Analytics · Freight Forwarders
Container utilization and consolidation analytics
A forwarder analyzed container fill and consolidation opportunities to move the same goods in fewer boxes.
Microsoft FabricPower BIAzure Data FactoryDAX measures
- Fill rate
- +12 pts
- illustrative
- Consolidation
- Identified
- pre-booking
- Cost per unit
- Lower
- per shipment
- Lanes covered
- All
- major
Illustrative scenario · example figures
The challenge
Containers shipped under-filled because booking decisions were made in isolation, and no one could see where orders could have been consolidated.
What we built
We modeled volume and weight utilization per container and identified consolidation opportunities by origin, destination, and time window.
- Fill rate by volume and weight per container and lane.
- Consolidation opportunities by origin, destination, and window.
- Trend on utilization against target.
Outcomes
- Under-filled containers are visible and reduced.
- Consolidation opportunities are acted on before booking.
- Freight cost per unit shipped falls.
Where the data came from
TMSBooking recordsOrder dataCarrier EDI
Data is drawn from the systems the operation already runs on and delivered in the client’s own tenant.
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