Analytics · Ports & Terminals
Terminal throughput and dwell-time analytics
A terminal operator measured container dwell and gate throughput to ease congestion and move boxes faster.
Microsoft FabricPower BIAzure Data FactoryDAX measures
- Dwell time
- -17%
- illustrative
- Throughput
- Per shift
- and hour
- Congestion
- Flagged
- early
- Areas covered
- Gate to berth
- full yard
Illustrative scenario · example figures
The challenge
Congestion built up at the gate and in the yard, but the operator had no measured view of dwell time or throughput to act on before it became gridlock.
What we built
We modeled gate, yard, and berth events into throughput and dwell-time analytics by container type, shift, and area.
- Dwell time by container type, status, and yard area.
- Gate and berth throughput by shift and hour.
- Congestion flags before the yard locks up.
Outcomes
- Dwell and congestion are measured instead of felt.
- Throughput bottlenecks are addressed before gridlock.
- Yard and gate resources follow real demand.
Where the data came from
Terminal operating systemGate eventsVessel schedulesEDI
Data is drawn from the systems the operation already runs on and delivered in the client’s own tenant.
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