That’s how much less it costs UPS to process a package in an automated facility compared to a conventional one. CEO Carol Tomé dropped that figure during the company’s Q2 2026 earnings call last week, and it landed with the kind of quiet authority that only comes from running the math on hundreds of millions of packages. Not a projection. Not a vendor’s slide deck. An operational result from one of the largest logistics networks on the planet.

At the end of Q2, 68.5% of all U.S. volume flowing through UPS moved through buildings equipped with automation. That’s up from 64% just a year ago, and it translates to 337 million additional packages handled by machines instead of human hands. The trajectory is clear, and UPS isn’t slowing down.

From 200 Buildings Closed to a Leaner Network

UPS’s “Network of the Future” initiative didn’t start as an automation project. It started as a hard look at an overgrown network that had accumulated facilities the way old companies accumulate conference rooms: one at a time, until nobody could explain why there were so many.

The plan called for closing roughly 200 sorting hubs and facilities. Dozens have already shut down, with more closures scheduled through the rest of 2026. But this isn’t just about shrinking. UPS is simultaneously converting existing sites and adding 24 new automated buildings to its network this year, bringing the total automated roster well past its earlier base of 127 buildings. The company’s long-term target is roughly 400 automated facilities by 2028.

EVP and CFO Brian Dykes put the human cost in stark terms during the earnings call: “We will have eliminated 50 million hours through the course of last year and this year, nearly 78,000 operational positions that were associated with that volume, and we’ll close nearly 150 buildings.”

Those aren’t abstract numbers. They represent a complete rethinking of how a parcel network should be structured when you can deploy pick-and-place robotics, autonomous guided vehicles, truck-unloading robots, and AI-driven routing systems at scale.

The 28% Question Every Operator Should Be Asking

The 28% cost reduction per package isn’t just a UPS story. It’s a data point that validates what the automation industry has been claiming for years, and it comes from an operator running at a scale that makes the finding hard to dismiss as a niche result.

For context, labor typically accounts for 60% to 70% of operating costs in manual parcel sorting operations. Industry research consistently shows that automated sorting systems reduce labor costs by 20% to 40%, with payback periods running two to four years for large-scale facilities. UPS’s 28% figure sits right in that range, but with a sample size that dwarfs most case studies.

The economics work because automation attacks the most expensive and least flexible part of warehouse operations: repetitive manual tasks. Unloading trailers, sorting packages by destination, moving goods through a facility. These jobs are physically demanding, hard to staff consistently, and scale poorly. When volume spikes (think peak season or a tariff-driven import surge), manual operations require overtime, temporary workers, and the error rates that come with both.

Automated systems don’t eliminate the complexity. But they change where the complexity lives. Instead of managing hundreds of temporary workers during a peak, you’re managing throughput rates and maintenance schedules. The per-unit cost stays flat whether you’re processing 100,000 packages or 300,000.

What UPS Is Actually Deploying

The technology inside UPS’s automated buildings isn’t science fiction. Most of it has been commercially available for years. What’s changed is the willingness to deploy it at network scale and the financial results that justify continued investment.

UPS has committed approximately $120 million to Pickle Robot for 400 truck-unloading units, with deployments starting across multiple facilities. These robots handle the grueling work of pulling packages off trailers, a job that’s been one of the hardest to staff and one of the most common sources of workplace injuries in distribution.

The company’s partnership with Geek+ has produced facilities like UPS Velocity, where more than 700 shelf-to-person robots handle sorting, storage, and order processing at rates exceeding 350,000 units per day. The robots move autonomously through the facility, bringing goods to stationary workers who handle the tasks that still require human judgment.

Singulators, high-speed conveyors, and AI-powered routing systems round out the picture. The AI component is worth noting specifically: machine learning models now help determine optimal package routing through the network, prioritizing shipments based on service level, destination, and available capacity. It’s not the kind of AI that makes headlines, but it’s the kind that compounds savings across billions of annual touches.

The Amazon Factor

There’s a subplot to UPS’s automation story that makes the numbers even more interesting. The company recently finished reducing its Amazon delivery volume by about 2 million packages per day, an initiative that kicked off in 2025. Tomé described the removed Amazon volume as “lower quality,” meaning it carried thinner margins and higher handling costs.

By shedding that volume and simultaneously automating, UPS has essentially rebuilt its network for profitability rather than pure throughput. “We now have a leaner, more automated, more agile network that will deliver operating leverage as volume grows,” Tomé said.

This is a strategic move that smaller operators can learn from, even if they can’t replicate the scale. The principle is the same: don’t automate everything indiscriminately. Automate the work that drives the most cost, shed the work that doesn’t generate adequate returns, and build flexibility into what remains.

What This Means for Mid-Market Warehouse Operators

UPS can spend $9 billion on network transformation. Most warehouse operators can’t. But the underlying economics don’t require UPS-scale capital to work.

The payback math is straightforward. If labor represents 65% of your operating costs and automation reduces that by 30%, you’re looking at roughly a 20% reduction in total operating expense. For a facility spending $5 million annually on operations, that’s $1 million per year in savings. A $3 million automation investment pays for itself in three years, and the savings compound as labor costs continue to rise.

And labor costs are rising. The Bureau of Labor Statistics reports that warehouse wages have increased roughly 22% since 2020, and the labor pool hasn’t expanded to match demand. Operators in tight labor markets (Southern California, the Northeast corridor, major metro areas) are already feeling the squeeze. Automation doesn’t just reduce cost per unit. It reduces the operational risk of not being able to staff your building during peak periods.

The technology has also become more modular. Five years ago, automating a facility meant a massive capital project with 18 months of implementation. Today, companies like Locus Robotics, 6 River Systems, and Geek+ offer robotics-as-a-service models that let operators add capacity incrementally. You can start with automated goods-to-person picking, prove the ROI, and expand from there.

The Productivity Metric That Matters

UPS tracks a metric called “volume-per-resource,” defined as average daily volume divided by U.S. employees. In 2023, that number was 51. The target for 2026 is 59, a 15.7% improvement in per-worker productivity.

That single metric captures the entire automation thesis. You’re not just replacing workers with robots. You’re fundamentally changing the ratio of output to human input. The workers who remain are doing higher-value work: managing systems, handling exceptions, maintaining equipment, and making decisions that machines can’t.

For operators evaluating automation investments, this is the metric to track. Not just labor cost reduction, but output per person. It accounts for the fact that automation often shifts labor from direct handling to supervision and maintenance, which is a different cost profile but not zero.

The $3 Billion Target

UPS has set a target of $3 billion in annual cost savings from its network transformation by the end of 2028, with approximately $1.5 billion expected by the close of 2026. Those numbers include savings from facility closures, network optimization, and technology deployment.

The scale of the target tells you something about how much inefficiency existed in the old network. But it also tells you something about where the logistics industry is headed. When the largest parcel carrier in the world publicly commits to this level of automation investment and reports results that validate the thesis, the rest of the industry takes notice.

The question for warehouse operators isn’t whether automation works. UPS just answered that with 337 million packages and a 28% cost reduction. The question is how quickly you can get started, and what happens to your competitive position if you don’t.

Related Video

See UPS’s automated Velocity facility in action, featuring 700+ Geek+ robots handling over 350,000 units per day:

The post UPS Just Proved the Math on Warehouse Automation. The Numbers Are Hard to Argue With. appeared first on Veridian.

The top 100 industrial leases totaled 93.6 million square feet, a 26% year-over-year increase. Average deal sizes grew to 936,000 square feet, up from 744,000 in the same period last year. And tenants aren’t just taking more space. They’re locking in longer commitments, with average lease terms extending to 89 months, up five months from last year.

For anyone tracking where supply chain investment is actually flowing (not where LinkedIn posts say it’s flowing), this data tells a clear story.

The Caution Era Is Over

The industrial warehouse market spent most of 2023 and 2024 in a correction. After the pandemic-fueled land grab that saw vacancy rates drop below 3% in some markets, a wave of speculative construction flooded the market with new supply. Vacancy climbed to around 6.7% by early 2026. Rental growth flattened. Tenants gained leverage.

That cooling period created a buyer’s market, and it turns out smart operators used it to their advantage. New leases accounted for 66 of the top 100 deals in H1 2026, up from 60 last year. Companies aren’t just renewing existing footprints. They’re actively expanding into newer, more capable facilities.

“The largest leases signal continued stabilization across the industrial and logistics sector,” said Chris Zubel, executive managing director for Americas industrial and logistics at CBRE. “Occupiers are also making longer-term commitments, which reflects increased confidence in their business prospects and logistics planning.”

That confidence shows up in the numbers. Renewals dropped from 40 to 34, but the total renewed square footage actually increased from 26.7 million to 31.7 million square feet. In other words, companies renewing their leases are also upsizing.

Who’s Signing and Where

Three metro areas dominated H1 2026 leasing activity: California’s Inland Empire led with 14 leases covering 12.6 million square feet, followed by Dallas-Fort Worth with 11 leases (10.5 million square feet) and Chicago with 9 leases (9.4 million square feet). These aren’t surprises. All three sit at the center of major transportation corridors with deep labor pools and proximity to large consumer markets.

