The Battle of the Light-Duty Pickup Truck

Paul MilnerMarch 7, 2018

We put two tough drive types — and data — to the test. With two drive types available in the light-duty pickup truck category, which one is best in the fleet utility space? Is the 4×2 really on the outs? Should the 4×4 be the standard for fleets? Utilimarc pulled data from over 50 of our utility fleet benchmarking clients to find out.

Using analytical data from over 8,700 light-duty pickup trucks dating from 2012 to 2016, we were able to reveal patterns of operation and performance between the Ford F150, Chevrolet 1500, and Dodge 1500 that were definitely interesting — and potentially business changing.

Read our results below and let us know what you think.

Drive Type Percentage

There’s been a shift in the light-duty pickup truck scene over the last five years. While unit count remained similar, there was a significant change in drive type.

In 2012, the 4×2 and 4×4 was close to a 50/50 split in popularity. By 2016, 4x4s saw an incredible increase of 18%. Future doesn’t look bright for the 4×2, but let’s examine other areas.

Average Age

None of us are getting younger. Same goes for fleets. It’s what we do within our years that matters. Which vehicle lives the longest?

As shown above, the average age of both the 4×2 and 4×4 has increased since 2012. During 2012 to 2016, the 4×2 saw an increase of 1.09 years, while the 4×4 increased .17 years.

Average Purchase Price

Initial vehicle costs tend to be one of the largest investments for utility companies. Especially when considering the number of new vehicles added.

As for the 4×2 and 4×4, both drive types saw a purchase price peak in 2013. Since then, the average purchase prices for both drive types have decreased.

Over the 5-year period, the average purchase price for a 4×2 increased nearly 12% — moving from $25,588 to $29,181. Whereas the average price for the 4×4 increased over 14.5% — moving from $29,535 to $34,552.

Operating Cost (Without Fuel) Per Mile

Comparing Cost Per Mile and Vehicle Age, we found both drive types saw operating costs per mile increase as the vehicle aged.

Operating costs for the 4×2 in year one were $0.06 per mile. By year 10, it reached $0.25 per mile, an increase of $0.19 per mile over 10 years. The average operating cost per mile for a 4×2 pickup over the same 10-year period was $0.12.

Operating costs for the 4×4 in year one were $0.07 per mile. By year 10, it reached $0.21 per mile, an increase of $0.14 per mile over 10 years. The average operating cost per mile for a 4×4 pickup over the same 10-year period was $0.12.

Average Miles Driven

Getting the most miles out of your vehicle could mean getting the most out of your investment. While close, the 4×4 rose to the challenge on this test.

Average Miles Driven remained fairly consistent for both the 4×2 and 4×4, with slight decreases for both heading toward 2016.

Surprisingly, data showed that the 4×4 pickup had historically driven an average of 3,641 more miles than the 4×2.

Average Number of Days Between Unscheduled/Demand Repair

It goes without saying, but keeping vehicles out of the shop and on the road is one of the best ways to stay productive. So, which vehicle stayed out of the shop the longest?

The 4×2 barely won this battle. The 4×2 saw a slight dip in average number of days between unscheduled repairs, and an average of 77 days between each visit.

The 4×4, however, saw an increase of days between unscheduled repairs, and was back in the shop every 78 days on average.

What surprised us the most?

Of the above data, Utilimarc was surprised to see that the percentage of 4×4 pickups keeps growing — possibly eventually leading to the demise of the 4×2. Especially considering the interesting fact that there was no substantial difference in parts and labor costs between the two drive types.

Paul Milner

Paul Milner

Senior Analyst

Paul Milner is a senior analyst at Utilimarc. He studied mathematics and philosophy at the University of St. Thomas in Minnesota. Working at Utilimarc for nearly ten years, he helps find the stories and solve problems within complex data sets. See more from Paul

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