Omnitracs ELD Driver Retention Model

Driver Retention has become an increasingly large problem for fleets of all sizes over recent years. That is why Omnitracs created the ELD Driver Retention Model (EDRM)— to help fleets identify drivers at risk of voluntary termination, allowing for timely remediation.

Omnitracs Analytics ELD Driver Retention Model is the first predictive model of its kind, created to reduce voluntary terminations (turnover) in the driver population by pinpointing the drivers most at risk through predictive modeling, and by providing proven remediation strategies for uncovering and resolving issues before they lead to driver resignation.

Safety Predictors

Omnitracs Analytics analyzes thousands of data points from clients’ Hours of Service logs to identify subtle changes in driver behavior, which represent a pattern in driver behavior that leads to voluntary termination, including those to the chart to the left.

It’s About the Big Picture

Contrary to conventional wisdom, no single data point can be used to accurately predict future events on a consistent basis. Omnitracs Analytics' predictive modeling technology uses all available data across thousands of hours of service data points to build a true picture of the driver's behavior and find the trends that matter.

We're at the Center of Big Data

Omnitracs Analytics further supplements your fleet’s data with external data sources and internal insights we’ve collected for over ten years. Touching more than 1,500,000 mobile assets each day, Omnitracs Analytics’ breadth of global transportation data is unmatched.   

Further, this data is used to create a comprehensive image of driver performance, and more importantly, a map to detect the changes in behavior that are proven to indicate higher voluntary termination risk.

The Proof is in the Numbers

Omnitracs Analytics’ predictive modeling and remediation strategies help you identify the drivers who are most likely to voluntarily quit so you can limit driver turnover, reduce related expenses, and enhance overall productivity.

The graph above shows the efficacy of the ELD Driver Retention Model when run across live data points from over 450,000 drivers’ hours of service data logs to determine which drivers are at risk of early termination. The ELD Driver Retention Model identifies similar outliers in a driver’s Hours of Service data that correlate with the data points of drivers who prematurely terminate employment. This allows Omnitracs to predict 63% of the quits within the top 20% of fleet drivers.

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