Third-party logistics providers still hold the biggest share, accounting for 30 of the top 100 leases. But their proportion actually dropped from 38 last year, which tells an interesting story. The demand base is broadening.

The most striking shift came from food and beverage companies. Their leased square footage more than tripled to 16.6 million square feet as they expanded regional distribution networks. This makes sense. The past few years exposed how fragile centralized food distribution can be. When a single facility goes down (whether from weather, a cyberattack, or equipment failure), entire regions lose access to products. Regional redundancy solves that problem, but it requires space. Lots of it.

General retailers and wholesalers, by contrast, pulled back. They accounted for just 17 of the top 100 leases, down from 28 in H1 2025. Many are optimizing existing networks rather than expanding, squeezing more throughput from current facilities through automation and better slotting strategies.

Amazon Keeps Building While Others Optimize

No discussion of warehouse real estate is complete without mentioning the biggest occupier of industrial space on the planet. Amazon announced two new facilities in late July: a 4 million-square-foot operations center in Holbrook, New York (a $1 billion investment creating roughly 1,000 jobs), and a 1.2 million-square-foot distribution center in Terrell, Texas ($98 million, with construction starting in August).

These join a growing pipeline. Amazon is also building a 250,000-square-foot sorting warehouse in Georgetown, Texas, and developing a 3 million-square-foot robotics fulfillment center in North Carolina. The company continues to close, convert, and renovate older facilities at the same time. A distribution facility in Port St. Lucie, Florida, is being temporarily shuttered and converted into a sortable fulfillment center.

Amazon’s strategy illustrates a broader trend: it’s not just about more square footage. It’s about the right kind of square footage. The Holbrook facility will be equipped with advanced robotics and technology. The North Carolina site is purpose-built for robotic fulfillment. Older buildings that can’t support modern automation get either upgraded or replaced.

This pattern applies across the market. CBRE’s 2026 outlook noted that mega big-box occupiers are prioritizing quick upgrades to newer facilities as first-generation large blocks (500,000+ square feet) become scarcer in top markets like Louisville, Columbus, Phoenix, and the Inland Empire.

Why Longer Leases Make Financial Sense Right Now

The shift toward longer lease terms isn’t just about confidence. It’s a financial play.

Warehouse rents surged during and after the pandemic. Between 2020 and 2023, asking rents for logistics space jumped 30-40% in many primary markets. While growth has moderated, rents haven’t dropped back to pre-pandemic levels. Locking in a 7+ year lease today protects companies from future rent inflation, especially in high-demand corridors where supply remains constrained.

There’s also the automation angle. Companies investing millions in automated storage and retrieval systems, goods-to-person robotics, or sortation equipment don’t want to move in five years. These systems take 12-18 months to install and commission. The ROI window typically runs 5-7 years. A short lease creates a misalignment between capital investment and occupancy timeline. Longer leases eliminate that risk.

For 3PLs specifically, longer commitments also help win and retain customers. A shipper evaluating 3PL partners wants assurance that the provider has stable access to well-located capacity. “We might not have this building next year” is a terrible thing to tell a prospective client.

What This Means for Supply Chain Leaders

If you’re running supply chain operations, the CBRE data carries a few practical implications.

The window for tenant-favorable deals is narrowing. Overall U.S. industrial leasing rose 14% year-over-year in Q1 2026, and CBRE projects total leasing activity to approach 1 billion square feet for the full year (a 5% increase). As demand absorbs available supply, landlords will regain pricing power. Companies that need to expand or relocate should be moving now, not waiting for conditions to improve further.

Modern building specs matter more than ever. Clear heights of 36+ feet, heavy floor loads, ample power for automation, and EV-ready truck courts are becoming table stakes for Class A distribution space. Older facilities with 28-foot clear heights and limited power won’t support the operational density that modern supply chains demand.

Regional distribution is winning over centralization. The food and beverage sector’s tripling of leased space reflects a broader shift. Companies across industries are building out regional fulfillment networks to reduce last-mile delivery times, manage disruption risk, and comply with increasingly tight delivery windows set by retailers and consumers.

Automation readiness drives location decisions. It’s no longer enough for a building to be in the right zip code. Companies are evaluating sites based on power availability, floor specifications, and the ability to support robotic systems from day one. This is filtering demand toward newer construction and away from aging industrial parks.

Conclusion

The mega-warehouse leasing surge of H1 2026 isn’t a speculative bubble. It’s the supply chain industry making deliberate, long-term bets on capacity, technology readiness, and network design. After two years of caution, occupiers are committing capital and signing longer leases because the math favors it: lock in modern space now, install automation, and build the regional networks that today’s fulfillment demands require.

The companies that secured their next-generation warehouse footprints in this window will have a structural advantage over competitors still operating out of older facilities with shorter leases and less flexibility. In supply chain, where you are and what your building can do have always mattered. In 2026, those factors matter more than they have in years.

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The post Mega-Warehouse Leases More Than Doubled in Six Months. Here’s What That Tells Us About Supply Chain Strategy. appeared first on Veridian.

Then you try to deploy it. And the whole thing falls apart.

New research from The Loadstar’s State of AI in Supply Chain 2026 report puts a hard number on what many operations leaders already feel in their gut: only 22.2% of organizations have deployed AI at scale across multiple teams or made it core to daily operations. Meanwhile, 43.2% are still experimenting or haven’t started at all.

The technology works. The organizations aren’t ready for it. And the gap between those two realities is becoming the defining challenge of supply chain technology in 2026.

The Demo-to-Deployment Gap

At FreightWaves’ AI Supply Chain Symposium in Chicago this month, Eric Rempel, Chief Innovation Officer at Redwood Logistics, didn’t mince words. He told the audience that supply chain AI is climbing toward Gartner’s Peak of Inflated Expectations, with the Trough of Disillusionment waiting on the other side.

“There are a lot of AI demos better than anything I’ve ever seen in my entire life,” Rempel said. “You can put an AI demo together, you can build something wonderful, you can do it for the enterprise, you can do the show. It’s unbelievable.”

But supply chains don’t run on clean demos. “Everything goes wrong all the time,” he added.

That tension between what AI can do in controlled conditions and what it actually delivers in a messy, exception-heavy logistics operation explains why so many organizations are stuck. The Loadstar survey found that 53.8% of respondents pointed to a lack of in-house AI expertise and change management capability as their biggest obstacle to scaling. Nearly half (48.7%) said integrating AI with existing systems was the wall they couldn’t get past.

These aren’t technology problems. They’re organizational ones.

The Boardroom-to-Warehouse Confidence Gap

Perhaps the most telling number in the research is the sentiment divide between leadership and the people doing the actual work.

Among vice presidents and executives, 77.5% described themselves as optimistic or enthusiastic about AI’s impact on their careers. For analysts, specialists, and individual contributors on the front lines, that number dropped to 37.5%.

But here’s the interesting part: only 9% of those frontline workers said they felt threatened by AI. The issue isn’t fear of replacement. It’s that leadership keeps selling a vision that execution teams haven’t seen delivered in practice.

James Coombes, CEO of logistics AI provider Raft, put it bluntly: “The issue isn’t frontline fear, but rather leadership selling a grand vision that their execution teams simply haven’t seen delivered in reality yet.”

This matches what Rempel described from 20 years of WMS and TMS implementations. “Substitute AI with any change and that’s the narrative,” he said. “There are always folks within the organization who say, ‘I’ve done it this way forever, it’s fine.’ Change is scary. This is why change takes three to five years in organizations.”

Where AI Is Actually Working

The picture isn’t all bleak. Where AI has been deployed with clear scope and measurable outcomes, the results are real.

Document extraction and processing leads the pack. A full 79.7% of respondents identified it as the area where AI generated the most tangible operational impact. Speed and productivity gains were cited by 89.5% of organizations already seeing measurable value from their AI investments.

Walmart’s supply chain technology team offers a blueprint for the more ambitious end of deployment. Indira Uppuluri, the retailer’s SVP of supply chain technology, described how Walmart uses AI agents and digital twins across its logistics network. Instead of optimizing one node at a time, associates use agents to see how resources are being leveraged across the entire system, then act on bottlenecks in real time.

The retailer’s transportation teams run virtual replicas of their logistics network to simulate how goods move under stress. If a facility goes down or demand shifts overnight, the digital twin tests responses before anyone commits resources.

“The systems behind the scenes leverage the data to come up with actions that we can take, and our associates can take those recommendations and implement them for us,” Uppuluri told Supply Chain Dive.

But Walmart has something most companies don’t: massive data infrastructure, dedicated AI teams, and the budget to build custom tools. For mid-market companies running on legacy ERP systems and spreadsheets, that level of deployment remains out of reach.

The Cost Shift Nobody’s Talking About

There’s another wrinkle emerging that could slow AI adoption further: the economics are changing.

