OM Podcast #44: Inside the Cold Storage Industry with Dr. Anna Johnson

Happy New Year!  In our first episode of 2026, Professors Barry Render and Misty Blessley sit down with Dr. Anna Johnson, Vice President of Marketing and Commercial Strategy at U.S. Cold Storage, to explore the fascinating world of temperature-controlled logistics.

Dr. Johnson explains how third-party logistics providers keep America’s food supply safe and efficient, why 98% of U.S. food storage is outsourced, and how sustainability initiatives like anaerobic digestion are reducing food waste.

Prof . Misty Blessley
Prof. Barry Render

The conversation also dives into industry trends—from the surge in capacity during COVID to the current state of the market—and highlights how AI, robotics, and digital twins are transforming operations, and creating new roles for skilled workers in this evolving sector.

Dr. Anna Johnson

 

Read the full transcript

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OM in the News: AI Is Mining Our Trash for Treasure

Here’s a job the computers can take without much complaint: sorting recyclables. For humans, it is a foul, laborious job that entails standing over a conveyor belt, plucking beer cans and detergent bottles from a stream of refuse. The job pays little and is hard to fill.

At one recycling facility near Hartford, machines are taking over the dirtiest jobs, reports The Wall Street Journal (Jan. 8, 2026). A few workers remain on the line, mostly to watch for hazardous items. Otherwise, the system of conveyors, magnets, optical sorters and pneumatic blocks runs largely unmanned. The technology allows them to sort up to 60 tons an hour of curbside recycling into precisely sorted bales of paper, plastic, aluminum cans and other materials. The material is sold to mills, manufacturers and remelt facilities, which pay more for cleaner bales.

AI is used to instantly spot recyclables and send instructions to machinery down the line at to remove them.

Watching over it all are computers that analyze material as it passes by at 7 mph. The devices use AI to identify recyclables, flag food-grade material, gauge items’ mass, assess market value and calculate points at which a robotic claw might best clasp each piece.

 The U.S. 50% aluminum tariff has lifted demand for scrap metal, while pulp mill closures have left box makers more reliant than ever on old corrugated containers. And consumer goods companies want to reclaim their bottles as states adopt extended producer responsibility laws aimed at reducing plastic pollution.

Part of the problem: Americans’ poor recycling habits are an obstacle to profit. A lot of beer cans and delivery boxes never even make it to sorting centers. A study in Virginia’s waste stream showed that 28% was recyclable, yet the system was stuck at a recycling rate of about 7% no matter how much it spent trying to teach people how and what to recycle.

The big breakthrough in recycling technology has been combining vision recognition systems with pneumatic blocks. Using puffs of air to separate items has proved much faster and more accurate than robotic pickers, which are limited to about 40 items a minute, compared with thousands for pneumatic system.

Classroom discussion questions:

  1.  Why has recycling been so inefficient?
  2. Should job loss through automation be a concern?

OM in the News: PepsiCo Turns To Digital Twins To Rethink Plants

We posted recently about the joint nuclear fusion digital twin work of Siemens and NVIDIA. Today’s news is that PepsiCo is working with the same two firms  to change how it designs, tests, and expands its plants and warehouses using AI and digital twins. “Physical industries are entering the age of AI. For companies with real-world assets, digital twins are the foundation of their AI journey,” said NVIDIA’s CEO.

By modeling factories and distribution centers digitally before making physical changes, PepsiCo hopes to cut down on costly mistakes while improving speed and capacity.

With AI-driven digital twins, teams can simulate plant layouts, equipment movement, and supply chain operations in detail, reports SupplyChain (Jan. 7, 2026). Instead of expanding facilities the old way, which can be slow and expensive, they can test changes virtually and see what works before spending money on physical upgrades.

“The scale and complexity of PepsiCo’s business is massive—and we are embedding AI throughout our operations to better meet the increasing demands of our consumers and customers,” said PepsiCo’s CEO. The digital models recreate machines, conveyors, pallet routes, and even worker movement, helping teams spot problems early and test different setups in weeks instead of months.

By finding bottlenecks and unused capacity in a virtual setting, teams increased throughput by 20%. The same approach has also shortened design cycles and helped cut capital spending by 10-15%. Testing ideas digitally first, teams can plan ahead, compare options, and move faster without the usual surprises that come with physical expansion.

Classroom discussion questions:

  1.  How is PepsiCo employing digital twins?
  2. How do AI and digital twins work together?

OM in the News: Digital Twins and Nuclear Fusion

Digital twins, which we cover in Module F (Simulations and Digital Twins), is a big topic at Nvidia and Siemens as they work together to make nuclear fusion a commercial reality. In that chapter (see p. 847), we define a digital twin as:  “an electronic virtual replica of an operation that allows organizations to mimic how a product, process, or system will perform.”

