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Lloyd’s List Intelligence launches Predictive Fleet Analytics

Transformative new maritime analytics to cut delays and costs

Lloyd’s List Intelligence has announced the launch of the first-ever ‘air traffic control’ for the world’s commercial shipping fleet, helping to address some of the most severe challenges to the global supply chain through accurate data on estimated vessel arrival, berth and departure times, and other unique features

A LACK of reliable data on estimated time of arrival for vessels puts pressure on ports, hampers logistics and pushes up costs. A new service from Lloyd’s List Intelligence will address these issues with accurate data for the global commercial fleet.

Predictive Fleet Analytics combines near real-time data collected from 3,000 sources, resulting in over 327m Automatic Identification System vessel positions monthly across the global fleet.

It helps customers gain greater certainty around estimated destination, arrival, berthing, and departure times, along with port congestion status and waiting times. This greater level of insight is key to more efficient voyages and port operations that optimise the use of vessels, fuel, port facilities and services, and the teams that operate them all, resulting in time and cost savings.

Specially designed advanced analytics, AI, and machine learning transform this unique data into accurate estimated times of arrival into port (ETA), arrival times at berth (ETB), and times of departure (ETD) for the global commercial fleet, along with current and future estimates of port congestion.

Lloyd’s List Intelligence is the first to bring ETBs and ETDs to market, and no other provider brings together a broader range of actionable insight.

According to Lloyd’s List Intelligence 2020 Automatic Identification System message analysis, more than a third (36%) of AIS messages are missing ETA data, while another 27% of vessels fail to arrive within a day of their published ETA. Even destination data is unreliable, with 63% of vessels publishing one port destination but ending up at another.

With analytics powerhouse partner SAS, a leader in AI, data mining, modelling and forecasting, Lloyd’s List Intelligence have developed this pioneering new method of calculating, predicting, and learning from vessel movements and behaviours in ways that were not possible before.

The AI and machine learning models predict destinations with an accuracy of 70%, ETA to port within +/- 10 hours, and ETB to within one to two hours, catering for all vessel types in the commercial fleet operating to both fixed and non-fixed schedules.

“Predictive Fleet Analytics allows our customers to let decisions on scheduling and routes be driven by the best quality data, so that shipping companies can save on resources and costs,” said Parvin Conners, vice-president of product and data for Lloyd’s List Intelligence.

“This new level of prediction around destinations and arrivals helps ports to optimise their services and facilities and for maritime servicing businesses to run more smoothly. All of this is possible thanks to the strength of our data and analytics and how we use AI and machine learning.”

For more information about Seasearcher Predictive Fleet Analytics, please follow the link below.

 

 

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