Inventory Aging Analysis: A Retailer’s Guide
Inventory aging analysis explained. Bucket definitions, action thresholds, and how to use aged-inventory data weekly.
Inventory aging analysis bucks inventory into age cohorts (0–30 days, 31–60, 61–90, 90+) and tracks the dollar value in each. Aged inventory is markdown waiting to happen — surfacing it weekly prevents margin surprises.
Standard buckets
0–30, 31–60, 61–90, 91–180, 180+ days. Apparel and fashion may use tighter buckets (0–14, 15–28, etc.). Track total inventory value and percent of total in each bucket.
Action thresholds
Once inventory in a bucket exceeds a target percentage, trigger markdown action. Many retailers target less than 10 percent of inventory above 90 days; above that, a markdown plan is mandatory.
How to use aging data
Weekly review of top aged SKUs by dollar value. Tie buyer incentives to aging metrics. Create automatic markdown rules at age thresholds. Combine with sell-through data for full context.
Frequently Asked Questions
What is a healthy aged-inventory percentage?+
Less than 10 percent above 90 days for most retailers; less than 5 percent for fast-moving categories.
Should aging analysis be at SKU or category level?+
Both. Aggregate for finance, SKU for action.
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