Buddhists believe we have a "third eye" that, when opened, allows for insights that lead to a higher consciousness. A third eye sees not only what is in the physical world but also the context and wider significance of ideas and events, giving a deeper understanding that leads to enlightenment. I think it's time for all of us to open a "third eye" in our supply chain consciousness. We need to get a clearer perspective on our place within the wider logistics world and use that perception to build and operate an intelligently shared delivery network—one that is based on collaborative distribution.
In a collaborative distribution environment, consumer packaged goods (CPG) manufacturers share warehouse and trailer capacity for products destined for the same retail distribution centers (DCs). This wise approach eliminates redundant warehousing space and delivery runs by creating a hyper-efficient, shared infrastructure for product distribution.
Collaborative distribution is not an idealist's dream. There are solid, practical reasons to adopt this approach. First and foremost is the fact that creating this shared infrastructure can reduce supply chain costs by up to 35 percent. Additionally, collaborative distribution offers a "greener" operating method that will strongly appeal to customers.
To understand why collaborative distribution makes such good sense, just take a look at the current U.S. model for CPG product distribution. It's riddled with inefficiency and redundancy. Industry analysts tell us that trucks are running empty 20 to 25 percent of the time. That's a terrible waste, especially when you consider that transportation accounts for 29 percent of U.S. carbon output and a whopping 70 percent of petroleum usage.
The reason for this shocking inefficiency is that each manufacturer treats each delivery to each customer as a separate shipment that exists in its own, unique universe. Because of that, two trucks can end up driving side by side on the highway, half-full of the same class of consumer products that are coming from the same area and going to the same destination. It's comparable to taking an expensive limousine to the airport, only to find that six of your friends were booked on flights leaving the same afternoon—and you could all have shared a shuttle bus at a much lower cost.
Because the greatest inefficiency occurs when small and medium-size CPG manufacturers plan and make their less-than-truckload (LTL) shipments, perhaps the most dramatic change could come in that sector. But everyone needs to participate. We have a broken system, and it's up to us—manufacturers, retailers, and third-party logistics service providers (3PLs) together— to mend it.
Savings in the real world
I want to make clear that "collaborative distribution" is not simply about freight consolidation. A collaborative distribution model is something more revolutionary. It requires the active participation of manufacturers, retailers, and 3PLs, and it entails a significant shift in practice for all of the parties involved. Manufacturers— even competitors—must agree to co-locate inventories. Retailers' buying groups must consolidate orders for different commodities. Third-party logistics companies must be matchmakers and facilitators, providing the processes, systems, and new pricing strategies to encourage a shared distribution infrastructure.
When this happens, the new model could yield as much as a 35-percent reduction in product distribution costs that comes from:
Reduced warehousing and inventory carrying costs as multiple inventory points are consolidated to one regional collaborative distribution center, where storage and labor costs are shared by participating companies.
Reduced LTL costs as orders for multiple manufacturers are consolidated and converted to truckload shipments.
Reduced empty miles as retailers leverage their own fleets' backhauls to pick up products at the collaborative DC after store deliveries.
Reduced chargeback fines as replenishment orders are delivered on an established schedule agreed with the retailer.
Those are actual savings, documented by CPG companies that are already using collaborative distribution. But discovering them requires an enlightened logistics manager, someone with an open "third eye" who sees his or her distribution chain as one of many that could be intertwined.
Here's an example of collaborative distribution from the real world. A few years ago, my company recognized that we were providing storage and delivery services for three medium-sized candy manufacturers that were all supplying the same customer, a company that services candy racks at retail stores. Separate trucks were leaving our warehouse and carrying the three suppliers' orders to exactly the same DCs. So we approached each of the suppliers and suggested that they work together. Not only did they agree to consolidate loads, they also jointly approached their shared customer and offered to reduce lead times if it would commit to a synchronized order cycle. Now, the candy manufacturers receive orders from that customer in a single, synchronized form. The manufacturers deliver those orders in consolidated (and therefore cheaper) truckloads, and the lead time has been shortened by 20 percent.
