Case studies Transport & logistics
Forecasting empty containers to free up dock space
A container shipping company
86%prediction accuracy on empty container arrivals
11%
Higher capacity utilisation
GCP
Production platform
The challenge
Stacks of empty containers occupied prime berth space. Because arrivals were unpredictable, operations planned capacity on gut feel and historical patterns that no longer held.
What we built
- An automated ETL pipeline unifies operational data from siloed systems.
- A machine learning model predicts how many empty containers will arrive and where they will return.
- Forecasts feed directly into capacity and scheduling decisions.
The results
- 86% prediction accuracy in production.
- 11% increase in capacity utilisation across dock operations.
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