Japanese wine lovers who uncorked a bottle of the new vintage of Beaujolais Nouveau on Nov. 17 had UPS Supply Chain Solutions to thank. To guarantee that the new vintage would be available on its official release date, the UPS division coordinated a complicated multistage move that stretched across two continents.
To get the 700,000 bottles to their destination on time, UPS Supply Chain Solutions chartered seven cargo aircraft to fly to Japan between Nov. 5 and 11. The planes took off from Vatry (in the Marne), Châteauroux (in the Indre) and Brescia (Italy), bound for the Japanese airports of Tokyo, Nagoya, Osaka and Fukuoka. From there, the cases were delivered to wine and spirit merchants in Japan. Though UPS has delivered the Beaujolais Nouveau in the past, it found this year's task to be particularly challenging. In total, it had to move 750 metric tons of wine from France to Japan in less than 72 hours. In 2004, it moved only 130 metric tons.
Warehouse automation vendor Locus Robotics marked the grand opening of its global headquarters facility in Wilmington, Mass., this week.
The state-of-the-art, 157,000 square-foot Locus Park facility “serves as the nexus for hundreds of Locus employees driving the company's mission to revolutionize global supply chains through advanced robotics solutions,” the company said in a statement Thursday.
The new headquarters boasts an expansive research and development, testing, and engineering space, and is home base to the firm’s nearly 200 New England area employees. The facility also handles all robotics manufacturing, shipping, and administration functions.
“Locus Park represents our commitment to innovation and our confidence in the future,” company CEO Rick Faulk said in the statement. “It's a launchpad for the next generation of robotics and AI solutions that will redefine warehouse efficiency and empower workforces worldwide. As we stand at the forefront of industrial automation, we're not just leading the industry but transforming it.”
Alongside the grand opening, Locus also celebrated surpassing four billion units picked across its customer deployments around the world.
Business leaders in the manufacturing and transportation sectors will increasingly turn to technology in 2025 to adapt to developments in a tricky economic environment, according to a report from Forrester.
That approach is needed because companies in asset-intensive industries like manufacturing and transportation quickly feel the pain when energy prices rise, raw materials are harder to access, or borrowing money for capital projects becomes more expensive, according to researcher Paul Miller, vice president and principal analyst at Forrester.
And all of those conditions arose in 2024, forcing leaders to focus even more than usual on managing costs and improving efficiency. Forrester’s latest forecast doesn’t anticipate any dramatic improvement in the global macroeconomic situation in 2025, but it does anticipate several ways that companies will adapt.
For 2025, Forrester predicts that:
over 25% of big last-mile service and delivery fleets in Europe will be electric. Across the continent, parcel delivery firms, utility companies, and local governments operating large fleets of small vans over relatively short distances see electrification as an opportunity to manage costs while lowering carbon emissions.
less than 5% of the robots entering factories and warehouses will walk. While industry coverage often focuses on two-legged robots, Forrester says the compelling use cases for those legs are less common — or obvious — than supporters suggest. The report says that those robots have a wow factor, but they may not have the best form factor for addressing industry’s dull, dirty, and dangerous tasks.
carmakers will make significant cuts to their digital divisions, admitting defeat after the industry invested billions of dollars in recent years to build the capability to design the connected and digital features installed in modern vehicles. Instead, the future of mobility will be underpinned by ecosystems of various technology providers, not necessarily reliant on the same large automaker that made the car itself.
This story first appeared in the September/October issue of Supply Chain Xchange, a journal of thought leadership for the supply chain management profession and a sister publication to AGiLE Business Media & Events’' DC Velocity.
For the trucking industry, operational costs have become the most urgent issue of 2024, even more so than issues around driver shortages and driver retention. That’s because while demand has dropped and rates have plummeted, costs have risen significantly since 2022.
As reported by the American Transportation Research Institute (ATRI), every cost element has increased over the past two years, including diesel prices, insurance premiums, driver rates, and trailer and truck payments. Operating costs increased beyond $2.00 per mile for the first time ever in 2022. This trend continued in 2023, with the total marginal cost of operating a truck rising to $2.27 per mile, marking a new record-high cost. At the same time, the average spot rate for a dry van was $2.02 per mile, meaning that trucking companies would lose $0.25 per mile to haul a dry van load at spot rates.
These high costs have placed a significant burden on the operations of trucking companies, challenging their financial sustainability over the last two years. As a result, 2023 saw approximately 8,000 brokers and 88,000 trucking companies cease operations, including some marquee names, such as Yellow Corp. and Convoy, and decades-long businesses, such as Matheson Trucking and Arnold Transportation Services.