Another example: Another of my company's customers, a manufacturer that produces different lines of food products, realized that it was receiving separate orders for different product lines from a large retailer. The retailer had separate buyers for cheese, crackers, cereals, and so on, and this resulted in multiple, less-than-truckload deliveries from the manufacturer's DC to the retailer's DC.
To persuade the buyers to talk to each other and consolidate their orders into one big order, the manufacturer offered the retailer an incentive: a 50-centper- case discount. When the retailer agreed, it saved money on goods, the manufacturer cut its freight costs, and there were fewer, fuller trucks on the road—a genuine "win-win" situation, where everyone benefited. How do we make this kind of shift in thinking and practices happen on a large scale? As is true of most spiritual journeys, some basic beliefs will need to be challenged. Everyone will have to accept change.
Challenge your beliefs
If manufacturers extend their thinking beyond their own individual lines of supply to their customers, they can quickly identify where they are replicating distribution efforts. Naturally, this can be challenging, as they will have to accept that their goods may be stored and transported right next to products from rival manufacturers. This is a concern for many manufacturers, but perhaps it should not be. After all, their brands compete when they reach the retail shelves, not in the back of a truck or in a warehouse storage bin.
Retailers, too, will need to begin thinking more carefully about how the goods they stock actually get delivered. Suppose mustard, ketchup, and pickles, all ordered separately, arrive at the retailer's DC on different days of the week. What if they all arrived together on the same truck, on the same day? It would cost less money, generate less carbon, and make receiving operations much more efficient for the retailer. It would also give the retailer a greater measure of predictability and a better opportunity for visibility—one delivery is far easier to manage and track than several.
Before that scenario can be achieved, however, there are a couple of barriers to overcome. The first is the retailers' typical lack of attention to transportation. Traditionally, retailers' merchandising arms have not cared much about how goods arrive, as long as they arrive on time. That's because the manufacturers pay the freight bill and therefore gain from any savings in freight charges, while the retailers receive no measurable financial benefit. As a result, retailers have little incentive to make changes affecting freight transportation. Under a collaborative distribution system, however, there are many opportunities to give the retailers their share of the savings.
Another barrier is the difficulty of getting the "front door" side of the retailers' operations—the people who order the goods and focus largely on product cost—to recognize the benefits the company will accrue at the "back door" in receiving. The cost and efficiency benefits are clear, though. If, for instance, the merchandising people order for the entire breakfast cereal aisle in such a way that the items can be shipped as a single load from a shared distribution center, then the retailer's DC will receive the same volume of goods in fewer shipments. In the new model, moreover, the retailer's logistics team can request that the 3PL build pallets to the retailer's specified dimensions and even pack the order in a sequence that makes it more efficient to unload product and stock store shelves.
Third parties guide the way
You'll see a pattern emerging here in these concrete examples of how collaborative distribution works in a practical sense. Relationships really come to the fore. For this to be successful, manufacturers and retailers have to negotiate in good faith as entities that are equally invested in an improved outcome. Trust is crucial, and so is the give-and-take of offering incentives for change on both sides. This is where transport providers, especially 3PLs, come into the picture. They have the opportunity to grow into a new role as a kind of matchmaker for CPG manufacturers and their customers. They are the natural choice to play such a role: On the one hand, 3PLs can provide the neutral ground for collaboration among manufacturers whose distribution operations could usefully be combined. On the other, they can entice their retailer customers to order from those suppliers on a more synchronized schedule.
Implementing this new model requires a significant change in a 3PL's pricing approach. Savings from collaborative distribution comes from shared storage space, pooled shipments, increased use of backhauls, and other efficiencies. The third parties will need to determine an equitable way to allocate costs and share those savings, and they will also need to clearly identify and quantify those savings beforehand. Sharing hard numbers on the expected savings and calculating the anticipated reduction in carbon footprint will make collaborative distribution much more attractive to retailers and manufacturers that want to be visibly responsive to the consumer's demand for a greener, more sustainable product.
