This week, a major logistics solutions provider announced that a new “big data” solution that can pinpoint which drivers and carriers are most likely to get into a crash.
On June 24, Convoy announced via the company blog that they have developed a “new predictive crash capability that uses machine learning and automation to qualify safe drivers into our network, yielding 16% fewer accidents vs. the industry average.”
Here’s how Convoy says the new crash predicting capability works:
We start by gathering extensive carrier safety and compliance data, and then apply machine learning to predict which carriers are likely to get into accidents. Our algorithm processes thousands of inputs—such as carrier crash history, vehicle maintenance, and speeding and traffic violations—across millions of records spanning the past 10 years, ultimately producing individual scores for the tens of thousands of carriers in our network. We then use automation to analyze compliance with those scores within seconds, every day, with every load to either qualify or disqualify carriers to haul loads. Our model gets smarter over time, driving continuous improvements as more data is generated, providing shippers with increasingly high levels of safe and reliable carriers.
Convoy says that their solution is superior to the Federal Motor Carrier Safety Administration’s Carrier Safety and Accountability (CSA) program, which they say was “never designed for private sector use in the carrier selection process, and is not predictive; rather, it was solely intended for reactive intervention by enforcement authorities.”
Convoy claims that their technology will provide shippers with access to a network of reliable, safe carriers while cutting down on cargo loss claims.