The Dynamic Nature of Grain Trading

Commodity traders do not operate like traditional manufacturers with stable plant-to-customer lanes. A trader may purchase grain today from a new elevator in rural Iowa and sell it tomorrow to a processor in Texas or an export terminal in the Pacific Northwest. This requires the ability to rapidly evaluate rail feasibility and costs between virtually any two points in the network.

Rail remains the backbone for bulk grain movements. Yet current SAP TM implementations face systemic barriers in supporting this fluidity.

How SAP TM Currently Models Rail Shipments?

In SAP TM, freight documents (Freight Units, Railcar Units, Freight Orders) are created between Business Partner Locations. These locations represent physical sites such as a specific grain elevator or a milling facility. Each BP Location is tied to a detailed postal address.

Default Routes — the primary mechanism for determining valid rail routings and rates — are built point-to-point between these exact BP Locations.

While this works for many industries, it creates fundamental issues for rail-based bulk commodity movements.

The Fundamental Problem: SPLC vs. Business Partner Locations

The rail industry does not use postal addresses for routing or rating. Instead, everything revolves around SPLC codes — standardized railroad station identifiers typically representing city + state combinations or specific rail stations.

Rail carriers publish rates and determine service availability based on these SPLC locations. Rate specialists and traders evaluate moves using questions such as: “Can we move grain from SPLC ‘Des Moines, IA’ to SPLC ‘Dallas, TX’ via Carrier X at published tariff rates?”

This creates a critical disconnect:

• BP Locations ≠ SPLC Locations: A grain elevator might be located 8–15 miles outside the city whose SPLC the railroad recognizes.
• No Native Mapping: TM lacks a standard, scalable way to automatically map thousands of BP Locations to the correct SPLC codes.
• Default Route Dependency: Valid route and rate determination usually requires a point-to-point Default Route between the exact BP Locations. Maintaining routes for thousands of possible combinations is impractical.

Partial Workaround: Zone-Based Default Routes

One commonly attempted approach to address the rigidity of point-to-point Default Routes is to use broad zone-based Default Routes.

In this setup:

• Origin zones represent large geographic areas (e.g., “Central Iowa Grain Region”).
• Destination zones represent broad receiving areas (e.g., “Texas Panhandle Processors” or “Pacific Northwest Export Zone”).
• Intermediate junctions/marshaling yards are defined as key hand-off points.
• Mainline Class 1 carriers (BNSF, UP, CPKC, etc.) are assigned to execute the long-haul segments between these zones.

This reduces master data volume because one Default Route can cover many possible elevator-to-buyer combinations within the defined zones. The system can then propose mainline routing options and apply published rates more dynamically across broader areas.

However, this approach has a critical limitation:

It cannot effectively model shortline or switch carriers responsible for first-mile pickup (from the actual grain elevator to the mainline interchange) and last-mile delivery (from the mainline drop-off to the final milling company or buyer facility).

Because zone-based routes focus on high-level regional movements and mainline carriers, the critical short-haul legs handled by smaller switch carriers are difficult — if not impossible — to incorporate accurately. These shortline carriers often have their own specific service areas, rates, and access agreements that vary significantly even within the same broad zone. As a result, the zone-based model provides incomplete routing visibility and forces manual handling of first-mile and last-mile segments outside the system.

Business Impact on Commodity Traders

This SPLC vs. BP Location gap, even with zone-based attempts, creates severe operational challenges:

• Limited Flexibility — Traders cannot systematically validate rail options for new or infrequent origin-destination pairs.
• High Manual Effort — Rate specialists must research SPLC-based tariffs and shortline options manually.
• Incomplete Cost Visibility — Especially for full Rule 11 multi-carrier moves involving shortlines.
• Delayed Execution — Slows down spot trading decisions where logistics cost is a key profitability factor.
• Scalability Constraints — The problem worsens as trading volumes and supplier/buyer networks expand.

In essence, SAP TM forces a rigid, location-specific structure on an industry that thinks and operates in a more abstract, SPLC-based network model.

Industry Perspective

Traders, rail rate analysts, and transportation planners in the agricultural sector are accustomed to working with SPLC codes and city/state tariff points. They expect a modern TMS to align with this established way of working rather than requiring the industry to adapt its core processes to the system’s structural limitations.

The mismatch between postal-address-based BP Locations and tariff-based SPLC locations remains the single biggest barrier preventing SAP TM from fully supporting dynamic rail transportation of bulk agricultural commodities in North America.

Conclusion

In Part 2, I will focus on how I used the existing TM objects and some enhancements to tackle this challenge providing the Traders with the ability to practically ship from anywhere to anywhere on the North American Railroad network. Stay Tuned!