Chicago-based FourKites, a provider of real-time tracking and visibility solutions across transportation modes and digital platforms, announced today it has introduced a new offering, entitled Dynamic ETA for LTL, that is geared towards shippers, carriers, and 3PLs, in order to track LTL (less-than-truckload) shipments from pre-pickup to proof of delivery that includes highly accurate dynamic and automated estimated arrival times.
FourKites’ Chief Product officer Priya Rajagopalan told LM there were various drivers for rolling out this new offering.
“In ongoing conversations with customers, a common theme emerged: LTL delivery windows are notoriously unpredictable, due to the inherent complexity of multiple terminal stops and widely variable transit times for LTL freight,” she said. “The lack of predictable and reliable ETAs translates into delays and dissatisfied customers, up and down the supply chain. While many accepted this as an unsolvable problem, we approached it as an opportunity for operational optimization and better customer service. We decided to solve this problem by using our vast troves of historical and real-time data, and created a machine-learning algorithm across millions of LTL loads and more than 3 billion transit miles. This generates a robust and accurate LTL ETA model that applies to all shippers in every geography.”
Rajagopalan added that this new capability also includes automated PRO number generation and comprehensive document retrieval capabilities to streamline processing and keep supply chain partners on the same page.
“Now, LTL stakeholders can see one, reliable ETA that updates based on real-time status updates, empowering supply chain professionals to plan their operations effectively and arrange dock and labor schedules to best fit their needs,” she said. With 6x the ETA accuracy of industry-standard predictions, FourKites' customers progress from weekly estimates to Time of Arrival estimates, a level of granularity traditionally only available to dedicated fleets and FTL.”
When asked to provide a basic example of Dynamic ETA for LTL at work, Rajagopalan explained that the new offering enables a user to see, upon load creation, a four-hour delivery window for LTL loads, backed by trillions of data points.
“As the LTL freight continues on its journey, the Dynamic ETA updates as statuses arise to accurately inform the final delivery time,” she said. “The FourKites Machine Learning also continually calculates the probability that something may not work out as expected. For instance, a transportation analyst may receive an 85% confidence level for a noon arrival, plus or minus one hour. That lets the receiver know their lunch break may be busier than usual.”
What’s more, she noted that after implementing FourKites’ LTL capabilities, one of America’s largest food producers experienced 87% more accuracy with FourKites' ETA when compared to industry standards.
As for the biggest advantages of Dynamic ETA for LTL from a FourKites’ perspective, Rajagopalan noted that FourKites Dynamic ETA for LTL introduces a new era in LTL freight management.
“With exponentially more accurate arrival times, in addition to automated document generation and retrieval capabilities, the supply chain can now take advantage of LTL shipping with far greater confidence, lowering costs, streamlining operations and improving customer service in the process,” she said. “FourKites was able to build this capability because of the breadth and depth of our data network - an advantage that no other supply chain visibility provider on the market can offer. To build this algorithm, we applied machine learning to 3.2 billion tracked LTL miles and 3.2 trillion transit patterns, to offer a much-needed alternative to the status quo.”