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Brian George is vice president of sales at Petrageous Designs, which designs and sells pet clothing and feeding products, such as dog and cat bowls and water dishes.
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Keith Moore is CEO of AutoScheduler.AI, a warehouse resource planning and optimization platform that integrates with a customer's warehouse management system to orchestrate and optimize all activities at the site. Prior to venturing into the supply chain business, Moore was a director of product management at software startup SparkCognition. He is a graduate of the University of Tennessee, where he earned a Bachelor of Science degree in mechanical engineering.
Q: Autoscheduler provides tools for warehouse orchestration—a term some readers may not be familiar with. Could you explain what warehouse orchestration means?
A: Warehouse orchestration tools are software control layers that synthesize data from existing systems to eliminate costly delays, streamline inefficient workflows, and [prevent the waste of] resources in distribution operations. These platforms empower warehouses to optimize operations, enhance productivity, and improve order accuracy by dynamically prioritizing work continuously to ensure that the operation is always running optimally. This leads to faster trailer turn times, reduced costs, and a network that runs like clockwork, even during fluctuating demands.
Q: How is orchestration different from a typical warehouse management system?
A: A warehouse management system (WMS) focuses on tracking inventory and managing warehouse operations. Warehouse orchestration goes a step further by integrating and optimizing all aspects of warehouse activities in a capacity-constrained way. Orchestration provides a dynamic, real-time layer that coordinates various systems and processes, enabling more agile and responsive operations. It enhances decision-making by considering multiple variables and constraints.
Q: How does warehouse orchestration help facilities make their workers more productive?
A: Two ways to make labor in a warehouse more productive are to work harder and to work smarter. For teams that want to work harder, most companies use a labor management system to track individual performances against an expected standard. Warehouse orchestration technology focuses on the other side of the coin, helping warehouses "work smarter." Warehouse orchestration technology optimizes labor by providing real-time insights into workload demands and resource availability based on actual fluctuating constraints around the building. It enables dynamic task assignments based on current priorities and worker skills, ensuring that labor is allocated where it's needed most, even accounting for equipment availability, flow constraints, and overall work speed. This approach reduces idle time, balances workloads, and enhances employee productivity.
Q: How can visibility improve operations?
A: Due to the software ecosystem in place today, most distribution operations are highly reactive environments where there is always a "hair on fire" problem that needs to be solved. By leveraging orchestration technologies, this problem is mitigated because you're providing the site with added visibility into the past, present, and future state of the operation. This opens up a vast number of doors for distribution leadership. They go from learning about a problem after it's happened to gaining the ability to inform customers and transportation teams about potential service issues that are 24 hours away.
In the fallout from the pandemic, the term “omnichannel” seems both out of date and yet more vital than ever, according to a study from consulting firm EY.
That clash has come as retailers have been hustling to adjust to pandemic swings like a renewed focus on e-commerce, then swiftly reimagining store experiences as foot traffic returned. But even as the dust settles from those changes, retailers are now facing renewed questions about how best to define their omnichannel strategy in a world where customers have increasing power and information.
The answer may come from a five-part strategy using integrated components to fortify omnichannel retail, EY said. The approach can unlock value and customer trust through great experiences, but only when implemented cohesively, not individually, EY warns.
The steps include:
1. Functional integration: Is your operating model and data infrastructure siloed between e-commerce and physical stores, or have you developed a cohesive unit centered around delivering seamless customer experience?
2. Customer insights: With consumer centricity at the heart of operations, are you analyzing all touch points to build a holistic view of preferences, behaviors, and buying patterns?
3. Next-generation inventory: Given the right customer insights, how are you utilizing advanced analytics to ensure inventory is optimized to meet demand precisely where and when it’s needed?
4. Distribution partnerships: Having ensured your customers find what they want where they want it, how are your distribution strategies adapting to deliver these choices to them swiftly and efficiently?
5. Real estate strategy: How is your real estate strategy interconnected with insights, inventory and distribution to enhance experience and maximize your footprint?
When approached cohesively, these efforts all build toward one overarching differentiator for retailers: a better customer experience that reaches from brand engagement and order placement through delivery and return, the EY study said. Amid continued volatility and an economy driven by complex customer demands, the retailers best set up to win are those that are striving to gain real-time visibility into stock levels, offer flexible fulfillment options and modernize merchandising through personalized and dynamic customer experiences.
Geopolitical rivalries, alliances, and aspirations are rewiring the global economy—and the imposition of new tariffs on foreign imports by the U.S. will accelerate that process, according to an analysis by Boston Consulting Group (BCG).
