Methodology Example — Deadhead Reduction

How the methodology models a 120-truck regional carrier's non-revenue drive time reduction from 36% to 14%

Applied to a Southeast dry van operator's operational profile bleeding margin on empty repositioning. The methodology surfaces $2.8M in recoverable annual value and produces a ranked playbook to capture it.

120
Trucks in fleet
36%
Non-revenue time (before)
14%
Non-revenue time (after)
$2.8M
Annual value identified

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About this methodology example

This page presents a worked example of the deadhead reduction methodology applied to a representative regional truckload carrier’s operational profile. Identifying details are anonymized — we never share client information without explicit approval. Numbers reflect modeled recoverable value and projected outcomes from the analysis. Your results will differ based on your network, equipment, and operating conditions.

The operational profile

The profile applied is a regional truckload carrier operating 120 power units across the Southeast — primarily dry van, running lanes between Atlanta, Charlotte, Jacksonville, Nashville, and Memphis. The fleet is profitable but margins are thinning. Leadership at this scale typically suspects empty miles are a problem but lacks visibility into the root causes.

The TMS shows a deadhead percentage of 18%, which looks close enough to the industry average. But when the methodology examines loaded drive time as a percentage of total drive time — the metric that actually reflects asset utilization — the real number is 36% non-revenue drive time.

Key insight

Traditional deadhead metrics only capture empty trailer miles. They miss bobtailing, stem time, relay repositioning, and out-of-route miles to pickup. Loaded drive time tells the full story.

What the methodology surfaces

Over 10 days, the methodology ingests 14 months of TMS data, IFTA reports, and driver logs. Every non-revenue mile is classified by root cause and ranked by recoverable value.

Root cause Share of empty time Recoverable value
Imbalanced lane pairs (outbound-heavy corridors) 34% $1.12M
Excessive stem time to shipper facilities 22% $640K
Relay and drop-yard repositioning 18% $490K
Dispatch sequencing gaps (driver resets in wrong location) 15% $380K
Customer dwell time forcing off-schedule pickups 11% $170K
Total recoverable $2.8M/yr

What the methodology recommends

The methodology produces a 90-day implementation playbook with 14 specific actions. The modeled outcomes below reflect projected impact at full implementation. The top five recommendations alone account for 72% of the recoverable value:

1. Rebalance the ATL–JAX corridor. This lane pair runs 3:1 outbound-to-inbound. The methodology surfaces candidate regional shippers with consistent northbound freight that can fill 60% of the return gap through dedicated lane contracts.

2. Consolidate drop yards. The fleet operates five drop-yard locations, three of which are within 40 miles of each other. Consolidating to three yards reduces relay repositioning miles by 31%.

3. Shift three high-stem accounts to meet-and-turn. Three shipper facilities require 45+ minute stem drives. Converting these to meet-and-turn arrangements with partner carriers eliminates the stem entirely for the fleet.

4. Implement dispatch-aware driver reset planning. Drivers frequently reset in locations with no outbound freight. Pre-positioning resets at high-demand origin points reduces post-reset empty driving by 40%.

5. Renegotiate dwell-time penalties. Two accounts consistently hold drivers 4+ hours beyond appointment windows, causing cascading schedule disruptions. The methodology provides data-backed leverage for renegotiating detention terms.

Modeled outcome — baseline vs. methodology target

Baseline (operational profile)
Non-revenue drive time36%
TMS-reported deadhead18%
Drop-yard locations5
Avg stem time (top 10 accts)38 min
ATL–JAX lane ratio3:1
Methodology target (post-implementation)
Non-revenue drive time14%
TMS-reported deadhead7.2%
Drop-yard locations3
Avg stem time (top 10 accts)14 min
ATL–JAX lane ratio1.6:1

The methodology timeline

Days 1–3
Data intake
TMS export (14 months), IFTA mileage reports, driver settlement records, and top-20 customer contracts are intaken through the methodology’s secure intake portal.
Days 4–10
Fingerprint and diagnose
Every non-revenue mile is classified by root cause. Driver-level and lane-level heatmaps are built. The five corridors responsible for 61% of all empty driving are identified.
Days 11–25
Model and build playbook
Combinatorial optimization models are run on lane pairing. Every recommendation is scored by effort, timeline, and dollar impact. The 14-action implementation matrix is built.
Days 26–30
Executive readout
The deliverable presents findings to ops leadership (CEO / VP Ops / dispatch). The analysis identifies $2.8M in annual recoverable value and produces a prioritized 90-day action plan.

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