After a truck accident, trucking companies may choose to take action against a truck driver who failed to perform his or her duties in a safe manner. New technology may allow fleet operators predict future driver behavior and take steps before a truck accident even occurs. Predictive analytics software can use information regarding a driver's past behavior, including information gathered from onboard computers, GPS tracking systems, citations and accident reports, and use it to determine the safety risks a particular driver might pose.
Predictive software may allow companies to address problems they would be unlikely to see on their own. When a driver with an excellent safety record suddenly demonstrates changes in their driving patterns, a company may not take notice until it is too late. Software can look past the driver's record and give an honest assessment of areas where the driver needs to focus. This allows the company to provide coaching and get to the bottom of what has caused the change in behavior. By acting before an accident, companies can prevent truck injuries and deaths while also preserving the careers of skilled drivers.
Different models study different factors in attempting to determine which drivers pose the highest risk. Some models gather data that extends beyond the actions of a driver behind the wheel. By analyzing things such as salary, when a driver typically starts and ends a shift, whether a driver is working on the weekend, and other data, some software can show when personal or financial strain could be affecting a driver's decision-making. Several programs have demonstrated good results in reducing the accidents per driver of a given fleet.
If such programs can be used to reduce the number of people injured or killed in truck accidents, truck companies would be wise to implement them.
Source: Truckinginfo.com, "Using Analytics for Proactive Predictions," by Jim Beach, 23 August 2012