Digital load matching: What is the real impact?
Digital load matching uses digital, app-based technologies to match customers’ needs in freight services with available truck capacity.
Ask any refrigerated food company about their top opportunities to improve operating expenses, and you’ll likely hear about their need to reduce transportation costs. One of the most talked-about means to do so is digital load matching, otherwise known as the “Uberization” of freight.
Digital load matching uses digital, app-based technologies to match customers’ needs in freight services with available truck capacity, dramatically reducing or even eliminating empty space on trailers and trucks. Much of this spot market freight is handled by “load boards,” featuring interactions—often by phone—among shippers, brokers, carriers and owner-operators.
Traditionally, this process has been fragmented, tedious and slow, and the outcome is not always ideal. There are plenty of missed opportunities and shippers left in need of capacity.
How digital load matching can help
In recent years, online and cloud-based load matching, specialized software and mobile apps have made it possible for trucks seeking freight to match up almost instantly with freight-seeking trucks. What has made digital load matching viable is the growth in vehicle connectivity.
Connected solutions, which started as telematics solutions enabling fleets to communicate with drivers, now provide detailed information on the health of the vehicle and its components. Increasingly, connected vehicles are also sharing data about the vehicle’s location and other factors, including driver availability that can be useful in figuring out opportunities for freight consolidation.
Zero tolerance for wait time
However, the trucking industry needs to ask itself whether digital load matching is really the “one-size-fits-all” answer to capacity issues, particularly the specialized and demanding needs of the refrigerated and frozen foods business.
An audit conducted by the inspector general’s office at the U.S. Department of Transportation, Washington, D.C., shows that unexpected wait time on loading docks is robbing truckers of more than a billion dollars of income each year. This is the problem commonly known as “detention time,” which industry contracts typically define as anything up to two hours of wait time for which drivers do not get paid.
The industry norm is that truckers are simply expected to wait for long periods of time for everything from loading and unloading their vehicles to sitting in a truck dealership waiting for a diagnosis of their truck. And, for every 11 driving hours available to a driver under the federal Hours of Service regulations, only an average of 6.5 hours are actually spent behind the wheel. This poses special requirements for the refrigerated and frozen food industry, where perishability is a real concern.
Use big data
The data from connected vehicles, which can certainly lend itself to digital load matching, can also be used in a more comprehensive way to dramatically improve vehicle uptime, and as a result, the on-time delivery of perishable goods.
By analyzing the increasing flow of “big data” coming from vehicles and their drivers, freight carriers should assure that perishable cargo is no longer subject to unplanned delays due to waiting at loading docks and other locations. Freight providers must be able to radically reduce the time needed for diagnosing and treating maintenance issues. Instead of accepting unplanned breakdowns as par for the course, companies should be able to convert most, if not all, maintenance into predictive, planned maintenance, where parts are replaced before they break down.
If fleets use data and other technology to work smarter, then operational efficiencies can be ironed out in virtually every aspect of fleet management. Fleets can use this data to optimize the supply chain to connect carriers and shippers, improve routing, reduce drivers’ idle time and increase truck utilization.
Used correctly, that information can also help fleets overcome larger structural challenges, such as the ever-present driver shortage. Reducing wait times and loading times has the potential to take 6-7% out of the supply chain in terms of both cost and time.
To hold down food costs, trucks and drivers need to be used efficiently. When data-driven fleets and the shippers who use them understand the true cost of unplanned delays, they will demand real solutions. “Big data” from the truck itself offers tremendous potential to match loads and improve every aspect of trucking operations.