Detroit and Cummins cost per mile can differ by $0.07/mile or more on the same routes — RC Willey’s fleet found exactly that gap running both engine families under identical delivery conditions. But which engine wins on your fleet is a different question entirely, and the answer depends on your lanes, your loads, and whether your data is actually connected enough to produce the comparison.
That’s the real issue. Most fleets are making six-figure engine procurement decisions without knowing their own CPM by powertrain — not because the trucks aren’t generating data, but because that data is scattered across telematics platforms, fuel cards, shop systems, and spreadsheets that were never designed to talk to each other.
If you’re running Detroit and Cummins trucks side by side — or spec’ing new iron for 2025 — here’s how to find your actual answer, and why it’s almost certainly different from RC Willey’s.
Why “Which Engine Is Better” Has No Universal Answer
The Detroit DD15 and the Cummins X15 are both proven, capable powerplants. Fuel economy, repair frequency, and total ownership cost all shift meaningfully based on:
- Route profile — highway linehaul vs. urban stop-and-go vs. mountain grades
- Load weight and variance — consistent near-gross-weight hauls vs. partial loads
- Idle time — a refrigerated delivery operation idles very differently than a dry van linehaul truck
- Regional shop access and parts availability — warranty recovery rates and repair cycle times vary by geography
- PM compliance discipline — reactive repairs cost 3–9x more than scheduled maintenance on the same component, and that gap often shows up unevenly across engine families in a mixed fleet
RC Willey’s $0.07/mile delta emerged from a specific combination of those variables — their routes, their loads, their maintenance program. Godfrey’s fleet showed a $0.12/mile CPM gap across vehicle segments that would have been invisible without normalized cross-fleet data. Same methodology, different answer — because use case drives outcome.
Why Engine Cost Comparisons Usually Fail
Most fleets can’t run this comparison at all. Not because they lack trucks — plenty of operations run mixed OEM configurations — but because their cost data lives in disconnected silos:
- Fuel spend is in Comdata or another fuel card platform
- Repair history is in a shop management tool, a DMS, or a spreadsheet
- Telematics mileage is in Geotab, Samsara, or Motive
- Warranty recoveries may not be tracked systematically at all
When you try to compare Engine Family A vs. Engine Family B, you’re manually stitching together exports from three or four systems with different formats, different odometer readings, and mismatched date ranges. The result: most “comparisons” are gut feelings dressed up as data — or benchmarks borrowed from the manufacturer’s spec sheet rather than your actual operating environment.
What Samsara, Geotab, and Motive Can’t Tell You Here
Your telematics provider surfaces real value: mileage, idle time, fault codes, fuel consumption per vehicle. That data is genuinely useful input to a Detroit vs Cummins cost per mile comparison.
What telematics alone cannot produce:
- Normalized repair invoices from multiple vendors, categorized by engine OEM and cost system
- Warranty recovery attribution by drivetrain component and coverage window
- A side-by-side CPM comparison across engine families running the same lanes
- Trend visibility showing which engine population is drifting higher before it becomes a budget problem
Samsara and Motive now ship work order and maintenance modules. Geotab surfaces fault-code history. These are meaningful additions — but they’re designed around vehicle-level maintenance management, not cross-OEM cost analytics normalized against fuel card transactions and warranty recovery data simultaneously.
Answering “which engine costs less to operate per mile on our specific routes” is an analytics-layer question that sits above what any single telematics platform is built to answer.
The Four Cost Drivers That Shift the Answer by Fleet
Understanding what moves CPM by engine OEM tells you where to look in your own operation.
1. Fuel Efficiency at Real-World Load and Speed
Manufacturer MPG ratings come from idealized test conditions. Your routes aren’t idealized. A DD15 and an X15 perform differently depending on grade, stop frequency, idle percentage, and average load weight. Real-world MPG on your lanes is the only figure that matters — and producing it requires matching fuel card transactions to vehicle-level telematics mileage over a consistent period, not reading a spec sheet.
