From TRIR to MVI: Why Backward-Looking Metrics Crash in Predicting Safety

In safety performance management, metrics are critical tools for evaluating risks and implementing preventative measures. However, as with the Total Recordable Injury Rate (TRIR), the use of Motor Vehicle Incident (MVI) frequency as a key performance indicator (KPI) warrants scrutiny. A closer look reveals that MVI frequency often fails to meet the criteria for statistical validity and predictability, limiting its utility in assessing and improving safety outcomes.

Statistical Instability of MVI Frequency

A statistically valid metric relies on consistent, sufficiently large data sets collected over reasonable timeframes to allow for accurate estimation of uncertainty and statistical precision. MVI frequency often falls short in these areas for several reasons:

Data Volume and Variability: Many organizations record relatively few MVIs annually, particularly in smaller fleets or low-risk industries. With small sample sizes, a single incident can disproportionately impact the overall rate, introducing high variability and undermining the reliability of year-over-year comparisons.

Inconsistent Reporting Practices: The definition of an MVI can vary between organizations or even within the same organization over time, depending on changing policies or subjective judgment. This inconsistency undermines the comparability of data and compromises the metric’s validity.

Short Measurement Windows: Quarterly or annual reporting periods may not provide enough data points to establish statistically stable trends, especially for events that occur sporadically. As a result, the metric becomes susceptible to noise (e.g. minor accidents) rather than reflecting meaningful patterns.

Lack of Predictive Power

Predictive validity is another essential criterion for an effective safety metric. A truly predictive metric should offer insights into future risks or outcomes. However, MVI frequency, much like TRIR, is inherently backward-looking and fails to reliably predict future incidents or risks.

Past Performance ≠ Future Risk: An organization with a low MVI frequency in one period is not guaranteed to maintain the same performance in the next. Factors such as changing road conditions, vehicle maintenance practices, driver behavior, and external environmental influences can significantly alter risk profiles.

Disconnection from Severe Outcomes: MVI frequency aggregates all vehicle incidents, regardless of severity. Minor fender-benders are counted alongside major collisions, diluting the metric’s ability to signal catastrophic risks. Moreover, the absence of MVIs in a reporting period does not indicate that the organization is immune to serious incidents in the future.

Behavioral and Systemic Influences: Relying on MVI frequency can lead organizations to focus on lagging indicators rather than addressing root causes of unsafe driving behaviors or systemic risks, such as insufficient driver training or inadequate route planning.

Toward Better Safety Metrics

To overcome the limitations of MVI frequency, organizations should adopt metrics that emphasize leading indicators and root cause analysis. Examples include monitoring near-miss events, vehicle telematics data (e.g., harsh braking or speeding), and proactive safety interventions like driver training programs or equipment upgrades.

Ultimately, while MVI frequency may offer a snapshot of past performance, its statistical instability and lack of predictive validity render it insufficient as a standalone safety metric. By shifting focus toward more robust and actionable indicators, organizations can better identify risks, mitigate hazards, and achieve meaningful improvements in motor vehicle safety.