Predictive analytics: the new hot ticket in shipping?

Predictive analytics: the new hot ticket in shipping?
Joe Baker 28 February 2018

The adoption of predictive analytics for port operations is proving increasingly popular, as the technology can help ports help achieve better unloading and offloading times and less truck idling. But despite successful case studies in the US, challenges still remain in the implementation of new predictive technologies.

Predictive analytics is commonly defined as the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes.

Using new technologies to enable enhanced collection, storage and analysis of historical data, shipping companies are able to make predictions to enhance their operations. For example, sensor data can be used to identify which areas require priority in terms of maintenance, reducing the amount of time they need to be dry-docked and preventing delays.

Nevertheless, predictive analytics is also being increasingly used to speed up various steps in the supply chain. From a shipping perspective, certain ports are beginning to invest in predictive visibility projects as a means of keeping cargo moving when ships come in to dock.

“If one can more accurately predict when a ship arrives (or even better, when a specific container gets unloaded from a ship), many of the processes needed to move this container from the port to the final customer can be planned ahead of time,” says ManWo Ng, assistant professor of maritime and supply chain management at Old Dominion University in Virginia, US.

“For instance, terminal resource needs can be optimised, motor carriers can be better informed and containers can be picked up sooner, clearing congestion in container yards.”
The growing need for data analysis

For maritime, the concept of predicting the future is not a new one. According to Ng, terminal operators “have done forecasting for as long as there have been seaports”. Nevertheless, certain technologies, such as radio-frequency identification (RFID) and differential global positioning systems (DGPS), have facilitated the collection of more accurate real-time information. This enables a more precise prediction of when cargo will be available for pickup.

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