360° Freight Market Intelligence: Difference between revisions
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Supply chain data sources used by most industry practitioners provide only general information at a regional level. This obscures the commercially-relevant specifics: which commodities move on which routes between which locations. This leads to misallocated capital, suboptimal facility design, and strategic decisions that increase costs for users and society. | Supply chain data sources used by most industry practitioners provide only general information at a regional level. This obscures the commercially-relevant specifics: which commodities move on which routes between which 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, and the next 3,100 shippers account for an additional 17%. The remaining 495,000 shippers—the other half of all imports—operate largely out of sight of ports, railroads, and infrastructure planners. These aren't inconsequential players; they're the heart of regional economies and communities. Yet most freight analysis focuses only on what's easily counted: the largest players and aggregate tonnage flows. | The problem also extends beyond data quality to market visibility. Consider U.S. imports: 500 shippers account for 33% of volume, and the next 3,100 shippers account for an additional 17%. The remaining 495,000 shippers—the other half of all imports—operate largely out of sight of ports, railroads, and infrastructure planners. These aren't inconsequential players; they're the heart of regional economies and communities. Yet most freight analysis focuses only on what's easily counted: the largest players and aggregate tonnage flows. | ||
This traditional supply chain data exacerbates the problem by focusing on equipment movements rather than commodities and by emphasizing imports over balanced import-export analysis. Planning often relies on public agencies without commercial freight expertise. Critical decisions are made daily based on inaccurate and incomplete information about shippers, commodities, trade lanes, and future plans. | |||
== '''Why Standard Sources Fall Short''' == | == '''Why Standard Sources Fall Short''' == | ||
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Evaluating a potential truck-to-rail transfer facility required distinguishing through traffic from local origin-destination activity and identifying high-density trade lanes suitable for rail conversion. | Evaluating a potential truck-to-rail transfer facility required distinguishing through traffic from local origin-destination activity and identifying high-density trade lanes suitable for rail conversion. | ||
FAF tonnage data showed regional volumes but couldn't provide | FAF tonnage data showed regional volumes but couldn't provide the needed detail. Detailed movement analysis quantified through-traffic and identified viable trade lanes for the specific facility location. | ||
==== '''Nevada State Rail Plan – Statewide Truck Analysis (2020)''' ==== | ==== '''Nevada State Rail Plan – Statewide Truck Analysis (2020)''' ==== | ||
Revision as of 01:10, 21 January 2026
The Data Problem
Supply chain data sources used by most industry practitioners provide only general information at a regional level. This obscures the commercially-relevant specifics: which commodities move on which routes between which 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, and the next 3,100 shippers account for an additional 17%. The remaining 495,000 shippers—the other half of all imports—operate largely out of sight of ports, railroads, and infrastructure planners. These aren't inconsequential players; they're the heart of regional economies and communities. Yet most freight analysis focuses only on what's easily counted: the largest players and aggregate tonnage flows.
This traditional supply chain data exacerbates the problem by focusing on equipment movements rather than commodities and by emphasizing imports over balanced import-export analysis. Planning often relies on public agencies without commercial freight expertise. Critical decisions are made daily based on inaccurate and incomplete information about shippers, commodities, trade lanes, and future plans.
Why Standard Sources Fall Short
Most infrastructure planning relies on the Freight Analysis Framework (FAF)—a dataset produced by the U.S. Department of Transportation that shows aggregate freight flows between regions. FAF serves well for macro-level policy analysis, but its granularity ends where investment decisions need to begin.
The questions landowners, developers, and economic development professionals ask demand answers at a different scale: Which specific rail line carries what tonnage of which commodities? Where do those shipments originate and terminate? How do seasonal patterns affect capacity requirements? What additional routings provide shippers with important new market access?
FAF reports freight flows between 173 regional zones and state-level aggregates. This regional aggregation obscures the intra-regional patterns needed to evaluate individual sites, can't distinguish through-traffic from local activity, and doesn't identify specific origin-destination pairs. For infrastructure decisions that require county- or city-level precision, FAF's resolution is insufficient.
The 360° Approach
360° Freight Market Intelligence addresses this problem by combining granular freight movement data with in-the-field research and stakeholder interviews to build a comprehensive picture of the market. Where conventional analysis stops at aggregate trends, this approach identifies specific opportunities and risks that affect investment returns and operational performance.
The methodology integrates multiple specialized datasets—revealing shipper identities, actual volumes, trade lane preferences, commodity flows, and routing patterns that are invisible in standard regional aggregates. This digital intelligence is validated against insights from the people who move, receive, and depend on that freight—uncovering future plans that don't appear in any dataset.
This grounded intelligence answers the specific questions landowners, developers, and economic development professionals need answered: Where should investment occur? What design meets actual demand? Which shippers would benefit from locating at this property?
What Complete Intelligence Reveals
Northern Nevada Development Authority (2020)
A four-county region sought to identify opportunities to divert truck traffic to rail. FAF's regional aggregation couldn't answer location-specific questions about which corridors carried divertible freight or where transfer facilities would capture meaningful volumes.
Detailed county-level analysis revealed specific corridors, quantified capture opportunities, and identified which communities offered viable development sites. The resulting recommendations pinpointed commercially feasible projects with specific geographic coordinates—impossible with FAF's regional zones.
Nevada State Rail Plan – Fernley Transload Feasibility (2020)
Evaluating a potential truck-to-rail transfer facility required distinguishing through traffic from local origin-destination activity and identifying high-density trade lanes suitable for rail conversion.
FAF tonnage data showed regional volumes but couldn't provide the needed detail. Detailed movement analysis quantified through-traffic and identified viable trade lanes for the specific facility location.
Nevada State Rail Plan – Statewide Truck Analysis (2020)
An analysis of 10.5 million truck movements found that 4.1 million trips—40% of total activity—involved empty-trailer returns or warehouse-to-distribution transfers and were invisible in FAF commodity reporting. For one bulk commodity, half of all truck trips were empty returns.
This fundamentally changes infrastructure planning. FAF data showed 650,000 productive movements. Complete analysis revealed 1.3 million truck trips generating road wear, congestion, and emissions—with half carrying no payload. This doubled the apparent infrastructure burden and revealed both the true cost of truck-based movement and the opportunity for rail conversion.
Port of Mobile / Alabama State Port Authority (2020)
Alabama needed visibility into state-domiciled beneficial cargo owners, their locations, international trade lanes, and actual volumes to evaluate a proposed $230 million rail infrastructure project and assess the viability of inland facilities.
Initial surface-level data showed 321 TEUs—too small to justify a major investment. A 360° comprehensive analysis integrating multiple specialized sources and stakeholder validation identified 60-70% of state-wide international trade activity. Actual volume was 70% higher than the initial reporting indicated.
The comprehensive intelligence 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 and improve service for existing customers. This supported Alabama Governor Ivey's approval of the state-funded $230 million A-USA Rail Corridor infrastructure project and provided the commercial foundation for facility planning.
Why It Matters
Infrastructure investments, economic development strategies, and facility designs require answers to specific questions: Where should this be built? What capacity does actual demand require? Which trade lanes justify new services? Who are the shippers, and what do they need?
The choice between data approaches determines whether analysis informs appropriate investment of billions of dollars or produces expensive, underutilized infrastructure designed around regional averages rather than freight reality. The long tail of 495,000 small- and mid-sized shippers accounts for half of U.S. import volume. Infrastructure that serves 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 development depend.
