Machine Learning Times
Machine Learning Times
AI Success Depends On How You Choose This One Number
 Originally published in Forbes, March 25, 2024. To do...
Elon Musk Predicts Artificial General Intelligence In 2 Years. Here’s Why That’s Hype
 Originally published in Forbes, April 10, 2024 When OpenAI’s...
Survey: Machine Learning Projects Still Routinely Fail to Deploy
 Originally published in KDnuggets. Eric Siegel highlights the chronic...
Three Best Practices for Unilever’s Global Analytics Initiatives
    This article from Morgan Vawter, Global Vice...

10 years ago
Making the Case


Making the case
Load One expediter Tom Evans drives team with his wife, Tina, running a three-truck Class 8 straight truck fleet based in Mattoon, Ill. Besides their compensation for doing their jobs the right way, the Evanses are eligible for additional perks for the same reason.

Load One uses a driver rewards program called Stay Metrics that takes data gleaned from surveys of drivers during their first weeks with the carrier to help predict which ones are at risk of leaving. The system builds on that relationship with a program that allows drivers to earn points redeem-able for merchandise.

“The biggest thing is simply getting rewards for doing something that’s no more than what you’re already supposed to be doing,” such as turning in logs on time and completing surveys, Tom Evans says.

The pace of available information and data gathering intrucking is accelerating, and with it, more companies to manage that data for fleets.

A handful of vendors are helping fleets crunch mountains of information to spot broad patterns and take preemptive action with individual drivers to improve retention and safety. The results so far have been impressive.

Predictive modeling remains relatively new in trucking, and while no major complaints have emerged within the industry, broader concerns over privacy or misapplication of data-based conclusions have been voiced elsewhere.

One major fleet using a predictive analytics company expressed such concerns. The fleet’s media contact, declining an interview request, wrote that, “It’s a topic we aren’t eager to talk publicly about due to its tendency to be used in litigation.”

An expert in the field says he’s unaware of actual litigation based strictly on predictive modeling practices. Still, there has been controversy, says Eric Siegel, founder of the Predictive Analytics World conference series and author of “Predictive Analytics.”

Much of the concern has stemmed from publicity over telephone eavesdropping by the National Security Agency. Yale law professor Jack Balkin, writing about NSA’s data mining, says such activities “allow the state and business enterprises to record perfectly innocent behavior that no one is particularly ashamed of and draw surprisingly powerful inferences about people’s behavior, beliefs and attitudes.”

View the complete article here.

By: Max Heine
Originally published at Commercial Carrier Journal

Leave a Reply