Without a broad increase in tariffs, world trade in goods will keep growing at an average of 2.9% annually for the next eight years, the firm forecasts in its report, “Great Powers, Geopolitics, and the Future of Trade.” But the routes goods travel will change markedly as North America reduces its dependence on China and China builds up its links with the Global South, which is cementing its power in the global trade map.
“Global trade is set to top $29 trillion by 2033, but the routes these goods will travel is changing at a remarkable pace,” Aparna Bharadwaj, managing director and partner at BCG, said in a release. “Trade lanes were already shifting from historical patterns and looming US tariffs will accelerate this. Navigating these new dynamics will be critical for any global business.”
To understand those changes, BCG modeled the direct impact of the 60/25/20 scenario (60% tariff on Chinese goods, a 25% on goods from Canada and Mexico, and a 20% on imports from all other countries). The results show that the tariffs would add $640 billion to the cost of importing goods from the top ten U.S. import nations, based on 2023 levels, unless alternative sources or suppliers are found.
In terms of product categories imported by the U.S., the greatest impact would be on imported auto parts and automotive vehicles, which would primarily affect trade with Mexico, the EU, and Japan. Consumer electronics, electrical machinery, and fashion goods would be most affected by higher tariffs on Chinese goods. Specifically, the report forecasts that a 60% tariff rate would add $61 billion to cost of importing consumer electronics products from China into the U.S.
In his best-selling book The Tipping Point, journalist and author Malcolm Gladwell describes the concept of a tipping point as "that magic moment when an idea, trend, or social behavior crosses a threshold, tips, and spreads like wildfire."
In the warehousing and freight transport world, that definition could very easily apply as well to the rise of artificial intelligence (AI) and its rapid infiltration into just about every corner of the technological ecosphere. That's driving an accelerating evolution in transportation management systems (TMS), those tech platforms that do everything from managing rates, finding trucks, and optimizing networks to booking loads, tracking shipments, and paying freight bills. They are incorporating AI tools to help shippers and carriers work smarter, faster, and better than ever before.
"Twenty years ago, we could not build [and operate] software with the capacity to store and access huge caches of historical information and data and calculate [things like] 10-dimensional optimization," recalls Pawan Joshi, chief strategy officer for e2open, a leading developer of transportation management software. "We didn't have the data or the computing resources to build these decision-making models." With the advent of artificial intelligence and the extremely powerful computing resources behind it, "now we have the computing power with the speed to do it."
Srini Rajagopal, vice president of logistics product strategy for Oracle, sees AI as just the latest step in the continuing journey of maturity and innovation in the TMS space. He breaks the development of AI into two parts. "The first is the standard, classic AI model. These support specialized [computing and analytics] models built for specific purposes," such as developing optimization and consolidation plans, routing or ETA predictions for trucking, or cycle-time predictions for warehouses.
The next step is "generative AI, which has come about because of the maturity of the large language models (LLMs) now available," he explains. This development allows the software to interact with users in a natural language format, creating new opportunities for task automation in the typical cycle of transportation planning, execution, and exception management.
"What we use that for is [to give the model] the ability to interact [with a user] in a natural language format and then do reasoning about what actions to take [based on the user's input]."
He cites as one example the returns process, where typically a customer service agent will engage with a customer and answer questions over the phone. "The AI agent can take over a lot of that role, responding to the customer's questions by voice and making recommendations based on the user's input." That frees up time for the human agent, who now may have to intervene only with a small portion of questions that the AI agent cannot handle. "Now the human agent has more time to focus on other, more complex or higher value-added tasks," he notes.
Yet even with the advent of more advanced and sophisticated machine learning algorithms and artificial intelligence taking on more complex tasks, at the end of the day, "when it comes to execution, that's where the rubber meets the road," says Oracle's Rajagopal about the principal role of a TMS and the realizable and measurable results it can provide. That should be the priority, he notes: Value measured, quantified, and validated across numerous metrics—whether it's lower operating costs; more efficient, less error-prone processes; better transportation procurement; or optimized and more productive use of assets and people.
One shipper cites his rule of thumb for ROI (return on investment) as being "for every dollar spent on a TMS annually, it should return at least $2 in direct annual cost savings and/or productivity gains."
Those gains can be measured in a host of ways, notes Rajagopal. "It might be something as simple as billing accuracy," he says. "Are you getting paid accurately for your services, billing correctly, eliminating duplicate bills?" Then there are what he calls the "soft" benefits, such as user productivity and time savings from automating tedious, manual tasks. "Is your dispatcher or planner able to do more in a day with the new system?" he asks.
