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Friday, November 15, 2024
Logistics

Optimizing logistics management with quantum computing

The supply chain industry has been steeped in manual operations for years, relying heavily on pen-and-paper systems. Yet as customer demands evolve, this old-fashioned approach is proving increasingly inadequate. The industry is rapidly modernizing, and automation and data-driven insights are replacing outdated methods.

Parcels and containers traveling through the supply chain from origin to destination generate vast quantities of data. As the industry continues to digitize operations, it’s grappling with effectively utilizing this data to its full advantage.

Several factors are causing this challenge. Among the most significant is the difficulty in disseminating specialized industry knowledge that exists solely in the expertise of industry professionals, thereby restricting the collective sharing of vital insights.

“The big challenge is how do I get that [data] out of a person’s head and into a format where I can actually use it,” said Sean Tinney, VP of global enterprise computing solutions at Unisys.

A second challenge comes from evolving customer expectations. Elevated by large e-commerce businesses, consumers now expect on-time delivery, real-time tracking and a seamless user experience from all companies, regardless of size. Tinney says the key to meeting these expectations is the skillful use of supply chain data.

For decades, Unisys has been facilitating connections between its air cargo partners and various logistics players such as freight forwarders, 3PLs, 4PLs and ocean carriers, all while meeting escalating service demands. Now, Unisys combines industry knowledge and deep experience with cutting-edge technology to launch Unisys Logistics Optimization. This solution merges industry expertise with advanced technology to tackle some of the most stubborn bottlenecks during the critical last mile of shipping.

The last leg of the freight journey presents a multitude of variables — from building a pallet to loading it successfully onto a plane while considering important details such as temperature and weight distribution. Unisys tackles these challenges by leveraging the combination of artificial intelligence, advanced analytics and quantum computing. This multifaceted approach aids logistics organizations in refining inventory storage locations, planning pallet configurations and determining the most efficient parcel delivery routes. The net effect is a reduction in claims, fewer product damages and a decrease in the overall inventory carrying costs.

In the often unpredictable world of logistics, expert logistics professionals can problem-solve on the spot to readjust freight and get the shipment moving. But this can sometimes result in suboptimal operations, such as space left on the truck or a pallet half-filled, leaving money on the table and increasing a business’ cost base. Unisys’ solution also helps shippers dynamically readjust to these everyday inefficiencies with the help of quantum computing.

“When something goes wrong, and you have to crunch thousands upon thousands of potential scenarios instantaneously, the introduction of quantum computing can power those models and allow someone to get the best answer of what they should do, whether it’s putting on another package, sending it out three-quarters full based on where it’s going. It becomes a key component of this solution,” Tinney explained.

By integrating artificial intelligence, advanced analytics and quantum computing, Unisys Logistics Optimization enables almost instantaneous decisions, leading to significant reductions in time and expenses throughout the supply chain. This solution benefits airlines, freight forwarders and ground handlers, offering enhanced operational processes, revenue efficiency and reduced environmental impact.

Ready to embrace the future of logistics management? Learn more about Unisys and join FreightWaves and Unisys for a webinar on Nov. 30. Details will be coming soon.

The post Optimizing logistics management with quantum computing appeared first on FreightWaves.

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