The impact of motor vehicle crashes goes well beyond damage to vehicles. Crashes can injure employees, injure the public, and significantly disrupt your business operations. Taking steps to reduce the human and financial impact on your business is an invaluable investment.
The National Highway Traffic Safety Administration Motor Vehicle Traffic Crash Fatality Counts and Estimates of People Injured for 2007 (DOT HS 811 034 September 2008) states that during 2007:
41,059 people were killed in motor vehicle crashes
Daytime restraint use was 82%
54% of the passenger vehicle occupants killed were unrestrained (45% daytime & 63% nighttime)
Alcohol related crashes were responsible for 12,998 fatalities
Speeding related crashes were responsible for 13,040 fatalities
Comparing your results to others with similar operations is a common business practice. Comparing crash frequency between fleets has many challenges. Most crash frequency comparisons use crashes per vehicle per year. Vehicles that pay taxes based on miles are typically measured in crashes per million miles traveled. Vehicle crashes are a result of vehicle use, and exposure to crashes plays a significant role in expected, average or median crash rates. Even within an industry there are likely to be differences based on geography that impact exposures.
Some vehicle types have more exposure to crashes because of how they are used. Exposure or use varies by industry and the business need. In addition, crash rates vary by state. Crash benchmarks that can take into account the type of vehicle, industry group and state would provide a more accurate picture of how crash rates compare than just comparing crashes per vehicle across a large group.
To assess the impact of the variables (vehicle type, industry and location), Liberty Mutual looked at vehicles insured, crash data and liability insurance premium distribution by state. This allowed the establishment of relativity factors used to calculate an expected frequency based on vehicle type, industry group and state of garaging. Each of the variables had different ranges from highest to lowest and had impact on the expected crash frequency.
There was a 250% difference between the lowest vehicle relativity and the highest vehicle relativity.
There was a 53% difference between the lowest industry group relativity and the highest industry group relativity.
There was a 650% difference between the lowest state relativity and the highest state relativity.
The impact of vehicle type will be influenced by the nature of the work done with the vehicle and being in situations where more crash potential exists.
