Capacity Matching and Digital Load Boards: Reducing Empty Trucks with a Logistics Platform
KEY TAKEAWAYS - READ IN 30 SECONDS
Introduction
Digital load boards and capacity matching exist to solve one specific, expensive problem: trucks driving without freight.
Empty miles are one of the largest controllable costs in trucking, and the gap between carriers who manage this well and those who do not is a direct, measurable margin difference.
This piece covers what empty miles actually cost, what is driving continued high rates despite decades of “digital freight matching” technology, and what a genuinely connected platform changes.
01 - The Scale of the Problem
According to the American Transportation Research Institute’s 2025 operational cost analysis, empty miles rose to an average of 16.7% across the US trucking industry in 2024.
Industry-wide estimates put the broader range at 15% to 35% of all miles driven empty, depending on measurement methodology and market segment, representing tens of billions of empty miles annually.
At a typical operating cost of $2.26-$2.27 per mile - fuel, driver wages, maintenance, insurance, all incurred with zero revenue to offset them - the aggregate cost runs into the tens of billions of dollars industry-wide.
Empty miles are not just a utilization metric. They are paid miles with no revenue attached.
02 - Why Deadhead Stays High Despite Digital Tools
Load boards have existed for decades, and digital freight matching has been marketed as a solution for nearly as long.
Deadhead rates remain stubbornly high for a structural reason: most load-matching still happens reactively, after a truck is already empty, rather than proactively, before the outbound delivery is even complete.
A dispatcher checking a load board once a truck is sitting idle has already lost the head start that makes backhaul matching efficient. The radius of realistic, on-time backhaul options shrinks the longer a truck sits without a next load lined up.
03 - What Actually Moves the Needle
Uber Freight’s internal analysis of algorithmic load bundling - automatically pairing an outbound delivery with a backhaul before the truck departs - demonstrated a 22.6% reduction in deadhead miles on the lanes where it was applied.
The mechanism is not a bigger board with more listings; it is earlier visibility.
Platforms that begin surfacing backhaul candidates the moment an outbound delivery is confirmed, rather than waiting until the truck is empty, consistently outperform reactive load-board searching.
| Deadhead rate | Typical segment |
|---|---|
| Under 10% | Dedicated-lane carriers with consistent freight patterns |
| 12-15% | Solid spot-market performance |
| 20%+ | Significant recoverable margin being lost |
04 - Why This Matters for Platform Evaluation
This is where capacity matching connects to the broader logistics platform conversation: a genuine collaborative platform gives dispatchers visibility into the full network - not just their own fleet’s status, but nearby freight and lane history - early enough to act on it.
A point-solution load board that only shows available freight, without integrating a carrier’s own delivery schedule and hours-of-service data, forces the same reactive search pattern that keeps deadhead rates high.
See Logistics Platform vs. Point Solutions: Why a Single Collaborative Interface Wins for Global Supply Chains for the broader architecture argument this reflects.
Get Your Own Deadhead Rate Benchmarked
Industry averages are a starting point; your fleet’s actual deadhead rate by lane is what determines the real opportunity.
Request a deadhead analysis and we will show you where backhaul visibility would recover the most margin on your specific routes.
Conclusion
Empty miles are one of the most controllable - and most persistently mismanaged - costs in trucking, running at close to 17% of all miles industry-wide despite decades of load-board technology.
The fix is not more freight listings; it is earlier visibility into backhaul opportunities, surfaced before a truck goes empty rather than after.
That is an architecture difference, not just a feature difference, between platforms.
Reduce empty miles by matching capacity before the truck goes empty.
Deadhead analysis
Benchmark your empty miles by lane
Bring your recent lane history and identify where earlier backhaul visibility could recover margin before trucks sit idle.
FAQ - Frequently asked questions
What percentage of truck miles are driven empty?
The American Transportation Research Institute found empty miles averaged 16.7% of all truck miles in 2024, with broader industry estimates ranging from 15% to 35% depending on segment and measurement approach.
How much does an empty mile cost a carrier?
Roughly $2.26-$2.27 per mile in fuel, wages, maintenance, and insurance costs, with zero revenue generated to offset any of it.
Can digital load boards actually reduce deadhead miles?
Yes, but the timing matters more than the size of the board. Algorithmic approaches that surface backhaul freight before a truck is empty - rather than after - have demonstrated deadhead reductions of over 20% in real deployments.
What is considered a good deadhead rate for a trucking fleet?
Dedicated-lane carriers with consistent freight patterns typically run below 10%. Spot-market operators at 12-15% are performing solidly; rates above 20% generally indicate significant recoverable margin being lost.
How is a connected logistics platform different from a traditional load board?
A connected platform integrates a carrier's own delivery schedule, hours-of-service data, and lane history with available freight, surfacing backhaul opportunities proactively. A traditional load board simply lists available freight for a dispatcher to search reactively.
References
- Summar Financial, Route-Planning and Deadhead Miles in Trucking: Challenges and Solutions (citing ATRI’s 2025 operational cost analysis) - https://summar.com/route-planning-and-deadhead-miles-in-trucking-challenges-and-solutions/
- Apex Capital, What is Deadheading? Freight Management Tips to Reduce Empty Miles - https://www.apexcapitalcorp.com/blog/what-is-deadheading/
- Kilian Heilmann (Uber Freight), How Efficient Load Matching Can Reduce Deadhead Miles in Trucking - https://medium.com/uber-under-the-hood/how-efficient-load-matching-can-reduce-deadhead-miles-in-trucking-75e77ccb7d4d
Related reading: Logistics Platform vs. Point Solutions - Digital Logistics Platform: Frequently Asked Questions (2026 Glossary)