Harnessing Data Analysis for Fleet Safety: Turning Information into Action

Motor carriers have access to an ever-increasing volume of data. The Federal Motor Carrier Safety Administration (FMCSA) collects substantial amounts of roadside inspection data available to each motor carrier. Although Electronic Logging Devices (ELDs) and dash cams do not prevent violations or crashes, they are excellent at recording them, providing invaluable data. Additionally, motor carriers can now monitor speed and hard braking, leading to a wealth of information that, while not preventative on its own, can significantly enhance safety when properly analyzed.

The Value of Data in Fleet Safety

The true value of this data lies in its analysis, action, and coaching. Simply collecting data is not enough; the key is to analyze it to uncover trends and relationships that can inform safety initiatives and driver coaching.

Setting Up Data Analysis

1. Data Integration: The first step is to capture data in a format that allows for effective analysis. This can be challenging, as data often comes from multiple sources in various formats. Motor carriers may need to seek assistance from external vendors to successfully integrate this data.
2. Identifying Trends and Relationships: Look for patterns in the data. For instance, is there a correlation between hours of service violations and speeding tickets? Are there geographical variations in the types of violations and tickets issued? Understanding these trends can help create targeted safety and prevention initiatives.

Practical Applications of Data Analysis

• Driver Coaching: Use data to identify coaching moments. For example, if data shows a driver frequently hard brakes or speeds, this could indicate the need for additional training.
• Safety Initiatives: Develop safety programs based on identified trends. For example, if evening commute hours are shown to be riskier, implement measures to mitigate these risks.
• Operational Insights: Use data insights to inform maintenance schedules and dispatching decisions. For example, if data shows a higher incidence of violations in certain geographic areas, adjust routes or schedules accordingly.

Case Study: Evening Commute Risks

A recent report from a technology company working with trucking companies revealed that the evening commute hours (4 pm – 7 pm) are three times riskier than the morning commute (5 am – 8 am). This information, while speculative in its reasoning, highlights the importance of analyzing data to understand and mitigate risks. By integrating these findings into daily operations, motor carriers can take proactive steps to reduce risks and improve safety outcomes.

Final Thoughts

Data analysis for fleet safety is a powerful tool for motor carriers. By effectively capturing, analyzing, and utilizing data, carriers can create actionable insights that lead to improved safety and reduced risks. The task may be challenging, but the potential rewards in terms of enhanced safety and operational efficiency are significant.