Anyone involved in driver safety management or driver risk management will know the importance of effective communication. Without it, a program is likely to have little meaning to drivers, and little chance of success. With artificial intelligence (AI), those involved in safety management can not only access new layers of risk knowledge but also data-driven insights to strengthen communication and employee engagement.
While establishing a workplace safety culture is the starting point for any driver safety management program, it’s also important to fully understand driver risk level. After all, how can you communicate effectively with drivers about their risk exposure if you don’t know how they drive?
Over the past 15-20 years, driver safety communication has largely been built on information coming directly from the vehicle through telematics. Unfortunately, first generation telematics has required some interpretation to determine what the risk level is and what the message to drivers should be. Fortunately, communication becomes much easier when you move to today’s second generation telematics enhanced with AI.
Second generation AI-enabled in-vehicle intelligence dramatically deepens your understanding of driver behavior and risk level. That’s why AI is proving a highly effective tool in driver risk and safety management.
AI used to analyze existing telematics data can uncover real-time crash probability insights that provide the knowledge you need for safety communication. This takes you past viewing a few highly risky events. With AI, you can see a driver’s crash probability, as well as the type of crash they’re likely to be involved in and why. You can even understand what impact their driving behavior has on the climate.
A common problem for anyone involved in risk or safety management is communicating with drivers who regard themselves as safe, because they haven’t had a crash. However, crash probability changes all the time, and data confirms that driving crash-free for many years does not necessarily mean that current crash risk is low.
A high-risk score could be the result of a few risky decisions or a few lapses in concentration, but often a sudden change in crash probability can mean that a crash is imminent. It’s therefore extremely useful to utilize real-time data-driven insights in your safety management program. This helps to ensure you can effectively communicate with employees about their crash risk before it gets them into trouble.
At Greater Than, it’s our mission to empower our customers with the most meaningful driver impact insights. To do this, we convert GPS data into comparable crash probability and climate impact scores. This provides an at-a-glance view of individual driver risk and climate impact, making it easy to identify drivers in need of training or support, and those in need of recognition.
Often, drivers aren’t aware that their driving requires attention. In fact, a study of drivers in the United States found that 73% considered themselves better-than-average. Having the tools to measure driving attitude and identify strengths and weaknesses can therefore prove valuable in demonstrating the importance of safety management to drivers.
Of course, it’s important to remember that communication around driver safety isn’t intended to shame or single out drivers. Instead, it’s to empower drivers to want to adopt safe, eco-friendly driving attitudes.
At Greater Than, we not only identify crash probability, type, and associated cost for every driver in real-time, but also the primary contributors to the driver’s risk level and recommended action to remediate risk.
With our Crash Probability Tool, you can view drivers by risk level, see crash type and cost, observe risk level changes between days and trips, and also reasons for risk level. The Tool also recommends a course of action, such as an informal conversation and training, and allows you to track and evaluate the action taken.
Our AI works by converting GPS data into driving patterns, which we then compare against our database of over 7 billion real-life trips to identify if that particular driving pattern has been seen before. By doing this, we have determined the most common patterns with high-risk. We’ve also identified some of the most common contributors to high-risk driving. These are:
Addressing the areas of Focus, Anticipation and Speed Control is likely to see a reduction in driver crash probability and climate impact, and contribute positively to your safety management program. And, if you implement AI into your program, you will see accurate insights for each driver that will support your communication plan.
GPS data is all that’s needed to get started with Greater Than’s AI, which can be shared with us via a simple API connection. No in-vehicle hardware is required, nor is any additional technology. The data can be transferred via dashcam, connected car, telematics device, or any other system.
Our driver scores – Crash Probability Score or Climate Impact Score – can be pushed to your existing safety management programs, a driver app, SDK or visualized via one of Greater Than’s add-on solutions, such as the Crash Probability Tool.