Independent fleet analytics

Cut empty miles.
Protect your margin.

We find the 30–45% of drive time that generates zero revenue and build you a ranked playbook to recover it. In 30 days.

Plus Class 6-8 BEV transition strategy for private fleets navigating the post-CARB economic decision.

Methodology example
36% → 14%
Empty miles cut
30 days
To signed implementation plan
Findings Promise
if Phase 1 doesn't substantiate Phase 2, we tell you not to engage
Methodology example
$0.38/mi
Cost per mile reduction
30 days
To signed implementation plan
Findings Promise
if Phase 1 doesn't substantiate Phase 2, we tell you not to engage
Methodology example
$1.4M+
Incentives identified
30 days
To full transition roadmap
Findings Promise
if Phase 1 doesn't substantiate Phase 2, we tell you not to engage
Methodology example
Class 6-8
BEV transition modeling
Medium- and heavy-duty
5 years
TCO modeling horizon
Findings Promise
if Phase 1 doesn't substantiate Phase 2, we tell you not to engage
MarginHaul methodology overview Five-scene cycle: fragmented freight networks across US city pairs, chaos-to-clarity data transformation, diagnosis grid, optimized green network, and outcome — truck, growth chart, and MarginHaul wordmark. Real US map with 12 city dots (SEA, PDX, SFO, LAX, SLC, DEN, DFW, ORD, BNA, ATL, JFK, MIA). Five trucks travel multi-stop amber and red dashed routes representing fragmented, inefficient hauls and empty backhauls. SEA PDX SFO LAX SLC DEN DFW ORD BNA ATL JFK MIA 01 — THE PROBLEM Fragmented networks. Empty miles. Carbon burden. Three vertical zones: scattered raw-data fragments on the left, a central MarginHaul transformer node, and organized actionable insights on the right. Arrows flow from left through center to right. RAW DATA ACTIONABLE INSIGHTS FUEL COST ROUTE 47 dwell 4.2h 8.7 MPG 78% $0.42/mi DEADHEAD stops 11 empty lane MARGINHAUL PROCESSING Fleet Utilization 87% Empty Miles 14% TCO $1.89/mi Compliance Ready Cost Savings $2.4M/yr Scenario Modeled 02 — INTELLIGENT ANALYSIS Chaos in. Clarity out. Every mile. Every metric. Diagnosis grid: feasibility heatmap, TCO crossover curves, incentives pyramid, transition roadmap — all linking to a central MarginHaul wordmark. FEASIBILITY TCO INCENTIVES ROADMAP MARGINHAUL 03 — DIAGNOSIS TCO modeled. CARB mapped. Incentives captured. Same US network as Scene 1, transformed: solid green multi-stop routes, fewer trucks in purposeful motion, pulsing green hub nodes at Denver, Dallas, and Atlanta consolidation points. SEA PDX SFO LAX SLC DEN DFW ORD BNA ATL JFK MIA 04 — THE SOLUTION Optimized network. Reduced miles. Zero-emission ready. MarginHaul logo composition revealed progressively. A semi-truck cab slides in from the left and comes to rest in the lower-left. Six blue bars build sequentially flush against the cab's right edge, forming the trailer body — each bar taller than the last. A blue trending arrow draws above the bars, ending with an arrowhead at the upper right. The MARGINHAUL wordmark fades in below, centered and fully visible. MARGINHAUL 05 — THE OUTCOME Your fleet. Optimized. On your terms.
$2.27
per mile — record marginal operating cost
96%
of carriers still use legacy dispatch methods
30–45%
of drive time generates zero revenue
90%+
of fleets lack the tools to optimize their own networks
Jun 30 2026
Federal 30C charging credit expiration
16.7%
ATRI-reported deadhead — real non-revenue time runs ~2x higher

What every empty mile costs you.

Source: ATRI 2024 Operational Costs Report. Every empty mile burns this at zero revenue.

Where your $2.27/mile goes
Driver wages
$0.82
Fuel
$0.59
Truck payment
$0.36
Insurance
$0.26
Maintenance
$0.18
Other
$0.06
Total marginal cost
$2.27/mile
Every empty mile burns this at zero revenue. With 30–45% of drive time non-revenue, a 100-truck fleet wastes millions annually.

From data intake to
dollar impact in 30 days.

A fixed-scope, fixed-timeline engagement. We move fast because we've built the tools to do it.

