Key Takeaways
- Cybersecurity incidents rose 25% in LTL 2023.
- Capacity shortages affected 62% LTL shipments Q3 2023.
- Driver shortage: 80,000 gap projected for LTL by 2025.
- LTL cost per shipment rose 8.5% to $125 in 2023.
- Fuel costs represent 28% of total LTL operating expenses.
- LTL labor costs increased 7.2% YoY accounting for 35% expenses.
- The North American LTL market reached $92.3 billion in revenue in 2022.
- LTL freight tonnage in the US grew by 4.8% year-over-year in 2023 Q1.
- Global LTL market projected to hit $250 billion by 2028 at 6.1% CAGR.
- Average LTL shipment weight in US is 1,200 lbs as of 2023.
- On-time delivery rate for top LTL carriers averaged 98% in 2023.
- LTL transit times averaged 2.3 days for regional hauls in US 2023.
- 45% of LTL carriers adopted TMS by end of 2023.
- AI-driven forecasting used in 32% of LTL networks.
- IoT sensors on 60% of LTL trailers for temp monitoring.
In 2023 LTL faced higher costs and shortages amid surging cyberattacks, disrupting 62% of shipments.
Challenges and Risks
Challenges and Risks Interpretation
Cost Analysis
Cost Analysis Interpretation
Market Size and Growth
Market Size and Growth Interpretation
Operational Metrics
Operational Metrics Interpretation
Technology Adoption
Technology Adoption Interpretation
Trends and Future Outlook
Trends and Future Outlook Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Ryan Townsend. (2026, February 13). Supply Chain In The Ltl Industry Statistics. Gitnux. https://gitnux.org/supply-chain-in-the-ltl-industry-statistics
Ryan Townsend. "Supply Chain In The Ltl Industry Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/supply-chain-in-the-ltl-industry-statistics.
Ryan Townsend. 2026. "Supply Chain In The Ltl Industry Statistics." Gitnux. https://gitnux.org/supply-chain-in-the-ltl-industry-statistics.
Sources & References
- Reference 1STATISTAstatista.com
statista.com
- Reference 2ARMSTRONGASSOCIATESarmstrongassociates.com
armstrongassociates.com
- Reference 3FREIGHTWAVESfreightwaves.com
freightwaves.com
- Reference 4JOCjoc.com
joc.com
- Reference 5TTNEWSttnews.com
ttnews.com
- Reference 6TRUCKINGtrucking.org
trucking.org
- Reference 7MCKINSEYmckinsey.com
mckinsey.com
- Reference 8BLSbls.gov
bls.gov