"ROI is all about knowing how you were doing before, quantifying the as-is state and what it costs you, and then, as you implement, measuring what it looks like in the new state and validating that you, in fact, got the savings expected."
Tom McLeod, president and chief executive officer of McLeod Software, has spent decades helping truckers and brokers use technology to work better, smarter, and more efficiently. Over those decades, he says, two demands from customers have remained constant: connectivity and visibility. "That's been an ongoing theme in technology development for our industry in the last 10 years," he notes.
He sees AI as a tool that will streamline the exchange of information between shippers and carriers, ultimately improving the executional accuracy and efficiency of the transportation planning and execution lifecycle.
One key foundational aspect of achieving that goal is integration and how effectively and seamlessly companies like McLeod and other TMS operators can help customers accomplish and maintain that. It's a continuing challenge that gets more complex but also is benefiting from technology advancements that make the task both simpler and faster to accomplish. "We have seen a real explosion of integration requests and requirements," McLeod says. "More and more companies are coming into the market providing information services, and the pace of change is accelerating."
McLeod's focus has been "to offer the … best integration to our customers so that they have a chance to compete. And to have an open platform that enables them to do so," he says, adding that "once it's complete, that process needs to be automated, with the information going where it's needed, and being accurate and reliable." And for the technology providers to be adaptable as the industry continues to change and new solutions come on the market.
McLeod supports this strategic imperative through its Certified Integration Partner program, which offers off-the-shelf, supported integration solutions for over 180 different trucking industry software products or services, from over 130 different companies.
Even with the advances in TMS platforms, in the trucking world, there are still "a lot of niche markets that require almost totally different services" as well as a lot of repetitive, manual tasks still waiting for automated solutions, says McLeod. He sees significant opportunities for TMS providers to help customers truly re-engineer their operations, addressing important metrics such as reducing deadhead miles, increasing revenue per mile, and getting more revenue per employee.
"It's not for the faint of heart," he adds. "As apps get more sophisticated, it is important for us to continue to handle more and more details, on a more automated basis. That's what carriers want and need to help them better serve their customers, keep costs in line, and compete."
Nevertheless, with all the promise of technology and the opportunities for AI to accelerate the shift to automation, "it is still a relationship business, between people who need to ship goods and those who provide the assets, resources, and expertise to do that," McLeod stresses.
"Even as routine transactions are automated, when it is crunch time and there is a problem, people still want to have someone on the other end they can reach out to, that they know and trust," he says. "Technology cannot get in the way of strengthening those relationships—or replacing them. It must support and facilitate that."
As the nation's largest broker and freight forwarder, C.H. Robinson (CHR) has a view of the market—and the role of technology in it—that could certainly be considered informed. With integrated management services that touch every mode of transportation, both nationally and globally, the company has a deep view into the needs and wants of shippers worldwide—and how technology can address those needs.
One recurring theme among CHR's customers, says Jordan Kass, CHR's president of managed solutions, is "shippers are not looking for a point solution anymore. They don't like the idea of a patchwork quilt. They want one pane of glass [through which] they can see and control their entire supply chain," he notes, adding that over 50% of CHR's revenues come from customers who use both its forwarding and surface transportation management capabilities, across modes.
He believes that is a function of shippers who are stressed to the max, are coping with a shortage of supply chain talent, "and are being asked to do much more with much less." For CHR, he cites as a key advantage its proprietary TMS—which is both global and multimodal—and an engineering team that continually works to improve and expand its capabilities. He also believes the advent of AI will be incredibly transformative for the industry.
"Because we are building [the TMS] and using it at the same time, we have a really unique and valuable eye into how it performs and what customers want and need. As we operate the platform, we identify use cases with our customers and then go to our engineering team to build a solution," he notes.
Kass says CHR's technology approach as a builder and operator of its TMS gives it a unique look into "how transformative AI can be in this space and how we can lean into some of the larger problems that shippers are dealing with."
As one example, he cites CHR's development and implementation of "touchless" appointments for freight pickup and delivery. "If you think back, making a [pickup or delivery] appointment used to take multiple tries [with phone calls, texts, and emails], and it sometimes required more than a day to get that appointment in place," he recalls. With its AI-driven process, "now we are doing that in under two seconds, greatly enhancing the speed of that process and adding huge value to it."
