Client: Midwest Inland Port Authority
Introduction
A strategically positioned Midwest inland port authority with multimodal connections to multiple Class I railroads engaged our port and rail experts to conduct a phased steel coil market study — identifying barge-to-rail conversion opportunities and building a value proposition framework to attract new rail volume.
The Challenge
The port occupied a strong multimodal position but had not fully mapped its competitive opportunity in steel coil traffic moving by barge on the adjacent river system. Understanding which origin-destination lanes could support a viable barge-to-rail conversion — and what commercial proposition would attract shipper and carrier interest — required rigorous market modeling and stakeholder validation.
What We Did
- Mapped steel coil production facilities adjacent to the relevant river system, segmenting origins by barge loading capability and directional rail conversion potential.
- Modeled comparative economics across barge-to-rail and all-rail routing options, finding the port’s barge-to-rail option neutral to moderately favorable in select corridors — with potential per-car savings of up to $3,200 on certain lanes.
- Identified Western US markets (California, Front Range, Mountain West) as the highest-probability conversion targets from in-scope river origins.
- Built a value proposition framework covering demurrage flexibility, railcar supply management, port inventory control advantages, and market reach expansion.
- Conducted stakeholder interviews with logistics and steel industry contacts to validate the commercial model and align key rail partners on the initiative.
Results
Delivered a refined annual tonnage opportunity range across conservative, base, and stretch scenarios — with near-term volume achievable by diverting existing flows without requiring modal changes from steel producers. The study produced actionable shipper targeting, Class I engagement strategy, and a commercial positioning framework for the port’s marketing program.