Rempel pointed out that AI pricing is shifting from the flat-rate subscription models that made early experimentation cheap to usage-based costs as enterprises try to scale. During the subsidized era, a $20 or $200 monthly plan gave companies access to enormous compute power. That model is disappearing at the enterprise level.

“It’s becoming a spot market,” Rempel said. “And organizations are rethinking how they staff.”

For a supply chain operation processing billions of transactions monthly, the cost of running AI across every decision point adds up fast. Companies are discovering that throwing AI at everything is both expensive and ineffective. The winners will be the ones who pick their spots: high-volume document processing, exception management, demand forecasting, and other areas where the ROI is clear and measurable.

The Measurement Problem

Even among companies getting real value from AI, proving that value remains a challenge. The Loadstar report found that 62.8% of respondents either hadn’t measured the ROI from their AI initiatives or didn’t know how to.

That’s a problem when budgets tighten. If you can’t show the CFO what AI is doing for the operation, the next round of funding gets harder to justify. And without clear metrics, it’s difficult to separate genuine transformation from technology theater.

The Trax Technology team argues that traditional ROI metrics simply don’t capture how AI transforms operations. Instead, companies need portfolio views of value creation that track direct cost reductions (automated exception handling, optimized routing), operational velocity improvements (cycle time compression, faster decisions), and strategic capability enhancements (better scenario modeling, improved risk visibility).

That’s a heavy lift for organizations still struggling to integrate AI with their existing systems.

What Actually Moves the Needle

So what separates the 22% who’ve deployed AI at scale from the 78% who haven’t? Based on the research and industry interviews, a few patterns stand out.

Data foundations come first. Clean, unified data across ERP, WMS, and TMS systems is table stakes. Sophisticated algorithms can’t compensate for fragmented data and unstandardized processes. Companies that skip this step get disappointing returns no matter how good the AI model is.

Start narrow, prove value, then expand. The organizations seeing real results aren’t trying to transform everything at once. They’re picking one process (document processing, invoice reconciliation, demand forecasting), deploying AI with clear metrics, proving the ROI, and then expanding.

Invest in people, not just platforms. Rempel made the point that AI adoption isn’t a technology problem anymore. It’s a people and process problem. Companies need change management capability, not just data scientists.

Treat AI agents like employees. As AI agents take on more autonomous roles, organizations need to think about governance the same way they think about HR. Who reviews what the agent says? Who handles customer feedback? What happens when you need to roll one back?

“HR is going to be a function of people and agents,” Rempel said. “Do you have a learning enterprise where this is managed, or are you just building things on top of each other and the whole thing can collapse?”

Conclusion

The supply chain industry isn’t short on AI capability. Every major WMS, TMS, and planning platform now ships with AI features baked in. The models are good. The demos are spectacular. What’s missing is the organizational muscle to put it all to work.

For supply chain leaders watching the hype cycle play out, the message from the front lines is clear: slow down on the vision, speed up on the foundations. Get your data right. Pick your first AI use case carefully. Prove it works before you scale it. And invest as much in change management as you do in the technology itself.

The companies that do this won’t be the ones with the flashiest keynote slides. They’ll be the ones quietly compounding operational gains while everyone else is still stuck in pilot mode.

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The post Only 22% of Supply Chains Have Deployed AI at Scale. Here’s What’s Holding the Rest Back. appeared first on Veridian.

The attack didn’t poison any products. It didn’t compromise consumer data (as far as we know). What it did was something arguably worse for a company moving perishable goods through a time-sensitive supply chain: it stopped the machines. For a business built on ultra-filtered milk and protein shakes with short shelf lives, every hour of downtime translates directly into spoiled inventory, missed retail windows, and empty shelves.

And Fairlife isn’t an outlier. It’s a data point in a trend that supply chain leaders can’t afford to ignore.

The Numbers Are Getting Worse

The Food and Agriculture Information Sharing and Analysis Center (Food and Ag-ISAC) confirmed that the food and agriculture sector has been hit with roughly 205 ransomware attacks so far in 2026. That accounts for about 4.9% of all ransomware incidents tracked globally.

For context, the sector experienced 265 attacks across the entirety of 2025, up sharply from prior years. At the current pace, 2026 is on track to surpass that total before October.

The IT-ISAC’s annual report paints a broader picture. Across all industries, 6,351 ransomware attacks were observed in 2025. The IT sector itself saw nearly 750 incidents, more than double the 300 it experienced in 2024. Manufacturing led the list. Commercial facilities came second. IT was third.

What’s changed isn’t just the volume. It’s the speed. The IT-ISAC noted that attackers are now “weaponizing critical zero-day vulnerabilities in platforms within hours of disclosure.” Not days, not weeks. Hours. That’s a fundamentally different threat model than the one most supply chain security programs were built to handle.

Why Supply Chains Are Targets

Scott Algeier, executive director of the Food and Ag-ISAC, put it bluntly: attackers “scan for exposed, vulnerable systems at machine speed and determine the victim’s details after initial access.” They’re not necessarily picking the food industry on purpose. They’re finding unlocked doors, walking through them, and then figuring out who owns the building.

That matters because of how modern supply chains are wired. A warehouse management system (WMS) talks to an ERP, which talks to a transportation management system (TMS), which connects to carrier APIs, which feed data to customer portals. Each integration point is a potential entry. Each legacy system running unpatched software is a vulnerability.

And the attack surface has grown. Think about what’s connected in a modern distribution center: RF scanners on the warehouse floor, IoT sensors tracking temperature in cold chain operations, automated sortation systems, robotic pick modules, yard management terminals. Ten years ago, most of this equipment ran on isolated networks. Today, it’s increasingly connected to cloud platforms for real-time visibility, predictive maintenance, and AI-driven optimization.

That connectivity drives efficiency. It also creates pathways for attackers.

The Cl0p ransomware gang, one of the most active groups tracked by the IT-ISAC, has shown a disproportionate interest in food and agriculture targets. More than 9% of Cl0p’s attacks in 2025 targeted the sector, well above the 4% average across all threat actors. Meanwhile, Qilin, a ransomware-as-a-service operation, has deployed a Rust-based encryption tool that can efficiently target multiple operating systems, making it adaptable across the mix of Windows, Linux, and proprietary platforms common in warehouse and logistics environments.

The Operational Reality of an Attack

When ransomware hits a supply chain operation, the damage extends far beyond encrypted files. Consider what happens when a WMS goes offline at a distribution center:

Inbound receiving stops because the system can’t process ASNs or generate putaway instructions. Outbound shipping halts because pick lists can’t be generated and orders can’t be allocated. Inventory accuracy goes to zero because every movement since the last clean backup is uncertain. Carrier appointments get missed. Retail compliance penalties start accumulating.

For Coca-Cola, Fairlife’s perishable product line amplifies every one of these problems. Ultra-filtered milk doesn’t wait for your IT team to finish incident response. The company invested $650 million to expand its Coopersville, Michigan facility and planned to open a 745,000-square-foot plant in Webster, New York this year. Those investments assume continuous production throughput. Ransomware breaks that assumption.

The company said the attack “has had no effect on the quality and safety” of its products, which suggests production was halted as a precaution rather than because products were contaminated. That’s actually the right call. But it also shows how a cybersecurity incident becomes a supply chain disruption, which becomes a financial event, which becomes an SEC filing. The cascade is fast and the blast radius is wide.

What Supply Chain Leaders Should Be Doing

If you’re running warehouse or logistics operations, the Fairlife incident should trigger a conversation that goes beyond your IT security team. Here’s where to focus:

Segment your OT networks. The single most impactful step is separating operational technology (warehouse automation, conveyor controls, RF systems) from your corporate IT network. If ransomware gets into email servers, it shouldn’t be able to reach your sortation system. Network segmentation isn’t glamorous, but it’s the difference between a contained incident and a full operational shutdown.

Audit your WMS and TMS backup and recovery plans. Most companies test disaster recovery for their ERP. Far fewer have tested what happens when their WMS goes down for 72 hours. Can you run your warehouse on paper? Do your operators even know how? Running tabletop exercises specifically for supply chain system outages will expose gaps you didn’t know existed.

Patch aggressively, especially edge devices. Those RF scanners, IoT sensors, and edge computing devices in your DC are running software too. They need updates. The IT-ISAC report highlighted that living-off-the-land techniques, where attackers use legitimate system tools to move laterally, are increasingly common. An unpatched device on the warehouse floor can be the pivot point.

Vet your integration partners. Your WMS vendor, your 3PL’s TMS, your EDI provider, your cloud analytics platform. Every API connection is a trust relationship. Ask them about their security posture. If they can’t answer clearly, that’s information you need.

Build manual fallback procedures. The companies that recover fastest from cyber incidents are the ones that have practiced operating without their systems. Print your pick process documentation. Train supervisors on paper-based receiving. It feels old-fashioned until the morning your systems are encrypted and your customers are calling.

