Using Predictive Analytics to Estimate Fleet Fuel Consumption

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Understanding predictive analytics is an integral part of a fleet manager’s job. Predictive analytics uses a combination of statistics, machine learning, modeling, and driver histories to make predictions. This technology can apply to various fleet issues, including maintenance, budgets, fuel consumption, and safety. It is a potent tool for fleets to take advantage of, particularly to manage fuel consumption, one of the biggest drains on a fleet business’s budget. So how does predictive analytics help reduce fuel costs? 

Regular Maintenance

Predictive analytics can determine when a vehicle needs maintenance before it breaks down or suffers a broken part. Monitoring vehicles’ maintenance needs is an essential part of ensuring their fuel economy. For example, a tire underinflated by ten psi can reduce fuel economy by about 3.3%. If all four tires are underinflated by ten psi, that can reduce the truck’s fuel economy by 10% and cost an additional 31 cents per gallon. A simple alert that tells the fleet manager when a vehicle’s tires are underinflated can save hundreds of dollars in fuel over time. In addition, regular maintenance can improve a vehicle’s gas mileage by an average of 4%, and fixing serious maintenance problems can improve mileage by as much as 40%. Therefore, predictive analytics that alerts managers to a vehicle’s maintenance needs is supremely useful for reducing fuel costs. 

Route Optimization

One of the day-to-day uses of predictive analytics is in route optimization, particularly for fleets whose routes change throughout the day. Route optimization can dramatically improve a fleet’s efficiency and productivity. Predictive analytics can help fleet managers update routes as jobs come in, helping drivers get from one job site to another while using as little time and fuel as possible. Many companies who take advantage of route optimization software find mileage reductions of 10 to 25%. This reduction can mean significant savings for any sized fleet business. It is a worthy investment for any company looking to save both time and money, making everyone’s lives easier. 

Driver Behavior

Of course, predictive analytics cannot guess what a driver will do, but machine learning can analyze patterns in driver behavior to create reports that identify specific problems. For example, if a driver excessively idles the vehicle, that can cause significant fuel waste that costs the company hundreds of dollars. Some drivers eat lunch in their running vehicles or leave them running while they take naps, so excessive idling can become a significant problem for fleets. Analytics can pinpoint vehicles that idle excessively and help fleet managers make decisions to solve the problem. Another example of driving behavior that wastes fuel is rapid acceleration, which is usually a sign of aggressive driving. Like excessive idling, analytics can find this behavior and alert fleet managers so they can act. It is vital for the sake of the driver, the vehicle, and the company that these issues be resolved. 


Predictive analytics is a fantastic technology for fleets to put to good use. Saving on fuel costs is just one of the many perks. It also improves safety, efficiency, and cost savings in other areas across the board. As with any technology, more uses develop all the time. Follow Azuga to stay up to date on the latest in predictive analytics. Azuga is the leader in fleet management software, which harnesses predictive analytics to make fleet managers’ jobs easier every day. Contact us for more information about our fleet management software and other technologies.