Fashion Inventory
Index
This index tracks 109 observable brands across US, UK, and European markets — anonymised, but specific. Every metric below is derived from public ecommerce signals: product availability, price history, size matrix changes, and social engagement timing. No surveys. No self-reporting.
Market Aggregates
Spotlight Brand Scorecard
| Brand | Stockout Rate |
Markdown Depth |
First MKD Timing |
Broken Sizes |
Promo Pntr. |
Health |
|---|---|---|---|---|---|---|
|
Skims
|
18% | –16% | Wk 11.4 | 12% | 15% | Strong |
|
Forever 21
|
38% | –29% | Wk 7.1 | 34% | 58% | At Risk |
|
Sezane
|
27% | –22% | Wk 9.8 | 25% | 32% | Watch |
|
Kith
|
44% | –21% | Wk 8.3 | 40% | 18% | At Risk |
|
Ganni
|
29% | –18% | Wk 10.9 | 21% | 26% | Watch |
|
Lululemon
|
14% | –12% | Wk 12.1 | 10% | 8% | Strong |
|
ASOS
|
42% | –35% | Wk 6.5 | 38% | 62% | At Risk |
|
Aritzia
|
19% | –15% | Wk 10.5 | 14% | 12% | Strong |
|
Boohoo
|
48% | –40% | Wk 5.2 | 45% | 70% | At Risk |
|
Everlane
|
25% | –20% | Wk 9.0 | 28% | 22% | Watch |
|
Cohort Avg
|
31% | –24% | Wk 9.2 | 26% | 30% | — |
Forever 21 stocked out of core sizes 4 weeks before Skims cleared equivalent items, leading to a much higher Broken Size Ratio (34%) — while having a Promo Penetration of 58%. That gap is not a demand problem. It is a planning problem: an OTB decision made without a signal weighting model that accounts for hero vs. growth vs. markdown-exit SKUs differently.
Analysis: Size-Level Stockouts
Percentage of tracked SKUs that registered OOS for each size before week 8 of season. Sizes showing >40% OOS rate indicate systematic under-allocation, which drives a high Broken Size Ratio (where core sizes are sold out, leaving only extreme sizes).
Size-level stockout data exposes a stark market divide. In 76 of 109 tracked brands (most heavily in Fast Fashion), we observed a recurring pattern: fringe sizes (XS, XL) disappear from the size selector an average of 3.5 weeks earlier than core sizes (M, L). By cross-referencing with pricing data, brands trapped in this pattern are forced to initiate their first site-wide markdown 14 days earlier than the cohort average just to clear the stranded M/L inventory. In contrast, DTC natives like Skims maintain a highly balanced availability matrix across the first 8 weeks, allowing them to hold full-price integrity significantly longer.
Analysis: Pricing & Agility
Distribution of brands by when they initiate their first season-wide markdown.
Mapping our Spotlight Brands by their speed to market (Trend Lag) against buying accuracy (Stockout Rate).
Analysis: Assortment Shifts
While many brands claim a "Wide & Shallow" strategy during economic downturns, our Depth Index tracking reveals the opposite: brands are retreating to safety by offering fewer styles but more colors per style. Simultaneously, the low Size Inclusivity Index (12%) across the cohort indicates that extended sizing remains a marketing talking point rather than a true operational investment.
Top 10 Spotlight: Deepest Assortment (Colors per Style)
| Rank | Brand | Depth Index | vs Cohort Avg (3.2) |
|---|---|---|---|
| 01 | Skims | 8.5 | +165% |
| 02 | PANGAIA | 6.8 | +112% |
| 03 | Ganni | 6.2 | +93% |
| 04 | Savage x Fenty | 5.9 | +84% |
| 05 | Kith | 5.4 | +68% |
| 06 | Outdoor Voices | 4.9 | +53% |
| 07 | Sézane | 4.5 | +40% |
| 08 | Suitsupply | 4.2 | +31% |
| 09 | Marmot | 3.9 | +21% |
| 10 | KUIU | 3.8 | +18% |
Analysis: Hidden Margin Leaks
| Metric Focus | Cohort Median | Top Quartile | Bottom Quartile |
|---|---|---|---|
|
Price Resilience
Avg days from launch to first discount
|
64 days | 82+ days | < 21 days |
|
Stealth Markdowns
% of SKUs discounted without a "Sale" badge
|
14% | < 5% | > 28% |
|
Colorway Divergence
Difference in days to OOS (Best vs Worst color)
|
31 days | < 10 days | > 60 days |
|
Restock Velocity
Days between size going OOS and reverting to Available
|
11 days | < 4 days | > 21 days |
|
Zombie SKU Rate
>12 wks old + >30% off + full size run available
|
12% | < 4% | > 25% |
The data reveals a staggering gap in Restock Velocity. While contemporary leaders like Sézane and Ganni (Top Quartile) resolve stockouts in just 3-4 days, traditional giants like Forever 21 leave shelves empty for over 3 weeks, directly bleeding revenue to competitors.
All data is derived from publicly observable ecommerce signals: product availability matrices, price delta tracking, and social post engagement timing. Brands are anonymised by revenue band and category. Metrics reflect online channels only — in-store inventory is not observable. Stockout detection is based on size selector disappearance or explicit OOS flags; brands that suppress OOS listings entirely may be undercounted. Trend lag is calculated against the brand's own Instagram post engagement peak, not industry-wide trend indices. This is a signal-based, not survey-based, publication. Figures are directional benchmarks, not audit-grade data.
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Data observed from public ecommerce sources. Not financial advice.
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