2. Repair Frequency and Cost Profile
Engine families differ in failure mode distributions. One may carry lower cost-per-event repairs but higher frequency. Another may have rarer but more expensive events. Without repair data categorized by engine OEM and normalized across vendors, you see only a total R&M budget — with no visibility into why it moves.
3. PM Compliance by Engine Family
If your preventive maintenance schedule isn’t calibrated to each OEM’s manufacturer interval — and tracked by actual mileage or engine hours rather than calendar date — one engine family may be systematically under-maintained relative to the other. That compliance gap will show up in repair costs long before it shows up in your shop’s awareness. Work order discipline, DVIR completion rates, and inspection history all feed into whether your PM program is actually protecting each powertrain equally.
4. Warranty Recovery Rates
This is the most commonly overlooked variable. If your shop isn’t flagging warranty-eligible repairs at write-up time, you’re absorbing cost the OEM should cover. Mixed-OEM fleets frequently show inconsistent warranty recovery rates by brand — not because of OEM policy differences, but because tracking discipline varies by technician, vendor, or shop location. A single missed warranty claim on a major engine component can skew your CPM comparison by several cents per mile.
How to Run This Comparison on Your Fleet
You can build this analysis manually. Here’s the framework:
- Segment vehicles by engine OEM. Year, make, engine family, configuration.
- Normalize mileage from telematics odometers — not DOT logs — for consistency across vehicles.
- Pull R&M cost by vehicle, categorized by system (engine, drivetrain, electrical, HVAC, tires, etc.).
- Match fuel card transactions to each vehicle. Calculate actual MPG over a minimum of 6 months; 12 months produces more reliable results.
- Subtract warranty recoveries. If you haven’t been tracking these, flag any repair from the past 12 months that may still fall within OEM coverage windows.
- Calculate CPM by engine family: (Fuel cost + R&M cost − warranty recovery) ÷ total miles.
Run that for each OEM segment and you have a real comparison. The breakdown point for most fleets is steps 2–5: clean, connected data across those sources is where the process collapses.
How Link-X Surfaces This Automatically
Link-X sits as an intelligence layer on top of your existing telematics (Geotab, Samsara, Motive), fuel cards (Comdata), and maintenance data — standardizing and connecting them without replacing any system you’ve already invested in.
The platform automatically:
- Calculates cost-per-mile by vehicle, engine OEM, route, and division using live, connected data
- Processes and normalizes repair invoices from any vendor into a consistent cost structure
- Tracks warranty eligibility and recovery at the work order level, so missed recoveries surface before the window closes
- Manages preventive maintenance scheduling by actual mileage or engine hours, with alerts calibrated per OEM interval — so neither engine family gets under-maintained
- Flags engine-family cost trends before they become budget surprises
- Generates replace-vs-repair analysis using actual CPM, not book depreciation
- Connects DVIR and inspection data into the maintenance workflow, so driver-reported issues feed directly into work orders rather than getting lost
The RC Willey result — a $0.07/mile gap across engine families on the same delivery routes — wasn’t produced by a manual analysis project. It’s the kind of insight that emerges when fuel, repair, mileage, and warranty data are normalized continuously at the fleet level. Godfrey’s $0.12/mile variance came from the same methodology applied to a different operation, with different conclusions. Same process; the data tells you the answer specific to your fleet.
The Spec Decision You’re Making Without Your Own Data
If you’re ordering trucks this year and you don’t have CPM broken out by engine OEM on your routes, you’re making a six-figure procurement decision based on someone else’s operating environment. Manufacturer incentives, dealer relationships, and shop familiarity are all real factors. But none of them tell you what your specific combination of lanes, loads, and maintenance discipline actually costs per mile by powertrain.
There is no universal right answer between Detroit and Cummins. There is only the answer your fleet’s data produces — and right now, most fleets don’t have the connected infrastructure to find it.
See what your engine cost data looks like when it’s actually normalized and connected — start with Link-X.
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