More so than ever before, trucking companies need to get better at efficiently using their assets and reducing operational costs. So, what is a trucking company to do? Technology is the answer! Given the nature of the problem, technology-led innovation will be critical to ensure companies can balance rising costs through efficient operations.
One technology that could be the answer to many of the trucking industry’s issues is the concept of digital twins. A digital twin is a virtual model of a real system and simulates the physical state and behavior of the real system. As the physical system changes state, the digital twin keeps up with the real-world changes and provides predictive and decision-making capabilities built on top of the digital model.
DHL, in a 2023 white paper, suggests that—due to the maturation of technologies such as the internet of things (IoT), cloud computing, artificial intelligence (AI), advanced software engineering paradigms, and virtual reality—digital twins have “come of age” and are now viable across multiple sectors, including transportation. We agree with this assessment and believe that digital twins are essential to radically improving the processes of fleet planning and dispatch.
THE NEED TO AUTOMATE
Outside of attaining procurement efficiencies, trucking companies can achieve lower costs by focusing on critical operational levers such as minimizing deadheads, reducing driver dwell time, and maximizing driver and asset utilization.
However, manual methods of planning and dispatch cannot optimally balance these levers to achieve efficiency and cost control. Even when planners work very hard and owners strive to improve processes, optimizing fleet planning is not a problem humans can solve routinely. Planning is a computationally intensive activity. To achieve fleet-level efficiencies, the planner has to consider all possible truck-to-load combinations in real time and solve for many operational constraints such as drivers’ hours of service, customer windows, and driver home time, to name just a few. These computations become even more complex when you add in the dynamic nature of real-world conditions such as trucks getting stuck in traffic or breaking down or orders getting delayed. This is not a task humans do best! For these sorts of tasks, technology has the upper hand.
When a company creates a digital twin of its trucking network, it has a real-time model that factors in truck locations, drivers’ hours of service, and loads being executed and planned. Planners can then use this digital model to assess possible decisions and select ones that increase asset utilization, improve customer and driver satisfaction, and lower costs.
For example, a digital twin of the network can offer significant insights and analysis on the state of the network, including exceptions such as delayed pickups and deliveries, unassigned loads, and trucks needing assignments. Backed by AI that takes business rules into account, digital twins can allow companies to optimize their fleet performance by finding the most efficient load assignments and dynamically adjusting in real time to changes in traffic patterns and weather, customer delays, truck issues, and so on.
With a digital twin, carriers can optimize the matching of assets, drivers, and freight. Typically, an investment in this innovative technology results in a 20%+ increase in productive miles per truck, while also improving driver pay and significantly decreasing driver churn. Drivers get paid by the miles they run, so when they run more, they are able to make more money, resulting in less need to chase the next job in search of better pay.
ADDITIONAL BENEFITS
Digital twins also combat deadheading, another source of driver dissatisfaction and cost inefficiencies. On average, over-the-road drivers spend 17%–20% of road miles driving empty. Using a digital twin, a company can search across several freight sources to find a load that perfectly matches the deadhead leg without impacting downstream commitments. These additional revenue miles will help drivers to maximize their earnings on the road and carriers to maximize their asset utilization and profitability.
The traditional manual dispatch planning model is becoming increasingly outdated—each planner and fleet manager tasked with overseeing 30 to 40 vehicles. Carriers try to manage this problem by dividing the fleet into manageable chunks, which results in cross-fleet inefficiencies. Such a system isn’t scalable. A digital twin acts as an equalizer for small and mid-sized fleets. It enables carriers to expand by venturing beyond the fixed routes and network they were forced to run out of fear of additional logistical complexity.
A digital twin can also give an organization the transparency and visibility it needs to find and fix inefficiencies. A successful carrier will leverage the technology to learn from the hitches in its operations. While this visibility is beneficial in its own right, it also provides the first step toward a seamless, digitized operation. “Digital revolution” is a buzzword frequently heard at transportation conferences. Yet not too many organizations are dedicated to digitizing their operations past the visibility stage. The end goal should be using decision-support systems to automate key elements of the system, thus freeing up planners from their daily rote tasks to focus on problems that only humans can solve.
Finally incorporating a digital twin can also help trucking companies work toward the broader trend of creating greener supply chains. Because they have lower deadhead and dwell times, trucking companies that have adopted a digital twin can be more attractive to shippers that are looking for more efficient operations that meet their environmental, social, and governance (ESG) goals.
THE FUTURE IS HERE
It is important to note that the benefits described here are not dreams for the future; digital twin technology is already here. In fact, choosing a digital twin can seem daunting because there are already a spectrum of options out there. First and foremost, an organization must ensure that the digital twin it selects aligns with both the goals and the scope of its operation.
Additionally, the ideal digital twin should:
Operate in near real time. A digital twin should be able to refresh as often as the network changes.
