BI Case Study

How UPS Uses Big Data With Every Delivery

26 February, 2015

How UPS Uses Big Data With Every Delivery

The different routes that can get a driver from point A to point B are overwhelming. What determines the best course to take? Is it the one with less traffic, the least amount of stoplights, the highest speed limit or the least amount of physical distance to travel? For many, the most efficient route isn’t a major concern, but for companies like UPS, minimizing driving time is crucial.

For this reason, UPS engineers sought to devise a plan for route-optimization. They used a system called Orion, short for On-Road Integrated Optimization and Navigation. This algorithm used 1,000 pages of code to analyze 200,000 possibilities for each route in real time. By using this big data, they were able to understand how vehicles performed during different routes and could easily see ways where deliveries could be improved. One of their major findings was the inefficiency of left turns. By essentially going against the flow of traffic, UPS vehicles were wasting time and gas money from idling. This led them to make one simple rule—to minimize, or if possible, eliminate left turns.

Even though this meant drivers would often travel a greater distance, results showed that more packages could be delivered in less time with a reduced amount of emissions by driving in a series of right-hand loops.

As a result, between 2004 and 2012, UPS saved 10 million gallons of gas and carbon emissions were reduced by 100,000 metric tons (the equivalent of pulling 5,300 cars off the road annually). It also saved the company 98 million idle minutes or about $25 million worth of labor cost each year. In other words, this one simple change increased profits, met customer demands, improved safety and positively effected the environment.

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