New Analytics Empowers Both Seasoned Professionals and Newly Hired Staff to Optimize Rates


arriers and brokers have access to more data on rates than ever before. Dispatchers and brokers frequently use rate indices that provide detailed historical information about rates on any given lane. You can specify a lane and see the maximum, the minimum, and the average rates that have been paid to haul freight on that lane.


Although this certainly is valuable information, there are critical pieces of the picture that are missing.


• What is the gap between rates paid to carriers and rates paid to brokers?


• Which of those rates are dominant on this lane?


• How is the rate data distributed across the range of rates reported?


• Does the rate data distribution indicate pressure that is currently pushing rates up or down?


The Data Science team at McLeod is working hard to provide LoadMaster® and PowerBroker® users with answers to these questions. The Rate Spectrum data within MPact™ pulls back the veil, so you get such a clear picture of rates that anyone on your staff can negotiate more effectively than ever.


Carrier Rates Versus Broker Rates


If you want to have an accurate view of rates on any lane, you have to consider the difference between what carriers and brokers are getting paid. Who controls capacity on that lane? Carriers have a limited number of trucks that exist in certain places; thus they have finite capacity. Brokers have access to countless trucks everywhere, so they have infinite capacity. In most cases, lanes are dominated by one side of this coin or the other. If you want to put yourself in the most profitable position on your rate for a lane, you need to know which rates are dominant on that lane.


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The problem is that people tend to rely on data from rate indices that aggregates asset and broker transactions into one data set. Given that brokers generally get paid more than carriers, these aggregated data sets will generate average rates that are too low for a broker and too high for an asset provider. When you average two dissimilar things - asset capacity versus broker capacity - the average you’re getting is not useful. This lack of distinction is an opportunity for data science to get involved and clarify the situation.


The Median Versus the Average


When you’re viewing rate data for a lane that shows a maximum, a minimum, and an average, it’s tempting to jump to the wrong conclusions about where you should put your rates. MPact’s Rate Spectrum data shows you the rates at the quartile boundaries in addition to the maximum, the minimum, and the average. From this you can see the median rate, which means that half of the rates are higher and half are lower. In most cases, this median figure will be different from the average.


The min and the max give you only the lowest and the highest rate, but when we introduce the Rate Spectrum, you get a better idea of the how the rates between the min and the max are distributed. However, by itself, this wider perspective of the range of rates in the market does not indicate movement. In order to learn that, we need to compare the median with the average. When we have this comparison, we can begin to distinguish any directional pressure that currently exists in the marketplace.


This is where it’s critical to differentiate between assets and brokers, because making that distinction finally allows real and actionable information to appear. In the chart on flatbed rates, we see that the asset median rate is $1.75, and the average is $1.73. This shows modest downward pressure of 2 cents per mile. The broker median is $2.16, and the average is $2.10, which shows downward pressure of 6 cents per mile. When the asset and brokers are mixed together, the median is $1.76 and the average is $1.86, which indicates upward pressure of 10 cents per mile.


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