The Bigger Picture

The Coca-Cola attack will get attention because of the brand name. But the 204 other attacks on food and agriculture operations this year happened at companies most people have never heard of. Regional distributors. Cold storage operators. Ingredient suppliers. The smaller the company, the less likely it is to have dedicated security staff, segmented networks, or tested recovery procedures.

That creates risk not just for those individual companies but for the supply chains they participate in. When your tier-two supplier’s warehouse goes offline because of ransomware, their problem becomes your problem. The interconnected nature of modern supply chains means cybersecurity is no longer just an IT concern. It’s an operational resilience concern, right alongside weather events, labor disruptions, and tariff volatility.

Supply chain leaders spend significant resources on visibility platforms, demand sensing, and network optimization. Those investments assume the systems themselves will keep running. Ransomware challenges that assumption, and the attackers are getting faster. The question isn’t whether your supply chain will face a cyber incident. It’s whether you’ve prepared well enough that it remains an incident, not a catastrophe.

The post 205 Ransomware Attacks on Food Supply Chains in 2026. Is Your Warehouse Next? appeared first on Veridian.

The facility, which broke ground in 2023 and became fully operational in June 2026, was built with Element Logic as the integration partner and AutoStore’s R5 pro robots as the backbone. The setup also includes roughly 24,000 linear feet of material handling equipment and an overhead monorail transport system. All of it is designed for one purpose: getting e-commerce orders out the door faster across the eastern U.S. and Canada.

But this isn’t just a story about one retailer building a big warehouse. It’s a signal about where the broader industry is moving, and moving fast.

The Goods-to-Person Model Is Eating Traditional Picking

For decades, warehouse picking meant people walking to products. An associate would receive an order, grab a cart, and walk the aisles. In a large facility, that meant walking 10 to 15 miles per shift, with actual picking accounting for less than half of their time. The rest was travel, searching, and waiting.

Goods-to-person (GTP) automation flips that equation. Instead of workers going to inventory, the inventory comes to them. In AutoStore’s case, robots on a grid retrieve bins from a densely packed cube of storage and deliver them to ergonomic workstations where associates pick, pack, and ship.

The productivity gains are substantial. GTP systems routinely deliver 2x to 4x the picks per hour compared to manual operations. And because the storage is vertical and dense (AutoStore claims up to 4x the storage density of traditional shelving), facilities can hold more product in a smaller footprint.

The market reflects this shift. The goods-to-person robotics segment is projected at roughly $2.9 billion in 2026, according to Future Market Insights, and is expected to grow at a 14.1% compound annual growth rate through 2036. That’s faster than the broader warehouse automation market, which itself is on a tear, with estimates ranging from $27 billion to $46 billion in 2026 depending on the research firm.

Why AutoStore Keeps Winning Deals

AutoStore isn’t the only goods-to-person technology on the market. Exotec, Symbotic, Ocado, and Attabotics all compete in various forms of automated storage and retrieval. But AutoStore has built an installed base that’s hard to ignore: approximately 1,950 systems running across 60-plus countries as of mid-2026, with more than 300 installations in North America alone.

Several things explain the traction.

Density. The cube storage design stacks bins on top of each other with no aisles, no wasted vertical space, and no gaps. In urban areas or expensive real estate markets, that density translates directly to cost savings. You can fit the equivalent of a 200,000-square-foot manual warehouse into 50,000 square feet of cube storage.

Modularity. Unlike a conveyor-heavy system that requires months of reconfiguration to scale, AutoStore grids can be expanded by adding more bins, more robots, or more workstations. When seasonal demand spikes, you add robots. When it drops, you redeploy them. Lululemon’s facility was clearly designed with this in mind. 525 robots across 292,000 bins gives them headroom to add capacity without ripping out infrastructure.

Reliability. AutoStore reports 99.8% uptime across its installed base. The robots are relatively simple mechanically (they move on tracks, lower a gripper, lift a bin) and the grid itself has no moving parts. When a robot needs maintenance, another one takes over the route. There’s no single point of failure.

Speed to deploy. Traditional automated warehouses with conveyor sortation, shuttle systems, or crane-based AS/RS can take 18 to 24 months to commission. AutoStore installations typically go live in 6 to 12 months. For a retailer like Lululemon that broke ground in 2023, the roughly three-year timeline from construction start to full operation makes sense when you factor in the building itself.

The Cross-Border Wrinkle Nobody’s Talking About

Here’s the part of the Lululemon story that makes supply chain professionals wince. Five of the company’s eight distribution centers sit in Canada, and the majority of its U.S. e-commerce orders are fulfilled from those Canadian facilities. That was a cost-effective model when de minimis exemptions allowed goods under $800 to enter the U.S. duty-free.

That exemption is gone.

The Trump administration’s elimination of de minimis, combined with broader tariff actions, cost Lululemon $275 million in gross profit during fiscal 2025. That’s not a rounding error. For context, the company’s total revenue was around $10.6 billion that year. A $275 million hit to gross profit from trade policy alone is enough to reshape network strategy.

This is exactly the kind of scenario that makes automation investments more, not less, attractive. If you’re going to absorb tariff costs on cross-border fulfillment, you need every other part of the operation running as efficiently as possible. Higher picks per hour, fewer errors, faster cycle times, and lower labor cost per unit shipped all help offset the trade policy headwinds. The Brampton DC’s automation isn’t just about speed. It’s about margin protection.

And it raises a question that other retailers fulfilling across borders should be asking: does your distribution network still make sense under the current tariff regime? For some, the answer will be reshoring fulfillment to the U.S. For others, like Lululemon, it’s doubling down on automation to make the cross-border model work despite higher costs.

What This Means for Mid-Market Companies

It’s easy to look at a 1-million-square-foot facility with 525 robots and think this only applies to companies with Lululemon’s budget. That’s not quite right.

AutoStore’s modular design means you don’t need to start with 292,000 bins. Smaller installations with 20,000 to 50,000 bins and a few dozen robots are common in mid-market deployments. The technology scales down as well as it scales up.

The economics have shifted, too. Labor costs in warehousing have climbed steadily since 2020, with average wages for warehouse workers up more than 25% in many markets. Turnover rates in distribution remain stubbornly high, often exceeding 40% annually. Every percentage point of turnover carries recruiting, training, and productivity costs that compound over time.

For a mid-market distributor or 3PL running 100,000 to 300,000 square feet, GTP automation is increasingly penciling out at 2- to 4-year payback periods. That’s within the range most CFOs will approve, especially when the alternative is competing for labor in a market that shows no signs of loosening.

The integrator ecosystem has matured as well. Element Logic, Swisslog (which has delivered more than 400 AutoStore projects), and a growing network of regional partners mean companies don’t need to manage the integration themselves. Implementation has become more turnkey than it was even three years ago.

The Bigger Picture

Lululemon’s Brampton DC is part of a larger pattern. Prologis, the world’s biggest logistics warehouse operator, just reported that second-quarter lease signings hit a record 67 million square feet, with net absorption in the U.S. at the highest level since 2022. The warehouse market is heating up, and automation is a major driver.

Companies aren’t just building bigger warehouses. They’re building smarter ones. AutoStore’s spring 2026 product announcement introduced VersaAI, a robotic picking capability powered by AI models trained for warehouse environments. The direction is clear: today’s GTP systems deliver bins to humans; tomorrow’s will also handle the picking.

For supply chain leaders evaluating their next move, the Lululemon deployment offers a few takeaways worth remembering. Goods-to-person automation works at massive scale. The technology is proven, with nearly 2,000 installations worldwide. Modularity means you can start smaller and grow. And in a world where tariffs, labor costs, and customer expectations are all moving in directions that punish inefficiency, the cost of not automating is starting to exceed the cost of doing it.

The robots aren’t coming. They’re already on the grid.

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The post 292,000 Bins and 525 Robots: What Lululemon’s New DC Reveals About Where Warehouse Automation Is Heading appeared first on Veridian.

“This is not rocket science technology,” Steiner told the Senate Committee on Homeland Security. “This is not technology that doesn’t exist. This is technology that exists that other companies use.”

He’s right. And that gap between what’s possible and what most organizations actually do with visibility technology tells a bigger story. The supply chain visibility market has matured past the point of simply answering “where is my shipment?” The real question in 2026 is what happens next, and the best platforms are starting to answer that on their own.

Visibility Used to Be a Dashboard. Now It’s an Operating System.

For years, supply chain visibility meant tracking numbers and status pages. You’d punch in an order ID, see “in transit,” and hope for the best. If something went wrong, you found out when a customer called to complain.

That model broke under the weight of modern supply chains. Companies now manage thousands of SKUs across dozens of carriers, multiple modes of transport, and warehouse networks spanning continents. A single shipment from a factory in Shenzhen to a retail store in Dallas might touch five carriers, two ports, three warehouses, and a last-mile delivery provider. Knowing the shipment left the port isn’t enough when the container is sitting on a chassis at the rail yard 200 miles from its destination.

