Buffer or suffer: Dynamic Multi-Echelon Inventory Optimization in action

Editor's note: The SCM thesis Buffer or Suffer: Dynamic Multi-Echelon Inventory Optimization in Action was authored by Vi Duong and Nic Holwerda, and supervised by Dr. Eva Ponce ([email protected]). For more information on this research, please contact the thesis supervisor.

Wake-up call: 57 days of supply – still missing the mark

In today’s retail world, too much inventory is as risky as carrying too little. One U.S. grocery chain, operating a hub-and-spoke distribution model, held 57 days of supply for dry food. Inventory turnover was low, safety stocks were excessive, and service levels still varied widely.

This issue? As business expanded and SKUs multiplied, traditional inventory policies fell short of managing the network effectively. To regain control and strike a better balance between availability and capital efficiency, the company adopted dynamic Multi-Echelon Inventory Optimization (MEIO), a network-wide planning approach.

When one size does not fit all

Traditional inventory management optimizes one node (inventory-holding location) at a time. In contrast, MEIO treats the entire supply chain—from plants to hubs to spokes—as an interconnected system. The MEIO approach helps to mitigate the bullwhip effect often observed in traditional, or single echelon, optimization approaches. As explored in our capstone research, applying MEIO dynamically (regularly updating inventory policies based on changing conditions) can unlock even greater value.

This capstone analyzes the value of dynamic MEIO by running multiple planning scenarios for 61 SKUs across 31 nodes in our sponsor’s retail network. Using Coupa’s Supply Chain Guru—a platform powered by AI and advanced optimization— we modeled 18 scenarios combining six update frequencies (annual to weekly) and three service level targets (90%, 95%, 99%). Products were segmented by demand volume and variability to reflect differing inventory needs.

Why so many scenarios? Because one size does not fit at all.

Our analysis showed that high-variability products benefit from more frequent updates, which better align supply with volatile demand. On the other hand, stable, low-variability SKUs see minimal gains from frequent updates and may incur unnecessary costs. A one-size-fits-all approach misses these nuances and the opportunities they represent for the organization.

Segment. Target. Win: High service, lean inventory

Our most compelling finding? Dynamic MEIO reduced total inventory value by up to 63%—about $9.3 million annually—for just 61 SKUs. Even a conservative annual update cut working capital by 40%, freeing up cash without sacrificing service levels.

While high service targets (like 99%) typically demand more safety stock, frequent updates allow inventory to adjust in near real time. This makes high service levels more affordable—a major win for retailers focused on customer experience.

Savings were not evenly distributed. Over 50% came from hub-level inventory reductions while spokes, where demand is more predictable, contributed only 2%. This highlights upstream overstocking as a key opportunity and MEIO as the tool to unlock it.

The biggest gains came from moving inventory policies from annual to biannual updates. More frequent updates delivered diminishing returns, particularly for low-variability SKUs. This insight helps teams focus effort where it delivers the most value.

Final word: MEIO is a strategic trade-off

Dynamic MEIO isn’t a one-size-fits-all solution. It’s not plug-and-play—it involves upfront investment, setup time, and close coordination between planning and operations teams.

But for businesses facing high demand variability or targeting premium service levels, the value is clear.

MEIO is about more than cutting inventory. It represents a shift from static, reactive processes to adaptive, data-driven strategies. For supply chain leaders, it offers a powerful framework to balance service and capital, risk and agility.

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