An Inside Look at How Big Data Is Changing Fleet Management

While you don’t hear a whole lot about it outside of the industry, big data has fundamentally and systematically changed the trucking industry forever. Over the past 18 months, new software and technology – fueled by big data – has revolutionized fleet management and given a breath of fresh air to an industry that’s critical to our country’s infrastructure.

Big Data Fueling Big Changes

While you don’t hear a whole lot about it outside of the industry, big data has fundamentally and systematically changed the trucking industry forever. Over the past 18 months, new software and technology – fueled by big data – has revolutionized fleet management and given a breath of fresh air to an industry that’s critical to our country’s infrastructure.

Big Data Fueling Big Changes

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Big (Data) Wheel Keep on Turning

Just this year, some of the industry’s biggest partners have released new products, services, and software solutions that are designed to improve everything from safety and fuel savings to driver logbooks. And while these aspects of fleet management may seem dissimilar, the fact is that they’re all powered by big data. Let’s look into some of the details regarding how big data is specifically impacting the industry for the better.

1.      Access to Better Routing Data

Fleet management is all about efficiency. Managers ask themselves, how can I get this truck from point A to point B in the shortest amount of time? They have to think about things like rush hour traffic, road construction, stoplights, speed limits, weigh stations, weather, and dozens of other factors. Now, compound this by 10, 25, or even 50 trucks in a fleet and you can begin to understand how challenging of a proposition this can be.

Fleet management systems, backed by big data, collect data and use that information to determine the shortest and most efficient routes. This can lead to thousands of dollars in savings and frees up fleet managers to spend more time focusing on the bigger picture.

2.      Enhanced Maintenance Scheduling

For companies with large fleets, ongoing maintenance is one of the biggest issues. And while it can save companies lots of money, preventative maintenance is often hard to track. You can’t simply look at the age of a vehicle and number on the odometer and tell if it needs serviced. 

The old method of maintaining trucks involved simply servicing different parts at predetermined mileage intervals. While this is better than nothing, it doesn’t take the actual condition of the vehicle into account. Big data is changing this, however. It’s allowing companies to accurately pinpoint the need for preventative maintenance for tremendous cost savings.

3.      Elimination of Traditional Log Books

While the industry has come a long way over the past few decades, there are still some processes that need to be kicked. The most archaic of them all is the use of paper log books. “Three million truck drivers today still use a paper log book, which is the same system we’ve had in the industry since 1938. And the worst kept secret is that drivers lie on their log books,” says Lane Kidd, Managing Director of the Trucking Alliance.

Once again, big data comes to the rescue. New programs allow for electronic logs that accurately track driver-specific statistics and prevent driver fatigue. “It gives the company a better view of what’s actually happening out on the highway.”

The Changing Face of Fleet Management

There are a lot of moving parts involved in the trucking business, and fleet management in particular. While it will take years to revolutionize the entire industry, recent developments in big data have proven that it’s possible to make the industry more efficient and profitable for all parties involved.

As new technologies, applications, and software solutions are developed in the coming years, it’ll be interesting to see how improvement unfolds. In the words of Steve Jastrow, strategic consultant for a major fleet services company, “The point is that we will be evaluating data in ways that we never would have imagined in the recent past.”