The global supply chain management software market is projected to hit roughly $184 billion by the end of 2026, according to industry estimates. A significant chunk of that growth is coming from visibility platforms that have evolved well beyond basic tracking. Gartner’s latest supply chain technology trends report, published just last week, identified what it calls “physical AI” (the combination of sensors, IoT, and AI-driven decision-making) as one of the top technology priorities for supply chain leaders this year.

From Tracking to Triggering

The shift happening right now is from passive visibility to active execution. Instead of a dashboard that shows you a red dot on a map, the new generation of platforms detects the problem, assesses the impact, and either recommends or automatically takes corrective action.

Consider what this looks like in practice. A temperature-controlled pharmaceutical shipment is moving from a distribution center in Memphis to a hospital system in Chicago. Traditional visibility tells the shipper the truck left Memphis at 6 a.m. and should arrive by 2 p.m. Modern visibility, by contrast, monitors the trailer’s internal temperature every 30 seconds via IoT sensors, cross-references the route against weather data and traffic patterns, and calculates a dynamic ETA that updates continuously.

If the temperature rises above the acceptable threshold, the system doesn’t just flag it on a dashboard. It alerts the driver, notifies the receiving dock, checks whether a backup shipment can be rerouted from a closer warehouse, and updates the customer’s order management system. All within minutes, often before any human even knows there’s a problem.

Project44, a visibility platform that Gartner has named a Magic Quadrant Leader for five consecutive years, rebranded its core offering as a “Decision Intelligence” platform in 2025. The naming is intentional. The company processes over 1.5 billion shipments annually for brands in CPG, automotive, retail, and manufacturing, and it’s positioning the platform not as a tracking tool but as an operational brain that ingests visibility data and outputs decisions.

They’re not alone. FourKites, Overhaul, and Tive are all pushing in the same direction, layering predictive analytics and automated workflows on top of raw location data.

What’s Actually Making This Possible

Three technology trends converged to make this shift work:

IoT sensors got cheap and connectivity got better. Five years ago, putting a cellular-enabled sensor on every pallet was cost-prohibitive for most shippers. Today, smart labels from companies like Sensos cost a fraction of what they used to, require minimal infrastructure, and track shipments across all modes of transport (ocean, air, rail, and road). The falling cost of sensors means companies can move from tracking containers to tracking individual cases or even items.

Cloud integration layers matured. The dirty secret of supply chain visibility has always been data fragmentation. Your TMS knows about transportation. Your WMS knows about warehouse inventory. Your OMS knows about customer orders. But nothing talked to anything else. Modern visibility platforms sit on top of these systems, pulling data via APIs and normalizing it into a single view. This isn’t glamorous work, but it’s what makes the “decision intelligence” layer possible. You can’t make smart decisions with partial data.

AI moved from prediction to prescription. Early AI applications in supply chain were predictive: here’s when your shipment will probably arrive, here’s the likelihood of a delay. Useful, but still reactive. The newer applications are prescriptive: given this delay, here’s what you should do about it, and here are three options ranked by cost, speed, and risk. Some platforms are starting to execute those decisions automatically for low-risk scenarios, with human approval required only for high-stakes exceptions.

The USPS Problem Is Everyone’s Problem

What makes the USPS story relevant beyond government logistics is that their visibility gap mirrors what most companies face, just at a different scale. Steiner pointed out that the Postal Service struggles with visibility at handoff points, specifically when third parties handle package pickups or when customers drop packages at a post office themselves. Once the Postal Service’s own infrastructure takes over, tracking works reasonably well.

This is the universal challenge. Supply chains break at handoffs. The shipment leaves your warehouse with full visibility, then enters a carrier’s network where tracking is spotty, then arrives at a cross-dock facility where it sits unscanned for hours, then gets loaded onto a last-mile vehicle with a different tracking system entirely. Each handoff is a visibility black hole.

The USPS is attacking this with Bluetooth beacons embedded in test packages to identify bottlenecks, bidirectional cameras to track container movements within facilities, and reinforced scan compliance through employee training. These are fundamentally the same tools that private sector companies are deploying, just applied to a government agency that processes 127 billion pieces of mail annually.

What This Means for Supply Chain Leaders

If you’re running a supply chain operation and your visibility technology still consists of tracking numbers and periodic status updates, you’re not just behind the technology curve. You’re leaving money on the table.

Companies with strong real-time visibility respond 2 to 3 times faster to disruptions than those relying on manual tracking and phone calls. That speed translates directly to lower detention and demurrage charges, fewer expedited shipments, better inventory positioning, and higher customer satisfaction scores.

But the technology alone isn’t enough. The organizations getting the most value from visibility platforms are the ones that have done the unsexy integration work first: connecting their TMS to their WMS to their OMS, establishing clean data pipelines, and defining the business rules that tell the system what actions to take when exceptions occur.

Start with the handoffs. Map every point in your supply chain where a shipment moves from one system, carrier, or facility to another. Those are your visibility gaps. Then work backward from there: what data do you need at each handoff, what system provides it, and what should happen automatically when something goes wrong?

The goal isn’t to build the perfect dashboard. It’s to build a system that makes the dashboard unnecessary for 90% of your shipments, because the platform is handling exceptions before anyone needs to look at them.

Conclusion

Supply chain visibility has quietly undergone a transformation from a reporting function to an operational one. The USPS investing in Bluetooth beacons and cameras, Project44 rebranding as a Decision Intelligence platform, Gartner highlighting physical AI as a top trend: these are all signals pointing in the same direction. The next generation of visibility technology doesn’t just tell you what happened. It tells you what to do about it, and increasingly, does it for you.

The companies that treat visibility as a strategic capability (not just a compliance checkbox or a customer service tool) will have a measurable advantage in speed, cost, and resilience. And the ones still refreshing a tracking page and hoping for the best? They’ll keep finding out about problems the old-fashioned way: when the customer calls.

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The post Supply Chain Visibility Isn’t Just About Tracking Anymore appeared first on Veridian.

AlixPartners’ 2026 U.S. Consumer & Executive Home Delivery Survey, now in its 14th year, dropped a stat that would have been unthinkable five years ago: 55% of retailers now use carriers outside the traditional UPS, FedEx, and USPS group. More than a third have actively moved volume away from the incumbents. This isn’t experimentation anymore. It’s a structural shift in how goods get from warehouse to doorstep.

The question isn’t whether last-mile carrier diversification is happening. It’s whether your supply chain is set up to take advantage of it.

The Pressure That Broke the Old Model

Consumers got faster. That’s the short version. The longer version involves years of Amazon conditioning shoppers to expect two-day (or same-day) delivery at zero cost. AlixPartners found that shoppers now expect free delivery in an average of 2.7 days, down from 3.5+ days in prior survey years. For grocery and food items, that number drops to 0.9 days. Nearly a day.

Here’s the part that should worry any retailer still running a single-carrier playbook: 94% of consumers say free shipping impacts their purchase decisions, and nearly 70% say it has a “great impact.” Over 20% of demand is at risk when timing expectations aren’t met. Customers don’t write angry emails about slow shipping. They just buy from someone else.

Meanwhile, delivery costs keep climbing. 83% of retailers in the survey reported that home delivery costs rose year-over-year, and 64% said home delivery isn’t accretive to profitability compared to in-store sales. You’re spending more to deliver packages that make you less money than a walk-in customer. That equation forces you to find efficiencies wherever they exist.

For most retailers, carrier diversification is where they found them.

What Multi-Carrier Actually Looks Like in 2026

The term “alternative carrier” covers a lot of ground these days. It’s not just about swapping FedEx for some scrappy regional player. Retailers are building layered delivery networks that match the right carrier to the right shipment based on geography, speed requirements, and cost.

Regional parcel carriers are the biggest story here. OnTrac now covers roughly 70-80% of the U.S. population across 31+ states after a series of expansions. In their core service areas, they deliver an average of 1.9 days faster than the national carriers, with seven-day delivery and cost savings typically running 10-35%. That’s not a marginal improvement. For a retailer shipping thousands of parcels daily from a West Coast fulfillment center, those savings compound quickly.

Then there’s Veho, which takes a different approach entirely. Their app-based driver network has posted 99%+ on-time delivery performance with a 4.9 out of 5 customer satisfaction rating. Macy’s, Sephora, and Lululemon all use them. The results are hard to argue with: brands using Veho report 40% higher customer lifetime value and 70% fewer delivery-related refunds. When the delivery experience becomes a brand differentiator, the carrier becomes a marketing asset.

GLS US is quietly expanding from its Western U.S. stronghold into Texas and beyond, often delivering a full day faster than nationals in their lanes.

Gig and crowdsourced delivery represents the other major shift. Dollar General runs same-day delivery through Uber Eats from more than 14,000 locations. Best Buy uses the same platform across 800+ stores for electronics and appliances. Home Depot pulls from Uber Eats, DoorDash, and Instacart simultaneously for same-day and bulky-item delivery. Old Navy, Pacsun, and Camping World have similar setups.

These aren’t pilot programs. They’re core fulfillment channels handling real volume.

