3PL Perspectives
Advances in Data Analytics Allow Brokers to Assess Lanes & Optimize Margins
Criss Wilson | McLeod Software
ALL FREIGHT MARKETS are not created equal. Some generate better returns than others, but brokers haven’t been able to tell in advance which ones are the best bets. For many years, the reality has been that you needed to work a lane before you could determine its profit potential. The arrival of better business intelligence tools and advances in data analysis have changed that. Today it is possible to take the rate data already available, crunch the numbers, and arrive at a synthesis that tells you right now where you’ll make money and where you won’t.
The data about the lanes and markets is there. We know how much the shippers paid the brokers and how much the brokers paid the carriers. We know where the loads originated and where they terminated. We know when the loads were hauled. By aggregating all of this data and ordering it in a variety of new ways, analytic tools are now able to present a dynamic view of rates that was not possible before.
Know the Lane Rate
With the right data set, you no longer need to run a lane before you can estimate the net profit from it. You can measure that before you commit to the lane. Data analytics evaluates the rates from loads that other companies have run in that lane and creates a rate spectrum that shows you the rates at the quartile boundaries in addition to the maximum, the minimum and the average. In lanes you’ve run before, your own rate history should be compared to the rate spectrum. Whether you’re handling a spot quote or managing a massive bid, you have the information you need to decide where your rate should be to optimize your margin. The fog has lifted.
Identify the Most/Least Profitable Lanes
The companies that offer rate indices for a subscription can present both buy and sell rates for most market pairs in the nation. With data of that scope in hand, data analytics can provide insight into net profit margins related to both origin and destination pairs focused on 3-digit zip codes out to areas as large as markets, states and zones. Data analytics can aggregate all of this information and present you with lists of the markets that are currently the most and least profitable. You don’t have to accept whatever freight comes your way and hope for a good margin. Instead, you can go out and recruit the lanes where you know there are good margins. The rate analytics will show you the current high-margin lanes, so direct your brokers to solicit freight in those lanes. At the same time, you can post a list of the low-margin lanes that should be avoided.
Data analytics can illustrate the rate spectrum by sorting the shipments into quartiles highlighting the rates that lay at the boundaries of each of the segments.
Detect Patterns & Trends
New opportunities open up with analysis that shows how rates change over time. Rates go through cycles in our industry, and the analytics can help you detect patterns. It could be a seasonal cycle or a pattern tied to any number of other factors. Over shorter time frames, it is possible to detect trends. Comparing today’s rates against all of the rate history for a lane, you will be able to see instantly if the rate is going up, going down, or holding steady.
Look at Every Angle
Using a series of filters during data analysis makes it possible to see data from every angle. How do asset-based companies compare to brokers with the rates paid by shippers? How do dry van rates compare to reefer rates within a lane? How do rates in this lane this year compare to the same period last year? Good data analysis shows you all of this.
Anticipate Rate Changes
Data analytics can illustrate the rate spectrum by sorting the shipments into quartiles highlighting the rates that lay at the boundaries of each of the segments. You can see not only the upper and lower limits, but how many of the shipments appeared in each quartile. When you can compare the rate data in terms of the recent past against the long-term, you can begin to make predictions. If the average rate in a market last week is above the market’s historical median rate, you can conclude that there is rate pressure on the upward side of the rate spectrum. If you are comparing your rate history against the market rate history, you might see that you’re at the low end of the spectrum possibly leaving money on the table, or at the high end and in danger of being undercut.
If you have not started using business intelligence and the many available analysis tools to crunch the market information accessible to you, don’t wait. This sort of insight is just the start. In the future, the power of data analytics will expand in ways that will help brokers optimize margin like never before. This new wave of data analysis has changed the game for brokers. These analysis tools and the understanding they provide will soon become indispensable. Before long, all successful brokers will wonder how they ever managed without them.
Criss Wilson is a Data Scientist at McLeod Software. He can be reached at [email protected]
Photo credit: ISTOCK.COM/GAUDILAB
