Freight Cost Analysis: Practical Methods to Optimize Transportation Spend

Key Takeaways

• Effective freight cost analysis requires a systematic approach to uncover hidden costs
• Basic calculations include cost per unit, cost per weight, and accessorial percentage
• Advanced techniques like lane-level analysis identify opportunities for significant savings
• Manual analysis methods face limitations in data quality and analytical resources
• Trax Technologies provides automated solutions that deliver 5-7% savings on transportation spend

Are you extracting maximum value from your transportation spend? Many companies still lack methods to analyze and optimize freight costs. Effective freight cost analysis goes beyond simply reviewing invoices—it requires systematic approaches to uncover hidden costs, identify optimization opportunities, and make data-driven decisions.

This article provides practical frameworks, calculations, and exercises to help supply chain leaders implement effective freight cost analysis processes. We'll walk through specific methodologies that can be applied immediately to your transportation data, regardless of your company's size or industry.

What Makes a Comprehensive Freight Cost Analysis?

Before diving into specific calculations, it's important to understand the core components that should be included in any freight cost analysis:

A comprehensive analysis incorporates all these elements to provide a complete view of transportation spend and performance.

Essential Calculations for Effective Cost Analysis

Let's start with fundamental calculations that form the building blocks of freight cost analysis.

1. Cost Per Unit for Direct Comparison

One of the most useful metrics for comparing shipments is cost per unit, which normalizes transportation expenses across different shipment sizes:

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Cost Per Unit = Total Freight Cost / Number of Units Shipped

Example Calculation:

• Shipment A: $1,200 for 600 units = $2.00 per unit
• Shipment B: $900 for 400 units = $2.25 per unit

While Shipment B has a lower total cost, Shipment A is more cost-effective on a per-unit basis.

2. Weight-Based Analysis for Mode Optimization

For weight-based shipping, calculating the cost per pound or kilogram allows for standardized comparisons:

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Cost Per Weight = Total Freight Cost / Total Weight

Example Calculation:

• Shipment A: $1,200 for 2,000 pounds = $0.60 per pound
• Shipment B: $900 for 1,200 pounds = $0.75 per pound

3. Route Efficiency Assessment

This metric helps evaluate the efficiency of different routes or carriers:

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Cost Per Distance = Total Freight Cost / Distance (miles or kilometers)

Example Calculation:

• Route A: $1,200 for 800 miles = $1.50 per mile
• Route B: $950 for 500 miles = $1.90 per mile

4. Accessorial Impact Measurement

Understanding what portion of your total spend goes to accessorial charges can help identify areas for negotiation:

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Accessorial Percentage = (Total Accessorial Charges / Total Freight Cost) × 100

Example Calculation:

• Total freight spend: $100,000
• Total accessorial charges: $23,000
• Accessorial percentage: 23%

If this percentage is high compared to industry benchmarks (typically 15-20%), it may indicate opportunities for process improvements or contract renegotiation.

Advanced Techniques That Deliver Significant Savings

With the basics established, let's explore more sophisticated analysis methods that provide deeper insights into transportation spend.

1. Lane-Level Profitability Analysis

A lane-level analysis helps identify which shipping routes are most cost-effective and which may need optimization.

Step 1: Organize your freight data by origin-destination pairs (lanes) 

Step 2: Calculate the following metrics for each lane:

• Total shipments
• Total weight
• Total transportation cost
• Average cost per shipment
• Average cost per weight unit
• Service level performance (on-time percentage)

Example Lane Analysis Table:

In this example, the Miami to Boston lane stands out with significantly higher costs and lower service levels, indicating a prime candidate for optimization.

2. Modal Optimization Analysis

This analysis determines whether you use the most cost-effective transportation modes for each shipment profile.

Step 1: Group shipments by weight ranges and distance bands 

Step 2: Calculate average costs by mode for each group 

Step 3: Identify potential mode shift opportunities

Example Modal Analysis:

This analysis reveals significant savings opportunities by shifting lightweight express shipments to ground service and heavy long-distance truckload shipments to intermodal.

3. Carrier Performance Index

This method evaluates carriers based on cost and service metrics, creating a balanced view of performance.

Step 1: Define key performance indicators (cost and service-related) 

Step 2: Assign weights to each indicator based on business priorities 

Step 3: Score each carrier on a standardized scale (e.g., 1-10) 

Step 4: Calculate weighted average scores

Example Carrier Performance Index:

In this case, Carrier A delivers the best overall value despite not having the lowest cost, while Carrier D underperforms across all metrics.

