KSMTA Launches New Tool To Help Carriers Develop a Well-Balanced Freight Network

Density, efficiency, and velocity are the pillars of success in the trucking industry. Yet, in the fast-paced world of daily trucking operations, it’s challenging for carriers to scrutinize each load for individual performance. This is where the FreightMath^™ Optimizer (FM Optimizer) comes in. By identifying the factors that drive profitability or hinder it, this tool can revolutionize how carriers allocate capacity and prioritize lanes and customers. It helps carriers separate the margin winners from the duds in their network.

The FM Optimizer is the result of meticulous research and development spanning over three years. This tool is designed to pinpoint the specific pieces of business in your “basket”’ of freight that will produce the highest potential margin and a well-balanced freight network.

The Genesis of the FM Optimizer

The following questions are routinely posed by KSMTA clients:

• How do I maximize the margin from my existing customers and the lanes in which we operate?
• How many trucks should my network have (e.g., right-size my fleet)?
• Are there loads in my logistics operation I should haul on my assets?
• I have newly awarded lanes, how can I proactively address potential problems?
• I’ve lost a customer. How will this affect my network?

The FM Optimizer allows us to answer each of these questions by utilizing a modified traveling salesman model, which is a classic example of a combinatorial optimization model. The starting point for running an optimization is to isolate a basket of freight for a specific timeframe. For our FreightMath clients, we will be conducting this analysis each period on their defined freight networks for the previous four weeks of load activity. In this monthly analysis, the FM Optimizer will only include loads that the carrier actually hauled. However, on an ad hoc basis and for further analysis and more effective decision-making, KSMTA can insert loads sold by your logistics department or future/expected loads (e.g., from potential shipper awards) as well as remove lost freight from the initial basket of freight.

Next, we can provide the model with a series of rules (constraints), which apply a layer of practicality to the output. The FM Optimizer has the singular goal of maximizing margin, potentially iterating through billions of combinations. However, to take the output from hypothetical to actionable, these constraints allow us to tailor the FM Optimizer to your specific needs and goals, empowering you in your decision-making process. The following constraints are currently available to be applied:

• Maximum Deadhead: Because the model is permitted to produce its own empty moves to connect one profitable piece of freight to another, this can result in impractical and unrealistic moves between markets. Thus, we can constrain the model to only generate deadhead moves that are within a specified milage limit.
• Minimum Margin Threshold (MMT): Our FreightMath process focuses on the direct and variable costs of hauling freight. Which is why simply producing a profitable network may not achieve enough profit to cover fixed, back office, and other costs of running your company. Again, this is not practical as every carrier has made a commitment to people and invested in assets to move freight. As a result, we set a Minimum Margin Threshold to ensure the model achieves a level of profitability that is needed in any potential market environment. We can also use the MMT as a means to continuously improve a carriers’ network. KSMTA recommends a MMT relative to the network’s current gross margin percent in the range of X+3% to X+10% (based on the realistic margin potential of a truckload carrier with an OTR ad hoc network).
• Capacity: Because the FM Optimizer has the ability to analyze other freight that was not hauled on your assets, the optimized network might exceed the actual capacity of your fleet. Or you might be in a situation where you need to reduce the number of trucks and right size your fleet and you want to know which freight should be kept to ensure a certain level of profitability. Both of these conditions can be addressed by providing a total milage constraint to the model. This will ensure the FM Optimizer provides only enough accepted loads to meet the capacity constraint, while still including the most profitable freight.
• Freight Commitments: The FM Optimizer is a binary integer model where the binary variable represents whether all trips (loads) in a target network are either accepted (1) or rejected (0). However, we acknowledge that many carriers have made firm commitments to provide capacity to key customers, which must be kept in the network. We call these loads “locked trips” and will require the model to accept them into the optimized network. Although we can use this last constraint, our advice is to limit the application of this rule – there should be no golden cows in any business.

The Output (Results)

The objective of this model is to maximize profit across the entire network while ensuring that all accepted trips are connected to another accepted trip. Accompanying the FM Optimizer, the KSMTA team has created a new FM Optimizer Dashboard to help make this information actionable. The FM Optimizer Dashboard contextualizes these results by customers, lanes, and capacity, providing an efficient way to interpret the results.

• Customers and Lanes: Providing the before and after from a load perspective – which loads you did haul, compared to the loads the FM Optimizer wanted you to haul (accepted). This dashboard allows you to drill into all the lanes for a given customer, and all the customers on a specific lane, isolating the freight you can take action on (i.e., increase price or move capacity).
• Capacity: Based on the MMT and your average tractor productivity (dispatch miles per tractor per week), the FM Optimizer computes the optimal number of tractors to effectively handle the freight that was accepted in order to achieve the target margin threshold.

Coming Soon – Automatic Tour Identification

By the end of the year, the FM Optimizer will automatically identify potential “tours,” which are patterns of consistent freight, that can be connected together to create more efficient assignment of capacity.

KSMTA’s FreightMath Optimizer Transforms Logistics Analytics

The launch of the FreightMath Optimizer marks a significant milestone in KSMTA’s commitment to driving innovation in the transportation industry. By combining advanced analytics, sophisticated modeling, and proprietary algorithms, this tool offers a solution that is not just about optimizing routes but revolutionizing the way logistics companies operate. As KSMTA continues to push the boundaries of what is possible, the FreightMath Optimizer stands as a testament to the power of technology in unlocking new levels of efficiency, profitability, and sustainability in freight transportation.

To learn more or discuss any of the ideas shared above, please contact a KSMTA advisor or complete this form.