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Reducing Workplace Accident using Analytics

Editorial Team
10/10/2016 9:23 PM


Accidents impact on a company’s greatest resources: its drivers, client property and the vehicles they operate. We tested 54 drivers from a local company in Zimbabwe using the Fitness To Drive Plus Vienna Test System. Each driver’s test results were then matched with the driver’s record of road traffic accidents from 2014 to 2015. This would allow us to build a logistic regression model (using psychometric results and accident records) that distinguishes good drivers from bad drivers.

Key Findings:

1. We established that psychometric attributes of an individual can be used to predict proneness to road traffic accidents.
2. We built a logistic regression model that distinguishes drivers who had a road traffic accident record and drivers who did not have a record with an accuracy rate of approximately 72%.
3. Concentration and Reactive Stress Tolerance dimensions had a statistically significant relationship with road traffic accident records.
4. There was no significant evidence in the data that we analysed to suggest that holders of a Defensive Driving Certificate (DDC) are less prone to accidents than non-holders. In other words, there was no significant evidence to suggest that holders of a DDC are better drivers than non-holders of a DDC.
5. The age of a driver and the number of years an individual has had a driver’s license have fairly significant relationships with the number of RTA. In other words older and more experienced drivers are likely to have less accidents than younger and less experienced drivers.
Download attachments:reducing_workplace_accident_using_analytics

Editorial Team

This article was written by one of the consultants at IPC

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