Be able to factor in specific customer delivery requirements as well as asset- and operator-specific constraints.
Be computationally efficient and comprehensive as it considers thousands of permutations in milliseconds. The digital twin should be able to reoptimize an entire fleet’s schedule of multi-day routes on the fly.
Before implementing a digital twin, carriers need to make sure that they have robust data management processes in place. Electronic logging devices (ELDs), customers’ tenders, billing, shipments, and so on are already inundating carriers with a glut of data. However, the manual nature of operations in many carriers leads to poor data quality. Carriers will need to invest in data management approaches to improve data quality to support the generation and use of high-fidelity digital twins. Otherwise, the digital twin will not be representative of reality and companies will run into an issue of “garbage in, garbage out.”
REINVENTION AND TRANSFORMATION
While data management is critical, change management through the ranks of dispatch operations is often a harder task. In fact, the largest roadblock carriers face when undergoing a digital transformation is the lack of willingness to change, not the technology itself. Many carriers cling to outmoded planning methods. Planners, used to operating based on well-worn business rules and tribal knowledge, could be wary of the technology and resistant to change. They may need to be assured that, while it is true that every trucking network is uniquely complex, digital twins can be set up to model the intricacies of their specific dispatch operations and drive value to the network. A significant amount of time and resources will need to be expended on change management. Otherwise even though trucking companies may invest in cutting-edge technology, they won't be able to fully capitalize on the added value it can provide.
As the truckload industry works through the current freight cycle, it is important to realize that change is inevitable. Carriers will need to reinvent their operations and invest in technologies to ride through the busts and booms of future freight cycles. Recent global events point to the many ways that wrenches can be thrown into global transportation networks, and the fact that such volatility is here to stay. Digital twins can provide companies with the visibility to navigate such changes. But above all, an operation that uses the digital twin to drive decisions can make customers and drivers happy, and help the carriers keep their heads above water during times such as now.
Regular online readers of DC Velocity and Supply Chain Xchange have probably noticed something new during the past few weeks. Our team has been working for months to produce shiny new websites that allow you to find the supply chain news and stories you need more easily.
It is always good for a media brand to undergo a refresh every once in a while. We certainly are not alone in retooling our websites; most of you likely go through that rather complex process every few years. But this was more than just your average refresh. We did it to take advantage of the most recent developments in artificial intelligence (AI).
Most of the AI work will take place behind the scenes. We will not, for instance, use AI to generate our stories. Those will still be written by our award-winning editorial team (I realize I’m biased, but I believe them to be the best in the business). Instead, we will be applying AI to things like graphics, search functions, and prioritizing relevant stories to make it easier for you to find the information you need along with related content.
We have also redesigned the websites’ layouts to make it quick and easy to find articles on specific topics. For example, content on DC Velocity’s new site is divided into five categories: material handling, robotics, transportation, technology, and supply chain services. We also offer a robust video section, including case histories, webcasts, and executive interviews, plus our weekly podcasts.
Over on the Supply Chain Xchange site, we have organized articles into categories that align with the traditional five phases of supply chain management: plan, procure, produce, move, and store. Plus, we added a “tech” category just to round it off. You can also find links to our videos, newsletters, podcasts, webcasts, blogs, and much more on the site.
Our mobile-app users will also notice some enhancements. An increasing number of you are receiving your daily supply chain news on your phones and tablets, so we have revamped our sites for optimal performance on those devices. For instance, you’ll find that related stories will appear right after the article you’re reading in case you want to delve further into the topic.
However you view us, you will find snappier headlines, more graphics and illustrations, and sites that are easier to navigate.
I would personally like to thank our management, IT department, and editors for their work in making this transition a reality. In our more than 20 years as a media company, this is our largest expansion into digital yet.
We hope you enjoy the experience.
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In this chart, the red and green bars represent Trucking Conditions Index for 2024. The blue line represents the Trucking Conditions Index for 2023. The index shows that while business conditions for trucking companies improved in August of 2024 versus July of 2024, they are still overall negative.
FTR’s Trucking Conditions Index improved in August to -1.39 from the reading of -5.59 in July. The Bloomington, Indiana-based firm forecasts that its TCI readings will remain mostly negative-to-neutral through the beginning of 2025.
“Trucking is en route to more favorable conditions next year, but the road remains bumpy as both freight volume and capacity utilization are still soft, keeping rates weak. Our forecasts continue to show the truck freight market starting to favor carriers modestly before the second quarter of next year,” Avery Vise, FTR’s vice president of trucking, said in a release.
The TCI tracks the changes representing five major conditions in the U.S. truck market: freight volumes, freight rates, fleet capacity, fuel prices, and financing costs. Combined into a single index, a positive score represents good, optimistic conditions, and a negative score shows the opposite.