How Size Curves and Pack Configurations Improve Inventory Performance

In this article, learn about: 

• How size curves influence inventory allocation, sell-through, and markdown risk. 

• When to use pre-packs, open stock, and bulk shipments to improve assortment performance. 

• How store-level sales data helps suppliers refine assortments and improve future planning. 

If you've ever watched a style sell out in medium while extra-small inventory sits untouched, you've seen the cost of a poor size curve. When stores receive the wrong mix of sizes, the result is more than a merchandising problem. Suppliers lose sales, retailers mark down excess inventory, and both sides miss revenue opportunities. 

A size curve helps prevent those outcomes by forecasting demand for each size before inventory reaches the sales floor. That forecast then becomes a pack configuration, or the assortment of sizes shipped to each store. 

The process sounds straightforward, but every planning decision has operational consequences. An accurate size curve means little if item data, carton labels, or shipping documents don't match what's inside the box. Likewise, flawless execution can't overcome a size curve that doesn't reflect actual customer demand. 

Here's how size curves and pack configurations work together, why they matter, and how suppliers can improve both over time. 

Related Reading: What is CPFR? Collaborative Planning, Forecasting, and Replenishment 

What Is a Size Curve? 

A size curve is a forecast that estimates how many units of each size a retailer expects to sell for a specific product. Instead of assuming every store needs the same assortment, size curves help suppliers match inventory to local demand, which can vary significantly. 

For example, one store may sell mostly medium and large sizes, while another consistently sells more small and medium. Shipping the same assortment to both locations increases the risk of stockouts in popular sizes and excess inventory in slower-moving ones. 

The strongest size curves combine several sources of information, including: 

• Historical sales data 

• Point-of-sale (POS) data 

• Regional buying patterns 

• Store characteristics, such as location and format 

Even a simple regional approach is often more accurate than using one national size curve across every store. For example:  

The goal isn't to create a perfect forecast. It's to improve inventory decisions enough to reduce stockouts, limit excess inventory, and increase full-price sell-through. 

How Size Curves Become Pack Configurations 

Once demand has been forecasted, suppliers must translate that forecast into physical shipments. That's where pack configurations come in. 

A pack configuration defines exactly which sizes are included in each carton. If a retailer orders a prepack containing one small, two medium, two large, and one extra-large, every store receiving that carton gets the same size assortment. 

Most suppliers rely on one of three approaches. 

Prepacks remain the most common option because they're inexpensive to process and help retailers stock shelves quickly. The downside is that mistakes are difficult to correct. If the size mix is wrong, every store receives the same imbalance. 

Open stock offers more flexibility because individual units can be picked to match each order, but that flexibility comes with higher labor costs and more complex fulfillment. 

Choosing the right pack configuration depends on how confident you are in your forecast. Established products with predictable demand often work well as prepacks. New products or new retail channels may benefit from open-stock replenishment until demand patterns become clear. 

Why Incorrect Size Curves Cost More Than You Think 

An inaccurate size curve can affect sales, profitability, and retailer relationships throughout the season. 

A common scenario results from inaccurate size curves: 

• Popular sizes sell out early. 

• Less popular sizes remain on shelves. 

• Stores develop broken size runs. 

• Retailers mark down excess inventory. 

• Suppliers lose full-price sales opportunities. 

When shoppers can't find their size, many simply buy another product.  

Retailers also monitor these patterns closely. Consistent inventory imbalances can influence future purchase decisions, replenishment strategies, and vendor scorecards. 

Old Navy’s Lesson on Poor Planning for Size Equality 

The apparel industry has seen the impact of incorrect size curves play out before. Old Navy's BODEQUALITY initiative expanded its women's assortment to include a broader range of sizes across its store fleet to reflect customer needs. While the initiative reflected a commitment to size inclusivity, demand varied significantly by location. Many stores sold through core sizes while excess inventory accumulated in less frequently purchased sizes. The result was broken size runs, increased markdowns, and inventory that didn't match local demand.  

Although Old Navy continues to offer extended sizing online and in select stores, the company scaled back the in-store rollout. The takeaway wasn't that extended sizing failed, but that successful size assortments depend on accurate, store-level demand forecasting. Without it, even well-intentioned merchandising strategies can create inventory imbalances that hurt sales and margins. 

