There are few industries more straightforward, fundamentally, than trucking. You have a product and a destination, and you have to figure out the best way to get those two together. In an increasingly competitive economic landscape, however, this once-simple process could benefit from some complicated analysis. That's where custom web application development and big data could come in.
A lot of companies already have business intelligence tools, which can effectively monitor past and present situations. The problem is, these sorts of tools are backwards-looking: They're very good at describing that a problem has already happened, but can't provide much predictive value. That's where large-scale data analysis comes in.
Custom database models can be built to give past events greater forecasting value. Analytics can help determine the most fuel-efficient ways to travel, which in turn can give companies a better understanding of how fuel performance will affect their bottom line. Jeff Foster Trucking, a 225-truck carrier based in Superior, Wisconsin, is considering this variable heavily as it plans its purchase of 50 new trucks.
"In the purchasing world [0.1 to 0.2 miles per gallon] is a profound amount," says Dean Norrell, manager of operations and driver development in an interview to the Commercial Carrier Journal.
It can also help to map events. Knowing the likelihood of an outcome in a given situation could also prevent serious accidents. According to the Bureau of Labor statistics, 456 truckers sustained fatal injuries on the job last year, the highest total of any single profession. While there is some danger inherent in any profession that involves driving, if companies can analyze patterns of when deadly accidents are most likely to happen, they can help to avoid them.
Even for the most uncomplicated of tasks, the right application of big data principles can save time, money, and even lives.