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AI Case Study

UPS plans to streamline internal operations by tracking every package and asset in real-time using sensors and machine learning

UPS has plans to develop an AI platform called Enhanced Dynamic Global Execution (EDGE) to optimise its internal operations. Using sensors all the objects involved in package delivery is tracked in real-time and this data will help employees make informed decisions. UPS expects 100s of millions of saving from the project.



Freight And Logistics

Project Overview

"EDGE uses data across UPS facilities to plan everything from how workers place packages inside delivery trucks in the morning to how the vast army of temporary hires that UPS recruits during the busy holiday season are trained. Eventually, data will even dictate when UPS vehicles get washed. This includes Preload Smart Scan addressing concerns of incorrectly loaded packages and re-routing of drivers."

According to UPS, "EDGE helps us share real-time data across operations to improve real-time decision-making, use data to locate every operations asset instantly, utilize mobile tools in our operations to provide real-time information to our team and optimize our operating plans to reduce cost. And, of course, EDGE continues to make our logistics network smarter."

Reported Results

The company claims:

* Expected savings of USD$200m in operating costs
* Expected to cut down incorrectly loaded package errors by 70%



Supply Chain



"The boom in e-commerce means UPS now delivers as many as 31 million packages a day. Keeping track of all that is an immensely difficult problem."



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