SmartWarehouse Smart Warehouse Analytics
US06

Dataset Methodology

Methodology

Metric Rule
Completion rate Confirmed tasks divided by total tasks
Short pick rate Tasks where picked quantity is below requested quantity
Exact-fill accuracy Tasks where picked quantity equals requested quantity
Over-pick rate Tasks where fill rate is above 1.0; shown separately from quality until classified
Median execution time Median start-to-confirmation minutes
Median cycle time Median creation-to-confirmation minutes
Backlog units in limbo Open tasks multiplied by average units per task

Interpretation Rules

Decision Reason
Prefer median over mean for cycle time Long-tail open tasks distort average performance
Compare cold and ambient separately Queue physics and labour conditions are materially different
Treat active tasks as operational risk, not completed work They represent unresolved inventory and service exposure
Rank labour by both productivity and concentration The top performer can also be a single-point-of-failure

Gaps Still Requiring Joins

Gap Needed join
Revenue or customer impact of short picks Order and shipment data
Product naming and category analysis Product master
Replenishment vs true pick exception Task classification or movement type
Labour cost per task Payroll or labour standard tables
On-time fulfilment Delivery schedule or carrier milestone data