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We’ve all heard the transportation market is cyclical, right? Years are marked as “shipper” or “carrier” markets. Transportation and procurement teams are judged on how well they leverage shipper friendly years. Recent developments in transportation management have started to help take cost of out the equation rather than trade it back and forth from carrier to shipper and reverse. Much of this innovation relies on process improvement and removal of waste. Two of the most promising technologies are the digitization of freight brokerage and the use of AI and Machine learning.

Digital Brokerage

Digital brokerages have several advantages over their older, labor intensive competitors. While Uber Freight and Convoy are players that have been at it for the last few years, JB Hunt, XPO and CH Robinson are also making significant capital investments in their brokerage platforms to more closely manage the digital pioneers.

On advantage of digital brokerage is speed. App based coverage systems bypass the assignment to broker, “dialing for diesel”, and other manual steps that can keep freight out of the carrier’s visibility. This speed can help freight get covered faster and at better cost.

Another big payoff in the usage of the digital broker model is the ability for very large shippers to engage with very small carriers. Many of the smallest carriers (1-5 trucks) are still operating via phone (or gasp…fax). 

These newer app- based load boards help the small business owners find freight to increase utilization, but they also open them up to more opportunities by acting as a middle man and handling the EDI connections and other costs that would prevent the carriers from hauling for a more sophisticated shipper. Beyond that, many digital brokers assist carriers getting tires, fuel and repairs.

Recent Developments in Transportation Management Have Started To Help Take Cost Out Of the Equation Rather Than Trade It Back And Forth from Carrier to Shipper and Reverse

All of this niche freight coverage, carrier loyalty programs, and speed allow carriers to haul more freight with less non-revenue moves, truly taking costs out beyond a hard procurement negotiation.

AI and Machine Learning

Artificial intelligence could be the most game changing technology in transportation right now. Using machine learning to form algorithms to find continuous loops or other multiple leg routes captures capacity and the utilization gain removes waste and therefore cost.

It’s important to find a partner you can trust to help implement this kind of initiative. Several of the carriers above and some Transportation 3PLs have working models at various stages of maturity. Partnering combines several transportation networks and grows the opportunity. Trust is required because the logic works best when there are fewer restrictions placed upon the technology.

While working best unrestricted, careful consideration should be given to how to balance offering freight to the most optimal carrier when you have already made commitments to carriers in a bid. Implementation of this kind of logic should be rolled out in concert with a bid award, identifying a percentage that should be left to AI to manage, while keeping your commitments to your carrier base. Running the logic alongside current operation will help in identifying the best lanes for the next contract cycle.

Sharing Gains vs. Negotiating

The reductions in cost associated with the technology described here are true net reductions. Most are related to the reduction of waste – miles and time. These savings should prove to be cycle- proof. The object of the game regarding transportation procurement is to flatten the wave of carrier vs. shipper market swings. Using technology to improve processes and eliminate waste flattens that curve because, instead of there being a “losing” party, both partners are sharing a true reduction in cost.