In a collaborative distribution environment, the 3PL must also look beyond its own walls to create efficiencies for the entire system. For instance, it could ship outbound loads using a retailer's own backhaul capacity. The retailer could get a backhaul rebate from the 3PL if the retailer was willing to make a slight detour on the way back from a store delivery to pick up loads from the 3PL's facility and deliver them to the retailer's own DC. These rebates could run between US $500 and US $750 per truckload, which means that the retailer has the option of using its own fleet for the backhaul or paying a lower amount to a for-hire motor carrier and making a little money on the move.
Another important role for 3PLs is to act as arbiters and implementers of the most appropriate and useful technology. In fact, technology is a key enabler of collaboration, because collaborative distribution requires analyzing complex relationships, ordering the related data into useful, actionable plans, and distributing them quickly to all interested parties. Software can often identify opportunities for collaboration from huge volumes of data that would be overwhelming for a human to analyze.
Turn vision into reality
Although it may sound as if manufacturers and retailers are not working closely together, the fact is that they are already collaborating all the time—on promotional programs, sales incentives, and new product introductions. It seems natural that this collaboration should extend from marketing and sales into the supply chain.
Imagine a future in which collaboration was a key component of the whole supply chain. A retailer would combine orders from multiple buying groups, and then send those to the CPG manufacturers. Those multiple orders would be relayed electronically to a collaborative DC operated by an "enlightened" 3PL, which would then intelligently pick orders from inventory belonging to multiple manufacturers of similar commodities, including competitors. The orders would be staged for smart, consolidated delivery, with pallets built to the retailer's specifications. The retailer would then pick up its own order as a backhaul using a truck that has made a store delivery nearby. The delivery then arrives at the retailer's dock (tracked all the way through a logistics management system) and is unloaded by workers who know exactly where it is going. Finally, the 3PL calculates the total space and shipping charges for each participant in this efficient, collaborative operation, and bills each manufacturer based on the percentage of the total volume their products represent.
Take note of this vision, because it is the future. Moving to a collaborative model in which thousands of separate supply chains begin to intertwine in a shared, intelligent, greener delivery network makes so much sense that it is a great deal more than a vision. It is an inevitability.
However, I need to emphasize that the journey to a more enlightened supply chain starts within the four walls of the company. Inefficiencies, and therefore opportunities to collaborate, often originate internally. Just as each company needs to change its self-image from that of a stand-alone entity to part of a community of companies with shared goals (as well as competing ones, of course), so must the various groups inside a company need to change their "silo" way of thinking and think in terms of the greater good.
The difficult journey to a truly collaborative supply chain begins by realizing that any distribution network, even the largest one in the world, is simply one of many. It's time we all started looking more consciously beyond our own separate organizations to a wider universe of collaboration. I believe it is possible to attain an enlightened, ideal operational state—"supply chain nirvana," if you will. But it can't happen without mutual support and cooperation among all involved.
The launch is based on “Amazon Nova,” the company’s new generation of foundation models, the company said in a blog post. Data scientists use foundation models (FMs) to develop machine learning (ML) platforms more quickly than starting from scratch, allowing them to create artificial intelligence applications capable of performing a wide variety of general tasks, since they were trained on a broad spectrum of generalized data, Amazon says.
The new models are integrated with Amazon Bedrock, a managed service that makes FMs from AI companies and Amazon available for use through a single API. Using Amazon Bedrock, customers can experiment with and evaluate Amazon Nova models, as well as other FMs, to determine the best model for an application.
Calling the launch “the next step in our AI journey,” the company says Amazon Nova has the ability to process text, image, and video as prompts, so customers can use Amazon Nova-powered generative AI applications to understand videos, charts, and documents, or to generate videos and other multimedia content.
