Precise predictive maintenance is a new addition to a well-established suite of management reports based on telematics data. These have historically focused on key performance indicators such as driver behaviour and engine idling times.
Analysis of the data can identify higher risk drivers who accelerate more quickly and brake more sharply than their peers, paving the way for subsequent training.
Tracking vehicles in real-time is central to a number of customer service initiatives, from courier firms being able to offer narrow time windows for deliveries, to taxi and ride-hailing businesses to give precise pick-up times.
Drilling into journey data has also provided valuable insights for route planners to avoid congestion hotspots. In one of the most productive applications of telematics data, logistics giant UPS identified that turning across the flow of traffic caused significant delays for its vehicles, costing time and fuel, so the company optimised its routes by minimising and even eliminating left-hand turns (the research was conducted in the US where vehicles drive on the right).
This simple idea has saved UPS more than 10 million gallons of fuel, with a commensurate fall in its CO2 emissions, despite the extra distances involved in avoiding the left turns.