From smarter fleet telematics to video intelligence, transportation technology is constantly advancing. But the driving force behind all of these technologies remains the same: fleets need to be safer, more productive, and as cost efficient as possible. To that end, fleet management solutions are progressing into new territory.
Without a doubt, predictive analytics will play a significant role in the future of transportation. Let’s examine the current capabilities of this technology—and how companies like Trimble are paving the way for more advanced applications and insights.
What Is Predictive Analytics?
What do we mean when we talk about predictive analytics? There’s definitely some confusion around the phrase, with some fleet managers and other industry professionals expecting detailed and accurate insight into the future. This “crystal ball” view doesn’t quite hit the mark. In reality, predictive analytics relies on using existing data to identify patterns and prepare for the likelihood of events to come.
It’s easy to see predictive analytics at work in everyday life—simply look at e-commerce stores that suggest products based on what you’ve recently clicked on or purchased, or peruse the “recommended for you” section on your streaming service of choice. These technologies are already a part of many consumers’ daily routines, and now they’re being put to good use in the transportation industry.
What Predictive Analytics Offers the Fleet Management Industry
The goal of predictive analytics is to provide an operational awareness of an enterprise that goes beyond merely reporting data. Where current telematics solutions amalgamate and display the information that’s already there (crucial in its own right), evolving technologies are leveraging machine learning to more closely isolate patterns and help fleets predict and prevent problems before they even occur. Here’s a look at how predictive analytics are already making their mark on the transportation industry.
Advanced Fleet Telematics
Current fleet maintenance management technologies are making excellent use of engine data, parts tracking, and other important information to monitor truck health and catch faulty or worn parts before they cause an expensive breakdown and excessive downtime for the driver. This is made all the more valuable by machine learning, which enables massive amounts of data to be analyzed effectively without requiring back-office staff to invest hours of manual labor.
Trimble’s Fault Code Monitoring™ is a prime example of exactly this. A telematics device collects data from an engine’s electronic control module. This information includes everything from oil pressure to coolant levels, and it’s quickly analyzed to identify any indicators of potential fault. With that information in hand, fleets can ensure trucks receive preventative maintenance and needed repairs—instead of emergency roadside assistance.
Improved Driver Retention
Improving the driver experience is key to reducing turnover and attracting experienced drivers. But quantitative data can only tell you so much. Wouldn’t you also like to understand the qualitative side of things? Predictive analytics is already being used to identify at-risk drivers and empower back-office staff to work to retain them. The result? Happier drivers, improved driver utilization, and a more productive fleet.
Just look at Trimble’s recent addition to our already predictive Driver Retention model. Sentiment analysis brings an extra layer of insight to the table. Along with operational data, such as how many trips drivers are making, analyzing changes in driver messaging can provide a more thorough understanding of a driver’s turnover risk. Ultimately, this predictive model can help fleets eliminate pain points and retain their skilled drivers.
Fleet safety is one of the most prevalent topics in the transportation industry today. Fortunately, technologies like Trimble’s Video Intelligence™ solution are making it increasingly simple to promote safe driving behaviors and address risks. Video recording triggered by company-controlled parameters, wireless backup cameras, and side view cameras all work together to provide a clearer picture of the road for both drivers and dispatch personnel.
Machine learning comes into play here, as well. For example, Trimble’s Intelliview™ employs Artificial Intelligence to automatically identify and flag both “primary” and “secondary” risks. With a better understanding of which drivers require coaching, back-office staff are more able to address dangerous driving behaviors—before they lead to an accident.
The Future of Transportation Technology
As machine learning continues to advance, we expect to see the transportation industry further embrace predictive models and machine learning. This method of processing and interpreting data with a future-focused mindset has untold potential. From fleet safety and maintenance to driver retention, predictive analytics has plenty more to offer—and we intend to unlock those benefits. Trimble is committed to continuing to develop and deliver industry-leading solutions that make use of AI and machine learning.
Transportation Industry Insights and Solutions
We’re proud to produce cutting-edge transportation technologies that make a real difference in fleet safety, productivity, and your bottom line. Trimble also strives to provide key insights into current events and other forces affecting the transportation industry. For more news and further learnings, make sure you take a look at our blog. And if you have any questions about our scalable suite of mobility and management solutions, don’t hesitate to reach out.