What is Predictive Analytics in Fleet Management?

By integrating predictive data into your fleet management strategy, you will be able to anticipate vehicle complications, and even avoid them. Using historic data to identify patterns, predictive analytics will help predict trends and events, forecasting when, what, and how these events may happen.

Implementing tools that work with predictive analytics will allow you to plan effectively by making data-informed decisions. It can also help you anticipate future problems – and possibly prevent them from happening entirely.

In the context of fleet management, using software that employs predictive analytics can help you save time, money, and maybe even lives. Discover the best fleet management software on the market.

In this article, we’ll discuss the role of predictive analytics in fleet management, including route optimization and fuel efficiency. We’ll also dive into its benefits, challenges, and future trends, offering insight into how to plan your next move.

The Role of Predictive Analysis in Fleet Management

Predictive analysis within fleet management can involve many types of data, such as the information gathered from telematics systems, GPS tracking, driver behavior, cloud devices, traffic cameras, and dash cameras.

It wasn’t all that long ago when all of this data needed to be manually tracked and analysed, but this process is now automated and used in a much smarter way. In addition to having the foresight to predict problems in a way that was not previously possible, predictive analytics also reduces mistakes due to human error. Since predictive analytics is based on historic data, it’s necessary for your technology to collect accurate and timely data to make correct predictions.

In terms of cost reduction, detecting potential problems before they arise prevents downtime when your vehicles are out of action. Delegating data analytics to an automated system can also save you the wage cost you may have spent on a dedicated analyst.

Some examples of how predictive analytics can take place within fleet management technology are:

• Vehicle maintenance
• Scheduling and dispatching drivers
• Automatic route optimization
• Mileage
• Fuel and CO2 monitoring
• Driver behavior management:
• Driving style data
• Driver performance

Vehicle tracking products, such as Verizon Connect and Samsara, implement many of these features, meaning they can hugely lighten the load of your fleet management strategy.

Predictive Analysis: Our 5 Tips

To reap the benefits of predictive analysis, we’ve mapped out a general roadmap to help you get started. Firstly, always do your research and locate areas of your business that could do with some fine-tuning. Then, evaluate your options in terms of software. There’s plenty to choose from. Training is of utmost importance any time you’re rolling out new technology, so is accurately recording data to set yourself up for the best chance of success.

Predictive Maintenance in Fleet Management

A key area in which predictive data can help fleet managers is to anticipate issues involving vehicle maintenance.

Predictive maintenance works on the basis of identifying potential problems before they develop into larger issues. With a proactive rather than a reactive approach, you can ensure your vehicles are in top condition and don’t unexpectedly fail on you.

Maintenance will take place based on necessity rather than factors such as mileage, age, and time since the last service. This means unnecessary maintenance does not take place, saving on costs.

Fixing problems before they develop also reduces downtime, so you’ll avoid lengthy repair times and your vehicles will be on the road when you need them to, ensuring that you don’t lose out on business. Crucially, it can also help prevent accidents from happening because you’ll be alerted to any potential issues with your vehicles.

Predictive Analysis for Fuel Efficiency

Another valuable advantage of utilizing predictive data in your fleet management strategy is to gain insights into your fuel consumption. The data includes vehicle performance, miles per gallon (MPG), and route planning, allowing your fleet management technology to predict the fuel consumption of your fleet.

For example, Teletrac Navman’s DIRECTOR application gives you pre-trip and average fuel consumption figures. The app also offers you the power to further manage your fleet via route planning, maintenance scheduling, and alerts on unnecessary fuel burn. You can learn more about DIRECTOR and Teletrac’s other features in our Teletrac Navman review.

Alternatively, Quartix’s vehicle tracking system provides CO2 emissions reports that estimate the carbon emissions of your vehicles. Verizon Connect is another fleet management product that will give you an insight into your carbon footprint. Since EPA has stated new, more stringent standards for the reduction of gas emissions of heavy-duty vehicles, it’s important that fleet managers are tapped into this information.

Predictive Analysis for Route Optimization

When it comes to route optimization, predictive analysis is a powerful asset. By leveraging data from previous traffic conditions, satellite information and logistical needs, the most suitable route can be determined. This is done via an algorithm that takes into consideration the above factors and can automatically reroute drivers in the case of unforeseen circumstances, such as heavy traffic, roadwork, or accidents.

In our Samsara review, we explain their vehicle tracking system, which features route tracking that allows you to plan and monitor journeys in real-time, taking into consideration scheduled time of arrival, successful arrivals and missed stops. This kind of insight goes further than a rudimentary GPS planner and can promote maximum driver productivity, fuel efficiency, and effective communication with customers regarding delivery times.

Challenges in Implementing Predictive Analysis

As with the introduction of any new technology, there’s a learning curve with predictive analytics. Here are some tips to keep in mind when embarking on the journey of predictive analytics:

• Becoming overloading with data: Audit your existing workflow to see what types of data are relevant to the goals you want to achieve, thus ensuring you avoid being overloaded with multiple data sets.
  • If you are looking to become greener, fuel consumption data and CO2 emissions data are important.
  • If safety is a priority for your fleet, driver behavior and predictive maintenance should be your focus.
• Finding the right product: Look at what software products are on the market. This will help ease you into your transition to using predictive analysis. We’ve got you covered here as we’ve collated many comprehensive guides to the best fleet management tools.
• Alienating your team: One of the biggest challenges is to ensure your team does not feel alienated. Help them along by dedicating adequate time for training key team members, which will maximize the benefits of predictive analysis for everybody involved.
• Recording accurate and timely data: It’s also important to ensure that the data used to forecast future events is accurate and timely, otherwise you may end up with inaccurate predictions and make decisions based on false conclusions.

The Future of Predictive Analysis in Fleet Management

In the near future, we can expect to see predictive analysis take an even more prominent role in fleet management and fleet management software.

Artificial Intelligence

You’d be hard-pressed to find an industry that is not considering the impact that artificial intelligence and machine learning will have on their workflow. Since predictive analytics already incorporates machine learning in its process, we can expect to see this as an area of rapid advancement in the next couple of years.

Greener Transport

With low or zero-carbon emissions targets increasingly prevalent worldwide, many fleet managers are facing pressure to electrify or significantly reduce their fossil fuel-powered operations. Therefore, we can expect predictive analytics that focus on emissions and fuel consumption to become extremely popular (and necessary) as we move towards Biden’s 2030 target to reduce greenhouse gases.

Autonomous Transport

Another revolution is in sight: self-driving vehicles. Autonomous transport is already in development and, while it needs to overcome some regulatory hurdles, we can expect it to become prevalent in the coming years. When it comes to safe driving, predictive analytics may be the key that autonomous transport needs to become the norm on roads in the US.

Conclusion

In summary, predictive analytics is a hugely fertile area for those in the transportation industry. It can help fleet managers and drivers overcome some common hurdles, such as route optimization, fuel consumption, CO2 emissions, driver behavior, and customer satisfaction.

With so many software providers already implementing predictive data into their vehicle tracking and fleet management products, the transition to a progressive workflow can be smooth and straightforward. To find a provider that will best suit the needs of your business, we’ve conducted extensive research into some of the best fleet management software providers so you don’t have to.