Protecting equipment through predictive modeling
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Predictive Truck Analytics Road

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Protecting equipment through predictive modeling

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“In the transportation industry, drivers are our biggest asset and equipment runs a close second,” says Dean Croke, Omnitracs senior manager of product marketing. “From fleet owners to drivers, damage to our equipment can put us out of commission for days, even weeks at a time, costing us time and money. With this in mind, we invest in the latest alarm and trailer tracking systems to prevent theft. Additionally, we take our trucks in for maintenance on a ritualistic basis in hopes of protecting our equipment from being out of service. But, what do we do to prevent the biggest downtime threat of all: accidents?”

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Traditionally, accidents have been viewed as inevitable events that occur randomly without observable patterns. Contrary to this traditional belief, accidents are not random, but rather the culmination of a series of subtle, but profound developments that can be detected well in advance by identifying faint changes in driver behaviors captured through a series of raw data points. While this data holds information vital to the identification and prevention of accidents, it is of little use unless collected accurately and promptly, analyzed efficiently and acted upon with precision, Croke adds.

“Examining historical data patterns from past events such as accidents or even engine failure, predictive analytics identifies changes in data and associated behaviors to forecast the outcomes of specific situations, providing fleet managers with the right information about the right drivers at the right time,” Croke notes. “Armed with this information, managers can have remedial discussions with their drivers to intervene and avoid accidents and other safety related events. By preventing an accident, fleet managers in turn avoid damage to their equipment, saving both time and money spent on equipment repairs and replacements.”

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Additionally, fewer accidents translate into fewer trucks in the shop for repair, more rolling time, greater millage and heightened productivity.

Take, for example, Averitt Express, a Cookeville, Tenn.-based privately owned transportation and supply chain management company that utilizes FleetRisk Advisors’ predictive analytics model across nearly 2,100 trucks. Since deploying FleetRisk Advisors’ model six years ago, Averitt has seen a 41% reduction in accidents, saving the fleet thousands of dollars in equipment repairs and increased productivity.

Predictive analytics technology is challenging traditional equipment management practices by turning to preventative techniques and data to reduce risk. As fleets continue to look beyond traditional methods to better understand and avoid accidents, they will be able to capitalize on technology to proactively identify and avoid damage to their equipment, Croke adds.

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