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Why did Store 37 miss target last week?

You · 9:42 AM

Schema Scout · routed to Merchandising Agent

I pulled Store 37’s last 28 days against the chain baseline. Two root causes, both compounding.

Signal	Finding
labor_efficiency	Rev/labor-hour −22% vs. cluster, staffing mismatch at 11a–1p peak
inventory.fresh	Fresh fill 83%, backroom replenishment lag at 2–4p
promo.lift	BOGO crackers cannibalized Brand Y by 28%, net category +6%

Recommend: re-baseline Store 37 schedule against true peak, raise replen window to 1p, and review the BOGO before next cycle.

8 parallel queries 3 sources cited confidence 0.92

Show me how to fix the staffing mismatch.

You · 9:43 AM

Labor Agent · drafting schedule diff

Querying labor_scheduling…

› Ask anything, Ward routes to the right agent. Cmd+K

Reporting

Pinned views built from saved data-lake queries. Every number re-derivable from its SQL.

7d13w52w

Revenue vs. forecast

$48.2M

+4.2% WoW

Gross margin %

24.1%

−3.2pp

Fill rate, fresh

83.4%

−4.1pp

Shrink, West region

2.41%

+0.8pp

Revenue vs. forecast 13 weeks actual, 6 weeks forecast, 80% interval

Actual Forecast 80% interval

Holt-Winters + weather regressor MAPE 4.1% at 4wk Backtested 24 months Crosses plan in 3 weeks

Forecast error by horizon MAPE, 24-month backtest

1wk 2.1%

2wk 3.0%

4wk 4.1%

8wk 6.3%

13wk 8.9%

Accuracy bar for promo decisions: ≤5% at 4wk

Models in production Every forecast ships a model card

Model	Horizon	MAPE
holt_winters	4wk	4.1%
arima_sarimax	13wk	8.9%
gbm_demand	1wk	2.1%
bayes_hier	new store	11.4%

Sources

Connect external systems. Ward AI maps the schema and drafts the cleaning rules.

+ New source

Search sources…

Name	Type	Last sync
sap_pos_transactions	import	2m ago
sap_inventory_shrinkage	import	2m ago
sap_labor_scheduling	import	14m ago
retail_inventory_weekly	import	1h ago
retail_google_ads_daily	import	1h ago
retail_meta_ads_daily	import	1h ago
retail_ga4_website_daily	import	1h ago

Architecture

Two ways to connect. Federate against your live systems, or ingest into Ward’s data lake. Toggle below.

Federated query Data lake ingest

Your systems · read-only

SAP Retail

Snowflake

BigQuery

Shopify

NCR Voyix

Ward Gateway

TLS 1.3 · AES-256

Querying live · data stays put

Federated answers

SELECT * FROM sap.pos

JOIN retail.inventory_weekly

WHERE store_id = 37

→ insight cards

Ward Data Lake

→ baselined per store

TLS 1.3 in transit AES-256 at rest Read-only credentials SOC 2 Type II underway VPC peering · PrivateLink