Ward for
Fashion retail.
Markdown timing. Size curve misallocation. Seasonal sell-through, size curve optimization, and markdown timing. Ward monitors style velocity and flags slow movers before the window closes.
Ranked on GMROI and velocity together, not units alone, so profitable slow movers survive the cut.
gmroi.sku | 412 SKUs below $0.90 GMROI holding $1.8M in working capital |
|---|---|
assortment.gap | 31 SKUs selling in the urban cluster are unstocked in a demographically matched cluster |
Gross lift looked strong. Net of cannibalisation and pull-forward it destroyed value.
promo.gross_lift | Promoted SKU +41% against its own baseline |
|---|---|
promo.net | After category cannibalisation and pull-forward, net contribution −$14K |
Pulled Store 37’s last 28 days against the chain baseline. Two compounding causes.
labor_efficiency | Revenue per labor hour −22%, staffing miss at the 11a–1p peak |
|---|---|
promo.lift | BOGO crackers cannibalised Brand Y −28%, net category only +6% |
Three stores in the ten-store cluster breach the 2% threshold on one SKU. The cause is upstream, not theft.
shrink.rate | Stores 4, 11, 19 at 2.4–3.1% against a 1.2% cluster baseline |
|---|---|
delivery.defect | All three take delivery from the same lane, defect rate 4.8% above goal |
Problems Fashion operators
find too late.
The failure modes that usually surface in a post-mortem, weeks after anyone could act on them.
Source: McKinsey State of Fashion Report
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" |
Where Fashion operators
leave money on the table.
The KPIs Ward monitors, and what changes when someone is watching.
Ward requires at least 2 full selling cycles to baseline style velocity and markdown timing. Results vary between basics and trend-driven categories.
Insight cards for Fashion.
What Ward covers
for fashion retail.
Fashion integrationsRead-only by default.
Built for fashion leadership
Metrics Ward moves
Platform pieces fashion teams lean on
Operator stories
and the alternatives.
Questions about Ward for fashion retail.
First insight cards within 48 hours of connecting to your data. Stable baselines across 15,000+ SKUs and your store estate within roughly two weeks.
Ward connects to the systems fashion operators actually run: ERP, POS, e-commerce, data warehouses, and BI tools. Read-only API access. No data movement required.
No. Ward sits on top of the data your dashboards already visualize and surfaces what changed, why, and what to do, between dashboard refresh cycles, while your team is doing other work.
Two ways to start.
A fixed-fee pilot on your fashion data, or a broader advisory engagement.
Playbooks for Fashion.
By department and system.
Tuned to Fashion & Apparel velocity and systems.
Merchandising
See what Fashion operators are missing.
Ward finds the margin leaks, shrinkage patterns, and promo misfires your reports don’t surface.
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.