Fleet data analysis: how to collect and use data

A fleet manager seeking operational efficiency always looks for trends and applies the best solutions to achieve the desired results. That is why you are here and want to understand fleet data analysis better, right?

To start, you should know that you need an organized system to collect and store this data.

Then you also need to know how to interpret the information received to understand where problems are and create strategies that really work, with objectives matching the fleet’s reality.

But where should you start? Find out now:

How do you collect data for analysis?

There are two alternatives: digital tools and manual tools. With digital tools, work is easier because processes are automated.

But even if you do not have software for this purpose, your spreadsheets and manual tools can be used and constantly updated following a standard for data entry.

This second alternative is undoubtedly more labor-intensive, especially for fleets exceeding 50 vehicles in operation. After all, the volume of data produced is huge: information about vehicles, tires, fuel, drivers, and much more to analyze.

This is precisely where you need to take care! Just because you have so much available does not mean you need to use it all. So keep reading to understand:

How do you use fleet data analysis?

The first step in fleet data analysis is to understand which information is most important for you to monitor. This decision should be based on company objectives.

For example, if strategic planning aims to reduce fuel costs, you need to analyze indicators related to that management, such as average consumption per month, per driver, the cost per km driven per vehicle, and so on.

With this clear view of what to prioritize, data analysis will be more effective.

From there, it is advisable to determine how data can help improve your operation.

Continuing the example, with data on fuel consumption per driver, including a view of the vehicle used, mileage covered, and trip time, you can determine whether drivers are following economical and safe driving practices.

In general, having data readily available is essential in decision-making to shape your fleet’s present and future. Therefore, determine which data is most important, the means to collect it, and which data analysis systems to use for your management.

Want to see this in your fleet? Talk to a Prolog specialist

Why is data analysis necessary?

Information generated in a transport operation can be used for several different but equally important purposes. The first and most common reason in fleets is the carrier’s optimization strategy.

That means using data analysis to understand the operation and its daily processes thoroughly. After some time, you have enough information to start gaining predictability about fleet demands and capacities.

From that point, it becomes possible to start implementing new routines aimed at improving results and measuring their impact.

Beyond this, fleet data analysis allows better performance management, identifying the company’s standout drivers and vehicles with the most problems, among other information.

With this, you can significantly reduce corrective maintenance costs and optimize training provision for low-performing drivers.

Establishing benchmarking is also possible with data collection and analysis, generating comparison standards between units of your own company or against the logistics market as a whole.

Data integration: what is it, and how does it work?

If your company operates a fleet, you need access to a wide variety of data sources to manage vehicles, drivers, and the operation effectively. This information is usually available in various applications, documents, and systems in your business.

For example, accounting software may hold the most up-to-date customer data, while HR software provides driver profiles and training information. A maintenance management app provides controls over vehicles out of operation or available for trips, and may also provide parts and repair costs.

The possibilities are numerous. That is why data integration began to be used and is expected only to grow.

To explain further, integration is the automatic exchange of data between systems, eliminating the need for manual data entry and coordinating information across systems. This makes information stored in different locations easier to see and access.

This is a solution to ensure the manager always has information, data cross-analysis, and reliable reports for decision-making and to optimize fleet results.

What type of data should you collect for the fleet?

We already answered this question above: it depends on your objective! As you recognize the need to improve tire costs, you need to collect data such as the average life of each model, cost per kilometer traveled, reasons for disposal, and so on.

If you want to reduce vehicle maintenance costs, you should focus on analyzing which items have the most problems, repair costs, cost per distance traveled, etc.

Can you see how each stage of the transport operation has a large amount of data you can analyze? First, focus on identifying the points you want more control over. Based on them, you will know which data to collect.

These points can also be called fleet performance indicators, or KPIs. To continue expanding your knowledge, watch our video on the topic:

(video in Portuguese)