Ward monitors fill rate so your Fashion team can act on it early.
Store-level fill rate signals, caught before they compound into margin loss.
Why fill rate matters
in fashion retail.
Fashion fill rate must be measured at the style-size-color level. A store can hold 200 units of a dress and zero in the most popular size, technically "in stock," functionally a stockout. Ward surfaces broken assortments where key sizes are missing from otherwise healthy inventory positions.
Benchmarks. Healthy fashion size-level availability runs 85-92% on top styles by week 6 and 70-80% by week 10. Operators with active size rebalancing typically maintain 5-10 percentage points higher size-level availability and recover 2-4 points of full-price sell-through.
Broken size run detection, peak season
Ward reveals that a significant share of top styles have broken size runs across the chain, popular sizes depleted while other sizes sit. Ward recommends urgent inter-store transfers for the highest-revenue styles and a size curve recalibration for the next allocation cycle. Operations executes within 48 hours to protect at-risk revenue.
Three pitfalls Ward catches
in fashion fill rate.
- 01 Fill rate measured at the style level masks size brokenness, which is what the customer actually experiences in the fitting room.
- 02 OMS shows "in stock" when size XL is the only thing left; conversion craters but the dashboard reports availability.
- 03 Inter-store transfer thresholds are set on freight cost rather than at-risk full-price revenue; the math usually justifies more transfers than ops authorizes.
How Ward runs fill rate
for fashion retailers.
-
01
Measure availability at the SKU level
Ward computes size-level on-hand and projects depletion using current velocity per store, exposing broken runs by mid-season.
-
02
Calculate transfer ROI per gap
Each broken-size gap is paired with a candidate donor store; the freight-vs-revenue trade is computed so transfers run only where they pay.
-
03
Feed back into next-season size curves
Recurring size demand signals (XL under-allocated in cluster B, size 2 over-allocated in cluster A) become inputs to the next pre-season.
What a Ward card looks like.
Chat
Ask anything. Ward routes to the right agent and returns cited answers.
I pulled fall denim against last season’s curve at the same selling week. Two causes, both still fixable this week.
| Signal | Finding |
|---|---|
sell_through | Week 6 sell-through 38% vs. 52% plan, concentrated in 3 of 9 door clusters |
size_curve | Waist 30–32 sold out in 41 doors while 36–38 sits at 71% on hand |
markdown.ladder | First markdown is 3 weeks later than LY, weeks-of-supply now 11.4 |
Recommend: transfer 30–32 out of the 12 overstocked doors, hold the ladder on core indigo, and take the first markdown on light wash now while it still clears at 20%.
sell_through_weekly…
Dashboards
Pinned views built from saved data-lake queries.
Sources
Connect external systems to the data lake.
| Name | Type | Last sync |
|---|---|---|
shopify_orders_daily | import | 2m ago |
shopify_returns_reasons | import | 2m ago |
netsuite_inventory_snapshot | import | 14m ago |
cegid_store_sales | import | 1h ago |
retail_size_curve_actuals | import | 1h ago |
retail_markdown_ladder | import | 1h ago |
retail_ga4_website_daily | import | 1h ago |
Policies
Browse and manage Cedar access policies for your tenant.
| Policy ID | Effect | Resources |
|---|---|---|
merch-read-default | permit | Model::* |
finance-read-markdown | permit | Model::"markdown_ladder" |
vendor-blocked | forbid | Model::"labor_*" |
ecom-read-returns | permit | Model::"returns_reasons" |
Fashion fill rate:
the shift.
- ×Markdown timing
- ×Size curve misallocation
- ×Style velocity prediction
- ✓Estate-wide fill rate dashboard
- ✓Threshold-based alerting
- ✓Store-vs-estate benchmarking
Questions about fashion fill rate.
Fashion fill rate must be measured at the style-size-color level. A store can hold 200 units of a dress and zero in the most popular size, technically "in stock," functionally a stockout.
Ward reveals that a significant share of top styles have broken size runs across the chain, popular sizes depleted while other sizes sit. Ward recommends urgent inter-store transfers for the highest-revenue styles and a size curve recalibration for the next allocation cycle.
Ward tracks style-size-color availability, broken assortment rates, size-level sell-through velocity, and transfer opportunity value. It distinguishes supply-driven stockouts from allocation-driven gaps where inventory exists but sits in the wrong stores.
First fill rate insight cards arrive within 48 hours. Stable fashion baselines form within two weeks.
Fashion fill rate
by data source.
More Fashion insight cards.
Fashion retailers: see what fill rate problems Ward catches.
Root causes, not just alerts. See it on your data.
Read-only to start · your LLM keys · SOC 2 Type II underway · or book a call directly
Find out what your data has been hiding.
Tell us about your operation. We’ll show you the problems Ward catches, and the ones your current tools miss.