What is a rate curve? If you do not know the answer to this question or only have a vague notion of what the term means, then you are missing out on a relatively simple, but powerful freight management tool. Don’t feel bad if you are nonplussed; in our experience many practitioners are unfamiliar with the concept.
When used in conjunction with the analytics of a good transportation management system, rate curves consistently drive cost savings and network efficiencies by improving the performance of route guides. This graphic representation of shipments provides a snapshot of how cost effective your freight operations are in a specific lane. By delving a little deeper into the data, you can develop strategies for lowering freight costs without compromising customer service.
Rate curves come in many shapes and sizes, but are typically right skewed with the lower bound being the minimum rate that carriers will accept for that lane and the tail to the right being the higher rates paid. For the purposes of this explanation let’s consider two examples: the Long Tail and Short Tail Above Benchmark rate curves depicted in Figure 1 and Figure 2 respectively.
Both curves plot freight rate per mile versus number of loads in a lane. Each bar represents the number of loads transported at that particular rate over a certain time period, in this case one year. For example, in Figure 2 there were 225 moves at a rate of $1.20 per mile over the period represented. The user can consult the route guide to identify which carriers are matched with each of the bars on the charts. The overall aim is to keep the degree of variation between the rates to a minimum.
In the Long Tail chart (Figure 1) rates are quite widely distributed from $1.15 to $2.30 with a cluster at the lower end, hence the “long tail” designation. The mode (the rate with the most occurrences) is $1.30, the median (half the occurrences are above and half are below this number) is $1.34, and the mean (mathematical average) is $ 1.46.
This data combined with information on freight flows in that lane can reveal much about how the route guide is operating. For instance, the extended tail could be a function of unplanned shipments. In a typical scenario the shipper needed capacity at short notice at 5 pm on Friday and had to go deep into the route guide to find an available carrier. In order to move this freight it paid an above-market rate of $2.30 for almost 200 loads.
In the Short Tail Above Benchmark curve (Figure 2) the rates are more clustered at the lower end of the distribution. A possible explanation is that the shipper provided backhaul opportunities that fit into the networks of these carriers, and since they valued the business, offered favorable rates. Looking into the structure of the curve in more detail might reveal that the $2.00 per mile provider could afford to take the freight when it was the last-option carrier because it had already built a sizeable premium into its rate. At the other end of the scale the $1.11 carrier provided back up capacity and might have accepted only one in 10 tenders.
After analyzing the rate curve perhaps a better strategy – one that will reduce the variation and shorten the tail – is to propose shifting the cheaper carriers further up the route guide with more generous freight payments in return for higher load acceptance rates. Another way to compress the curve is to approach the expensive carriers and offer more consistent business if they agree to bring their rates in line with the rest of the market. Too often, rate negotiations are focused on obtaining a rate lower then their current lower bound (lowest rate). This may work for the short term, but carriers will quickly replace that lane with one that is closer to the market price.
The overriding theme is trying to achieve alignment with your carriers to reduce the variation in rates. Increasing rates to secure more capacity or renegotiating to achieve a lower rate in return for offering more business, are strategies you can deploy to smooth out the rate curve by adjusting your route guide.
A compressed curve where the rates are clustered indicates that you are buying capacity at satisfactory rates and the carriers are accepting high volumes because the business complements their network needs. The curve outlines a win-win situation where respective networks are in equilibrium.
Generating rate curves on a regular basis enables you to monitor the performance of your route guide and take corrective action when it goes awry. This is almost inevitable, because networks are changing constantly. The rate curve analysis provides a quick and easy measure of performance that alerts you to problems before the cost penalties become alarming.
Another, less tangible, payback is that by actively managing the route guide in this way, you develop a discipline and rigor that makes your network more competitive.
Given these returns, rate curves could be one of the freight industry’s best kept secrets.
Jordan Kass serves as the Executive Director for TMC, C.H. Robinson’s Managed TMS service that includes Six Sigma-based process engineering, TMS technology, and power users to ensure maximum software ROI. Jordan is a recognized industry leader, with over seventeen years of industry experience. TMC is a global division of C.H. Robinson Worldwide, Inc.