CHR has data on 35 million shipments a year, Kass says. That data informs the AI engine, which in determining the ideal appointment time, will consider things like patterns in transit time along a route, on-time performance, and dwell time at a facility. It will even take into account what's ideal for the carrier.
For example, Kass says "carriers in South Dakota need a longer time to get to the point of origin because they're typically traveling farther, so a 6 a.m. pickup appointment isn't good for them, while a 6 a.m. pickup appointment in an urban area might be great for a carrier because it can avoid traffic. The data [accounts for] these things better than a human can."
One area that TMS providers need to improve upon is predictive capabilities, Kass believes. With AI, "as you feed more data into the system, the more accurate you get." With that come more opportunities to expand the platform to automate and streamline tasks that continue to be done manually. It also helps the TMS get better at interacting in real time with transportation processes and accurately predicting outcomes. "We have the scale, and with AI, the more you feed it, the more intelligent it becomes."
Even with the inexorable march of technology, its permutations of AI, and its promise for positive change and automation that helps its human partners work smarter, faster, and better, in the end, it still comes down to cost—measuring and weighing what's being spent on the TMS against the operational cost savings and productivity being realized.
"The shipper's main concern is still cost," says Bart De Muynck, principal at consulting firm Bart De Muynck LLC. "That comes from a couple of areas. One is to better optimize the freight spend. Second [is to] put in a better process for the shipper to tender freight to the carrier and for the carrier to [handle] that freight in the lowest-cost manner possible. [Yet another is to obtain] transparency, providing better insights into how the shipper is procuring capacity so shippers end up with reliable, quality capacity at the most affordable rates."
And as technology has become simpler to integrate, implement, and use, "everyone can and should buy a TMS," De Muynck says. "There are many flavors; they have become more intuitive, faster, and easier to use." It's not about offering completely different things, he adds. "It's about streamlining the user activity and how the systems perform everyday tasks, making the job easier, and making it easier, more convenient, and less costly for the shipper to work with the carrier."
After seeing the possibilities of what a TMS can do, companies sometimes will be in a rush to get their solution implemented and operating. That can be a mistake that leads to errors and an unsatisfactory outcome, says Keith Whalen, corporate vice president of product management for TMS provider Blue Yonder.
Shippers should make sure they take the time to "focus not only on the really important cost savings, but also, when you scale volume, on doing performance testing" to ensure assumptions are holding up and performance meets expectations, he notes. "Not just [testing] the initial design and integration, but having a more holistic view in all areas, leaving adequate time and not rushing through. Don't skip steps," he advises.
Whalen counsels customers to spend the time and effort up front on knowing their current state, modeling out what they want the future state to look like, and, importantly, planning for training and change management to bring users who will be operating the platform successfully into the new realm.
"I think one of the things we do a really good job at is up front in the initial modeling," he notes. "The customer should be examining opportunities across its transportation network [and] do 'what if' analyses to look not only for savings, but also at where [it might get] the biggest bang for the buck." Such efforts might look at a nearshoring strategy and how it changes the supply chain, a decision on fleet asset deployment or type of service, or warehousing locations to optimize the network and respond to a shifting supply chain.
"That modeling and initial ROI calculation builds the business case. It not only justifies the deployment of the TMS, but also provides the guidance on how to roll it out as they go through their projects," he notes.
Lastly, he stresses that training the operating team, helping them change and evolve from past practice, and transition effectively to the new tools, can be the difference between success and failure.
Distribution centers (DCs) everywhere are feeling the need for speed—and their leaders are turning to automated warehouse technology to meet the challenge, especially when it comes to picking.
This is largely in response to accelerating shipment volumes and rising demand for same-day order fulfillment. Globally, package deliveries increased by more than 50% between 2018 and 2020, and they have been steadily growing ever since, reaching an estimated 380 billion last year on their way to nearly 500 billion packages shipped in 2028, according to a 2024 Capital One Shopping research report. Same-day delivery is booming as well: The global market for same-day delivery services was nearly $10 billion in 2024 and is expected to rise to more than $23 billion by 2029, according to a January report from consultancy The Business Research Co.
Adopting technologies that can boost DC throughput rates while improving accuracy and efficiency can go a long way toward helping companies keep up with those changes. Two recent projects reveal how both simple and more complex systems are answering the call for higher-velocity operations in DCs of all types and sizes.
