The logistics industry has a massive coordination problem that is costing shippers, carriers and brokers a serious amount of time and money as they scramble for more reliability.
Shippers are doing their best to manage in the volatile market environment that characterizes the industry, but no single shipper is large enough to create true network efficiencies in a vacuum. In order to bring true coordination and collaboration to the transportation industry, the industry itself needs an overhaul. AI presents an opportunity to coordinate at scale and introduce reliability to the transportation industry.
The traditional request-for-proposal process nurtures an environment of volatility due to the last-minute, load-by-load contracting norms of the industry. Shippers spend significant time and talent executing annual RFPs based on current and projected market conditions that are based on imperfect data. When conditions fail to align with those projections, all parties are apt to abandon those agreements in favor of more competitive rates in the spot market, creating volatile capacity and budgets.
While RFPs sound like formal agreements, volume and capacity commitments are often unenforceable, leaving shippers and carriers scrambling in the spot market when the market shifts and RFPs fall apart. This leads to frustration, strained relationships and, over time, increased costs for shippers and lost revenue for carriers and brokers.
Leaf Logistics believes there is a better way to navigate the freight market by leveraging artificial intelligence and machine learning to coordinate and schedule freight well ahead of time. That is why the company has built a solution from the ground up using AI to introduce reliable transportation plans with enforceable, long-term contracting that brings business stability for shippers, brokers, and carriers alike. This AI model is applied to transportation data to identify and coordinate multi-shipper moves at scale that coordinate and eliminate empty miles.
Leaf Adapt is an analytics platform that uses AI to build intelligent freight contract portfolio plans that can adjust in real time to meet shippers’ changing business needs or shifting market conditions. The solution monitors market conditions, as well as each shipper’s transportation network data on an ongoing basis. Adapt then provides actionable insights and delivers a freight portfolio plan that captures cost savings up to 20% and locks in 100% tender acceptance.
“Leaf works with your existing team and tools to provide actionable recommendations throughout the year to proactively manage your changing truckload requirements,” according to the Leaf website.
A Portfolio Approach
Adapt leverages AI to extend a shipper’s transportation plan and allow them to hedge their transportation plan to navigate future market uncertainty. This is more important than ever as the past five years have shown that the existing RFP process and tools are unable to meet shifting capacity needs throughout the year.
Trained on data from more than 450 shippers representing $29B in annualized freight spend, Adapt identifies a portfolio of contracting solutions based on variable transportation needs. For example, a shipper may have year-long contracts on freight that moves with certainty week in, week out, while they require a three month contract on another subset of their volume to capture seasonality. Leaf secures in these contracts with committed transportation providers and locks in guaranteed rates and tender acceptance.
Leaf also deploys AI to identify and coordinate multi-shipper round-trips and continuous moves, creating more efficiency and cost savings. Additionally, Leaf established the first multi-shipper dedicated fleets across the country. These solutions are beneficial for both shippers and carriers, as they drive up profitability and predictability for both parties.
Leaf is driven by the belief that 90% of freight can be coordinated and scheduled weeks, months or even entire quarters ahead of time by using machine learning to coordinate and schedule across shipper and service provider networks.
“We think it is inevitable that the industry is going to schedule freight months or years in advance at some point in the future,” said Mark Shaughnessy, a leader at Leaf.
Leaf Adapt begins making that dream a reality. Shaughnessy credits the company’s ability to create and optimize this type of solution with its unique position in the industry.
“We have unique access to shipper datasets because of our business model as a secure, neutral platform that coordinates freight across an unlimited number of shippers and service providers,” Shaughnessy said.
While 3PLs and other service providers across the industry have attempted to create similar solutions, they inevitably run into data availability issues because of their inability to be truly neutral third parties. By positioning themselves outside the process of moving freight, Leaf has bypassed this issue by becoming a trusted neutral third party.
AI introduces an opportunity for transportation stability; however, it will take more than just technology to reshape the market. Both shippers and carriers must commit to walking away from the volatile free market model that dominates the space and stepping into a more collaborative future.
While the standard 48 hour freight contracting window can be tempting due to the perceived possibility of big wins, it also universally delivers big losses. Although the market is considered shipper-friendly right now, a turn is inevitable, and many leaders across the industry believe it will come sooner rather than later. With that in mind, now is the time for shippers to consider taking a less volatile approach to moving their freight. Planning and scheduling freight ahead of time with Leaf Adapt allows shippers to hedge their transportation plans and better navigate upcoming market shifts.
Even in today’s market, shippers currently partnering with Leaf have realized up to 20% savings when it comes to run rates, while also seeing better service performance, according to Shaughnessy.
At the same time, carriers and brokers working alongside Leaf gain a level of revenue reliability they have never seen before due to the company’s commitment to keep drivers moving with coordinated round trips and reliable long-term contracting. This increased asset utilization means truckers are driving more loaded miles and making more money. Leaf’s unique long-term committed contracting locks in those opportunities with a predictable schedule that gets more drivers home at night, leading to improved retention. In an industry that consistently struggles with sky high turnover rates, that is no small feat.
“Machine learning is giving the transportation industry the tools to build a resilient portfolio approach,” Shaughnessy said. “It’s an extension of your team, helping you do what you have always wanted to do: coordinate and gain budget and service certainty.”
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