360° Freight Market Intelligence: Difference between revisions
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== '''The Data Problem''' == | == '''The Data Problem''' == | ||
The supply chain data sources used by most infrastructure planners provide only regional aggregates. This obscures what investors need to know: which commodities move on which routes between specific locations. This leads to misallocated capital, suboptimal facility design, and strategic decisions that increase costs for users and society. | |||
The problem extends beyond data quality to market visibility. Consider U.S. imports: 500 shippers account for 33% of volume | The problem also extends beyond data quality to market visibility. Consider U.S. imports: 500 shippers account for 33% of volume. The next 3,100 shippers add another 17%. The remaining 495,000 shippers—the other half of all imports—operate invisibly to ports, railroads, and planners. These aren't inconsequential players; they're the heart of regional economies and communities. They're manufacturers, distributors, and processors that employ people in these communities. Yet freight analysis focuses on what's easily counted: the largest players and aggregate tonnage. | ||
This traditional supply chain analysis exacerbates the problem by tracking equipment movements rather than commodities and by emphasizing imports over balanced trade analysis. Billion-dollar infrastructure decisions are made without knowing the actual shippers, commodities, trade lanes, and capacity needs. | |||
== '''Why Standard Sources Fall Short''' == | == '''Why Standard Sources Fall Short''' == | ||
Most infrastructure planning | Most infrastructure planning uses the Freight Analysis Framework (FAF)—a U.S. DOT dataset showing aggregate freight flows between 173 regional zones and the 50 U.S. States. It is also always several years out of date. FAF works for macro policy analysis. It fails for planning and investment decisions. | ||
FAF reports flows between regions and state-level aggregates. It cannot distinguish through traffic from local activity, identify specific origin-destination pairs, or provide county-level precision. An investor seeking a property development approach or evaluating an investment in a rail spur or transload facility needs to know: Which specific rail line carries what tonnage of which commodities? Where do those shipments originate and terminate? What seasonal patterns affect capacity? Which additional routings provide shippers with new market access? | |||
FAF | FAF cannot answer these questions. | ||
== '''The 360° Approach''' == | == '''The 360° Approach''' == | ||
360° Freight Market Intelligence | 360° Freight Market Intelligence combines granular freight movement data with field research and stakeholder interviews. The methodology integrates multiple specialized datasets to identify beneficial cargo owners, actual volumes, trade lane preferences, commodity flows, and routing patterns that are invisible in regional aggregates. This digital intelligence is further validated and enhanced through interviews with the people who move, receive, and depend on that freight—revealing future plans that exist beyond datasets. | ||
== '''What This Complete Intelligence Delivers''' == | |||
'''Northern Nevada Development Authority – Fernley Transload Feasibility (2020)''' | |||
A four-county region sought to understand its logistics-based economic development opportunities. Evaluating a truck-to-rail transfer facility requires distinguishing through traffic from local origin-destination activity and identifying the commodities carried by the trucks and railcars seen moving in the area. FAF's large regional generalities couldn't identify which corridors carried divertible freight or which services would capture meaningful volumes. | |||
Detailed county-level analysis by 360° Freight Market Intelligence illuminated the primary commodities originating in the eleven states west of Nevada and the specific destinations in California. Importantly, movements destined for domestic destinations in California were distinguished from those heading overseas. The resulting recommendations added up to a commercially feasible project and identified the specific commodities and shippers to be served—impossible with FAF-based generalized data approaches. | |||
'''Nevada State Rail Plan – Statewide Truck Analysis (2020)''' | |||
Analysis of 10.5 million truck movements found that 4.1 million trips—40% of total activity—were empty-trailer returns or warehouse-to-distribution transfers. FAF commodity reporting doesn't capture empty movements. | |||
FAF data showed only 650,000 full truck movements of aggregates. The complete analysis revealed 1.3 million truck trips, all generating road wear, congestion, and emissions. This revealed both the true infrastructure burden of truck-based logistics and the opportunity for rail conversion. | |||
'''Port of Mobile / Alabama State Port Authority (2020)''' | |||
Alabama needed to identify state-domiciled beneficial cargo owners, their locations, international trade lanes, and actual volumes to evaluate a proposed $230 million rail infrastructure project. | |||
Initial surface-level data showed 321 TEUs—insufficient to justify major investment. A comprehensive analysis integrating specialized sources and stakeholder validation identified 60-70% of statewide international trade activity. Actual volume: 70% higher than initial reporting. | |||
Results identified specific shippers, volumes, trade lane preferences, and optimal facility locations. Analysis showed that an inland Montgomery-to-Mobile intermodal shuttle would divert over 150,000 TEUs from congested East Coast ports while improving service for existing customers. This supported Governor Ivey's approval of the $230 million A-USA Rail Corridor and provided the commercial foundation for facility planning. | |||
== '''Why It Matters''' == | |||
Infrastructure investments and facility designs require specific answers: Where should this be built? What capacity does demand require? Which trade lanes justify new services? Who are the shippers, and what do they need? | |||
The | The choice between data approaches determines whether billions of dollars support appropriate infrastructure or produce expensive, underutilized facilities designed around regional generalizations rather than detailed freight realities. | ||
The long tail of 495,000 small- and mid-sized shippers accounts for half of U.S. import volume. Infrastructure serving only the top 500 shippers misses half the market and fails the communities where those businesses operate. | |||
Complete market intelligence requires granular movement data, identification of beneficial cargo owners, trade lane analysis, and ground-truth validation. Anything less yields incomplete answers to questions on which billions of dollars and regional economic futures depend. | |||
Complete market intelligence requires granular movement data, identification of beneficial cargo owners, trade lane analysis, and ground-truth validation. Anything less yields incomplete answers to questions on which billions of dollars and regional economic | |||
Latest revision as of 19:57, 24 January 2026
The Data Problem
The supply chain data sources used by most infrastructure planners provide only regional aggregates. This obscures what investors need to know: which commodities move on which routes between specific locations. This leads to misallocated capital, suboptimal facility design, and strategic decisions that increase costs for users and society.