“Inside Amazon, we have about 1,000 Gen AI applications in motion, and we’ve had a bird’s-eye view of what application builders are still grappling with,” Rohit Prasad, SVP of Amazon Artificial General Intelligence, said in a release. “Our new Amazon Nova models are intended to help with these challenges for internal and external builders, and provide compelling intelligence and content generation while also delivering meaningful progress on latency, cost-effectiveness, customization, information grounding, and agentic capabilities.”
The new Amazon Nova models available in Amazon Bedrock include:
Amazon Nova Micro, a text-only model that delivers the lowest latency responses at very low cost.
Amazon Nova Lite, a very low-cost multimodal model that is lightning fast for processing image, video, and text inputs.
Amazon Nova Pro, a highly capable multimodal model with the best combination of accuracy, speed, and cost for a wide range of tasks.
Amazon Nova Premier, the most capable of Amazon’s multimodal models for complex reasoning tasks and for use as the best teacher for distilling custom models
Amazon Nova Canvas, a state-of-the-art image generation model.
Amazon Nova Reel, a state-of-the-art video generation model that can transform a single image input into a brief video with the prompt: dolly forward.
Economic activity in the logistics industry expanded in November, continuing a steady growth pattern that began earlier this year and signaling a return to seasonality after several years of fluctuating conditions, according to the latest Logistics Managers’ Index report (LMI), released today.
The November LMI registered 58.4, down slightly from October’s reading of 58.9, which was the highest level in two years. The LMI is a monthly gauge of business conditions across warehousing and logistics markets; a reading above 50 indicates growth and a reading below 50 indicates contraction.
“The overall index has been very consistent in the past three months, with readings of 58.6, 58.9, and 58.4,” LMI analyst Zac Rogers, associate professor of supply chain management at Colorado State University, wrote in the November LMI report. “This plateau is slightly higher than a similar plateau of consistency earlier in the year when May to August saw four readings between 55.3 and 56.4. Seasonally speaking, it is consistent that this later year run of readings would be the highest all year.”
Separately, Rogers said the end-of-year growth reflects the return to a healthy holiday peak, which started when inventory levels expanded in late summer and early fall as retailers began stocking up to meet consumer demand. Pandemic-driven shifts in consumer buying behavior, inflation, and economic uncertainty contributed to volatile peak season conditions over the past four years, with the LMI swinging from record-high growth in late 2020 and 2021 to slower growth in 2022 and contraction in 2023.
“The LMI contracted at this time a year ago, so basically [there was] no peak season,” Rogers said, citing inflation as a drag on demand. “To have a normal November … [really] for the first time in five years, justifies what we’ve seen all these companies doing—building up inventory in a sustainable, seasonal way.
“Based on what we’re seeing, a lot of supply chains called it right and were ready for healthy holiday season, so far.”
The LMI has remained in the mid to high 50s range since January—with the exception of April, when the index dipped to 52.9—signaling strong and consistent demand for warehousing and transportation services.
The LMI is a monthly survey of logistics managers from across the country. It tracks industry growth overall and across eight areas: inventory levels and costs; warehousing capacity, utilization, and prices; and transportation capacity, utilization, and prices. The report is released monthly by researchers from Arizona State University, Colorado State University, Rochester Institute of Technology, Rutgers University, and the University of Nevada, Reno, in conjunction with the Council of Supply Chain Management Professionals (CSCMP).
Specifically, 48% of respondents identified rising tariffs and trade barriers as their top concern, followed by supply chain disruptions at 45% and geopolitical instability at 41%. Moreover, tariffs and trade barriers ranked as the priority issue regardless of company size, as respondents at companies with less than 250 employees, 251-500, 501-1,000, 1,001-50,000 and 50,000+ employees all cited it as the most significant issue they are currently facing.
“Evolving tariffs and trade policies are one of a number of complex issues requiring organizations to build more resilience into their supply chains through compliance, technology and strategic planning,” Jackson Wood, Director, Industry Strategy at Descartes, said in a release. “With the potential for the incoming U.S. administration to impose new and additional tariffs on a wide variety of goods and countries of origin, U.S. importers may need to significantly re-engineer their sourcing strategies to mitigate potentially higher costs.”