Pickers at European fruit and vegetable wholesaler Gebr. Gentile AG are working faster and making fewer errors in getting fresh produce out the door after a pick-by-voice solution was installed at the wholesaler's Näfels, Switzerland, logistics center in 2023. Company leaders implemented Lydia Voice from logistics technology vendor Erhardt + Partner Group, allowing the wholesaler to move from a paper-based picking system to an automated one that has streamlined the process and is helping workers get the thousands of shipments that move through the nearly 10,000-square-foot refrigerated facility each day out the door quickly.
"The products stay in our warehouse for an average of 0.7 days, meaning the goods that come in are immediately shipped out again," Renato Häfliger, managing director at Gentile AG, said in a statement describing the project late last year. "We handle approximately 80 to 100 tons of goods daily. Ideally, our inventory rotates quickly, ensuring maximum product freshness."
In all, the Näfels facility handles between 200 and 300 different items for roughly 200 customers.
"On average, this corresponds to 6,000 to 10,000 shipping units that our pickers must process daily," Häfliger adds. "Each order involves about 20 to 60 picks. Using paper lists made this process challenging, as employees never had both hands free. This led to errors and noticeably slowed down the workflow."
Häfliger and his colleagues wanted a hands-free solution that would speed up the picking process—but they couldn't afford the downtime of a complex IT project or the added time to train both regular and seasonal workers on a new system. The beauty of the voice-picking system was that it could be used by any worker without prior training—regardless of gender, accent, or dialect—and could be installed and up and running quickly. That's because the system uses deep neural networks—technology that simulates human brain activity, particularly pattern recognition—to learn and understand language instantly. The software acts as a voice assistant, guiding workers through the picking process via a headset and wearable computer—leaving workers' hands and eyes free for picking tasks. The technology can be integrated into any enterprise resource planning (ERP) system or warehouse management system (WMS) so that work flows seamlessly to the pickers on the floor.
Häfliger says the system proved to be "very easy and intuitive to use during testing, so it [was] ready to go immediately. This was one of the main reasons why we quickly decided on this system, as we employ many seasonal workers in addition to our core team. Long training periods are simply not an option for us."
Today, workers are picking faster, with fewer errors, and orders are moving more swiftly through the Näfels DC—Häfliger cites a double-digit increase in efficiency since switching from paper to voice.
Sometimes, DC operations call for even more automation to best respond to their picking challenges.
That was the case for contract logistics services specialist DHL Supply Chain when business leaders there were looking for a way to improve warehouse operations in the company's health-care fulfillment business.
Workers supporting one of DHL's health care-focused clients were using a manual, cart-based picking system that simply wasn't allowing them to keep up with the fast-paced facility's fulfillment demands. Pushing heavy carts long distances throughout the warehouse left associates fatigued at the end of the day, slowed the overall fulfillment process, and opened the door to errors. DHL Supply Chain leaders needed a system that would alleviate the physical strain on workers, cut cycle times, and improve quality. They turned to warehouse automation vendor Locus Robotics to solve the problem, ultimately deploying 100 autonomous mobile robots (AMRs) to boost picking operations.
Today, the AMRs work alongside pickers, directing them to bin locations throughout the warehouse via the most efficient path—eliminating the need for pickers to push those heavy carts long distances and allowing for hands-free picking directly into shipping boxes. The AMRs then deliver completed orders to the next stage of the process on their own.
DHL Supply Chain has been reaping big rewards since launching the AMR system in 2018. The "pick-to-box" approach has helped reduce errors by 50% and has boosted efficiency by eliminating the need for a separate packing area in the warehouse. Cycle time for orders has fallen by 60%, worker training time has decreased by 90%, and pickers are feeling less fatigued.
"By replacing carts with AMRs, DHL saw increased consistency in warehouse associate output, as the physical demands of walking long distances with heavy loads were minimized," leaders at Locus Robotics explained in a case study about the project. "By integrating [AMRs], DHL improved order quality, reduced operational touchpoints, and enabled rapid cycle times—all essential for a health care-focused supply chain."
Demand for AMRs and similar automated material handling equipment is unlikely to slow in the years ahead: The global market for logistics automation was valued at $34 billion last year and was projected to reach more than $37 billion this year, rising to an expected $81.5 billion in 2033, according to data published last fall by Straits Research. Hardware—which includes AMRs, automated storage and retrieval systems (AS/RS), automated sorting systems, and the like—is the driving force behind that market growth, according to the research.
Such anticipated demand circles back to those accelerating shipment volumes: The Straits research also found that more than a third of material handling executives said their primary need for implementing DC automation is to fill more orders—faster and at a lower cost.
