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Freight Spend Analysis Guide: What to Measure and What to Act On

Learn how to run a freight spend analysis, including data inputs, key metrics, and which findings to prioritize for the fastest cost reduction impact.

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A freight spend analysis requires 12 months of invoice data by lane, mode, and carrier to identify cost concentration and anomalies.

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Accessorial charges as a percentage of freight cost is the single metric most operations teams are surprised by. Industry average is 22 to 35%.

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Cost per pallet by lane is the actionable output: it surfaces mode mismatches and carrier pricing outliers that rate shopping alone misses.

What a Freight Spend Analysis Is

A freight spend analysis is a structured review of your total transportation cost (by lane, mode, carrier, and charge type) to identify where money is going, whether it is being spent optimally, and where the highest-return reduction opportunities exist. It is the prerequisite to any meaningful rate negotiation, network redesign, or mode optimization initiative.

Unlike a simple invoice audit (which checks for billing errors), a spend analysis asks strategic questions: Are we on the right mode for each lane? Are some carriers consistently more expensive than others on the same lanes? What percentage of our spend is accessorial charges that could be eliminated structurally? Which lanes have the highest cost-per-pallet and why?

Most enterprise shippers run a formal spend analysis once per year, typically before a carrier RFP cycle. The most operationally disciplined teams run quarterly reviews on their top 20 lanes by spend, using the data to inform ongoing bilateral negotiations rather than waiting for annual RFP events.

Data Inputs Required

The spend analysis is only as useful as the data behind it. The minimum dataset required:

  • Invoice data: 12 months of freight invoices, line-item detail including base rate, fuel surcharge, and each accessorial charge separately. Aggregate invoices without line-item detail make accessorial analysis impossible.
  • Lane data: Origin and destination at ZIP code level (not city or state. ZIP is required for meaningful lane-level analysis), shipment weight, freight class or commodity, and pallet count per shipment.
  • Mode and carrier by shipment: Which mode and carrier moved each shipment. This allows apples-to-apples comparison across carriers on the same lanes.
  • Transit time actuals: Actual transit time versus quoted transit time by carrier and lane. Service failure analysis often reveals that a low-cost carrier is only cheap because service failures create downstream costs (expediting, chargebacks, customer penalties) not captured in the freight invoice.

If your TMS does not output this dataset cleanly, the fastest path is freight invoice data from your AP system combined with shipment records from your ERP. Most 3PLs can provide a data extract in standard format within 5 to 10 business days.

Key Metrics to Track

Once you have the data, these are the metrics that produce actionable findings:

  • Cost per pallet by lane: The primary output metric. Normalizing by pallet eliminates the distortion of shipment size variation and makes carrier and mode comparison meaningful. Build a lane-level table ranked by cost-per-pallet descending. The top 20 lanes by this metric are your audit targets.
  • Cost per mile by mode: Reveals mode mismatches. If cargo van lanes are running at a higher cost-per-mile than LTL lanes of the same length, you may be over-using cargo van. If LTL lanes are running at a higher cost-per-mile than FTL break-even suggests, consolidation is the lever.
  • Accessorial as % of total freight spend: Industry average is 22 to 35% of total LTL spend. If yours is above 30%, accessorial elimination (structural, not negotiated) is the highest-return near-term initiative. See our guide on per-pallet pricing for how to structurally eliminate accessorials.
  • Carrier cost index by lane: For lanes where you use multiple carriers, index each carrier's cost-per-pallet to the lane average. Carriers consistently above 1.15x (15% above average) should be reviewed or replaced.
  • Mode mix by lane length: What percentage of your shipments on lanes under 400 miles are on LTL vs. cargo van vs. box truck? What percentage of lanes over 14 pallets are on LTL vs. FTL? Mode mix mismatches are structural cost sources that rate shopping cannot fix.

What Findings to Act On First

Prioritize findings using two criteria: magnitude of cost reduction opportunity and speed of implementation. The typical priority order:

  • Accessorial reduction (fast, high impact): If accessorials exceed 25% of total spend, move immediately to per-pallet pricing or structured accessorial waivers in your next carrier renegotiation. This is the fastest path to a visible cost reduction.
  • Mode optimization on mismatched lanes (medium speed, high impact): Identify lanes where mode is wrong for load size or distance. Re-tendering those shipments to the correct mode takes 30 to 60 days. See our box truck vs. LTL comparison for threshold decision logic.
  • Carrier replacement on outlier lanes (medium speed, medium impact): Replace carriers consistently priced above lane average. This requires sourcing alternatives and running a controlled A/B for 60 to 90 days before full volume shift.
  • Network restructuring (slow, highest long-term impact): DC placement, cross-dock utilization, lane consolidation. These findings require capital decision-making and 6 to 18 months of implementation. Act on them through a separate initiative after the quick wins are captured.

Running the Analysis Without a TMS

Many mid-market shippers run freight spend analysis in spreadsheets without a dedicated TMS. This is feasible for networks under 200 lanes but becomes unmanageable above that threshold due to data volume and the need for dynamic lane-level comparison.

The practical workaround for TMS-less teams is to use freight audit and payment (FAP) provider data exports, which typically include line-item invoice detail in standard format. Most FAP providers can produce a 12-month extract with lane, mode, carrier, and charge-type fields ready for pivot analysis.

For shippers evaluating Warp, the Orbit monitoring platform provides lane-level cost and performance data as a standard feature, making the ongoing spend analysis a continuous process rather than an annual project. Use our LTL freight class calculator to validate that your freight is correctly classified before running a spend analysis, as misclassification distorts cost-per-pallet benchmarks.

Related: Freight Rate Negotiation Guide · How to Reduce Freight Costs · Per-Pallet Pricing Explained · Freight Invoice Audit Guide · Freight Contract Terms Guide

What matters

Freight Spend Analysis Guide should change the freight decision, not just fill a browser tab.

Signal 01

A freight spend analysis requires 12 months of invoice data by lane, mode, and carrier to identify cost concentration and anomalies.

Show what changes in cost, service, handoffs, timing, or execution control once the team acts on this point.

Signal 02

Accessorial charges as a percentage of freight cost is the single metric most operations teams are surprised by. Industry average is 22 to 35%.

Show what changes in cost, service, handoffs, timing, or execution control once the team acts on this point.

Signal 03

Cost per pallet by lane is the actionable output: it surfaces mode mismatches and carrier pricing outliers that rate shopping alone misses.

Show what changes in cost, service, handoffs, timing, or execution control once the team acts on this point.

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Use the topic to move toward the right freight decision.

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