Grocers and retailers are struggling to get their systems back online just before the winter holiday peak, following a software hack that hit the supply chain software provider Blue Yonder this week.
The ransomware attack is snarling inventory distribution patterns because of its impact on systems such as the employee scheduling system for coffee stalwart Starbucks, according to a published report. Scottsdale, Arizona-based Blue Yonder provides a wide range of supply chain software, including warehouse management system (WMS), transportation management system (TMS), order management and commerce, network and control tower, returns management, and others.
Blue Yonder today acknowledged the disruptions, saying they were the result of a ransomware incident affecting its managed services hosted environment. The company has established a dedicated cybersecurity incident update webpage to communicate its recovery progress, but it had not been updated for nearly two days as of Tuesday afternoon. “Since learning of the incident, the Blue Yonder team has been working diligently together with external cybersecurity firms to make progress in their recovery process. We have implemented several defensive and forensic protocols,” a Blue Yonder spokesperson said in an email.
The timing of the attack suggests that hackers may have targeted Blue Yonder in a calculated attack based on the upcoming Thanksgiving break, since many U.S. organizations downsize their security staffing on holidays and weekends, according to a statement from Dan Lattimer, VP of Semperis, a New Jersey-based computer and network security firm.
“While details on the specifics of the Blue Yonder attack are scant, it is yet another reminder how damaging supply chain disruptions become when suppliers are taken offline. Kudos to Blue Yonder for dealing with this cyberattack head on but we still don’t know how far reaching the business disruptions will be in the UK, U.S. and other countries,” Lattimer said. “Now is time for organizations to fight back against threat actors. Deciding whether or not to pay a ransom is a personal decision that each company has to make, but paying emboldens threat actors and throws more fuel onto an already burning inferno. Simply, it doesn’t pay-to-pay,” he said.
The incident closely followed an unrelated cybersecurity issue at the grocery giant Ahold Delhaize, which has been recovering from impacts to the Stop & Shop chain that it across the U.S. Northeast region. In a statement apologizing to customers for the inconvenience of the cybersecurity issue, Netherlands-based Ahold Delhaize said its top priority is the security of its customers, associates and partners, and that the company’s internal IT security staff was working with external cybersecurity experts and law enforcement to speed recovery. “Our teams are taking steps to assess and mitigate the issue. This includes taking some systems offline to help protect them. This issue and subsequent mitigating actions have affected certain Ahold Delhaize USA brands and services including a number of pharmacies and certain e-commerce operations,” the company said.
Editor's note:This article was revised on November 27 to indicate that the cybersecurity issue at Ahold Delhaize was unrelated to the Blue Yonder hack.
The new funding brings Amazon's total investment in Anthropic to $8 billion, while maintaining the e-commerce giant’s position as a minority investor, according to Anthropic. The partnership was launched in 2023, when Amazon invested its first $4 billion round in the firm.
Anthropic’s “Claude” family of AI assistant models is available on AWS’s Amazon Bedrock, which is a cloud-based managed service that lets companies build specialized generative AI applications by choosing from an array of foundation models (FMs) developed by AI providers like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself.
According to Amazon, tens of thousands of customers, from startups to enterprises and government institutions, are currently running their generative AI workloads using Anthropic’s models in the AWS cloud. Those GenAI tools are powering tasks such as customer service chatbots, coding assistants, translation applications, drug discovery, engineering design, and complex business processes.
"The response from AWS customers who are developing generative AI applications powered by Anthropic in Amazon Bedrock has been remarkable," Matt Garman, AWS CEO, said in a release. "By continuing to deploy Anthropic models in Amazon Bedrock and collaborating with Anthropic on the development of our custom Trainium chips, we’ll keep pushing the boundaries of what customers can achieve with generative AI technologies. We’ve been impressed by Anthropic’s pace of innovation and commitment to responsible development of generative AI, and look forward to deepening our collaboration."