Predictive Analytics as a Fleet Management Tool
Fleet managers see predictive analytics as a means to customize driver safety training and extend the lifespan of their vehicles.
Predictive analytics is a powerful and multifaceted tool that helps users make informed decisions for the future by using known data to predict future outcomes. It utilizes a number of techniques to meet those objectives, including data mining, statistical modeling and machine learning.
The technology has become particularly popular in industries such as insurance, finance and retail, in which companies rely on predictive analytics to assess and manage risk. But predictive analytics also could be beneficial for fleet managers seeking to improve driver safety and minimize vehicle downtime.
1- Tailored Driver Safety Training
Safer driving behavior typically results in fewer collisions and insurance claims, but it can be difficult to determine the likelihood of a preventable collision based on a given worker’s driver record. Past incidents of speeding and collisions may be indicative of future tickets and claims, but they don’t paint a comprehensive picture. A more advanced assessment would require much more data.
Luckily for fleet managers, an excellent source of data is already built into many of their vehicles. Telematics systems that track speeding, harsh braking and harsh acceleration, among others, can be an excellent source of data for predictive analytics. Users can identify areas of risk and produce overall and category-specific scores for each driver. These scores can remain the purview of upper management, or they can be shared with drivers or even entire departments, divisions or locations to foster friendly competition.
By giving fleet managers detailed information about each employee’s driving performance, predictive analytics could help create safety training programs tailored to assess and improve performance in critical areas, improving safety scores for individual employees and the company as a whole.
2- Predictive Maintenance
Predictive analytics could also be used to monitor vehicle health and improve maintenance standards. Data generated by sensors located throughout the vehicle can feed models designed to determine the early-warning signs that can lead to parts failures, mechanical breakdowns and reduced fuel efficiency.
The results can reveal such insights as which vehicles or parts are most prone to trouble, how often vehicles must be brought in for routine maintenance, and whether parts inventories are properly stocked. The most advanced models can even predict parts failures before they happen.
In the long term, this level of insight could help fleet managers extend the lifespans of their vehicles while reducing downtime and its associated costs, including overburdened service facilities, lost work hours and nondelivery charges. Most importantly, it could improve the day-to-day health and reliability of the vehicles employees rely on for safe transport.
Predictive analytics is only one of many new tools that fleet managers and their industry partners could use to improve safety, maximize efficiency and reduce costs. Leveraging this new technology and other value-added innovations in the industry will ultimately help drive companies forward.