Among the factors contributing to the goodwill of a trucking company, the first thing that comes to our mind is the way their drivers ensure safety. And if companies can determine the drivers who make safety their priority, they can keep up this safety performance level.
But how does a company determine this aspect?
Well, thanks to the advancements in AI and Predictive analytics it is now possible for companies to gauge such parameters about the drivers. And depending on that, they can arrange proper training for the drivers to prevent accidents. Although data analytics has been in use for some time now in fleet-managing companies, the adoption of AI and data science is adding more accurate insights in helping companies prevent accidents.

How does this technology help fleet businesses?

With the help of predictive analytics, one can aggregate data generated from diverse platforms, which can help in tracking down drivers. But one cannot blame the drivers alone when it comes to accidents, because at times, even weather and road conditions are culprits. So predictive analytics can inspect and report data elements like road conditions, traffic, weather conditions that are outside the drivers’ control.
There are advanced applications like Idelic that can generate a distinct risk score for each driver by taking the history of their accidents (if any) and age. The safety suite of this software combines data from various systems for creating a driver profile and watch list.
How does predictive analytics work in favor of fleet businesses?
Predictive analytics digs into historical data to detect patterns which in turn generate the probability of the occurrence of certain events. You can find wide use of predictive analytics by e-commerce websites where additional products are recommended to customers by analyzing their past purchases.
When it comes to trucking businesses, predictive analytics is employed to analyze the probability of a risk incurred by fleet arising from accidents, crashes, etc. Once it finds something erroneous or problematic, it immediately warns the owner so that they can intervene and resolve the issues.
According to the president of ARL Network, Ron Faherty, they can now look into the data to find whether any of the drivers have a habitual problem of quitting and based upon the findings they can counsel their drivers, understand the problem points and finally reduce the driver turnover rate

Can predictive analytics indicate the owners about upcoming fatal crashes?

Tim Smith, the Hub Group Senior President says that after using driver safety software, they have started learning about problems that they were previously unaware of. That enabled them to identify the risk-takers before it impacts the other drivers or employees in the organization.
Although a fleet owner can hire a data scientist to track records of drivers adopting predictive analytics, if the service is outsourced to a data analytics enterprise, they can gain access to a wide array of trends and patterns. Predictive modeling, when used in transportation businesses, helps reduces the owners’ woes regarding the safety of driver and truck, since all the drivers would be tagged to a risk ranking score now.