Today, almost every aspect of fleet driver risk management involves a huge amount of data. And while all data is potentially useful, the sheer volume of it – and what to do with it – can be overwhelming for fleet operators. Thankfully, fleet driver risk management solutions don’t always have to be complicated, especially with AI in the picture.
Let’s focus on the safety and environmental concerns of running a fleet. Many fleet operators collect data from multiple sources such as telematics devices, dashcams, black-boxes, mapping technology, direct from the vehicle itself, and many others. This data can provide useful insights into how drivers and vehicles interact with the roads and environment. Interpreting the data and using it to stay on top of safety issues is not always easy. But AI transforms the process and harmonizes data from multiple sources, making risk identification and management simpler than ever.
“Big data” is a common term in fleet driver risk management. It basically refers to large amounts of structured and unstructured data from various sources. And the number of sources continues to grow.
Leveraging big data is important for fleets. It can help with everything from scheduling and routing to managing driver behavior. But to really get to grips with safety and sustainability, it’s how the data is analyzed and interpreted that really matters.
There are several tools on the market that “aggregate” multiple data sources and most of them have a corresponding “score”. These scores cover all manner of outputs including operational performance, fuel/eco scores and of course driver/fleet risk scoring. To turn big data into useful outputs these scores must be correlated to actual real-world outcomes. This is especially true when it comes to risk or eco data. Insurance companies and Boards of Directors are focused on the Environmental, Social and Governance (ESG) aspect. They therefore expect to see how scores correlate to the real world.
For fleet operators, this is a crucial factor when considering fleet risk management solutions. Being aware of individual driver risk is important for many reasons. It helps maintain safely levels. It helps ensure training is assigned where it’s needed. And it ultimately helps improve the bottom line.
With so much data available, the challenge is bringing it all together to create an individual risk picture for each driver. At Greater Than, we help fleets overcome this challenge by uncomplicating data, and aggregating GPS data from multiple sources into a single Crash Probability Score. Our AI provides fleet operators with crash probability for every driver, across the entire fleet. Because our data works in real-time it ensures continuous validation of crash probability to help prevent incidents before they happen. In other words, our score is correlated to actual crash outcomes.
Data is worthless if it doesn’t lead to action. And one of the major benefits of having an uncomplicated picture of driver risk is that it enables prompt, effective action. How data is acted upon depends on the requirements and goals of the fleet operator.
Driver training is a key area that can be enhanced with data. For example, with accurate crash probability insights, fleet operators can identify the drivers most in need of training and education. More importantly, they can pinpoint the exact areas in which drivers need training. There are also many other benefits of enhanced risk insights that help to optimize driver risk management.
Having a complete overview of crash probability and climate impact at the individual driver level is good for business in many ways. Armed with precision individual risk levels, fleet operators are in a good position to obtain tailored insurance pricing. By sharing driving data with their insurer, a fleet may be able to access dynamic pricing that recognizes and incentivizes safer driving. For the insurer, such behavior-based pricing is a great way to increase profitability.
Incentive and gamification programs are other considerations for fleets. Real-time assessment of driving behavior can lay the foundation for safety programs that provide transparency to drivers. By being able to see a real crash probability score, and how their score compares to others’, drivers are encouraged to adapt their driving style to climb the leader board. This is good for a fleet’s safety performance, and good for road safety in general.
The relationship between driver safety and sustainability remains an overlooked area of driver risk management. Yet, it’s only going to increase in importance. Soon, many companies – if they’re not already – will be facing taxes on their carbon output. Being able to measure usage will be a key priority.
While risk isn’t necessarily the first consideration when discussing fleet sustainability, it should actually be the starting point. At Greater Than, our artificial intelligence (AI) is not only trained with real driving claims, but also with fuel consumption and CO2 output. The AI is therefore an enabler to help fleets reduce their CO2 emissions and environmental footprint.
Fleets are facing many challenges. And, common to all fleets is the need to identify the most suitable of the risk management solutions available to them. Yet, despite the huge amount of data available to them, many fleets do not yet have a simple way of identifying driver risk at the individual level. With Greater Than’s AI, fleets can gain direct insights into the actual real-time crash probability of all their drivers. These insights can be used in many ways.
Whether you’re looking to identify risk to provide training, work with your insurer for more accurate pricing, or need help with CO2 reporting, we can help. Contact Greater Than or book a meeting with me to discover how your business could benefit from accurate crash probability predictions for each driver.