Logistics Series – Blog 1 - LTL Data and Translating Cost – Why Actual Class is Key

Source One is introducing a new series of blogs focused on logistics and transportation and covering a variety of themes. This blog will address LTL data collection and how specific data points are used to determine cost.

A common first step in any traditional sourcing exercise is to collect data. Less-than-truckload (LTL) is no different. But it can’t just be data; it needs to be quality data capable of representing the true freight profile of a shipper. LTL transportation is generally perceived as complex compared to other shipping modes.

LTL’s reputation for complexity persists for a number of reasons:

• Shipping characteristics like cargo weight, pallet count, and freight classification affect pricing.
• Each shipper is unique. Benchmarking the mode can be challenging because it is not easy to make direct comparisons between different shippers’ operations.
• There is a tendency to accept LTL for what it is, and not take the time to gain a deeper understanding of its cost drivers. Freight networks are constantly changing and shippers need to keep up with shifting patterns of supply and demand.

Traditionally, LTL shipments are rated according to tariffs. Carriers normally publish tariffs – also known as rate bases – on an annual basis. A tariff is a rate matrix that defines hundred weight (CWT) rates for all classes and weights for all zip code combinations.

When rating an LTL shipment, you need to know the origin and destination zip codes as well as the shipment’s weight and the classification for each product it includes. Classifications, or classes, are published by the NMFC (the National Motor Freight Classification is a standard that provides a comparison of commodities moving in interstate, intrastate and foreign commerce).

What are the 18 Different Types of Freight Class?

The NMFC issues an item number for each commodity. This number is assigned for the purpose of applying class along with governing rules and regulations. There are 18 different classes, ranging from class 50 to class 500.  Classes are based on a number of factors including product density, liability, handling, packaging, value, and stowability. Lower classes are less expensive, representing very dense and/or low-risk freight.  A high class indicates lighter freight that typically takes up more space. The higher the class of the freight, the higher the rate charged.

Until the LTL industry decides to convert to dimensional pricing instead of the classification system, LTL pricing will continue to depend to be based on using the National Motor Freight Classification (NMFC) system.

So, how does a carrier determine what a LTL shipment costs?

• Origin Zip = 60654
• Destination Zip = 33140
• Class = 75
• Weight = 2000 lbs or 20 CWT
• Tariff rate for class 75, 2000 lbs = 79.86
• 20 x 79.86 = $1,597.20 (the full freight rate without discounts)

Rates for the same lane can vary from tariff to tariff.  For example, the tariff published by a regional carrier may reflect better rates on short haul lanes than long haul.  Likewise, a national carrier’s tariff may reflect better rates on long haul lanes than short haul.  Large carriers often use the Czar Lite® tariff because it is a neutral nationwide rate base that does not favor either long or short haul lanes.

LTL carriers offer discounts off of tariffs. These discounts are negotiable, and often correlate directly with the amount of freight volume/revenue tendered to the carrier.  In addition to discounts, minimums are also negotiable. Minimums represent the absolute lowest amount charged per 

shipment.

The calculation set out above is a basic representation; when determining a line haul rate other factors such as shipping FAK (Freight All Kinds), deficit weight rating, and lane specific strategies, can add layers of complexity.

It is very important to capture the actual class when computing an LTL price. Often shippers are given an FAK cargo designation on invoices, a blanket classification that obscures the actual classes –there may be multiple types of goods involved – and introduces inaccuracies that can have a significant impact on price. The shipper has no way of knowing which specific classes of cargo are being shipped if everything is lumped under the FAK designation.

The most common obstacle to performing accurate LTL analyses, running procurement initiatives, or introducing new carriers, is missing or incomplete data – particularly the data elements that are critical to tariff calculations (such as the actual freight class). If these data elements are captured correctly, all parties involved will avoid having to make flawed assumptions throughout the process.

As a helpful tool, here is a list of the essential data fields required when collecting LTL data:

• Origin city, state, and zip code
• Destination city, state, and zip code
• Shipment date(s)
• Weights
• Freight class
• Historical costs (line haul, accessorials, fuel)
• Length of haul (mileage)

In conclusion, when working with LTL data, class is king. The ability for a carrier to gain clear insight into an accurate shipping profile is critical for vendor relations and proper pricing.