Whether you’re a shipper, freight broker or motor carrier, freight matching is the linchpin of business profitability. Even minor mistakes are costly given the value of time and the expense of labor, fuel and equipment.
Traditionally, only businesses with significant IT resources and density in their freight networks would invest in advanced software to optimally match freight with capacity.
Recent developments have leveled the playing field, giving companies of all sizes new, affordable options that tap the power of machine learning and cloud computing to make better load planning decisions.
Optimization for carriers
Motor carriers are also using new cloud-based TMS systems with built-in optimization tools to make better freight matching decisions. Some of the systems are now tapping into machine learning technology.
Optym recently launched a web-based TMS for small to medium-sized truckload carriers. The system, Axele, builds on the company’s footprint in the less-than-truckload sector where it has been optimizing linehauls for more than a decade.
The company saw an opportunity to bring optimization technology to smaller fleets in the truckload sector to help them keep up with digital brokers who are “making it harder [for carriers] to make any money,” says Ronda Lewis, chief revenue officer of Optym.
The Axele TMS can evaluate and identify the most profitable loads for carriers in the spot market, she says. The system integrates with load boards to find freight combinations that will create the best profitability per day. The system accounts for rates, hours-of-service and other variables and integrates with electronic logging devices (ELD), she says.