Using Separated Maintenance Costs to Improve Clarity of Cost of Operation

by Mathew Guice

Mathew Guice, CTP, is vice president of Sales, Capital Equipment Solutions at Corcentric. He has been with Corcentric for six years and is responsible for implementing customized financing terms to lower fleet’s total cost of ownership. Prior to joining Corcentric, he held positions with Stryker and Henry Schein.



Under the new lease accounting standards, maintenance costs must be separated from asset costs, which will give fleets a chance to re-evaluate how they account for maintenance and come to a more accurate total cost of operation.

The new lease accounting standards are going to do more than change the way leases are accounted for in financial statements. Putting lease payments on the balance sheet is also going to give fleets more insight into their true total cost of operation (TCO) if they pay attention to all the data available to them.

In the past, payment for the asset was often bundled under one category with things like maintenance, license and tags. In a full service lease, maintenance plans have historically been bundled with lease payments. Under the new accounting rules, assets and maintenance must be bifurcated or separated. This gives fleets an opportunity to re-evaluate the way they account for maintenance and financing of the asset to provide more clarity on TCO.

Having the maintenance unbundled from the asset itself gives a fleet the opportunity to really dive in to what the maintenance data is telling them. But the maintenance data needs to be combined with things like asset utilization rates, number of miles driven, number of hours on reefer units and fuel economy.

Considered in its totality, this information can help a fleet determine if there is an optimum spec for its operation, especially when it comes to fuel economy. Given that fuel is the largest expense a fleet has, getting the most out of a gallon of fuel is a plus no matter what the cost of fuel. Combining MPG data, especially when the fleet starts seeing degradation in that number, can tell a fleet manager the true cost of running each unit.

Once a fleet knows the actual cost to operate an asset, it can start to determine the right life cycle for the asset and set leasing terms that match asset life cycles for the fleet’s specific operation. If the lease term is set for 48 months, the fleet may feel good because of the low monthly lease payment. But what might not be readily apparent is that the maintenance dollars being spent in months 36 to 48 are offsetting any savings gained from the lower lease payments.

Looking at all the data may determine that the fleet would be better off with a 36- or 39-month term. Although it would be paying more in fixed costs on the asset, it wouldn’t be seeing the high maintenance costs which, in some cases, can be triple what was spent on the lease payment.

When the finance and maintenance departments operate in their own silos, a fleet may not be getting the best information. Finance may perform the lease vs. buy calculations but they may not reflect the true TCO for a given asset if maintenance isn’t factored in. It’s a huge piece of the total cost of operation equation.

The TCO calculation is easier to do today given all the data available. Fleets can use this data to set lease terms that will allow them to get out of the equipment before it starts costing them exponentially on the maintenance side.

Many decisions a fleet makes can and should be data driven. But fleets have to slow down and actually pay attention to what the data is telling them. Is it saying it’s best to lease for seven years? Or five years? Or 5.5 years? What about adding some extension options at the end of a lease to accommodate the fact that used truck prices can vary extremely from high to low?

The goal, of course, is to use all the available data to structure a lease that is most advantageous so that fleets can get in and out of truck commitments at the time that is best and most profitable for them.

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Terry Mulreany
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Frank Battista
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