Introduction

In retail supply chains, product variety drives customer loyalty — but it also introduces complexity. While fast-moving items receive most of the planning attention, a significant share of products moves slowly, occupies valuable warehouse space, and incurs higher handling and transport costs. Retailers with thousands of SKUs often grapple with the silent drag created by these low-velocity items. This article explores how better network design, inventory segmentation, and fulfillment placement can drive savings without compromising availability.

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The Hidden Cost of Variety

In 2023, Walmart operated over 150 distribution centers in the U.S., serving more than 4,700 stores. Its merchandise mix spans everything from perishable food to electronics, toys, and pet supplies — many of which have uneven demand across the year and region. A toothbrush head refill might sell five units a week in Phoenix and zero in Fargo. But under a decentralized fulfillment model, retailers often keep small quantities in multiple locations “just in case,” increasing holding costs, inefficient replenishment, warehouse congestion, and markdown or obsolescence risk. This isn’t about deadstock or obsolete goods — it’s about viable SKUs that are simply low velocity.

Real-Life Example: Overdistributed Toy Inventory at a Big-Box Retailer

In a recent public case study, Target’s supply chain team discovered that nearly 22% of their toy catalog SKUs were stocked across more than six regional distribution centers — even though 80% of sales for those SKUs came from just two regions. The original strategy prioritized availability over efficiency, but with post-pandemic freight costs spiking, the approach became financially unsustainable. Their analytics team developed a SKU rationalization model that clustered SKUs by demand intensity and geographic spread, identified regional outliers with excess safety stock, reassigned some SKUs to fewer ‘primary stocking nodes,’ and integrated store fulfillment and DC fulfillment logic. The result? A 12% reduction in network-wide toy inventory and a 14% improvement in trailer fill rate — all while maintaining >97% in-stock rate at the shelf.

Why the Traditional Forecasting Model Fails Here

Typical forecasting and replenishment tools are designed for high-volume SKUs, where demand signals are strong and consistent. For slower-moving SKUs, forecasts are volatile — and standard deviation often exceeds the average weekly demand. This volatility creates two failures: overdistribution (stocking too many sites due to uncertainty) and emergency replenishments (triggered when unexpected orders drain a site holding just 1–2 units). In both cases, cost goes up — via outbound shipping, underutilized trailers, or air freight when stock-outs hit.

A Smarter Approach: Placement Optimization Using Proximity and Demand Profile

Modern supply chain leaders are flipping the paradigm: instead of treating every fulfillment center as an island, they’re redesigning the placement strategy with proximity-based demand zones and SKU segmentation. Step 1: Classify SKUs by movement and margin using ABC-XYZ logic. Step 2: Create regional fulfillment zones to assign CZ SKUs to 2–3 regional hubs instead of spreading them across 10+ nodes. Step 3: Simulate fulfillment lead time impact to analyze if shipping from fewer nodes increases delivery time beyond SLA. Step 4: Align inventory targets with store and online forecasts to avoid duplication across e-commerce and store allocation systems.

Technology Stack: What Tools Are Needed?

Retailers don’t need to rebuild entire tech stacks to implement this strategy. They can start with multi-echelon inventory optimization (MEIO) tools, predictive analytics engines (e.g., using machine learning to spot placement inefficiencies), simulation tools like anyLogistix or Llamasoft to model node reduction scenarios, and inventory rebalancing logic in warehouse management systems (WMS). Some advanced retailers are layering AI to continuously monitor SKU-lane-cost performance — adjusting stocking nodes dynamically.

Cost Impacts: Where the Savings Come From

Retailers piloting this approach have unlocked value in three core areas:

1. Outbound Transport: 6–10% reduction via better trailer fill
2. Inventory Holding: 12–20% drop in redundant stock
3. Fulfillment Efficiency: 8–15% productivity gain in FCs

One retailer reported saving $9M annually by reducing low-velocity SKU stocking points from 12 to 4 across non-perishable categories.

Obstacles to Overcome

Rebalancing slower inventory is not without challenges: internal resistance from teams fearing SLA hits, decoupled systems that don’t talk across store and online inventory, and vendor replenishment contracts tied to multi-node commitments. But the payoff justifies the change — and success is often highest when retailers test a category (e.g., toys, home goods, books) before scaling.

Conclusion

In modern retail, efficiency doesn’t come from having every item everywhere — it comes from putting the right items in the right places, at the right time, with the right frequency. By redesigning how low-volume SKUs are fulfilled, retailers can unlock hidden working capital, reduce freight miles, and keep the customer promise — even with fewer touchpoints. As supply chains mature, strategic placement becomes just as vital as sourcing and forecasting.

Author Bio

Debanshu Sharma is a University of Michigan–trained logistics strategist with 15+ years of experience in global supply chain design and transportation optimization. He writes about predictive logistics, inventory optimization, and network transformation.