Workers at Commonwealth Fusion Systems’ campus in Devens, Mass

Fusion engineers at the Nvidia/Siemens venture, called Commonwealth Fusion Systems (CFS), will use its digital twin to run simulations, ultimately to hasten the goal of producing fusion energy at a commercial scale. CFS “will be able to compress years of manual experimentation into weeks” with the AI assistance, said its CEO.

Nuclear fission, which splits atoms to produce energy, is already in use in power plants, reports The Wall Street Journal (Jan. 7, 2026).  But many companies see fusion, the energy process that powers the sun by joining atoms together, as a longer-term bet because it can provide much more energy in a cleaner process. Nuclear energy appeals to tech giants because it releases minimal carbon emissions while providing round-the-clock power—particularly as they look to fuel their AI ambitions.

CFS said it was working with Google on an AI project, and explained that that effort has created something like a co-pilot for its fusion machine, while the digital twin plan “is the virtual airplane.” Google also recently signed a power purchase agreement with CFS to secure energy from what could be the first grid-scale fusion plant.

“The race is on for AI. Everyone is trying to get to the next frontier,” said Nvidia’s CEO.

Classroom discussion questions:

  1. Provide other examples of how digital twins can be used.
  2. Why is this fusion project so important as an OM tool?

Our Top Five OM Podcasts of 2025

Our podcasts are gaining a wider and wider audience  and we are creating new ones every few weeks. In case you missed them, here are the top five of those that went live in 2025.

  1. OM Podcast #37:Global Supply Chain Vulnerabilities Professor Darrell Edwards at the U. of Tennessee shares his decades of industry experience.

  2. OM Podcast #34: An Inside Look at Tariffs  Bob O’Donnell, VP of Business Development of Life Sciences at East Coast Warehouse, who previously spent 13 years with Maersk, discusses tariffs and their potential impacts.

  3. OM Podcast #38: Editorial Leadership and the Future of  Operations Management Texas Christian University Prof. Tyson Browning  discuss Tyson’s six-year tenure as journal editor of the Journal of Operations Management, the evolving role of AI in research, and the future direction of the operations management field.

4. OM Podcast #32: Supply Chain Risk Management George Zsidisin, the Barringer Professor of Supply Chain Management at the University of Missouri – Saint Louis is author of several books on Supply Chain Risk.

5. OM Podcast #31: The Impact of AI on Jobs and the Environment  Charlie Render is President of Render Analytics, which helps businesses of all kinds implement AI.  He is also the creator of the popular job-search engine, Apply Genie (ApplyGenie.ai)

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Our Top 10 Posts in 2025

Happy and Healthy New Years from our team of coauthors–Jay, Barry  and Chuck. As we close out 2025, we wanted to share the ten most highly read posts this year.

  1. The Supply Chain of the Future— a story of the “connector states” in Asia, led by Vietnam and Cambodia
  2. Top Five Global Supply Chain Risks–which include climate change, tariffs, cybercrime, rare minerals, and forced labor
  3. How China’s BYD is Squeezing Suppliers in the EV Price War–The Chinese automaker follows the word neijuan, which refers to a situation in which people work hard and compete fiercely without anyone getting ahead.
  4. Why Is It So Difficult for Robots to Make Your Nike Sneakers?— Nike has poured millions into an ambitious effort to partly automate what has always been a highly labor-intensive industry.
  5. The U.S. Made T-Shirt–Walmart has pledged to buy more items that were made, grown or assembled in the U.S.
  6. Supply Chains and Tariffs–Some manufacturers have reconfigured supply chains by reshoring portions of  production, by nearshoring—leveraging the USMCA free trade agreement (see Ch.2) to source more from Mexico and Canada—and by growing trade with countries such as India and Vietnam, which offer cost advantages.
  7. Holy Guacamole!–Few companies can match Chipotle Mexican Grill’s avocado appetite.
  8.  U.S. Energy Independence and Manufacturing–Over the past two decades the U.S. has evolved from a degree of foreign-energy dependency that threatened its economy and national security to the premier energy producer in the world.
  9. McDonald’s Gives Its Restaurants an AI Makeover–The fast-food giant’s new initiative uses artificial intelligence to target order accuracy and help restaurants detect equipment issues before they fail
  10. Starbucks Uses New Technology to Fill Orders Faster–Starbucks says new technology is helping fix one of its customers’ biggest gripes: waiting too long for their coffee

OM in the News: 3 Core Skills for the AI Manufacturing Workforce

 Companies invest heavily in workforce development—global corporate training represents over a $350 billion market—but few can answer the fundamental question: Does our workforce actually possess the capabilities required for AI-era manufacturing? The problem, writes IndustryWeek (Dec. 16, 2025), is that firms are training for yesterday’s skills while tomorrow’s requirements remain undefined.