Over 90% of retailers now use a carrier mix, according to AlixPartners, and roughly a third use four or more carriers. The single-carrier model is functionally dead at scale.

The Reliability Flip

Here’s something that shifted between last year’s survey and this one: reliability has overtaken price as the top carrier-selection criterion for retailers. That’s a meaningful change. For years, procurement teams optimized carrier contracts around cost per package. Now they’re optimizing around delivery consistency.

The logic makes sense when you look at the consumer data. 84% of shoppers say the delivery experience influences their future shopping decisions. A cheap carrier that misses windows or damages packages costs you the customer, not just the shipment. The math changes when you factor in customer lifetime value instead of just per-package rates.

This is also why Amazon consistently leads consumer carrier preferences for timeliness and package condition. Whatever you think about Amazon’s broader market impact, they’ve trained consumers to expect delivery precision. Every other retailer is benchmarked against that standard whether they like it or not.

FedEx has responded to this environment by edging ahead as the most-cited primary carrier among retailers in the survey, at roughly 35-38%. UPS remains competitive, but the incumbents are both dealing with the same reality: they need to justify premium pricing against regional carriers that are faster in their lanes and gig platforms that can deliver from stores in hours.

What This Means for Supply Chain Technology

Carrier diversification sounds straightforward. Use more carriers. But operationally, it’s a technology problem.

A single-carrier setup needs a single integration, one set of label formats, one tracking feed, one claims process. A four-carrier setup needs all of that multiplied by four, plus intelligent routing logic to decide which carrier gets which package based on destination, service level, package dimensions, and cost.

This is where Transportation Management Systems (TMS) and multi-carrier shipping platforms become non-negotiable. You need automated carrier selection that evaluates options in real time. You need unified tracking across carriers so your customer service team isn’t checking four different portals. You need rate-shopping that factors in actual delivered cost, not just the base rate.

AI is entering this space aggressively. AlixPartners notes that AI is a high-priority investment area for retailers focused on ETAs, routing optimization, failed-delivery reduction, and predictive tracking. When you’re routing across multiple carriers and fulfillment nodes, machine learning models that predict carrier performance by lane and time of week become a real competitive advantage.

The retailers getting this right aren’t just diversifying carriers. They’re investing in the orchestration layer that makes diversification work at scale.

How Retailers Are Managing the Cost Squeeze

Even with carrier diversification reducing per-package costs, the overall economics of home delivery remain brutal. That 64% of retailers saying home delivery isn’t profitable compared to in-store sales tells you something about the structural challenge.

Retailers are responding with a mix of tactics. 56% now require minimum order values for free shipping, and half of those have raised the threshold recently. About 22% combine paid membership programs with minimum-order requirements. There’s also a renewed push toward in-store pickup and returns as a way to avoid last-mile costs entirely.

The smartest operators are using these levers together. A customer ordering $15 worth of product might see a shipping fee or a suggestion to pick up in-store. A customer ordering $75 gets free shipping routed through the lowest-cost carrier for their ZIP code. A customer who needs something today gets same-day through a gig platform at a premium.

That level of segmentation requires both the technology stack to execute it and the carrier network to support it. Neither works without the other.

Where This Goes From Here

Some forecasts project that Amazon plus alternative carriers will surpass the combined parcel volume of UPS, FedEx, and USPS by 2027. Whether that timeline proves accurate or not, the direction is clear. The Big Three aren’t going away, but their share of the last-mile market is shrinking as retailers build more flexible delivery networks.

USPS is accelerating this shift by opening its last-mile network of 18,000+ delivery units to external bidders through a formal process that kicked off in early 2026. That adds another option to an already crowded field.

For supply chain leaders evaluating their carrier strategy, the takeaway from AlixPartners’ survey is straightforward. Last-mile carrier diversification isn’t a logistics experiment or a procurement tactic. It’s becoming the operational backbone of competitive retail fulfillment. The technology to manage it exists today. The consumer expectations demanding it aren’t going to soften. And the retailers who build these networks now will have a structural cost and service advantage that compounds over time.

The days of negotiating one carrier contract and calling it a strategy are over. They’ve been over for a while. The survey just put a number on it.

Conclusion

The 55% figure from AlixPartners represents a tipping point. When more than half of retailers have moved beyond the Big Three for last-mile delivery, we’re not talking about early adopters or edge cases. We’re talking about the new default.

The winning playbook combines regional carriers for cost and speed advantages in their lanes, gig platforms for same-day and store-based fulfillment, and nationals for coverage where alternatives don’t reach. All of it tied together by technology that makes routing decisions automatically and tracking visible to the customer regardless of which carrier has the package.

If you’re still running a single-carrier or dual-carrier strategy, the gap between your delivery economics and your competitors’ is widening every quarter.

The post Why 55% of Retailers Are Moving Beyond UPS and FedEx for Last-Mile Delivery appeared first on Veridian.

In the span of two weeks this June, three announcements made the shift impossible to ignore. Nestlé opened a $330 million automated distribution center in California. Burlington cut the ribbon on a 2-million-square-foot facility in Georgia packed with 25 miles of conveyor. And Kimberly-Clark confirmed it’s halfway through a $3 billion productivity program anchored by ground-up automated facilities. These aren’t incremental upgrades. They’re replacements for the way distribution has worked for decades.

The Retrofit Trap

Here’s the problem with retrofitting automation into buildings that weren’t designed for it: you’re always compromising.

Ceiling heights limit what ASRS cranes can do. Column spacing dictates where conveyors can run. Floor load capacities restrict how much weight automated systems can handle. Electrical infrastructure wasn’t sized for the power demands of modern robotics. And network connectivity, the backbone of any automated system, gets layered on top of wiring that was designed for fluorescent lights and phone lines.

The result? Companies spend millions on automation projects that deliver 40% or 60% of their potential because the building itself becomes the bottleneck. It’s like putting a racing engine in a minivan. You get some improvement, but the chassis holds everything back.

What’s different about the current wave of investment is that companies have stopped tolerating that compromise. They’re spending more upfront to build facilities where the automation isn’t an addition. It’s the foundation.

Nestlé’s $330 Million West Coast Bet

When Nestlé opened its 700,000-square-foot distribution center in Arvin, California, earlier this month, the company was explicit about what made it different from a retrofit.

“This is the first new build where these capabilities were intentionally designed into the operations from the ground up,” a Nestlé spokesperson told Supply Chain Dive.

The facility houses the largest automated storage and retrieval system in Nestlé’s global network. Laser-guided vehicles move product through the building. Layer-picking robotics handle the kind of mixed-SKU palletization that used to require teams of workers. The $330 million price tag is part of Nestlé’s plan to invest $25 billion in U.S. operations over a decade.

But the investment doesn’t exist in isolation. It comes alongside 16,000 job cuts globally, with 4,000 of those in supply chain and manufacturing roles. The company is targeting $3.8 billion in cost reductions by the end of 2027. The Arvin facility is how those numbers start to connect: you build the automation first, then you restructure the workforce around it.

The Arvin center joins a $675 million beverage factory and distribution center Nestlé opened in Glendale, Arizona, last year. Two purpose-built automated facilities in two years. That’s not experimentation. That’s a strategic direction.

Burlington’s Off-Price Automation Machine

Burlington’s new distribution center in Ellabell, Georgia, tells a different version of the same story. At 2 million square feet, it’s twice the size of the retailer’s next-largest facility. It features more than 25 miles of conveyor, automated sortation systems, custom software, and workstations designed specifically for Burlington’s off-price business model.

That last detail matters more than it might seem. Off-price retail operates on speed. Product assortments rotate constantly. Merchandise needs to move from truck to store floor faster than in traditional retail because the inventory mix changes weekly. Burlington’s previous distribution infrastructure was built for a different tempo.

“Our new distribution centers are designed for higher productivity and faster turnaround times,” EVP and Chief Supply Chain Officer Greg Shultz said.

Burlington isn’t stopping at Georgia. A second 2-million-square-foot facility in Buckeye, Arizona, is planned for fiscal year 2028, with the same automation-first approach. The company currently operates seven distribution centers, opened approximately 115 new stores this fiscal year, and clearly recognized that its legacy distribution network couldn’t keep pace with that growth rate.

The decision to build purpose-built rather than lease and retrofit reflects a math problem that more companies are solving the same way. When your business model depends on speed and you’re opening 100-plus stores a year, the cost of a constrained, patched-together distribution center compounds every quarter.

Kimberly-Clark’s $2 Billion Supply Chain Overhaul

Kimberly-Clark’s approach adds another dimension to the trend. The Kleenex maker is midway through a $3 billion productivity enhancement program, and its supply chain is delivering the biggest gains.

The company’s investment includes $1 billion split between an automated distribution center built directly into its factory in Beech Island, South Carolina, and an advanced manufacturing facility in Warren, Ohio. The South Carolina DC will use robotics, AI-powered logistics systems, and optimized storage in a facility that already manufactures “almost every product” Kimberly-Clark offers.

