Shippers urged to take advantage of opportunities before the market flips
With demand cycles constantly shifting in the U.S. truckload market, Coyote Logistics, a global third-party logistics leader (3PL), today announced its “Coyote Curve” forecast model has identified the volatile market’s next inflection point and urges shippers to take advantage of opportunities in Q2 2019.
The company’s Coyote Curve analyzes three concurrent cycles – seasonal demand, annual procurement and more elusive market capacity – to help supply chain managers identify recurring patterns that can lead to better informed supply chain and logistics decisions.
“To remain competitive, companies must understand the forces that affect market shifts,” said Coyote Chief Strategy Officer Chris Pickett. “The market is vast, fragmented and dynamic, and market capacity cycles are often only visible in the rearview. From the Coyote Curve, we know seemingly sudden market shifts are moves-in-the-making several quarters in advance, and by comparing current cycle data to historical data, it can help forecast the trajectory of the market.”
With demand cycles constantly shifting in the U.S. truckload market, Coyote Logistics, a global third-party logistics leader (3PL), today announced its “Coyote Curve” forecast model has identified the volatile market’s next inflection point and urges shippers to take advantage of opportunities in Q2 2019.
The company’s Coyote Curve analyzes three concurrent cycles – seasonal demand, annual procurement and more elusive market capacity – to help supply chain managers identify recurring patterns that can lead to better informed supply chain and logistics decisions.
“To remain competitive, companies must understand the forces that affect market shifts,” said Coyote Chief Strategy Officer Chris Pickett. “The market is vast, fragmented and dynamic, and market capacity cycles are often only visible in the rearview. From the Coyote Curve, we know seemingly sudden market shifts are moves-in-the-making several quarters in advance, and by comparing current cycle data to historical data, it can help forecast the trajectory of the market.”
