FourKites fine-tunes predictions for shipment arrivals

user-gravatar Headshot
Updated Feb 27, 2019

FourKites screen viewFourKites announced a new DynamicETA algorithm that predicts shipment times with greater accuracy. Since launching five years ago, FourKites has focused on enabling shippers to improve on-time delivery and optimize their supply chains based on predictive intelligence.

The enhanced algorithm uses more than 150 data points associated with a single load — including shipper, carrier, lane, rest patterns, load, traffic and weather — and learns continuously from millions of monthly shipments to give shippers and carriers more precise arrival times.

“Ultimately what we need to apply any AI or data science is enough data,” says Priya Rajagopalan, chief product officer of FourKites. “This is not something we could have done four years ago. Every year we successfully add terabytes of data to the platform, enabling us to do highly advanced predictive models on ETA and dwell time.”

An early adopter of FourKites’ new feature is a top food and grocery wholesaler with more than 30,000 weekly deliveries. The customer achieved 91 percent accuracy in predicting arrival times within a one-hour window, according to the announcement, for improving communications with its own customers to coordinate delivery operations and staffing efficiency.

FourKites says the new feature can be useful for carriers as well. Some carriers already use ForKites as a customer service web portal to provide their shippers with shipment status information.

Additionally, FourKites is working on a new recommendation engine for shipper and carriers that will specify the time of day that loads must depart by in order to reach their destinations on time. The company is planning to release this engine, which uses historic and real-time traffic conditions, in the second quarter, she says.

The accuracy of DynamicETA is much more precise than the accuracy rates of traditional shipment visibility tools. These tools are roughly 45 percent accurate for day-of arrivals, FourKites says, and are based on top-down estimates using limited data – typically the standard drive time of the projected route, adjusted by remaining hours of service.

Partner Insights
Information to advance your business from industry suppliers

“Real-time data and predictive intelligence are critical to the future of supply chains,” said Mathew Elenjickal, founder and CEO of FourKites. “The industry must evolve from occasionally accurate day-of arrival times to consistently accurate hour-of arrival times.”

FourKites’ DynamicETA is based on a system of data models working together to generate the most accurate predictions.

The system is automatically re-trained every month to utilize recent history and account for seasonal and annual changes in behavior.

Because of the data requirements, FourKites’ DynamicETA feature is available to the largest enterprise customers of the FourKites platform.

The announcement comes a few weeks after FourKites announced $50 million in new funding to fuel growth of its real-time visibility network, bringing total capital raised to $100.5 million.

FourKites’ network now includes more than 250 of the world’s top shippers, including AB InBev, Conagra Brands, Kraft Heinz, Nestlé, Perdue Foods, Smithfield Foods, Unilever, Walmart Canada and many others.