Predictive Analytics: Get the Most Out of Your Data and Your Vehicles
When it comes time to replace certain vehicles in your fleet, many organizations use mileage and/or months in-service to determine when to cycle their assets. This method, however, doesn’t take into account the great variation in vehicle usage that can occur across a fleet or how the vehicle may have been driven.
This is where predictive analytics and leveraging big data can give fleet managers a clearer picture of the condition of their vehicles by using a model that incorporates factors like maintenance history, driver behavior, age, and mileage.
NAFA Member Bob McElheney, CAFM®, Director, Vehicle and Equipment Services for the City of Newport News, Va., said his team bases many replacement decisions on a vehicle-by-vehicle basis by examining the type of asset and what it is used for.
Data Safety: How Do You Protect Your Fleet from Hackers?
Today’s increasingly connected vehicles provide a trove of data and insight, but that brings with it another worry, especially for law enforcement fleet professionals: the valuable data also might be of interest to criminals.
What about a terrorist attack response that is dramatically slowed down because police vehicles are remotely disabled, wherever they sit?
Officers are sitting in an undercover police car, staking out a drug kingpin. Out of nowhere, the car is surrounded by armed men, because the bad guys hacked into the police network to find out vehicle locations.
The Finer Points of Fleet Data
The fleet management industry has seen an evolution in recent years centered on information technology (IT) and vehicle data. With the advent of telematics devices and vehicle tracking systems, fleet managers are utilizing IT more than ever. The statistics provided by these tools can be used to reduce vehicle downtime, keep up with preventative maintenance, improve driver safety, make informed decisions when selecting new vehicles, and more.