In this paper, Simcog explores predictive analytics and how its is used to enhance the efficiency of container handling in ports.
Predictive Analytics is used at a container terminal in Hamburg. By predicting the way of ongoing transport and the time of pickup it is possible to increase handling efficiency and to maximize the trading volume on a limited storage space.
In today’s container logistics landscape information is distributed unevenly. While there is GPS data readily available and many terminals are highly automated, the information link to the hinterland is rather weak.
As a consequence, most ports do not know when and how a container will be picked up after it arrives by ocean carrier. Attempts have been made to increase exchange of information, but there are many small stakeholders in the transport business.
There is small incentive for a small lorry-transport company to introduce planning software or even to decide in advance when to pick up a container. Moreover, ports rely heavily on computers and since A.P. Moller-Maersk was hit by ransomware in 2017 that caused a huge amount of damage, it is good practice to reduce connectivity to the outside.
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