C.R. England has always been a company that relies on the practical solution. Back in the 1940s, mechanical refrigeration was new and unreliable, so England cooled its trailers by blowing air across a pile of ice with a belt-driven fan.

That was before England's current president, Chad England, was born, but he inherited the instinct for methods that work.
Keeping the inside of a trailer cool was a simple problem, compared to the one Chad England started taking on in 2004, when he was managing the company's safety, recruiting and driving school programs.
"We were doing everything we could to try and improve our accident rates, but then we had a couple of terrible accidents," he says. "I always had a hard time, and still do, when we have a serious accident. Having two in real close proximity to each other gave me a resolve that we had to try something that was a dramatic departure from what we'd done before."
Accident frequency cut 30%
Over the course of a half-dozen years' work, he and his team worked to meld the latest technology and statistical science into a comprehensive safety management system. Onboard data collection, satellite communication and predictive modeling are a far cry from blowing air across ice, but England proved that they get the job done. The company's accident frequency is down by 30 percent, as are its costs.
There's nothing new about communications and tracking, or onboard management systems that record everything from driver hours to hard stops and lane departures. The application of predictive modeling to trucking is a relatively recent development, though. It involves using a statistical process called regression analysis to correlate a wide range of data with certain types of driver behaviors. From this, fleets can predict the results of driver behavior and circumstances on the road, and put systems in place to reduce the risk of an accident.
Chad and his team initially thought they could do the predictive modeling themselves to create a driver safety scorecard. But that highly technical work was not in their skill set. "We're a trucking company, not a statistical analysis company," Chad explains.
The practical solution was to link up with FleetRisk Advisors, a leading provider of predictive modeling services. (FleetRisk Advisors was recently acquired by Qualcomm, which uses the modeling system in its Predictive Performance Service.)
It took several years of work, but they came up with models that showed statistically viable predictors of the frequency and severity of accidents. The models contain thousands of data elements - "every piece of data we could find about the driver, the situation, the accident, the environment," Chad says. "There's no subjectivity to it. You throw all the factors in and you let the science tell you what the causal factors are."
Some of the results made sense intuitively. For example, drivers are at greater risk between 2 a.m. and 5 a.m. due to the natural dip in circadian rhythm at that time. Others did not.
"If the driver had ever received unemployment benefits, then he was at a much greater risk of having an accident," Chad says. "We never would have guessed that."
Managing the information
The harder part of the process was figuring out how to manage this information. It took countless hours to develop the processes and systems to address the particular causes of risk.
An example would be the way a driver's pattern - say, driving a certain number of hours at night - can come up as a predictor of performance in the near future. If it does, then the driver's manager can have him pull over for a rest, or have him come in for training on how to manage his driving time better.
"Real-time data is transmitted to us and within minutes we'll have a safety manager on the phone performing their countermeasure," Chad says.
This produced the dramatic results Chad cited, and not incidentally a promotion for him to president of C.R. England North America.











