The Challenge of Analyzing Rates When Fuel Prices Change Rapidly
The precipitous drop in fuel prices over the last year has affected the trucking industry in several ways. One ramification, in particular, is being felt in our work as trucking consultants.
Freight network optimization toolkits include rate indexes, which are used to analyze how a carrier’s rates compare to the market’s rates. When fuel prices change significantly in a short period of time, complications arise with rate analysis, and we have to confront the discrepancies that occur when the time periods between industry and carrier rate data vary considerably.
This is a vital issue right now for carriers who use rate indexes. Let’s take a closer look as to why this problem is occurring.
Changes in fuel prices create corresponding changes in the fuel surcharge billed by carriers (FSC). Due to the myriad FSC methodologies employed in today’s market, KSM Transport Advisors rely on the linehaul rate plus the fuel surcharge (LH+FSC) when comparing rates. The inclusion of the FSC in the rate means that rate data is directly affected by fuel-price fluctuations.
Over the past few weeks, some carriers have seen a pronounced trend in the metric that compares their rates with market rates. While the variance between carrier rates and the industry rates has increased substantially, these figures are inflated, due to a rapid decrease in the FSC that resulted from the steep decline in fuel prices.
This inflated variance occurs because the data set for carrier rates reflects one time period, while the industry index figures correspond to a longer and less recent time period. Most of the time, this time-period discrepancy between the two sets of data is far less significant. However, when the FSC figures change significantly and rapidly, the contrast in time periods becomes an issue.
For example, according to the Department of Energy’s (DOE) National Average Prices, fuel sold at an average of $2.519 and $2.143 in October 2015 and January 2016, respectively. As fuel prices have dropped from October to January, the FSC has dropped, and thus rates defined as LH+FSC have dropped. If industry rate data from the last quarter of 2015 is compared to carrier rate data from the first month of 2016, the analysis will be skewed, because the FSC component of the rates has changed significantly and independently of any change in the linehaul component of the rates.
In this case, comparing industry rates for the final quarter of 2015 to a carrier’s rates for the first month of 2016 is an apples-to-oranges comparison to some degree. For that reason, any comparison at this point between industry LH+FSC rates for a three-month period and your company’s LH+FSC rates for a more recent month should be taken with a grain of salt. (The problem becomes more pronounced for carriers as the time-period discrepancy increases.)
It is worth emphasizing that this article should not be taken as a criticism of rate indexes. The major rate indexes available today answer a vital need in the industry. In order to optimize freight networks, you need reliable data, and the success of our clients testifies to the value of the rate index data that we use. This current problem arises from a specialized circumstance that is specifically related to the FSC component of rates and in no way indicates that there is a larger issue with the rate index.
In terms of the time period KSM Transport Advisors uses for rate index data, there is a reason for our chosen structure. Usually, fuel prices change more gradually, so the time lag does not create a problem. We feel the time period for the data set from the industry index offers the best tradeoff between data time-matching, seasonality and density.
Nevertheless, it is difficult to say how fuel prices will move in the future, so KSM Transport Advisors is exploring several options for providing a clearer comparison between client and industry rates. We are specifically looking at the issues that arise during periods of quickly changing FSC.
Sophisticated analysis of freight networks will always involve an assortment of challenges in terms of choosing data sources, determining time periods and more. Our goal is to continuously improve the accuracy of our methods, which is why this issue deserves your attention.
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