Truckload freight demand ebbs and flows in two to three-year cycles. When the market is up, truck orders increase as forward growth assumptions, based on increasing rates, signal incoming revenue. Often in the time between new truck and trailer orders and delivery, the market starts to turn. As this excess capacity fails to find volume, freight rates decrease, accelerating a downward trend. 

Freight contracts, meanwhile, are negotiated annually. They were intended to serve annual budgets and address seasonality; a one-year term is long enough to suggest a stable revenue stream for carriers and a stable cost structure for shippers. But they don’t serve that purpose because freight and contract cycles are not aligned. Without clearer demand visibility, predicting shifts is difficult: There are no long-term contracting or hedging products for transportation in the futures markets as there are for fuel, electricity or metals.

Trucking in the U.S. is a fragmented $875 billion annual market of more than 1 million owner-operators, 90% of whom operate 10 or fewer trucks. The sheer market size, fragmentation, and low barriers to entry into the market feeds a massive and highly competitive spot market that often undercuts contract stability.

The freight contracting process further encourages short-term thinking. Contracts are usually initiated by freight tender requests for proposals (RFPs) intended to encourage competitive bidding, mainly on price. Freight bookings made under this contracting method are typically transactional, one load at a time and loads are tendered to secure a truck only 24-48 hours in advance, overlooking opportunities for planning or collaboration over longer-term or subsequent contracts.

Roughly every two years the freight cycle shifts mid-contract. With relatively low demand visibility in transportation to allow the same hedging capability in future markets as for fuel, electricity or metals, shippers and carriers have written flexibility into contracts allowing them room to maneuver when markets turn. Once that happens, the party with risk exposure — truckers when rates are rising, shippers when they’re falling — rushes to the spot market. As a result, when the market favors carriers, tender acceptance falls and capacity decreases, sending rates soaring. When the market favors shippers, the market is flooded with capacity and shippers are able to capture savings by securing low rates.

The Wrong Incentives, at the Wrong Time

Talk of opportunities for collaboration, common at industry conferences, mostly dissolves as contracts come up for renewal, especially for large firms with complex supply chains. “It’s a budget-cost problem if I’m Coca-Cola and every two to three years I suddenly run $220 million over budget on transportation,” explains Anshu Prasad, co-founder and CEO of New York-based freight coordination platform Leaf Logistics. “There’s a procurement team that’s supposed to go out there and beat everybody up for rate concessions, a service team that gets called to the mat weekly or monthly because Walmart’s not happy about service, a chief supply chain officer who says it’s absolutely necessary to spend $100 million to keep Walmart happy — there’s always a cost-service trade off, and anything cheaper than what I have today is better. It’s reflexive.”

The spot market plays into this sentiment, especially in years when a freight cycle is seen as likely to turn mid-contract. But it’s not an option that either shippers or truckers prefer. “The spot market cycle is wildly volatile, with rates moving plus or minus 35-45% in a given year,” says Chris Pickett, an independent industry researcher and also chief operating officer of Encinitas, California, shared truckload platform Flock Freight, which matches loads to available empty backhaul, LTL or other capacity in the field for multi-stop delivery. “Any shipper of meaningful size and contractable freight is sure to be exposed to that volatility and is out there trying to source capacity more consistently.”  

Truckers need similar certainty in an environment where anyone with a license, operating authority, a leased truck, and a smartphone can compete for the same business. Those in it for the long haul want stable rates and revenues over longer time periods; full truckloads, including on return trips; full, predictable hours of service and more time at home. All of these things are not only good for business, but for attracting and retaining new drivers.

Rewriting the Contract

So, what’s the answer? Companies have tried various fixes to conventional contracts, such as shorter-duration, quarterly or seasonal mini-bids and variable rates, with mixed results. At some point, more frequent bidding isn’t the answer – it encourages even shorter-term thinking from shippers and carriers.   

Recent advances in freight technology suggest a different way forward for contracting, with help from artificial intelligence (AI) and machine learning (ML). By connecting shippers and carriers across the transportation industry, freight coordination platforms optimize loads and trips over time to improve utilization and eliminate empty miles. These efforts allow shippers to achieve cost reduction and secure reliable service, as carriers see improved utilization and stable revenues, while the transportation industry lowers its carbon footprint. Pickett notes that this can be done primarily by neutral service providers balancing lanes to build round trips on specific corridors, or by load matching; for example, filling empty returns or underutilized LTL space on individual trucks. Then, he says, long-term contracts can be secured to meet the needs of both parties, with the flexibility to scale up or down based on changing business needs or market shifts. 

“Where there’s a trusted exchange, as there is with corn,” Prasad says, “I trust that the price of corn is correct, that you or I will pay the same price for corn, and ADM or Cargill can sell corn at fair, transparent prices. If trucking had that we would all start behaving differently.”