How to Conduct a Freight Spend Breakdown Analysis

One of the most valuable analyses is breaking down transportation spend across multiple dimensions to identify focus areas. Here's a step-by-step process for conducting this exercise:

Step 1: Gather your freight data for the previous 12 months, including:

• All invoices and shipment details
• Carrier information
• Mode and service level
• Origin and destination
• Weight and dimensions
• Accessorial charges

Step 2: Create spend breakdowns across multiple dimensions:

By transportation mode:

By carrier:

By charge type:

Step 3: Identify key insights and opportunities

In this example, several findings emerge:

• Parcel shipping costs are growing significantly faster than other modes (+12.3%)
• Residential delivery charges are increasing rapidly (+15.3%)
• Four carriers represent 86% of total spend, suggesting negotiation leverage
• Detention charges constitute 5.5% of spend, indicating potential operational inefficiencies

Real-World Applications That Drive Results

Let's apply these analytical methods to realistic business scenarios.

Scenario 1: Regional Distribution Network Optimization

Company Profile:

• Consumer goods manufacturer
• 5 distribution centers serving the US market
• $15M annual transportation spend
• Mix of truckload, LTL, and parcel shipments

Analysis Process:

• Conduct lane-level analysis for all DC-to-customer combinations
• Calculate the average cost per pound by distance band and shipment size
• Identify high-cost lanes with significant volume
• Explore alternative routing options

Findings:

• 18% of lanes account for 62% of total transportation spend
• The northeast region shows 22% higher cost per pound than other regions
• 35% of shipments under 500 pounds are currently shipping via LTL
• Alternative carrier options could reduce costs by 14% on the top 10 lanes

Recommendations:

• RFP for Northeast region carriers to address high costs
• Shift small shipments from LTL to consolidated parcel
• Optimize DC assignment rules based on total landed cost
• Implement a continuous freight cost analysis process

Scenario 2: Modal Optimization for Global Manufacturer

Company Profile:

• Industrial equipment manufacturer
• Global supply chain with imports from Asia and Europe
• $28M annual transportation spend
• Historically prioritized speed over cost

Analysis Process:

• Group shipments by weight, value, and transit time requirements
• Calculate cost trade-offs between air, ocean, and expedited ocean
• Analyze inventory carrying costs against transportation savings
• Develop a decision matrix for mode selection

Findings:

• 28% of air freight shipments are non-critical and could use ocean
• Expedited ocean service offers 40% savings vs. air, with a 7-day longer transit
• Consolidated shipments could reduce costs by 12-18%
• Lack of visibility into total landed cost is driving suboptimal decisions

Recommendations:

• Implement the mode optimization decision matrix
• Shift non-critical air shipments to expedited ocean
• Enhance inventory planning to enable slower, less expensive transportation
• Deploy automated freight analysis tools for ongoing optimization

Build a Sustainable Freight Analysis Program

One-time analyses provide value, but implementing continuous freight cost analysis delivers sustainable benefits. Here's a framework for establishing this process:

Standardize data collection:

• Ensure consistent data capture across all shipments
• Implement proper coding and classification
• Maintain historical data for trend analysis

Establish a regular analysis cadence:

• Weekly: Review operational metrics and exceptions
• Monthly: Analyze carrier performance and spending trends
• Quarterly: Conduct deep-dive analyses on specific opportunities
• Annually: Perform comprehensive network optimization

Define KPIs and targets:

• Cost per unit/pound/shipment
• Mode and carrier utilization
• Accessorial percentage
• On-time performance
• Invoice accuracy

Implement visualization and reporting:

• Executive dashboards showing high-level metrics
• Operational reports for day-to-day decision making
• Exception reports highlighting opportunities
• Trend analyses showing progress over time

Why Manual Analysis Falls Short

While the frameworks described above provide valuable insights, many companies struggle to implement them effectively due to:

• Data quality issues - Inconsistent, incomplete, or inaccurate transportation data
• Analytical resource constraints - Lack of dedicated personnel with freight analysis expertise
• System limitations - Inadequate tools to process and analyze large volumes of freight data
• Reactive approaches - Addressing issues after they occur rather than proactively identifying opportunities

These challenges often result in missed savings opportunities, suboptimal decisions, and limited strategic visibility into transportation spend.

Maximize Cost Savings with Trax Technologies

Trax Technologies addresses these limitations with AI-powered solutions that automate and enhance freight cost analysis. Rather than struggling with manual processes and limited data, Trax provides comprehensive visibility and intelligent insights through advanced technology.

Trax's Freight Data Management solutions deliver:

• Data normalization and cleansing - Converting disparate freight data into a standardized, analysis-ready format
• Automated cost analysis - Performing all calculations and analyses described above automatically and continuously
• AI-driven optimization - Identifying opportunities human analysts might miss through pattern recognition
• Predictive analytics - Forecasting future costs and proactively identifying potential issues

Trax's Global Freight Audit solution audits 100% of invoices across all countries, modalities, and currencies and then uses the extracted and normalized data to enable Spend & Compliance Management. On average, Trax customers save 5-7% of their annual transportation spend.

Contact the Trax team today to learn how our AI-powered solutions can optimize your transportation spend.