The same principle applies to suppliers of every size. Better forecasting leads to better assortments, stronger sell-through, and fewer markdowns. 

Planning Is Only Half the Job 

A strong size curve depends on accurate execution. Suppliers should ensure every carton, label, and business document must match the physical shipment. Small errors in item setup or shipping data can create inventory discrepancies that ripple throughout the supply chain. 

That means suppliers need accurate product information, consistent labeling, and reliable electronic transactions from purchase order (PO) through delivery. 

Accurate Execution Keeps Inventory Moving 

A well-planned size curve only delivers results if suppliers execute it accurately. Every item record, carton label, and shipping document needs to reflect what's actually inside the shipment. Otherwise, retailers can receive incorrect inventory information before the cartons are even opened. 

Four areas deserve close attention. 

Item setup 

Every size in a pack needs accurate product information, including the correct universal product code (UPC) and stock-keeping unit (SKU). Many retailers also require pack-level identifiers so they can distinguish prepacks from individual units. 

If item setup doesn't match the physical contents of the carton, downstream systems won't either. 

Electronic data interchange (EDI) 

Electronic data interchange (EDI) keeps suppliers and retailers aligned throughout the order lifecycle. Documents such as the PO, advance ship notice (ASN), and invoice all need to reference the same product information. 

The ASN is especially important because retailers use it to prepare for incoming shipments before they arrive. If the ASN lists the wrong sizes or quantities, inventory records can become inaccurate from the start. 

Carton labeling 

Many retailers require GS1-128 carton labels to identify shipments throughout their distribution network. Missing or inaccurate labels can delay receiving, increase manual work, and lead to retailer deductions. 

RFID requirements 

Some retailers also require radio frequency identification (RFID) tags that meet specific formatting and placement standards. Because these requirements continue to evolve, suppliers should regularly review retailer compliance documentation before shipping new products. 

Each of these steps supports the same goal: ensuring the inventory that retailers expect is the inventory they actually receive. 

Related Resource: 2D Barcode and RFID Readiness for Retail 

Use Store-Level Data to Improve Future Size Curves 

Store-level POS data shows which sizes sold, where they sold, and when inventory became unavailable. That information helps planners identify patterns that shipment data alone can't reveal. 

For example, a shipment may appear successful because every unit left the warehouse. POS data tells a different story if medium sizes sold out within two weeks while extra-large inventory remained unsold for months. That visibility allows suppliers to adjust future assortments before the next buying cycle begins. 

Five Ways to Build Better Size Curves 

Improving size curves doesn't require a large planning team or sophisticated forecasting software. Many suppliers can make meaningful improvements by following a few practical steps. 

1. Start with retailer guidance. Many retailers provide recommended size curves based on category performance across their store network. Use those recommendations as a starting point instead of applying a national average to every location. 
2. Segment stores into logical groups. Even grouping stores by geography, format, or customer demographics can improve inventory allocation. 
3. Review size performance during the season. Don't wait until the end of the season to evaluate results. Mid-season POS reports often reveal opportunities to adjust replenishment orders. 
4. Match the pack type to forecast confidence. Stable, high-volume products often work well in prepacks. New products may benefit from open-stock replenishment until demand becomes more predictable. 
5. Review compliance requirements regularly. Retailer labeling, EDI, and RFID requirements change over time. Staying current helps avoid deductions and shipping delays. 

Better Planning Leads to Better Performance 

Size curves and pack configurations influence much more than inventory allocation. Together, they affect product availability, retailer performance, and profitability throughout the supply chain. 

The strongest suppliers continuously refine both planning and execution. They use store-level sales data to improve future forecasts while ensuring every shipment reflects accurate item data, labels, and electronic documents. 

SPS Commerce Analytics gives suppliers the visibility to evaluate size performance at the store level, identify demand patterns, and make more informed assortment decisions.  

SPS Commerce Fulfillment supports the execution side by helping suppliers exchange accurate electronic data interchange (EDI) documents, manage item data, and ship compliant orders that match retailer requirements. 

When planning and execution work together, suppliers can reduce stockouts, minimize markdowns, and deliver assortments that better match customer demand.