SMART 360° FLEET PREDICTIVE ANALYTICS

Why it’s not enough to know where your drivers are heading to.

Fleet management solutions have been around for quite a while and have gained a lot of trust from fleet operators.
They are a necessary tool to do real-time mapping of fleets, dispatch drivers, and do basic reporting. Most of the larger commercial fleets are equipped with tracking systems connected to the OBD port to retrieve maintenance alerts and failure codes.

The daily job of fleet managers is to maximize the fleet’s profitability and mitigate risks of fleet vehicles using various tools to get the right information to make informed decisions. Fleets need to cut costs — with steadily growing energy expenses, every single Euro spent is too much. With mobility data, being it at the granular level of the individual trip, the single driver, the vehicle, or the overall fleet, operators can optimize and ensure profitability. We enable that with data augmentation, profiling, and predictive algorithms design based on your historical data.
Moreover, analyzing this data helps in better risk assessment, effective implementation of coaching plans for drivers, improving eco-efficiency, and doing the first step into predictive maintenance.

Predictive analytics can be the right hand of fleet managers to help them proactively manage their fleets in a highly competitive landscape. Forget thinking one-dimensional, only about where your drivers are and discover how to go from basic tracking to multi-dimensional insights, thanks to the contextualization of data and profiling. Let’s dive into the fascinating world of using predictive mobility data analytics for your fleet.

Basic ABC(S) (Acceleration, Braking, Cornering, and Speeding) analytics are widely used to monitor driving behavior, but they do not mirror your drivers’ exposure to an accident. Why that? Simply because they do not contextualize these risk events. Imagine a simple scenario: you are accelerating as you are entering a highway. Without context, this maneuver could be detected as a risky driving event — which it is obviously not. However, being speeding much faster than the average traffic in an urban environment but being slower than the speed limit indeed increases your risk of having an accident. The difference between both is the augmentation of mobility data with its spatial-temporal context. Where and when your fleet members are driving is significantly influencing their risk and your opportunities to coach them in safe driving to predictively lower accidents. Side note: A proven low-risk portfolio of your fleet will allow you to negotiate better tariffs with your preferred insurance partner. Lower accident risk means lower claim costs — every insurer likes that type of customer.

Over the past years, the lifeblood of your fleet — fuel — has become more and more expensive. Coaching drivers in eco-efficient driving, meaning helping them improve their driving style (e.g., avoiding aggressive driving, harsh acceleration, …), is a proven means to cut costs and stay competitive.

On par with lowering fuel consumption, the increasing number of commercial vehicles powered by electricity allows fleet operators to optimize their fleet. Still, there is a lot of insecurity around if it makes sense to flip from traditional combustion to hybrid or full EV. Fleet operators and managers need to have deep insights into their overall fleet’s mobility patterns, such as average trip distances, idle times available for charging, charging infrastructure at trip end locations, and along the most common routes, among others. With all the data already available, fleet operators can objectively assess EV suitability to be prepared for upcoming regulatory changes regarding CO2 emissions.

Vehicle downtimes are causing costs — not only repair costs but also the ones of unproductive workforce and revenue loss. Assessing the influence of individual driving behavior on vehicle component wear gives you insights into your fleet’s health status and lets you coach your drivers to reduce wear. Before a breakdown happens, scheduling maintenance is much more favorable and cheaper than all related costs of corrective, ad-hoc repairs.

Each and every route has its characteristics: the number of accidents happening, the route topology, among other factors. Rating routes not only by distance and the probability of traffic, but profiling them regarding the three dimensions of risk, eco-efficiency, and wear allows you to assess the costs for a trip holistically. Stop thinking one-dimensional but harness the power of data to create a smart way of route planning.

To conclude: predictive fleets analytics takes massive amounts of data into account but helps you ultimately to gain profound, simple to understand, and actionable insights into your fleet’s performance. Convert your tracking data from traditional telematics systems installed in your vehicles into smart predictive models for your fleet wear and operations.

Key takeaway: Do not limit yourself only to track your drivers but use your greatest asset — driving data.

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