By incorporating these historical trends with satellite navigation and each vessel’s declared arrival time, the model proved more accurate than the port operator’s previous system. More precise arrival times enabled more accurate workforce planning, which, in turn, enabled better anticipation of potential choke points and allowed for real-time suggestions of faster driving routes through the yard. Together, these three solutions helped enable a significant increase in the port’s efficiency that created substantial cost savings within just four months of the initial proposal. For vessel prediction alone, the team increased accuracy by 3% beyond the client’s benchmarks, which translates to approximately US$10.2 million in savings. Most importantly, this allowed the client to use advanced data analytics technologies to drive disruptive operational changes toward building their intelligent ports.
The port operator developed trust in the EY team because of its ability to understand the problem, engage fully with the organization and ultimately transform the operation. The team was awarded an additional major project, and it swept the three top prizes at the port operator’s global innovation challenge — designed to promote transformation within the 30+ ports under its control.
Beyond the macro impact for the port operator, these solutions affected the workers on the ground too. Better planning meant they had more predictable hours, rather than hours of idleness followed by extensive overtime caused by delays. It even enabled them to schedule holidays that were previously impossible to take due to the port’s unpredictability.
Each new day brings additional information to inform the model and improve its accuracy. Any improvement in the model, no matter how minor, could exponentially improve the port’s operation and the flow of goods around the world.
