SKU Productivity Calculator
The SKU Productivity Calculator helps apparel merchandise planners and buying directors quantify how efficiently their assortment is working — converting season-end data into actionable productivity metrics: sales per SKU, sell-through rate, weeks of supply, markdown exposure, and the cost of non-productive styles.
Metrics calculated
Enter your season data
Your season data
Use season-end actuals for the most accurate picture. Estimates work fine for a directional view.
Sales & SKU Mix
Enter your season totals across all departments.
Total net sales for the season (after returns)
SKUs that sold at least one unit during the season
All SKUs bought into the season, including non-starters
Inventory & Season
Number of trading weeks in the season
Units on hand at season open
Units remaining at season close (before clearance markdowns)
Average selling price per unit across all active SKUs
Markdowns
Total dollar value of markdowns taken during the season
How to use these metrics to improve your next season
SKU productivity analysis is most valuable as a post-season planning input, not just a reporting exercise. The goal is to enter next season's pre-season planning with a clear view of which product categories drove disproportionate value and which consumed OTB without returning it.
A high non-productive SKU % (above 10%) typically indicates one of three things: over-width assortment selection, poor size/colour planning that creates phantom options, or a buy process that doesn't filter for commercial viability before commitment.
A high markdown rate (above 18%) in combination with a low sell-through (below 70%) is the signature pattern of an overbuy — often driven by OTB managed by feel rather than a connected plan. The fix is not buying less; it is building the receipt plan from a constrained OTB with a live view of committed vs remaining.
Frequently asked questions
What is SKU productivity in apparel planning?
SKU productivity measures how efficiently each SKU in your assortment generates revenue and turns inventory. The primary metric is net sales per active SKU — how hard each product is working. High-performing assortments generate $6,000–$12,000 per active SKU at mid-price apparel. Low productivity signals assortment over-width: too many styles chasing too few sales.
What is a good sell-through percentage for apparel?
A healthy pre-clearance sell-through rate for apparel is 75–85% at end of season. Below 65% indicates systematic overbuy — you are landing more inventory than the market will absorb at full price. Above 90% can indicate underbuying, which means leaving revenue on the table from stockouts.
What is weeks of supply (WOS) and why does it matter?
Weeks of supply (WOS) measures how many weeks your current inventory will last at the current sales rate. At end of season, a healthy WOS is under 6 weeks. Above 10 weeks means significant clearance markdown exposure. Tracking WOS weekly mid-season allows planners to take early action before overstock becomes a season-end crisis.
What percentage of SKUs should be productive?
Target is greater than 92% of introduced SKUs selling at least one unit. If more than 8% of your assortment are zero-sellers (non-starters), this signals selection risk in your buy process. Common causes: buying too narrow a commercial edit, over-reliance on new styles without testing, or poor size/colour range planning.
How is the deadweight inventory estimate calculated?
The calculator estimates the retail value of inventory tied up in non-productive SKUs using: non-starter SKU count × assumed 2-unit average depth × your average unit retail (AUR). This is a conservative estimate — actual depth varies. The purpose is to quantify the opportunity cost of assortment decisions, not provide an audit-grade figure.
How does RetailNorthstar improve SKU productivity?
RetailNorthstar tracks SKU productivity in real time throughout the season — not just at season end. Planners can see which SKUs are underperforming by week 4 and redirect OTB to productive reorders before the window closes. The system also flags assortment width risk during pre-season planning, before the buy is committed.
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