What Is Predictive Analytics in Fleet Management?

Fleet management is the process of managing various aspects of commercial vehicle operations. This includes vehicle acquisition, maintenance, fuel, and driver management. Fleet management can be used to optimize a company's transportation resources, lower costs, and improve safety.

Traditionally, managers tracked fleet performance using manual methods such as spreadsheets and self-reporting from fleet drivers. Using these methods led to errors where many data inputs were either omitted or overlooked. This meant that fleet managers had to make decisions based on incomplete information.

However, predictive analytics is changing the game by providing managers with actionable insights that can be used to improve fleet performance. Predictive analytics uses historical data and predictive modeling to identify trends and patterns for a wide range of factors. This information can be used to make predictions about future events, such as vehicle maintenance needs or driver behavior, and take proactive steps to improve fleet performance.

If you're looking to get started with predictive analytics in fleet management, there are a few things you need to know. In this article, we'll cover the basics of predictive analytics and how it can be used to improve fleet performance.

What Is Predictive Analytics?

Predictive analytics is a branch of data analytics that deals with making predictions about future events based on past data and trends. Predictive analytics in fleet management can be used to forecast factors such as vehicle maintenance needs, fuel consumption, and driver safety. This information can help fleet managers make better decisions about allocating resources and keeping their vehicles running safely and efficiently.

It might sound like a cumbersome, impenetrable field that few can leverage, but predictive analytics is actually quite straightforward: predictive analytics in fleet management uses algorithms and data to make predictions about future events and can be accessed by using an established telematics platform with a simple dashboard. MiX by Powerfleet offers a number of solutions for fleet managers that can help them get the most out of their fleet using a variety of predictive analytics tools and data-collection methods.

Predictive Analytics in Action: An Example

Predictive analytics can be used to monitor driver behavior and identify patterns that may lead to accidents. This information can then be used to forecast and take proactive steps to improve safety, such as implementing training programs or changing company policies. Let's look at an example to understand how automated predictive analytics can be used in fleet management:

For instance, predictive analytics might reveal that a particular driver has a habit of speeding and not wearing a seatbelt. This information can be used to put the driver on a safety plan that includes coaching and training on how to drive more safely, and a real-time driving coach can provide in-vehicle support through the use of an AI-powered driver camera.

In addition, the company might implement a policy that requires all drivers to wear seatbelts while operating a company vehicle. These proactive steps can help reduce the risk of accidents and improve safety for all drivers in the fleet.

Data Management For Predictive Analytics

When it comes to predictive analytics, there are two main types of data that are used:

• Operational Data: This type of data includes information such as vehicle location, mileage, fuel usage, and maintenance records. Traditionally, fleet managers would use reporting methods like logbooks, fuel receipts, and odometer readings to get a general sense of the operational data, but full and accurate data collection with these measures was, and still is, nearly impossible.
• Driver Data: This type of data includes information such as driver behavior, accident history, and traffic violations. Without a telematics platform, information about driver behavior was only available after someone else on the road would call to complain about a driver. With MiX by Powerfleet'ss in-vehicle monitoring, you can utilize AI to provide real-time coaching to drivers, recognize and correct dangerous or costly maneuvers, and more — all without needing to rely on a third party to report driver behavior.

Operational data is usually collected through telematics devices, while driver data is typically collected through driver applications or vehicle black boxes. Once collected, both of these types of data streams must be input into a spreadsheet to be manually manipulated and analyzed by the fleet manager in order to develop a strategy based on the available information.

There are a few steps necessary to arrive at a clear output for your analytics predictions:

• Data collection: predictive analytics starts with data. This data can come from a variety of sources, including vehicle telematics, maintenance records, driver logs, and GPS data. This step is simple, with MiX by Powerfleet providing multiple data streams to a manager for each fleet vehicle.
• Data cleaning: once the data is collected, it needs to be cleaned and organized. This step ensures that the data is accurate and ready for analysis. With MiX by Powerfleet, it can be easy to identify outliers or normalize data to help you make clear sense of the information presented in your dashboard.
• Data analysis: this is where predictive analytics really starts to take shape. Data analysts will use a variety of methods, such as regression analysis and machine learning, to identify trends and patterns in the data.
• Predictive modeling: once the platform has useful, clean data, it can start to build predictive models. These models use statistical techniques to make predictions about future events, such as vehicle maintenance needs or driver behavior.
• Validation and implementation: after the predictive model is created, it needs to be validated to ensure that it is accurate. Once it is validated, it can be implemented into the fleet management system.

Does this mean that fleet managers now need to have a dual master's degree in analytics and statistics? It may sound like the benefits available through predictive analytics might require some sort of deep understanding of analytics and predictive modeling techniques, but that's not necessarily the case — especially with MiX by Powerfleet'ss robust predictive analytics solution, MiX Insight.

MiX Insight is a cloud-based predictive analytics platform that takes data from telematics devices and turns it into actionable insights through its algorithms. It doesn't require any special training or knowledge of predictive modeling techniques — all you need is a willingness to improve your fleet management.

If you're ready to take your fleet management to the next level with predictive analytics, Contact MiX by Powerfleet today. We'll be happy to show you how MiX Insight can help you improve your fleet performance.

Predictive Analytics Applications For Fleet Management

Predictive analytics has a wide range of applications in fleet management. It can be used to improve vehicle utilization, optimize routes, reduce fuel consumption, and prevent accidents. Predictive analytics can also be used to improve driver retention and identify at-risk drivers. As fleet managers become more comfortable with the possibilities of a predictive analytics platform paired with AI handling the massive amount of data collected through telematics platforms, they will continue to recognize and implement new methods to manage their fleet, cut costs, and improve operations with ease.

The Benefits of Predictive Analytics in Fleet Management

The impact predictive analytics has on fleet management can be profound. By using predictive analytics, you can improve efficiency, save money, and ensure the safety of your drivers. Predictive analytics is a powerful tool that can help you improve your fleet management.

There are many reasons why fleet managers would want to consider incorporating this type of management platform into their own operations. A few of the benefits include:

• Monitoring driver behavior: By tracking data such as speeding, braking, and seatbelt usage, predictive analytics can help identify risky drivers and take steps to improve their safety.
• Optimizing vehicle maintenance: By monitoring data such as mileage, fuel usage, and engine temperature, predictive analytics can help identify when a vehicle is due for maintenance and take steps to prevent unexpected breakdowns.
• Reducing fuel costs: By tracking data such as route planning, driver behavior, and traffic patterns, predictive analytics can help fleet managers find ways to reduce fuel consumption and save money.
• Improving customer service: When your predictive analytics platform identifies optimal routes and can build a historical dataset, things like delivery estimates will become increasingly accurate, and customers will know that they can rely on your services more than ever before.

These are just a few of the most general benefits of implementing predictive analytics into a well-managed fleet. The possibilities are really only limited by the creativity of the fleet manager in question.

Contact MiX by Powerfleet To Learn More About How Telematics and Predictive Analytics Can Change The Way You Manage Your Fleet

Predictive analytics with MiX by Powerfleet is a powerful tool that can help you improve your fleet management. Gone are the days of manually entering data into spreadsheets, or worse, running your fleet on a gut feeling. Predictive analytics gives you the ability to make data-driven decisions based on analytic data that can improve your bottom line.

If you're ready to take your fleet management to the next level, Contact MiX by Powerfleet today. We'll be happy to show you how our variety of options can help you improve your fleet performance and help you understand the actionable benefits with case studies and real-world examples.