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.
- 86% prediction accuracy in production.
- 11% increase in capacity utilisation across dock operations.
- Planning based on foresight instead of guesswork.