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Auburn University to Study LTL Pricing

As reported in this blog and in other sources, the LTL (less than truckload) segment of the freight transportation industry has been one of the hardest hit by the economic downturn. According to an estimate prepared by the SJ Consulting Group, revenue at the top 25 LTL carriers dipped by twenty-five percent in 2009 from $33 billion to $25 billion. Almost all of the U.S. publicly traded LTL carriers lost money on their LTL operations during the latter part of 2009.

The significant decline in revenues and profits has been precipitated by several factors. The terminal infrastructure and geographical footprint required to compete in this sector represent a high fixed cost. As business drops, it is difficult to reduce fixed costs without having a negative impact on service. Aggressive price competition, some of it targeted at YRCW, the large financially troubled LTL carrier reduced margins to unprofitable levels. In addition, the pricing model that has been in use for decades, namely discounting a rate base that is tied to various classes of goods, is cumbersome and rigid.

The high and low ends of the LTL business have both come under attack. The parcel carriers have targeted the low end with their hundredweight programs while the high end (e.g. up to 10,000 pounds) has been attractive to truckload carriers seeking to fill their empty trucks.

The rise of 3PL’s over the past decade has encouraged many shippers to migrate to them for LTL service. These companies can mix and match LTL carriers to come up with a freight program that is often more cost effective than what individual LTL carriers can devise on their own.

SMC3, a rate bureau that dates back to the days of a regulated trucking industry, is sponsoring the study to be conducted by a team of researchers at Auburn University. The research will be performed in two phases. As part of the research, 12-to-15 in-depth interviews will be conducted with shippers, carriers and 3PL’s. Feedback from the initial round of interviews will be used to frame questions for phase 2.

This is not the first time that LTL pricing has been studied. Previous research efforts were undertaken in 1993 and 2002. Nevertheless, despite the fact that trucking deregulation has been around for thirty years, the classification system tariff has been the basis for pricing and discounting through this period and subsequent to the two previous research efforts. During the apex of the recession, discount levels reached as high as 90%.

In some of my previous blogs I have provided overviews of some new LTL pricing tools (e.g. Cube Based Pricing, Density Based Pricing) that have been developed in recent years. They have gained limited traction. “One thing we want to determine is whether there is a stomach out there within the industry to maybe look at a new pricing mechanism or process,” commented Joe Hanna professor of supply chain management at Auburn University .

SMC3 vice president of business development Danny Slaton, who is sponsoring the research, stated that “We have done these studies before and want to understand how things have shifted over a period of time. We are not really looking at a shift in levels of price; we are looking at the mechanics of the business process and how much more has technology changed what is applied to pricing and how pricing is integrated into the overall business process at the enterprise level.”

The results of this research will be closely monitored by the key players in this industry. Any revisions to current processes will need support from shippers, carriers and 3PL’s and will require a change management procedure to make sure they are implemented in a methodical way.

Comments (1)

Jay B.:

You mean "25 million", right? "...revenue at the top 25 LTL carriers dipped by twenty-five percent in 2009 from $33 million to $25 billion."

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This page contains a single entry from the blog posted on August 7, 2010 12:28 PM.

The previous post in this blog was Seeking to Improve the Profitability of your Trucking Company – Try Cleaning and Mining your Data.

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