July Truck Tonnage Slips: A Lane-Level Test for Separating Demand Weakness From Mode Shift

July's truck tonnage decline looks like a demand warning, but it is not enough to justify a network-wide forecast cut.

The same period also produced growth in rail carloads and intermodal units. That divergence may indicate that freight disappeared, shifted modes, moved between commodities, or was consolidated into fewer and fuller truckloads. Each explanation calls for a different operating decision.

Transportation teams should treat the headline indexes as prompts for investigation. The answer sits in lane-level shipment history: what moved, how far it traveled, which equipment carried it, and how efficiently capacity was used.

Read the truck decline in context

Logistics Management reported that the American Trucking Associations' advanced seasonally adjusted For-Hire Truck Tonnage Index fell from 114.7 in June to 113.5 in July, a 1.2% decline. The July reading was also 0.5% below the prior year, although year-to-date tonnage remained 1.4% higher.

The not seasonally adjusted index, which represents tonnage actually hauled before seasonal adjustments, registered 117 in July versus 118 in June, a 0.9% decrease. ATA Chief Economist Bob Costello described freight as lackluster outside a few pockets of strength and said the industry's recovery was being driven largely by excess capacity leaving the market.

Those figures describe trucking in aggregate. They do not reveal whether a shipper lost orders, changed its product mix, consolidated deliveries, or moved suitable freight to another mode.

Rail data reinforces that limitation. FreightWaves reported that U.S. railroads handled 525,099 carloads and intermodal units in the week ending August 15, up 2.4% year over year. Carloads increased 1.9% to 233,261, while intermodal containers and trailers rose 2.7% to 291,838. Across the first 32 weeks of 2026, carloads were up 2.7% and intermodal volume was up 3.8%.

That does not prove a broad truck-to-rail conversion. Commodity effects were substantial: metallic minerals and ores rose 19.2% in the reported week, while motor vehicles and parts fell 13.2%. National mode totals can diverge simply because the underlying freight is different.

Segment the shipment history before revising demand

Start with a comparable lane dataset covering at least the current period, the preceding period, and the same period a year earlier. Avoid comparing only shipment counts. Include orders, weight, cube, pallets, miles, revenue units, and transportation cost.

Then segment the history along three dimensions.

Commodity or product family. Separate construction materials, metals, consumer goods, automotive freight, food, chemicals, and other materially different flows. A decline concentrated in one product family is a demand or production signal, not necessarily a transportation-market signal.

Haul length. Group shipments into practical distance bands. Long, regular lanes with schedule tolerance are more plausible intermodal candidates than short, variable routes. If truck volume falls mainly on long-haul corridors while the same origins and destinations show rising rail use, mode shift becomes a credible explanation.

Equipment and service. Split dry van, refrigerated, flatbed, specialized, expedited, and drayage moves. Equipment-specific declines can reflect product mix or capacity constraints. Combining them into one truck total hides the operational cause.

Use consistent definitions throughout the test. A lane should use stable origin and destination regions, and comparable shipments should have similar service requirements. Otherwise, a network redesign or customer change can masquerade as disappearing demand.

Test three competing explanations

The analysis should force each lane into one of three evidence-based explanations rather than accepting the national headline.

Demand disappeared. Orders, shipped units, weight, and truckloads all decline together, with no corresponding rail or intermodal activity. Inventory may rise upstream, or production and customer orders may fall. Forecasts and carrier commitments may need adjustment, but teams should first confirm that the change is not a timing issue.

Freight moved to rail. Total shipped units or weight remain stable while truck miles and truckload count decline. New intermodal tenders, rail billing, drayage legs, or ramp events appear on the same long-haul corridors. Measure the full door-to-door move so a rail conversion is not misclassified as two unrelated dray shipments.

Loads became fuller. Shipment count falls, but total weight or units remain steady and average truck utilization rises. This is often an efficiency gain from order consolidation, better appointment planning, or reduced partial loads. Cutting the demand forecast in this case would be a mistake; planners should preserve the demand signal while updating the load plan.

A fourth category, unexplained, is useful. Missing mode codes, inconsistent lane definitions, or incomplete order-to-shipment links should trigger data cleanup rather than an immediate routing-guide change.

Set thresholds before changing the routing guide

Do not let one month of volatility automatically remove carriers or shift committed volume. Establish thresholds before reviewing results so decisions are repeatable.

For example, require a lane to show a meaningful truckload decline across multiple comparable periods, stable underlying units or weight, and a corresponding increase in intermodal moves before labeling it a mode shift. Require minimum shipment volume so that two delayed loads do not produce a dramatic percentage swing.

Pair volume thresholds with service and cost evidence. A mode conversion should clear a door-to-door cost threshold after drayage, fuel, transload, inventory carrying cost, and accessorials. It should also meet an on-time performance threshold and stay within the customer's delivery window. Lower linehaul cost alone is not enough.

For genuine demand weakness, adjust routing-guide commitments in stages. Reduce forecasted volume first, monitor primary-carrier acceptance and spot exposure, and preserve backup coverage until the new pattern holds. Capacity is leaving parts of the truck market, so a premature broad reduction in carrier commitments can become expensive when freight returns.

Make the TMS the evidence layer

A transportation management system should connect the original order to every execution leg, regardless of mode. That lineage lets planners compare shipped demand with truckload count, intermodal conversions, utilization, cost, and service without relying on separate spreadsheets.

Build a monthly lane scorecard with orders, weight, units, truckloads, average utilization, intermodal share, cost per unit, tender acceptance, and on-time delivery. Flag material changes, then attach the underlying shipment records so analysts can validate the cause.

July's tonnage decline is a useful alert, not a complete diagnosis. Shippers that test it against commodity, distance, equipment, and utilization can distinguish a real demand contraction from a deliberate mode shift or an operational improvement.

CXTMS unifies orders, tenders, shipment legs, carrier performance, and freight costs so teams can make routing decisions from lane-level evidence. Request a CXTMS demo to turn broad freight signals into defensible transportation actions.