Balance Network Profitability with Customer Capacity Requirements

Every day, North American carriers face the challenge of booking or accepting freight that benefits them while still meeting customer expectations. Based on government regulations for driver hours, carriers have a limited amount of time to generate revenue. And they have to balance this limitation with the capacity they’ve committed for their customers while dealing with the random nature of their network.

Traditionally, the role of the CSR (Customer Service Representative) at a carrier was to book freight for all trucks in their market, the focus being on finding outbound loads. A CSR would wait for contact from customers to book freight for the trucks; if they were short on freight, they would either reach out to known customers or contact brokers. More advanced CSRs utilize rates or total revenue to determine the best loads to accept. The catch is that this focus on outbound booking does not drive profitability or balance.

The focus on outbound booking leads to two major problems on a daily basis:

  1. Imbalance issues in the network are not solved, just shifted across the network
  2. The decision to move a truck from an outbound region does not guarantee future revenue creation

Imbalance problems will persist in the network due to other CSRs continuing to book freight, landing trucks in markets that don’t have the customer base or load volume to support the inbound freight. A lack of freight at the inbound market reduces profitability as drivers lose time waiting for a load to materialize or for freight to be booked by a broker. Broker freight traditionally is not profitable and is generally the lowest-rated freight a carrier hauls.

How can carriers build the most profitable and balanced network in real time and enable CSRs to make smarter load booking and capacity move decisions? The answer depends, in part, on using intelligent tools that utilize historical profitability and booking patterns, customer commitments, and real-time availability of capacity and demand over the next few days to build a network solution for execution.

An important capability, for example, is real-time recommendations for capacity — that is, the ability for the tool to run continuously during the day to react to changes in capacity status and loads booked outside of the recommendations. Given the random nature of a carrier network, it is important to not generate one plan for the day, but to adjust as the day progresses. Additionally, the model should not only provide recommendations of what freight lanes to book, but also recommend when and where to shift capacity and where to hold capacity.

There are other important capabilities too look for, but in general, carriers that have deployed such tools and integrated them into their daily workflow have experienced significant benefits, including improved service for customers and increased driver satisfaction via more miles and less down time.

In spite of the challenges carriers experience running their network, by leveraging intelligent tools and strategic data, they can proactively drive network profitability and balance while providing service and capacity to their customers.

Mark Drewry is a Senior Design Lead in Carrier Management and is the product manager for Load Analyzer at Manhattan Associates. He holds a bachelor’s degree in Aerospace Engineering and a master’s degree in Industrial Engineering (Logistics and Economic Decision Analysis), both from the Georgia Institute of Technology in Atlanta, GA.

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