FourKites® Introduces Recommendation Engine to Proactively Mitigate Supply Chain Delays and Improve On-time Delivery
Early Adopters Achieve 2.1x Improvements in Overall On-time Delivery Performance
CHICAGO, May 14, 2019 /PRNewswire-PRWeb/ -- FourKites®, the leader in predictive supply chain visibility, today introduced a new predictive analytics capability to help customers ensure a higher percentage of on-time deliveries by anticipating potential bottlenecks and recommending course corrections. A new addition to the company's Insights portfolio, Recommendation Engine (SM) uses a combination of historical data - such as average dwell at origin facility - and real-time transit conditions - such as traffic and weather - to make proactive recommendations in real-time to mitigate potential problems before they occur.
In addition to 2.1x improvements in on-time delivery when following FourKites' "Departure from Origin" recommendation, early users have been able to improve load planning accuracy, understand delivery risks before the load is even picked up, and reduce fees related to late reschedules, detention, and missed appointment times.
"As supply chains grow in complexity, companies can no longer rely on approaches that worked in the past to plan their shipments," said Priya Rajagopalan, Chief Product Officer at FourKites. "The industry must evolve and become more proactive, harnessing data and intelligence that can provide actionable insights, and anticipate and mitigate problems to ensure on-time delivery of a shipment before a load has even left the dock."
Traditionally, the use of analytics in supply chain could identify historical patterns in data, but failed to detect and prevent problems in advance. FourKites' Recommendation Engine is the first analytics solution to manage unexpected problems and predict future bottlenecks by providing actionable recommendations in real time to keep shipments on time. For instance, companies can now identify potentially late loads before they are even picked up, so that shippers can proactively work to reschedule the load or implement a recovery plan, and notify customers of possible delays. The system can also provide real-time alerts when a shipment deviates from the most optimal route or when new risks appear, enabling companies to intervene to address these issues.
The introduction of FourKites' Recommendation Engine follows the recent launch of a new DynamicETA (SM) machine learning algorithm that predicts freight arrival times with greater accuracy in narrow time windows, demonstrating FourKites' continuous commitment to leverage the power of AI and large data sets to dramatically improve supply chain efficiency.
Since launching five years ago, FourKites has pioneered the industry shift to real-time visibility, enabling shippers to improve on-time delivery and optimize their supply chains based on actionable data and predictive intelligence. With a network that now includes more than 250 of the world's top shippers, including 18 of the top 20 food and beverage companies and 4 of the top 5 CPG companies, FourKites tracks more than 500,000 shipments every day.
FourKites, Recommendation Engine and DynamicETA are service marks of FourKites, Inc.
About FourKites
FourKites is the largest predictive supply chain visibility platform, delivering real-time visibility and predictive analytics for the broadest network of Global 1000 companies and third-party logistics firms. Using a proprietary algorithm to calculate shipment arrival times, FourKites enables customers to lower operating costs, improve on-time performance and strengthen end-customer relationships. With a network of more than four million GPS/ELD devices, FourKites covers all modes, including truckload, LTL, ocean, rail, intermodal, last mile and parcel. The platform is optimized for mobile and equipped with market-leading end-to-end security.
To learn more, visit http://www.fourkites.com.
SOURCE FourKites
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