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Definition
Per-day inventory rollup by (warehouse, category). Use `unique_skus_below_reorder` for cross-warehouse summaries — averaging `under_reorder_pct` unweighted misleads. Stockouts (`on_hand_qty=0`) are tracked as a count, not a percentage.
Watch out for
- highAveraging `under_reorder_pct` across warehouses unweighted
Each (product, warehouse) pair has its own reorder point; an average-of-averages weights small warehouses equal to large ones. Use `unique_skus_below_reorder` (a count) for cross-warehouse summaries.
- highSumming `on_hand_qty` across snapshot dates
These are point-in-time snapshots; summing across dates double-counts the same inventory. Use a `start_day=end_day` filter for current state, or `avg()` for the period mean.
Questions this answers
- “How many SKUs are below reorder by warehouse today?”
- “Stockout count by category over the last 30 days.”
Related metrics
- revenue
Stockouts cap revenue — out-of-stock SKUs lose sales.
- fulfillment_sla
Inventory location determines transit time.
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Column
Type
Description
Tests · PII
snapshot_date
Date
Snapshot date.
1 test
warehouse_code
String
`us-west` / `us-east` / `eu-central`.
1 test
category
String
Product category from the catalog (coalesced to `unknown`).
1 test
on_hand_qty
Int64
Sum of `on_hand_qty` in the bucket.
2 tests
reserved_qty
Int64
Sum of `reserved_qty` in the bucket.
2 tests
available_qty
Int64
Sum of `available_qty`. May go negative on overcommit.
1 test
unique_skus
UInt64
Distinct product_id count.
1 test
unique_skus_below_reorder
UInt64
Distinct product_id count where `on_hand_qty <= reorder_point`.
1 test
stockout_count
UInt64
Count of rows where `on_hand_qty = 0`.
1 test
avg_reorder_point
Decimal(10, 2)
Mean reorder_point across SKUs with a non-zero target. Decimal(10,2).