The Fuel Economy Benchmarking Experiment

The fuel economy benchmarking experiment allows you to analyze your fleets fuel economy based on real usage and calculate potential cost savings using the calculator. The knowledge gained from benchmarking lays a solid foundation for decision-making. Measuring your performance against the other fleets can lead to opportunities for improvement.

In the past, benchmarking has been a challenge, especially for small fleets, because they were not able to connect to the incredible amounts of data needed for accurate comparison. Geotab has assembled that data and made it accessible through this experiment alongside your current vehicle data.

After installing Analytics Lab, go to the Fuel Economy Benchmarking experiment and click try it.

What can I learn from the Fuel Economy benchmarking experiment?

First, in this experiment, you can easily view vehicles based on poor, average, and good categories for further analysis. It also displays vehicles based on your top performers and worst performers.

Additionally, by drilling into the groups, you can see more details on your vehicles. You can even select alternative vehicles to compare them to.

Fuel Economy Benchmarking Selections for comparison

Finally, the fuel economy benchmarking savings calculator allows you to input a comparison vehicle and fuel cost. By adding more vehicles to the list you can see the result of replacing a group of vehicles that you choose.

What are some practical applications for my benchmarking results?

With this tool, when it is time to buy new vehicles, you can more easily see which are your best candidates for replacement. Even better, you can easily research what to replace them with. It will also help to identify drivers that are getting below the expected fuel economy for the vehicle they are driving. Ultimately, those drivers can be monitored for the wasteful driving habits that contribute to their higher fuel consumption.

Geotab technology brings immediate insight to your doorstep. As soon as the connected device produces the data, it can be aggregated and benchmarked virtually in real-time. By revisiting this experiment after driver behavior has been addressed, or vehicles have been replaced, progress can be easily measured.