By Kayne Grau, CEO of Uptake
Many in the trucking industry are optimistic that 2023 will bring an increase in demand that will keep vehicles on the road and fleet managers busy. But there is another increase that is keeping these managers awake at night: the rising cost of doing business.
The industry was battered by economic headwinds in 2022. While some of these are beginning to abate, the backlog of supply chain issues is not easily or quickly resolved.
Last year, trucking companies extended the life cycles of their vehicles because of a lack of available new trucks and added stressors related to inflation. This year many of these older vehicles will keep on logging miles.
This means a likely increase in unexpected and unscheduled repairs that can threaten the bottom line. But there is another problem that can come with extending the usage of older trucks: it can exacerbate the country’s shortage of drivers. In 2022, the American Trucking Associations (ATA) estimated the trucking industry is short roughly 78,000 drivers, nearly a record-high. Consistently, fleets have reported that failing equipment and breakdowns has a direct impact on whether or not a driver leaves a fleet.
Fortunately, there are new technologies and data science techniques that fleet managers can use to not only stay ahead of the maintenance needs of older vehicles, but keep their drivers from looking for another job.
Keeping Drivers
Recruiting professionals say the country needs between 65,000 and 80,000 additional truck drivers to ensure the timely delivery of food, medicine and other goods from coast to coast. But the shortage could grow more severe – with as many as 160,000 empty driver seats – over the next decade unless there is a massive influx of new hires.
The ATA has the stated goal of bringing aboard one million new drivers by 2030; that will require the industry to face the many reasons why the shortage exists in the first place. These include a difficulty in recruiting younger workers to an industry where many older workers are retiring.
Driver turnover is another major problem that will need to be addressed. Carriers must hang on to every driver they hire, which could be more challenging as younger drivers take the wheel of older trucks. Frustrations will mount as drivers sit idle, waiting on parts and repairs when they should be driving and earning. With more vehicles on the road with higher miles, these delays could easily grow longer and more frequent.
There are steps that fleets should take now to help keep drivers on the road, or from departing the industry altogether, and it starts with predictive maintenance.
Staying Ahead of Maintenance Needs
By implementing a more predictive maintenance strategy, fleets can increase the uptime of their vehicles without keeping drivers sidelined. They do this by using the existing telematics device that is gathering sensor and fault data, which is abundant but difficult to decipher manually.
What trucking companies need is not more data, but a method to synthesize the information they are already collecting. They need actionable insights on which vehicles will likely need repairs, and when. Predictive analytics are the key, because they quickly analyze volumes of data so fleet managers don’t have to, recommending actions that can instantly be handed over to maintenance teams to extend the life cycles of vehicles.
Maintenance teams, in turn, can use work order analytics to get a historical view of their vehicles’ work orders to help identify trends — for example the time of year trucks see more unplanned maintenance because of inclement weather. These analytics can help them plan accordingly, enabling fleets to order replacement parts in advance and schedule repairs during routine maintenance visits to increase uptime.
Likewise, if fleet managers look at their work order analytics and notice their aging fleet is seeing an uptick in unplanned shop visits, they can shorten their preventative maintenance cycles to catch part failures before they occur.
Economic challenges facing the trucking industry mean that fleet operators will be keeping older vehicles on the road as long as they can. Standard preventive maintenance cycles suggested by OEMs – and predetermined intervals that worked fine for carriers in the past – aren’t likely to cut it anymore. Keeping vehicles optimized and ready for duty will take preventive and predictive maintenance.
Fleet operators can accomplish this without causing drivers to wait long stretches when they should be earning. By using analytics to turn data into action, they can help drivers avoid roadside breakdowns and keep their trucks rolling. Take it from Mark J. Anderson, President and CEO of United Road.
”We know truck breakdowns and maintenance are the number one dissatisfiers for our professional car haulers. Our fleet has aged slightly through the pandemic and we have found predictive maintenance to be an invaluable resource in avoiding breakdowns and downtime for our truck and our car hauler. Our pay and benefit programs are excellent whether our employees are behind the wheel or on the side of the road, but everybody – the customer, the company, and especially the professional car hauler – would prefer to be working at their skilled craft vs. dealing with a frustrating breakdown. Predictive maintenance has helped us accomplish just that!”
Predictive maintenance won’t solve the driver shortage overnight. But as these analytics save carriers money by recommending proactive repairs that eliminate more expensive repairs later, they can ease many of the frustrations that cause drivers to quit.
Kayne Grau is CEO and Board Member of Uptake, a leader in predictive analytics software-as-a-service (SaaS). Prior to Uptake, Grau held various senior executive roles at companies like KAR Global. When he’s not leading the team at Uptake, he spends his free time assisting various companies as a board member, advisor and investor.
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