By co-locating automated distribution with manufacturing, Kimberly-Clark eliminates an entire layer of logistics. Product doesn’t need to be shipped from a factory to a separate DC, stored, then shipped again. It moves from production line to automated storage to outbound truck with fewer touches, fewer miles, and fewer delays.

CFO Nelson Urdaneta pointed to three drivers of supply chain productivity: simplifying the value stream, optimizing the network, and scaling automation. The South Carolina investment hits all three simultaneously. And the company expects the productivity gains to accelerate starting in 2027, when the facility reaches full operational capacity.

There’s also the Kenvue merger angle. Kimberly-Clark expects to drive logistics savings by combining distribution with its merger partner, since K-C trucks typically cube out at 50% while Kenvue trucks weigh out at 50%, and both deliver to many of the same locations. Shared distribution infrastructure means fewer half-empty trucks.

What’s Actually Driving This Wave

The common thread isn’t technology for technology’s sake. It’s three pressures that hit simultaneously.

Labor economics have permanently shifted. Warehouse labor costs have risen 20% to 30% since 2019 in most U.S. markets, and turnover rates in distribution remain stubbornly high. Building a facility that requires 300 workers instead of 800 isn’t just cheaper on day one. It insulates operations from a labor market that swings wildly by season and geography.

The automation technology has matured. Five years ago, ASRS systems were expensive and inflexible. Today, modular designs from vendors like Symbotic, Dematic, and Knapp allow companies to start with core functionality and expand. Layer-picking robots that used to cost millions now come in configurations that pay back in 18 to 24 months. The ROI math has moved from “maybe” to “obviously.”

Speed requirements have ratcheted up. Consumer expectations, retail competition, and the shift toward omnichannel fulfillment all demand faster throughput. A manually operated DC processing 5,000 cases per hour can’t compete with an automated one pushing 25,000. When your competitor builds for speed and you’re still retrofitting, you’re not just slower. You’re structurally disadvantaged.

What This Means for the Industry

The gap between companies that build purpose-built automated facilities and those that keep patching legacy DCs will widen quickly. Nestlé, Burlington, and Kimberly-Clark aren’t outliers. They’re front-runners in a wave that includes Hershey leveraging decision-intelligence software and automated delivery-unit assembly, Walmart investing $8 million in a Texas DC remodel, and dozens of mid-market companies evaluating their first major automation investments.

For 3PLs, the pressure is equally real. Brands that invest in proprietary automated distribution gain capabilities that third-party providers struggle to match. It’s a build-versus-buy decision that increasingly tilts toward building, at least for companies with the volume to justify it.

The question for supply chain leaders isn’t whether to automate. That debate ended years ago. The question is whether to keep squeezing incremental gains from retrofitted facilities or commit to the ground-up approach that Nestlé, Burlington, and Kimberly-Clark are betting billions on.

Based on the numbers these companies are reporting, the answer is getting clearer by the quarter.

The post CPG Giants and Retailers Are Spending Billions on Purpose-Built Automated Distribution Centers. Here’s What Changed. appeared first on Veridian.

That milestone, announced during Walmart’s Q1 2027 earnings call in May, would have been a headline-grabbing novelty two years ago. Today it’s something else entirely: proof that drone delivery has crossed the gap between “interesting demo” and “repeatable logistics operation.” Walmart and Alphabet’s Wing are now expanding to seven new metro markets, with a target of 270-plus delivery locations by 2027. The days of treating drones as a PR stunt are over. This is becoming real infrastructure.

The Numbers Behind the Expansion

Walmart’s drone delivery footprint currently spans 66 locations across four states: Texas, Georgia, North Carolina, and Arkansas. That’s already larger than most people realize. But the expansion plan announced in early June takes things to a different level.

Seven new metro areas are on the board for 2027 launches:

• Philadelphia
• Phoenix
• San Diego
• San Francisco Bay Area
• Salt Lake City
• New Orleans
• Memphis

When these markets go live, Walmart and Wing will operate in nearly 20 U.S. metros. The stated goal is to reach over 40 million residents with drone delivery access by 2027.

The growth trajectory tells its own story. Of the 1 million total drone deliveries Walmart has completed, roughly 40% happened in the most recent quarter alone. That’s not linear growth. That’s an acceleration curve that suggests the operational model is working and customers are coming back for repeat orders.

Wing CEO Adam Woodworth has been public about the repeat usage data. “Our work with Walmart has shown that drone delivery isn’t just a novelty, it’s a service many customers count on multiple times per week,” said Heather Rivera, Wing’s chief business officer. That kind of repeat behavior is the signal that separates a gimmick from a genuine fulfillment channel.

What Makes This Different From Past Drone Hype

The supply chain industry has heard drone delivery promises before. Amazon announced Prime Air back in 2013. Google’s Wing project started around the same time. For years, both companies flew demo routes, posted slick videos, and generated headlines without much to show in terms of real commercial volume.

So what changed?

Three things converged. First, FAA regulations caught up. In March 2026, Wing received approval to fly drones after sunset, extending the delivery window significantly. Beyond-visual-line-of-sight (BVLOS) approvals have also expanded, allowing drones to cover larger service areas from each launch point.

Second, the technology matured. Wing’s drones now hit speeds of 60 miles per hour and handle a range of items up to about five pounds. That covers a surprising amount of the typical convenience or grocery basket: over-the-counter medications, snacks, phone chargers, cooking ingredients, baby supplies. The drone doesn’t need to carry a family’s full weekly grocery haul. It just needs to handle the “I need this in the next hour” orders that currently eat up the most expensive last-mile capacity.

Third, and this is the part that gets supply chain operators’ attention, the economics started working. Industry estimates peg the cost of a drone delivery at around $2 per drop, compared to $8 to $12 for a traditional last-mile van delivery. Even accounting for the infrastructure needed (launch pads, charging stations, maintenance), the per-delivery cost advantage is significant at scale. That’s why Walmart’s acceleration matters. Volume is what makes the unit economics viable.

The Store-as-Fulfillment-Hub Model Gets Another Layer

Walmart’s drone delivery program doesn’t operate from standalone drone centers. It launches directly from Walmart stores. That’s an important detail because it reinforces the retailer’s broader strategy of converting its 4,700-plus U.S. stores into multi-purpose fulfillment nodes.

The same store that serves walk-in shoppers, fills online grocery pickup orders, and stages deliveries for van-based last-mile routes now also functions as a drone launch site. Each new fulfillment channel layered onto the store’s existing operations improves asset utilization without requiring new real estate.

This model gives Walmart a structural advantage that pure-play e-commerce competitors can’t easily replicate. Amazon has been building out its own drone delivery through Prime Air, but it’s working from a much smaller physical footprint of fulfillment centers and delivery stations. Walmart’s store network gives it ready-made launch points already positioned within a few miles of residential customers.

For supply chain planners, this is worth watching closely. The economics of micro-fulfillment look very different when you can layer drone delivery on top of existing store-based operations instead of building out dedicated infrastructure from scratch.

What This Means for the Broader Market

The drone delivery market is projected to reach roughly $5 billion globally in 2026, according to Fortune Business Insights, with growth rates in the 20% to 40% range annually through the end of the decade. North America currently holds about 35% of the global market share, driven largely by Walmart/Wing, Amazon Prime Air, and a handful of healthcare and logistics players.

But the real market impact won’t show up in drone delivery revenue alone. It will show up in how drone availability changes consumer expectations and, by extension, how retailers and distributors have to rethink their fulfillment networks.

If 40 million Americans can get a five-pound order delivered in 30 minutes by drone, what does that do to demand patterns for traditional last-mile delivery? What happens to the math on dark stores and micro-fulfillment centers when a drone can cover a 10-mile radius from an existing store? How do inventory positioning algorithms need to change when a new delivery channel with different speed, cost, and capacity characteristics enters the mix?

These aren’t theoretical questions anymore. They’re planning decisions that supply chain teams at major retailers will need to work through in the next 12 to 18 months.

The Operational Challenges Nobody’s Talking About

For all the momentum, drone delivery still has real constraints. Weather is the obvious one. High winds, heavy rain, and extreme heat all ground drones, creating capacity uncertainty that doesn’t exist with van-based delivery. In markets like Phoenix (summer temps above 115°F) and New Orleans (hurricane season), weather-driven downtime could be a significant operational factor.

Payload limitations matter too. Five pounds handles a lot of convenience items, but it cuts out anything heavy or bulky. That means drone delivery will likely remain a complementary channel rather than a replacement for van-based delivery for the foreseeable future.

Then there’s the airspace coordination question. As multiple retailers and delivery providers scale up drone operations in the same metro areas, managing low-altitude airspace will get complicated. The FAA’s current framework handles the early-stage volumes, but it will need significant expansion to accommodate the kind of density that Walmart’s 270-store target implies.

And labor dynamics will shift. Drone delivery reduces the need for last-mile drivers but increases demand for drone operators, maintenance technicians, and the software engineers who keep the whole system running. It’s a different workforce, not necessarily a smaller one.