01
Days 1–3

Data Intake

02
Days 4–10

Fingerprint & Diagnose

03
Days 11–27

Model & Build Playbook

04
Days 28–30

Executive Readout

Data Sources
📊 TMS Export
⛽ IFTA Reports
📄 Customer Contracts
🔒
Secure
Intake Portal
📥
MarginHaul
Analysis
Collected
14 months TMS export
IFTA mileage reports
Driver settlement records
Top 20 customer contracts
Root Cause Analysis
Network Gaps42%
Contract Constraints31%
Dispatch Behavior27%
Composite from modeled fleet profiles — each fleet varies
Findings
3 root cause categories ranked
Lane-level cost attribution
Dispatch behavior patterns
Recovery value by priority
Lane Redesign
Before
Fragmented lanes
After
Hub-and-spoke optimized
36%
Fewer empty miles
90 days
To implement
Deliverables
Lane restructuring playbook
Meet-and-turn pairing guide
Broker integration targets
Ranked action plan
Audit Outputs
Methodology example
$1.4M–$3.2M
Modeled recoverable value range
✓ Findings Promise
90-Day Implementation Matrix
P1
Lane Restructuring
P2
Dispatch Protocol Update
P3
Driver Redomicile
Deliverables
90-day implementation playbook
Lane audit report
Executive briefing deck
Data Sources
📡 GPS / Telematics Feed
🗂️ Load Board Records
📍 Relay Point Logs
🔒
Secure
Intake Portal
📥
MarginHaul
Analysis
Collected
18 months of trip history
Relay dwell & stem times
Lane utilization by segment
Load board tender records
Network Diagnostics
Redundant Relay Points5 of 14
Avg Hub Dwell Time7.2 hrs
Avg Stem Time52 min
Network inefficiency mapped before any changes are proposed
Mapped
14 relay points evaluated
5 redundant points flagged
Hub dwell benchmarked
Stem time by origin zone
Relay Redesign
Before
14 relay points
After
9 relay points
−36%
Relay reduction
$1.85M
Identified / yr
Outcomes
3 scenarios modeled
Relays: 14 → 9 points
Dwell: 7.2 → 3.4 hrs
$1.85M recoverable value
Audit Outputs
ROI Projection
$1.85M
Projected annual savings
✓ Findings Promise
90-Day Implementation Matrix
P1
Relay Point Consolidation
P2
Hub Dwell Reduction
P3
Stem Time Optimization
Deliverables
90-day relay consolidation plan
New hub sequence map
Carrier contract guidance
Fleet Data
🚛 Vehicle Inventory
📍 Route Profiles
⚡ Charging Site Survey
🔒
Secure
Intake Portal
EV
Feasibility
Assessed
EV-eligible routes by range
Charging infrastructure gaps
CARB compliance exposure
Vehicle age & lease timeline
TCO Comparison
Diesel (baseline)100%
BEV Year 1–2 (ramp)108%
BEV Year 3 (break-even)91%
BEV Year 5 (optimized)82%
After incentives, energy savings & CARB compliance costs factored in
Modeled
5-year cost comparison
30C deadline planning
Energy cost per mile by route
Break-even timeline by vehicle
Incentive Stack
CARB HVIP Voucher — $85K–$120K standard fleet (Class 6–8) / $160K–$330K small fleet (≤20 vehicles)
Federal IRA Tax Credit$40K
Utility Demand Response~$8K/yr
Federal 30C charging credit expires June 30, 2026 — 10-port depot install can capture up to $1M before deadline
Identified
CARB HVIP voucher eligibility
Federal IRA tax credit (Sec. 45W)
Utility demand response programs
30C deadline planning + HVIP capture timing
EV Audit Outputs
EV Transition Value
$1.4M
Incentives captured + TCO savings
✓ Findings Promise
Phased Transition Plan
Ph1
Route Feasibility & Pilot
Ph2
Charging Infrastructure
Ph3
Full Fleet Conversion
Deliverables
Phased conversion schedule
Charging infrastructure plan
CARB compliance timeline

Quantify your savings
before you commit.

Run the numbers yourself. Both calculators are free, instant, and require no sign-up.

ROI Calculator
How much are empty miles costing your fleet?
Enter your fleet size, mileage, and current deadhead percentage. We'll show you exactly what you could recover with a MarginHaul audit.
Calculate Your Savings
EV TCO Calculator
Is an electric fleet actually cheaper over 5 years?
Compare your current diesel fleet against a BEV transition — factoring in incentives, charging costs, and CARB compliance exposure.
Run the TCO Comparison
See all tools

Enterprise intelligence.
Without the enterprise price tag.

Mega-fleets have internal data science teams. Most carriers don't. They're left making million-dollar network decisions on gut feel and spreadsheets. That's exactly who we built this for.

🔬

Engineering-grade analysis, not slide engineering

We run proprietary data ingestion scripts and combinatorial optimization solvers — tools legacy consultants don't have. The result is analysis delivered in weeks, not quarters.

📋

Findings-first commitment

Every engagement opens with a fixed-fee diagnostic that puts real numbers on the table. If our Phase 1 diagnostic doesn't surface enough value to substantiate Phase 2, we tell you not to engage Phase 2.

🎯

Specialized in freight — nothing else

Every framework, benchmark, and optimization model we've built is specific to commercial freight operations. This is all we do.

Get Started

Ready to see where your empty miles are hiding?

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No commitment required. We work with commercial fleets of all sizes.