The problem also extends beyond data quality to market visibility. Consider U.S. imports: 500 shippers account for 33% of volume. The next 3,100 shippers add another 17%. The remaining 495,000 shippers—the other half of all imports—operate invisibly to ports, railroads, and planners. These aren't inconsequential players; they're the heart of regional economies and communities. They're manufacturers, distributors, and processors that employ people in these communities. Yet freight analysis focuses on what's easily counted: the largest players and aggregate tonnage.
This traditional supply chain analysis exacerbates the problem by tracking equipment movements rather than commodities and by emphasizing imports over balanced trade analysis. Billion-dollar infrastructure decisions are made without knowing the actual shippers, commodities, trade lanes, and capacity needs.
Why Standard Sources Fall Short
Most infrastructure planning uses the Freight Analysis Framework (FAF)—a U.S. DOT dataset showing aggregate freight flows between 173 regional zones and the 50 U.S. States. It is also always several years out of date. FAF works for macro policy analysis. It fails for planning and investment decisions.
FAF reports flows between regions and state-level aggregates. It cannot distinguish through traffic from local activity, identify specific origin-destination pairs, or provide county-level precision. An investor seeking a property development approach or evaluating an investment in a rail spur or transload facility needs to know: Which specific rail line carries what tonnage of which commodities? Where do those shipments originate and terminate? What seasonal patterns affect capacity? Which additional routings provide shippers with new market access?
FAF cannot answer these questions.
The 360° Approach
360° Freight Market Intelligence combines granular freight movement data with field research and stakeholder interviews. The methodology integrates multiple specialized datasets to identify beneficial cargo owners, actual volumes, trade lane preferences, commodity flows, and routing patterns that are invisible in regional aggregates. This digital intelligence is further validated and enhanced through interviews with the people who move, receive, and depend on that freight—revealing future plans that exist beyond datasets.
What This Complete Intelligence Delivers
Northern Nevada Development Authority – Fernley Transload Feasibility (2020)
A four-county region sought to understand its logistics-based economic development opportunities. Evaluating a truck-to-rail transfer facility requires distinguishing through traffic from local origin-destination activity and identifying the commodities carried by the trucks and railcars seen moving in the area. FAF's large regional generalities couldn't identify which corridors carried divertible freight or which services would capture meaningful volumes.
Detailed county-level analysis by 360° Freight Market Intelligence illuminated the primary commodities originating in the eleven states west of Nevada and the specific destinations in California. Importantly, movements destined for domestic destinations in California were distinguished from those heading overseas. The resulting recommendations added up to a commercially feasible project and identified the specific commodities and shippers to be served—impossible with FAF-based generalized data approaches.
Nevada State Rail Plan – Statewide Truck Analysis (2020)
Analysis of 10.5 million truck movements found that 4.1 million trips—40% of total activity—were empty-trailer returns or warehouse-to-distribution transfers. FAF commodity reporting doesn't capture empty movements.
FAF data showed only 650,000 full truck movements of aggregates. The complete analysis revealed 1.3 million truck trips, all generating road wear, congestion, and emissions. This revealed both the true infrastructure burden of truck-based logistics and the opportunity for rail conversion.
Port of Mobile / Alabama State Port Authority (2020)
Alabama needed to identify state-domiciled beneficial cargo owners, their locations, international trade lanes, and actual volumes to evaluate a proposed $230 million rail infrastructure project.
Initial surface-level data showed 321 TEUs—insufficient to justify major investment. A comprehensive analysis integrating specialized sources and stakeholder validation identified 60-70% of statewide international trade activity. Actual volume: 70% higher than initial reporting.
Results identified specific shippers, volumes, trade lane preferences, and optimal facility locations. Analysis showed that an inland Montgomery-to-Mobile intermodal shuttle would divert over 150,000 TEUs from congested East Coast ports while improving service for existing customers. This supported Governor Ivey's approval of the $230 million A-USA Rail Corridor and provided the commercial foundation for facility planning.
Why It Matters
Infrastructure investments and facility designs require specific answers: Where should this be built? What capacity does demand require? Which trade lanes justify new services? Who are the shippers, and what do they need?
The choice between data approaches determines whether billions of dollars support appropriate infrastructure or produce expensive, underutilized facilities designed around regional generalizations rather than detailed freight realities.
The long tail of 495,000 small- and mid-sized shippers accounts for half of U.S. import volume. Infrastructure serving only the top 500 shippers misses half the market and fails the communities where those businesses operate.
Complete market intelligence requires granular movement data, identification of beneficial cargo owners, trade lane analysis, and ground-truth validation. Anything less yields incomplete answers to questions on which billions of dollars and regional economic futures depend.
