scales to thousands of nodes where manual planning cannot

A growing company's logistics network is a design problem, not an accumulation of decisions; solving it globally unlocks savings that local optimizations cannot see.

The project was named a 2024 Franz Edelman Award finalist, the only Chinese entry that year. McDonald's China planned to deploy the tools across its supply chain and data platforms for continuous network optimization and inventory planning as it expanded toward 10,000 stores.