Prasad offers examples of two client companies on the Los Angeles-Phoenix corridor, one is a leading beverage maker and the other is a packaging manufacturer. The beverage maker has a brewery in Los Angeles, and the packaging manufacturer has a manufacturing facility outside of Scottsdale. Both have similar demand patterns for trucking between the two cities. “We’re using machine learning to understand predictable patterns of demand across the network, and then help them plan, schedule and coordinate,” he says. In this case, it was determined that as much as two-thirds of combined LA-Phoenix freight, which was being independently transacted with different carriers, could be jointly planned in a round trip. 

Machine learning analytics and modeling can help with structuring and even managing the contract; with volume and rates assured in advance, parties avoid the adversarial RFP and bid process; full round trips simplify scheduling for motor carriers and offer more predictable hours for drivers, in a market where 30% of truck trips are now empty.   

The search for certainty

The beverage maker had been looking for a better approach to contracting and their director of procurement and sustainability began grappling with the cyclical volatility question shortly after joining the company in 2016, working across functions with internal divisions to find innovative, data-driven solutions.

The director of transportation at the beverage maker shared that they had spoken with carriers and learned that they were trying to manage the same peaks and troughs. At the time, in 2016, a lot of the new carriers entered the market, leaving small mom-and-pop operations unsure of where they were in the freight cycle. Similar challenges cropped up on the shipper side, with high turnover, changing roles and responsibilities, and a lack of clear accountability.

The manufacturer also had its own unique set of service constraints. With limited on-site storage for its products, it relied on precise scheduling and distribution patterns to deploy trailers as moving warehouses. The strategy prevented working with brokers, in turn limiting its available pool of carriers. On-time arrivals and deliveries were crucial; having carriers that suddenly rejected tenders or demanded rates above contract levels as the market shifted was a non-starter.

“For shippers, there’s a balance in the market between total cost, service level, and predictability,” Prasad says. “Customers can be made aware that they need a greater level of sophistication to see that and to make better decisions in how they allocate business — using data analytics in the buying decision to drive the right behaviors going forward, and also rewarding carriers showing greater compliance to contract and higher service level performance.”

The beverage manufacturer looked at various approaches for mapping seasonality over time and building incentives premiums into the contract to assure reliable service and reduce exposure to spot. It considered hedging options, integrating AI into its transportation management system (TMS) to build dynamic rate trees from live data, “shoulder bids” within a contract year to smooth out seasonal peaks and troughs, even universal trailer pools. It soon became apparent that all of these solutions, at their heart, in some way or to some degree relied on multi-party data generated and shared within a network — a capability that was largely unavailable at scale less than a decade ago, prior to cloud computing and digital platforms.

“Without these platforms to create strong networks between shippers and truckers, you see huge inefficiencies in the system and in decision-making,” Prasad maintains. “Think about the sheer size and number of carriers and shippers in the market, all of the empty backhaul miles on the road, the amount of loss occurring that isn’t making money for the driver, that shippers and carriers pay for in their operations, the fuel and emissions burned to essentially move air. The more visibility you can create in the network, the better for shippers, carriers, the supply chain, and the planet.”

Technological advances over the past 5 to 10 years — most recently AI and ML — are moving shippers steadily in the direction of innovations like dynamic pricing, long-term committed contracting, universal trailer pools and, ultimately, a fully automated bid process tailored to partners’ defined aggregate business. When that will become a reality is a chicken-and-egg question of ML perfecting data generated by a critical mass of networked supply chain partners.

Pickett believes change will be incremental and that annual contracts and RFP bids will remain in place “barring any material innovation from a technology standpoint or radical change from a regulatory standpoint” because they serve shippers’ annual budgeting and planning needs, and because low barriers to entry and economies of scale in resisting consolidation support a fragmented, chaotic spot market. The bright spot he sees is that “as technology improves, as forecasting improves, and as procurement processes improve, new constructs will arise that create more flexibility in the nature of contracts.”   

Prasad sees a future where 90% of all freight is planned, scheduled and coordinated ahead of time. Using an AI and ML-based approach, shippers and carriers will have better visibility and predictability into their costs and revenues to keep their businesses stable and reduce the impact of the transportation market’s volatile swings.

“The transportation industry treats each load as an emergency, with little-to-no line of sight into which carrier will be moving the next load and how much it will cost. On top of this, there is enormous waste in the form of empty miles from a lack of multi-party coordination,” he says. “When we coordinate and schedule ahead of time, the effects of the freight market cycle become outside noise. We’ve all looked at coordination and enforceable contracting once or twice in our careers, we know there’s a business case, but end up saying ‘Please, God, let me get back to my day job!’”

Now with state-of-the-art solutions, this is becoming a reality for customers. For now, Prasad will settle for 30% to 60% potential efficiency gains and cost reductions in trucking, which he says are doable and, by current standards, “would be amazing.”

Resource Link: www.leaflogistics.com