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Telematics systems are increasingly being used by fleet operators and insurance companies to mitigate occupational road risk. With the vast majority of fleet driving undertaken on a solitary basis, telematics systems enable driver behaviours to be remotely monitored in order to identify those at risk of a collision.
However, whilst telematics are excellent at monitoring individual driver behaviour, without adequate feedback the driver is unlikely to change their behaviour. Companies using telematics without taking into account how the information is given to the driver may not see the full benefits of the technology. Current research indicates five key principles to focus on when devising a telematics feedback strategy.
Large amounts of data are collected by modern telematics ystems and often the fleet manager can select what to monitor from a vast array of indicators such as harsh braking, speed violations, harsh acceleration, cornering etc. Anecdotal evidence from the telematics industry suggests that ‘less is more’ when it comes to feedback data to avoid overwhelming the driver with lots of information. A small number of key indicators for feedback may be preferable so that the driver can focus on particular components of their driving style.
The relative merits of immediate (in-vehicle) and delayed (post-driving) feedback of data are the subject of debate between researchers and road safety experts. Whilst immediate feedback can be effective, it can add to in-vehicle distractions, potentially placing the driver at risk of a crash (Green, 2004). Therefore, if immediate feedback is given it should not require any complex cognitive processing or be distracting.
Fleet managers should consider carefully how often information should be given to drivers about their driving.
Telematics systems enable the continuous delivery of feedback data to drivers in vehicle or after each journey via an app. One of the disadvantages of providing feedback via an app is that drivers may fail to check how they are doing on a regular basis and therefore fail to change their behaviour. On balance, the optimal frequency for telematics data feedback is likely to be weekly, for most drivers.
Telematics can be highly effective at measuring key indicators of high risk driver behaviours. However,
telematics data cannot tell us why this behaviour takes place or the motivations underpinning the behaviour. Using a research validated assessment such as DriverMetrics Profiling, will provide the information you need to understand the traits influencing high risk behaviours.
For example, a driver may speed for a number of different reasons – perhaps they are feeling stressed because they are running late, perhaps they feel angry about other road users getting in their way so they drive too fast to let off steam etc. DriverMetrics Profiling will allow you to make sense of the telematics data from a behavioural perspective.
Several studies (e.g. Carey, Phillipon & Cummings, 2011) have found that personal feedback is effective when delivered via a coach and there is no reason to doubt that this approach will not transfer to the driving context and lead to behavioural change. Behavioural coaching is increasingly being adopted as a methodology for behavioural change using telematics data, with coaches using psychological profiling in tandem to
facilitate effective coaching conversations with drivers.
The coach and the driver agree on goals for improving their telematics scores and give reinforcing feedback when their driving style improves over time. Many fleet operators have found that this method leads to long term behavioural change and reduces the number of collisions. It is clear that telematics systems are a very powerful asset for the fleet manager seeking to reduce collision risk.
However, careful thought needs to be given to the most effective use of the data collected, particularly how the data is fed back to the driver. An optimal telematics feedback strategy is likely to focus on the level of detail, timing and frequency of information, together with the use of psychological driver profiling and coaching.
This article originally appeared in Fleet Manager Magazine.
Carey, W., Philippon, D. J., & Cummings, G. G. (2011). Coaching models for leadership development: An integrative review. Journal of Leadership Studies, 5, 51-69
Green, P. (2004). Driver distraction, telematics design, and workload managers: Safety issues and solutions. SAE paper 2004-21-0022.