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Updating Your Safety Culture in the Age of ‘Big Data’

By Kevin Reilly, Editorial Communications Manager, The CEI Group, Inc.

As more fleets upgrade their safety programs with emerging technologies, particularly telematics and prescriptive analytics services, it is important for fleet managers to consider how these technologies will fit into and shape their safety culture. Knowing how these big data technologies function, as well as their varied reporting options, is the first step. Next, is the need to set realistic short- and long-term goals.

Telematics

Generally, drivers know how to drive safely, but throughout a busy work day, as the road distractions creep in, safety often takes a back seat. Telematics can be helpful in this area to act as a behavior change agent by continuously recording and reporting a driver’s actions. As a fleet manager, you will now become aware that a driver has a series of rapid accelerations and harsh braking episodes that could lead to an accident. Having access to a stream of information on erratic driving behavior allows a manager to take action with prescribed training. It also allows a driver to keep in mind those habits that they need to change.

Predictive and Prescriptive Analytics

Predictive models provide managers with the probabilities of an accident for the driver and are more accurate than classic risk grouping formulas that utilize only three years’ worth of MVR and accident history. Prescriptive analytics solutions combine predictive prognostication with recommended actions to reduce the probability of an accident using five years’ worth of MVR and accident history, driver demographics, national highway and traffic data, and more.

The difference between predictive and prescriptive analytics is the ability to take the actionable data and prescribe appropriate courses of action to rectify driving behavior to prevent a collision.

Tailoring Technologies for Specific Needs

Optimizing telematics and prescriptive analytics for driver safety is a case-by-case matter. Since every safety culture differs from fleet to fleet, it is vital to have the ability to tailor these tools for a fleet in a way that benefits drivers and managers up and down the chain of command. The manager of a small fleet may want to have an alert come in every time a driver breaks the posted speed limit by 5 miles per hour. But, a larger fleet may find that system to be too much and set an alert only for drivers who break the posted speed limit 20 times or more in a given week.

An often-overlooked policy for any fleet safety program: Keep both drivers and their managers updated on a driver’s risk assessment and events. Tailored alerts open up yet another means of communication to impart safety policy and to change driver attitude and behavioral change.

Active discussion allows drivers and managers to buy-in to these big data technologies that may have seemed too intrusive or time consuming to use just a few years ago. Full buy-in from drivers and managers is crucial to sustained improvements in a fleet’s driving safety culture.

Reasonable Goal Setting

Setting reachable goals is often the hardest part to successfully integrate big data technologies. With telematics, for instance, the first few months of technology adaptation may be rocky. Managers will want to correct and discipline drivers right away for the high number of bad driving habits their drivers will display. Still, it will take time for drivers to respond to data that shows them their bad habits, and managers need to realize that bad habits die hard.

Use of these big data technologies to improve a safety culture takes a long-term commitment and a series of small, reachable milestones to hit along the way. The reward for such commitment is seen in a multitude of ways such as less vehicle and driver downtime, savings in overall accident repairs and tune-ups, and most importantly fewer injuries for drivers. Telematics and predictive/prescriptive analytics technologies are shaking up the fleet industry. Now is the time to adopt.

 

Feb 20, 2017Janice
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