Data-driven management: what is the impact on your fleet?

Through data-driven management, it is possible to understand what happens in your operation, why it happens and which types of solutions are most suitable for guiding your decisions.

For example, one action that can be recorded is the mileage covered by each vehicle on a route, generating important data to analyze. With this data, you can understand whether the driver made a detour or used an alternative route to the planned one.

What is data-driven management?

Data is simply the information from a fleet's daily routine. And data-driven management is the collection and analysis of daily information from a transport operation.

You can measure and control everything that happens in this daily routine, from vehicle availability to driver behavior.

However, the goal of this type of management is to make better-informed decisions, achieving better results with fewer attempts. So identify which data contributes to the assessments you need to make.

Considering the goals established for the company, understand your fleet's role in achieving them and which actions are needed to do so. From there, you can identify which data is most important, how it can be measured and which metrics will be used to evaluate the results of your actions.

Data-driven management also has other functions, such as gathering enough information to start forecasting scenarios and demand in the operation. This makes it essential for monthly and annual fleet planning.

How does data-driven fleet management work?

It works through the strategic collection and analysis of fleet data.

But care and sound judgment are needed when using data, as it is easy to get lost among so many possibilities.

Before starting to practice this type of management, you need advance planning of what is most important and which information will actually contribute to the fleet. In other words, you need to prioritize, using data strategically and considering the company's and the fleet's objectives.

One example of how you can use data-driven management is to identify what kind of planning to do during periods of high fleet demand. Transport companies have busier times of year, such as holidays and Black Friday.

These are weeks when demand for moving cargo and products increases considerably.

However, with the data collected over a year, you can identify some patterns of behavior and generate a demand forecast. This allows you to prepare and make decisions in advance about certain matters, such as:

• Quantity of product available in the warehouse;
• Product transfers between warehouses and distribution centers;
• Number of available vehicles;
• New drivers hired;
• Amounts needed for refueling;
• Main delivery cities and routes used.

Benefits of data-driven management

More effective planning

Building a history of information allows you to assess what happened and why. This provides the conclusions needed for fleet planning to reflect the reality of the operation.

When you plan with a forecast and an expectation of what is about to happen, the chances of success increase.

In addition, data collection tools have integrations and automations that speed up your planning, such as automated fleet reports. It becomes easier to get a complete view of how the fleet works.

Information flow

Just as tools make planning easier, they also make the flow of information more practical. After all, data-driven management needs data to be centralized in order to work.

Even if you use different systems in the fleet, prioritize those that integrate with one another. This way, you create a logistics dashboard with the most important information and a view of the performance indicators you have defined for the fleet — including keeping track of the percentage of the goal that has been completed.

This allows you to avoid losing information and to cross-reference data for a complete understanding of what causes problems and positive results.

Operational efficiency

Operational efficiency is defined as generating the best results without harming the operation's functioning.

In data-driven management, you should use everything that has already happened, including mistakes, to prevent them from happening again and to strengthen the actions that had the best impact. This leads to operational efficiency.

Fewer errors and more productivity

Collecting data through technology is essential to avoid relying on word of mouth in fleet activities. A common example of this poor practice is a driver telling the manager in conversation that their vehicle has a problem, and the manager having to pass the situation on to the mechanic.

Most of the time, the information is incomplete and, in some cases, incorrect. The mechanic may end up not correcting the reported problem, working on other components or even returning the vehicle to operation without performing a service because no problem was identified.

In addition to avoiding situations like this, digital tools for data collection and analysis contribute to better productivity in routine activities, such as vehicle and tire inspection.

As a manager, you can also better direct employees toward the tasks that actually bring positive results, helping both operational efficiency and increased productivity in the operation.

Cost reduction

When you make decisions that bring more results, cost reduction is a consequence.

If you notice, for example, that maintenance is not taking place as frequently as it should, you can adjust the fleet's routine, reducing the costs of corrective work and unforeseen events on the road.

On the other hand, if the data shows that drivers behave inappropriately on the road, you can take the necessary measures, such as training, and will notice reductions in refueling and tire maintenance costs.

Which types of data should you use in your management?

It depends on your company's objectives and goals. Before starting data-driven management, you need to understand which information you need to collect to get where you want to go.

First, setting your priorities is essential. Think broadly: what do you want for your business? Some common objectives that fleet managers use are reducing fleet costs, reducing accidents (in Portuguese) and increasing the company's profitability.

Based on what you define, identify the most important information to collect.

The next step is to analyze the data in the correct context by centralizing information. Connecting the different areas of the fleet is essential to fully understand a piece of information, as on its own it can lead to incorrect conclusions.

If tires are wearing out quickly, the “obvious” conclusion would be to look for problems and solutions in the tires and the management of these assets. However, the problem may lie in inadequate vehicle maintenance and a lack of preventive services.

Technology is essential for data-driven management. Get to know Prolog's solutions.