AI Case Study
Portcast is a data analytics vendor promising to optimise logistics for the maritime industry using machine learning
Portcast is a start-up which is trialling using machine learning to improve maritime logistics. This includes analysing large datasets in order to predict demand and optimise shipping routes.
Industry
Transportation
Freight And Logistics
Project Overview
From Asian Scientist: "Portcast’s engine takes into account several baskets of data on a real-time basis: economic indices, such as currency rates and commodity and fuel prices; climate data at different locations in the ocean; and satellite location data, which pinpoints where vessels are. To this, it adds customer data, such as trade flows along various shipping routes, for each particular client.
Based on the engine’s predictions, Portcast provides shipping companies with daily information, up to eight weeks in advance, about how much cargo will need to be shipped, between which ports, and when... This allows companies to tune their operations accordingly, redirecting resources to ports where demand is high, adjusting pricing and targeting the appropriate customers—actions that will ultimately improve profitability. Portcast is now running two proof-of-concept trials with major shipping players, and is in advanced discussions with five more".
Reported Results
E27 reports that the founders claim "Our first trial showed prediction results that were 95 per cent accurate, saved 1,000 working hours and over US$1 million in potential revenue".
Technology
Function
Strategy
Data Science
Background
As reported by Asian Scientist, "The maritime logistics industry is hugely inefficient, says Ms Gupta. 'Every decision in the industry is made based on a prediction. But because predictions are primarily made based on intuitive sense, experience, market averages and historical data, they are not accurate,' she explains. Inaccurate demand prediction in fact results in a S$30 billion loss every year for the industry, she adds".
Benefits
Data
According to Asian Scientist, "several baskets of data on a real-time basis: economic indices, such as currency rates and commodity and fuel prices; climate data at different locations in the ocean; and satellite location data, which pinpoints where vessels are. To this, it adds customer data, such as trade flows along various shipping routes, for each particular client".