With the arrival of artificial intelligence (AI) and machine learning, there are definitely signs of new developments in the fleet management industry. While this could open up new avenues in the future, certain fundamental components remain integral.
With the arrival of artificial intelligence (AI) and machine learning, there are definitely signs of new developments in the fleet management industry. While this could open up new avenues in the future, certain fundamental components remain integral.
“Generally speaking, basic telematics commonly refers to the date, time, and location of the vehicle's movements,” said Stephanie Voelker, VP of Enterprise Sales Solutions at
Geotab. “Many fleets find that this data is sufficient to manage their fleet needs, however, savvy fleets soon find the value in advanced data that can be derived directly from the vehicle computer.”
For instance, engine faults have an almost immediate effect on the vehicle’s MPG (Miles per Gallon) rate. Given that average fault code takes 90 days to be resolved, a fleet can be operating at a nonoptimal MPG for as much as one quarter of the year without knowing it.
“As another example, immediate notification of a suspected collision can greatly shorten the time to respond,” Voelker continued. “Again, the difference between basic fleet telematics, and advanced is driven by the fleets’ need to solve for specific problems outside of just dots on a map.”
Industry differences
Depending on the industry and the location,
the requirements change too. Street sweepers, for example, have eight different metrics related to brooms, vacuums, and water that need to be monitored to show a municipality that the roads are properly cleaned.
“Waste haulers, on the other hand, may have to prove where a load of refuse was collected to be able to dump in a county landfill; a map of the route of the truck and the location of each compaction of the trash is needed in a use case like this,” Voelker said. “Semis in the U.S. are required to be equipped with a certified ELD solution by Dec. 16, 2019. These systems are built off of telematics and monitor the driving and rest cycles of drivers to improve highway safety. As you can see each industry has its own unique requirements for a telematics solution.”
Challenges hurting adoption
There are a variety of issues that fleets must address when deploying telematics.
First and foremost, fleets must use telematics as a means of creating value within an organization. Telematics should not be seen or used as “big brother,” although features like collision reporting telematics offer fleet the opportunity to show exactly what happened during the accident often proving a driver’s innocence.
The installation has been a bit of a barrier in the past but newer plug-in OBD (on-board diagnostics) devices remove a lot of these barriers. Most
modern telematics solutions are cloud-based, removing the need for extensive IT infrastructure. Fleets also need to consider how to manage all of the data that telematics can provide.
“The old adage is that you can’t eat the elephant whole, but you can accomplish the goal as a series of smaller steps over time,” Voelker said. “I encourage most fleets to start with the simple telematics data and manage the speeds, idle and arrival and departures, then later come back and learn how to use advanced engine data for improved fuel economy, route adherence, etc. A smart telematics solution can grow with the users; as their data management skills increase, telematics can provide more usable data.”
The unique situation in Asia
According to Gaurav Kumar, Founder of Cyrrup, which offers fleet management solutions in India, the slow pace of public policy change in the region could be a concern. This is often an issue in emerging economies as they come to terms with the rapid expansion and influx of investment. Other challenges include customers not being convinced that investing in new technology is worth it due to costs.