Omnitracs Predictive Analytics gives fleet safety managers a powerful tool to help prevent collisions before they occur. Predictive Analytics identifies driver behaviors on and off the road that indicate a greater level of risk. Fleets can then take proactive measures such as counseling to reduce that risk.
The failure to avoid a preventable crash, especially when warning signs went unnoticed and unheeded by fleet management, can have devastating consequences to human safety and fleet operations. In the US in the last few years:
Fleets generate enormous volumes of data from dedicated and mobile telematic devices on a daily basis. Predictive Analytics uses that data to establish accident patterns. AI and machine learning can then use that data to predict future risky behavior so fleets can take action.
Use the predictive power of AI and machine learning
Predictive Analytics uses AI and machine learning to automatically compare the driver’s current data against their historical trends. Using our proprietary algorithms, Predictive Analytics can spot changes in driving habits, even subtle changes, that can indicate increased risk.
A wide range of data for the complete risk picture
Each risk analysis searches for patterns among 1,200 comparative data points, including previous employment, time between jobs, number of positions and tenure, license and certifications, on-time reporting for duty, and other attributes.
Probability-based analytics achieves up to 90% accuracy
Probability-based analytics accurately models outcomes, with Omnitracs’ Accident Severity Model predicting 90% of severe accidents among high-risk drivers. By removing biases, fleets gain objective insights, enabling non-defensive collaboration with drivers to reduce risk.
The objectivity of data eliminates biases
Assumptions, guess-work, and personal biases have no role in data-driven risk assessment. By eliminating these, fleets have real information and can work with drivers in a non-defensive way to lower their risk assessment.