Where This Fits in the Fulfillment Stack

The smartest way to think about drone delivery isn’t as a replacement for anything. It’s as a new layer in the fulfillment stack, sitting alongside ship-from-store, curbside pickup, same-day van delivery, and traditional parcel shipping.

Each channel has a different cost profile, speed capability, and item constraint. The retailers and distributors that win will be the ones whose order management systems can intelligently route each order to the right channel based on real-time cost, capacity, and customer expectations.

That’s where the WMS and OMS integration challenge gets interesting. Today’s warehouse management and order management systems weren’t designed with drone dispatch as a native fulfillment option. As drone delivery scales, software vendors will need to add drone-aware allocation logic, airspace-aware delivery promising, and real-time drone fleet management into their platforms.

Walmart has the engineering resources to build this in-house. Most retailers don’t. That creates an opportunity for supply chain software vendors who move early to add drone delivery orchestration to their platforms.

Conclusion

Walmart’s 1 million drone delivery milestone is more than a round number for a press release. It’s evidence that drone delivery has found product-market fit in retail logistics. The 40% quarter-over-quarter acceleration, the expansion to seven new metros, and the path to 270 stores by 2027 all point in the same direction: this channel is scaling.

For supply chain leaders, the time to start thinking about how drone delivery fits into your fulfillment strategy isn’t “someday.” It’s now. The technology works. The economics are improving. And the retailers who figure out multi-channel fulfillment orchestration first are going to have a hard-to-replicate advantage.

The drone isn’t replacing the truck. But it’s absolutely joining the fleet.

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For years, Amazon built one of the largest logistics networks on the planet to serve itself. Now it’s selling that capacity to everyone else. And for supply chain leaders evaluating their transportation strategy, the question isn’t whether Amazon will change LTL freight. It’s how fast.

From Internal Tool to Open Platform

Amazon’s freight ambitions didn’t appear overnight. The company launched Amazon Relay, a warehouse check-in app for truck drivers, back in 2017. A year later came a load board. LTL services followed in 2019, though they only covered inbound shipments to Amazon’s own facilities.

The network quietly grew. By 2025, Amazon was moving millions of pallets within its U.S. network. Its fleet expanded to over 80,000 trailers, 24,000 intermodal containers, and more than 100 aircraft. The infrastructure was already there, built for Amazon’s relentless delivery speed targets. The LTL expansion simply opens the doors.

The new service covers palletized shipments of one to six pallets, between 150 and 15,000 pounds. Shippers can now send freight to third-party warehouses, distribution centers, retail partners, or any domestic destination. Real-time GPS tracking, automated scheduling, electronic proof of delivery, and sensor-equipped trailers come standard.

“We kept hearing the same thing from shippers: ‘I need LTL that performs like my full truckload service,'” said Jim Ruiz, director of Amazon Freight, in the announcement.

This follows an even bigger move from May 2026, when Amazon opened its entire supply chain network to all businesses through Amazon Supply Chain Services. That program bundles freight, distribution, warehousing, and fulfillment into one package. The LTL expansion is the latest piece snapping into place.

Why the Market Reacted So Sharply

The stock sell-off wasn’t just about Amazon entering LTL. Traditional carriers have been priced at premium valuations throughout 2026, with some running up more than 60% year-to-date on expectations of a rate upcycle. Amazon’s announcement forced investors to reconsider the durability of those gains.

Here’s the tension. Amazon currently operates roughly 30 terminals for its LTL service, concentrated heavily in the Eastern U.S. with expanding Western metro coverage. Compare that to FedEx Freight’s 365-terminal network or Old Dominion’s 250+ service centers. On paper, Amazon isn’t close to matching that footprint.

Analysts largely agreed on this point. Deutsche Bank’s Richa Harnain told investors that Amazon’s network isn’t yet that of a “formidable full-fledged nationwide asset-based operator.” TD Cowen’s Jason Seidl argued the offering will mostly compete in the economy three-to-four-day segment and take share “on the margins.”

But one analyst broke from the pack. Morgan Stanley’s Ravi Shanker warned that Amazon “has repeatedly demonstrated an ability to gain traction in transportation markets through a flexible and iterative operating model,” and that even an asset-light approach could strike at the “moat” anchoring the entire LTL bull thesis.

That warning resonates because we’ve seen this playbook before. Amazon Web Services started as spare computing capacity. Amazon Logistics began as a supplement to UPS and FedEx. Both became dominant forces in their markets. The pattern is consistent: build for internal use, refine at massive scale, then open to external customers with a cost and technology advantage that incumbents struggle to match.

The Technology Gap That Matters Most

Strip away the fleet sizes and terminal counts, and the real competitive advantage is technology. Amazon’s freight platform is built on the same infrastructure that powers its e-commerce logistics, meaning real-time visibility, predictive routing, automated capacity optimization, and tight integration with existing supply chain tools.

For shippers, this translates into a meaningfully different experience from traditional LTL. Most legacy carriers still rely on manual processes for appointment scheduling, paper-based proof of delivery, and limited shipment visibility once freight leaves the origin terminal. Amazon’s offering includes sensor-based monitoring, automated scheduling, and GPS tracking as baseline features, not premium add-ons.

This technology-first approach also gives Amazon a structural cost advantage. Its freight network was built to support its own delivery operations, meaning the fixed infrastructure costs are already absorbed. Selling excess capacity to external shippers generates incremental revenue at margins that legacy carriers, burdened with decades of terminal leases and union labor agreements, can’t easily replicate.

The integration with Amazon Supply Chain Services adds another layer. Shippers using Amazon for warehousing, fulfillment, or distribution can now add LTL freight as a seamless extension. That end-to-end visibility across the supply chain is something few traditional carriers can offer, and it’s increasingly what enterprise shippers demand.

What This Means for Supply Chain Leaders

If you’re managing transportation for a mid-to-large enterprise, Amazon’s LTL expansion deserves attention, but not an immediate overhaul. Here’s a practical framework for thinking through the implications.

Evaluate your economy LTL spend first. Amazon’s current service is best suited for cost-sensitive, non-time-critical shipments. If you’re spending heavily on economy-tier LTL with three-to-four-day transit times, Amazon’s pricing and technology could offer meaningful savings. Get quotes and run a pilot on a subset of lanes.

Don’t abandon your core carrier relationships yet. For expedited, time-definite, and specialty freight, legacy carriers still hold clear advantages in terminal density and service coverage. Amazon’s 30-terminal footprint can’t match the geographic reach of carriers with 200+ service centers. That gap will narrow over time, but it’s real today.

Watch the integration story. The most compelling long-term play isn’t Amazon’s LTL service in isolation. It’s the full Amazon Supply Chain Services bundle. If your company already uses Amazon for any part of its supply chain, whether warehousing, fulfillment, or parcel delivery, adding LTL freight creates a unified visibility platform that’s hard to replicate with a patchwork of traditional providers.

Pressure your current TMS. Regardless of whether you use Amazon, this announcement raises the bar on what shippers should expect from their transportation technology. Real-time tracking, automated scheduling, and sensor-based monitoring shouldn’t be differentiators. They should be table stakes. If your current carrier’s technology feels outdated, this is the forcing function to demand upgrades or evaluate alternatives.

The Bigger Picture: Platform Logistics Is Here

Amazon’s LTL expansion is part of a broader shift in how freight moves through the supply chain. We’re transitioning from an industry organized around specialized carriers (each handling one leg of the journey) to one where platform companies offer integrated, end-to-end solutions.

This mirrors what happened in cloud computing. Companies used to run their own data centers, then rented capacity from specialized hosting providers, and eventually consolidated onto platforms like AWS that offered compute, storage, networking, and dozens of other services in one place. The freight industry is following a similar arc.

Amazon isn’t the only company pursuing this strategy. Flexport has been building an integrated freight forwarding platform. Convoy (before its shutdown) tried to apply marketplace dynamics to trucking. And traditional 3PLs like XPO and C.H. Robinson are investing heavily in technology to defend their positions. But Amazon brings an asset base, technology stack, and customer relationship that no other player can match.

For supply chain leaders, the takeaway is straightforward. The carriers that survive and thrive over the next decade will be the ones that can compete on technology, visibility, and integration, not just on terminal count and lane coverage. Amazon’s entry into open LTL freight didn’t create that reality. It just made it impossible to ignore.

Conclusion

Amazon’s decision to open its LTL network to all shippers marks one of the most consequential moves in freight transportation in years. The immediate impact may be modest, given Amazon’s limited terminal footprint and focus on economy-tier service. But the trajectory is clear, and the technology advantages are real.

Supply chain leaders don’t need to rip up their carrier contracts tomorrow. But they should be running pilot programs, benchmarking Amazon’s rates against current providers, and, most importantly, using this moment to raise expectations for what transportation technology should deliver. The companies that treat this as a signal to accelerate their own digital transformation will be better positioned regardless of how quickly Amazon scales its freight operations.

The freight industry just got its AWS moment. The only question is who adapts and who gets left behind.

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