Research Study

Predict High Risk Drivers and Decrease Road Incidents

Identifying Fleet Driver Safety Risk Factors by Assessing Attitude, Values & Personality

Driver Safety Research Study

The Objective

This data analysis was performed to determine the effectiveness of TalentClick assessments in predicting job performance and safety-related behavior by analyzing data from new hires. The analysis builds on a research data sample collected from the largest privately-owned bus transportation company in Canada to predict and decrease road incidents. The data analyzed aimed to:

  • To establish which personality characteristics in drivers and Collision Rate operators are linked to behaviors and outcomes (safety incidents, collisions, absenteeism, company rule violations, etc.)
  • To help create a business intelligence tool which can be used to help hire safer drivers and coach existing drivers

TOP 3 Predictors of High-Risk Driving Behavior

1. Contented
more vehicles damaged
6x Higher Preventable Collision Rate
Achievement-Focused drivers are significantly less likely to receive complaints, have preventable collisions, or underperform compared to highly Contented drivers.
2. Distractible
low performing drivers
6.9x More Delays
Focused drivers are significantly less likely to have improper lane handling, tardiness issues, or passenger complaints compared to their Distractible counterparts.
3. Impulsive
higher telematics speeding
2.2x More Speeding Events
Cautious drivers are significantly less likely to speed or accelerate excessively, resulting in a safer, more reliable driving record.

Driver Safety Research Study

Highlights of Findings

The data analysis involved examining the relationships between the TalentClick assessment
data and the driver safety incident data.

  1. 1. Drivers with certain personality traits have elevated levels of risk for:
    • Problematic telematics data (lane handling, acceleration, speeding, cornering).
    • Problematic job performance (complaints, absenteeism, lateness, poor safety scores).
  2. Job Performance Ratings were shown to be a valid measure of driver performance.
    • Contentedness & Impatience were linked with under performance.
  3. An ‘Ideal Profile’ based on this analysis can be used for driver hiring and training
Incident Type #1: Tardiness
  • Drivers who scored high on the ‘Distractible’ dimension had a ‘Late to first stop’ rate that was 6.9 times higher than others (588% higher tardiness rate).
  • Drivers who scored high on ‘Impulsive’ had a ‘Late to first stop’ rate that was 5.6 times higher than others (463% higher tardiness rate).
Traits that Predict Tardiness
  • Distractible
  • Impulsive
Driver Safety Quotient
Incident Type #2: Performance
  • Drivers who scored high on the ‘Contented’ dimension had a complaint rate that was 6.2 times higher than others (523% higher complaint rate).
  • Drivers who scored high on the ‘Impatient’ dimension had performance rate that was 2.8 times lower than others (184% lower Performance rate).
Traits that Predict Poor Performance
  • Contented
  • Impatient
Attitude-Values-Personality
Incident Type #4: Preventable Collisions
  • Drivers who scored high on the ‘Contented’ dimension had a preventable collision rate that was 6 times higher than others (500% higher preventable collision rate).
Traits that Predict Collisions
  • Contented
Workstyle & Performance Profile
Telematics Data

The data analysis involved examining the relationships between the TalentClick assessment data and historical driver safety incident data provided by the organization on:

  • Lane Handling
  • Speeding
  • Acceleration
Traits that Predict Incidents
  • Distractibility
  • Impulsive
  • Impatient

Research Study

Driver Safety Research Study

Through analysis, the Company learned that by hiring more “ideal profile” employees who are less Impulsive, Distractible, Contented, Irritable and Rule-Resistant, they could improve the safety of their workforce, saving time, money and lives.

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transportation driver 1

Driver Safety Research Study

Detailed Research Outcomes

A clear view of which personality traits were most strongly linked to driving incidents, near misses and property damage. Knowing these risk factors helps ensure the most effective hiring, training, coaching and development programs are available.

transportation driver 2

Recommendations for Moving Forward

Using Workforce Insights To Make Better Hiring & Training Decisions

  • Use dimensions to make personnel decisions.

  • Develop “Ideal Profiles” of high performing employees.

  • Optimize job performance ratings

  • Analyze long-term patterns.

Recommendations for Hiring:

  • Assess ALL driver candidates.

  • Exercise caution with candidates who have scores outside the Ideal Profile.

  • Use personalized interview questions to probe potential problem areas.

Recommendations for Training and Coaching:

  • Use the assessment as a training and post-incident tool.

  • Use the assessment results to guide extra training and coaching.

  • Provide Participant copies of results to drivers for self-awareness.

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