If you only look at the annual maintenance costs in this graph, you get the impression that costs are roughly the same regardless of age. However, when you take annual cost per mile and annual mileage into consideration a far different picture emerges.Image: Utilimarc
In an increasingly connected world, technologies such as telematics are providing fleet managers with more information than ever before about their vehicles and their performance. But having that information and being able to analyze it in a useful way are two completely different things. Paul Milner, a senior analyst and product developer with Minnesota-based fleet analytics firm
“If you have a problem unit that’s constantly breaking down, it’s unlikely that it will ever make it to that higher life-to-date mileage.”— Paul Milner, Utilimarc
Utilimarc, spoke with Service Truck Magazine about the conflict between what people believe and what fleet data actually shows and the importance of finding the right ways to utilize and analyze the information available.
Where the conflict exists
While Utilimarc’s work is specific to the gas and electric utility industry it is nevertheless applicable to many other sectors, said Milner, who delivered a talk on fleet data misconceptions at the Work Truck Show in Indianapolis this March.
“We started out as a benchmarking firm, looking at maintenance performance between these like fleets,” Milner said. “One of the questions we always got from folks was ‘When should I be replacing my assets?’ The way we phrased the question after we were working with folks was ‘What effect is the vehicle age and the life-to-date mileage on the maintenance costs that we have recorded?’”
The company Utilimarc was working with had years of maintenance data on hand, so they attempted to use that to identify at what point it becomes more expensive to continue to maintain an asset as opposed to the cost of obtaining a new one. The company insisted that the data showed that maintenance costs were flat as their assets aged, and Utilimarc’s initial analysis showed the same thing. However, they were looking at the total maintenance costs as the assets age and were not accounting for the fact that as units got older crews tended not to use them as much.
“We could see the drop in utilization in terms of the mileage and fuel consumption on the assets,” Milner said. “We suspected it was either that the older units are breaking down more often so they’re not getting used as often or the crews don’t like using the older equipment or what have you. So we decided to rephrase the question as a cost per utilization and almost immediately we saw that there was a pretty significant linear trend in the cost per mile in these assets as they age.”
They found an association with age — as vehicles get older, the cost per mile goes up. But in terms of life-to-date mileage, they actually saw a negative correlation. Units that had a higher life-to-date mileage actually cost less per mile in order to do the same work, accounting for the utilization factor. It’s a surprising finding, but life-to-date mileage isn’t actually an indicator of how expensive a unit is to operate.
“This is a statistical relationship we’re seeing with the data, not a causal relationship,” Milner said. “We’re not telling folks to go run an extra lap around the garage every time you park the vehicle. We suspect it’s more likely, if you think about the way these vehicles drive, they incur a cost only when they’re not being utilized — when they’re in the garage and not at the job site. If you have a problem unit that’s constantly breaking down, it’s unlikely that it will ever make it to that higher life-to-date mileage.”
The balance of life cycle cost analysis
Many companies tend to view life-cycle cost analysis as a balancing game, where they either end up paying more for maintenance costs if they don’t replace a service truck or paying more in ownership costs if they do replace it. However, unless the truck is way outside of the life cycle, those costs should only be a few hundred dollars a year per unit, not in the thousands.
“If you’ve got a fleet that’s a couple of thousand units, over the lifetime of that asset it does add up,” says Milner. “But where it does wind up becoming an issue for a lot of folks that we’ve worked with is planning for the vehicles being available, whether they’re younger or older, and also planning for technician demand.”
During the economic downturn a few years back, many companies stopped purchasing new equipment. However, when their existing units broke down, many companies lacked adequate technical staff to cover the repairs. On the other hand, companies that leaned more heavily on purchasing new assets risked having underworked technicians because of the lower labour requirements on newer equipment.
“How folks are spending money in terms of replacement on their assets can affect the organization and how the organization runs as a whole, outside of just the straight maintenance costs on the vehicles,” Milner said. “When you’re comparing the maintenance and ownership costs, a lot of times there isn’t too much of a difference in terms of the long-term monetary strategy. But there is a difference in terms of the service that you can provide and the personnel that you’d need in order to maintain those units.”
Skills gap at the heart of the matter
Many companies that Utilimarc has worked with simply lack dedicated analysts who have the time or ability to process all the information being collected. With more and more information coming in, the problem is getting worse.
“Everybody is moving to telematics devices, which have a much, much larger data set than the historical work order systems that they’ve been utilizing,” Milner said. “There’s all this extra information, and we’ve shown that support staff has actually gone down in our industry almost 30 percent over the past five years. Those two factors come together and we’ve got folks with more information and less people to process it.”
Fleet managers, for example, are primarily tasked with keeping the vehicles up and running for the crews. That is a demanding full-time job on its own, leaving little time for exploratory analysis into datasets and processing what those numbers mean. For that reason, many companies would be well served to invest in a dedicated support staffer or to engage the services of a company with expertise in that area.
— Matt Jones
Matt Jones is a freelance writer based in Fredericton, N.B.