Manufacturing faces a dual disruption. AI, robotics and automation are reshaping production at unprecedented speed, while skilled labor shortages intensify when experienced workers retire, taking decades of knowledge with them. Most training programs rarely assess whether workers developed the fundamental capabilities needed to work effectively in AI-augmented environments.

There are the 3 Core Skills needed:

1. Human+ capability This isn’t about workers learning to code or becoming data scientists. Human+ is the ability to work effectively alongside AI and automation—knowing when to trust algorithmic recommendations, when to override them based on judgment and how to optimize human-machine collaboration for maximum productivity. Manufacturers invest millions in AI-powered quality control systems, predictive maintenance platforms, and autonomous production scheduling—then struggle to achieve projected ROI because their workforce lacks the core skills to extract value from these technologies.

2. Agentic AI orchestration As AI-era manufacturing evolves from simple automation to autonomous agents that manage complex workflows, workers need the capability to orchestrate multiple AI systems effectively. Agentic AI orchestration is the ability to coordinate these systems so they don’t work at cross-purposes. It means understanding how to deploy AI agents for quality control, predictive maintenance, supply chain optimization and production scheduling—and managing the interactions between these systems when they conflict or produce unexpected results.

3. Interoperability catalysis Modern manufacturing runs on complex networks: older machines next to new robots, ERP systems talking to manufacturing systems, logistics platforms feeding production plans, and partner data coming in from suppliers. Interoperability catalysis is the ability to make all of that actually work together:

  • Legacy and modern systems (the 40-year-old CNC and the AI-powered vision system)
  • Digital and physical environments (ERP and planning data vs. shop-floor reality)

The Path Forward: Manufacturing’s competitive advantage in the AI era won’t come from having the most advanced technology. It will come from having a workforce capable of extracting maximum value from that technology. These 3 core skills represent the foundation. Manufacturers who systematically assess and develop these capabilities will thrive as AI reshapes production.

Classroom discussion questions:

  1. Is the current workforce capable of managing AI-manufacturing demands?
  2. Are business students interested and willing to take these jobs?

Guest Post: Drinking Graywater Beer?

Prof. Misty Blessley, at Temple U., raises an interesting sustainability issue.

Every drop of water on Earth is part of a continuous cycle. The same water brewed into beer eventually  travels through wastewater systems before being treated and returned to the environment, ready to be consumed again. Gray water is defined as: wastewater from showers, baths, bathroom sinks, and washing machines, excluding toilet water (blackwater) and water from kitchen sinks/dishwashers.

A San Francisco firm, Epic Cleantec, makes this cycle explicit by brewing beer with recycled graywater from showers and laundry. Buildings globally use 15% of all potable water, yet almost none reuse it. Partnering with nearby Devil’s Canyon Brewing Company, it created two beers—Shower Hour IPA and Laundry Club Kölsch, using water purified through a multi-stage system until it meets or exceeds potable water standards. Their approach demonstrates how scarce resources can be sourced in new and innovative ways.

Reusing waste water can help counteract climate change

The supply chain implications are significant. Brewing is water-intensive, requiring several gallons of water for every gallon of beer produced. As climate volatility and drought increasingly pressure municipal water supplies, integrating recycled water helps mitigate supply risk. Pairing this with drought-tolerant barley and hops further enhances supply chain resilience by mitigating upstream agricultural vulnerabilities.

Epic Cleantec’s model represents circular economy principles in action: closing loops, recapturing resources, and turning waste streams into valuable inputs. Many other food and beverage companies are embracing similar strategies. Rubies in the Rubble (UK) creates condiments from surplus produce that would otherwise be discarded. Upcycled Foods, Inc. (U.S.) produces SuperGrain flour to make bread from spent brewing grain. Planetarians (U.S.) transforms spent yeast and soybeans into a vegan meat product that is competitively priced compared to chicken and below beef.

Epic Cleantec emphasizes the circularity of its inputs to build consumer acceptance, hoping customers celebrate the closed loop. For details on the “circular economy” see Supp. 5 of your Heizer/Render/Munson text.

Classroom Discussion Questions:
1.  Forecasting is covered in Ch 4 of the Heizer/Render/Munson textbook. How would you forecast demand for beers made with recycled graywater, given potential consumer hesitation?
2.  TQM Tools are covered in Ch 6. Which tools should the two firms use to ensure water quality and process reliability throughout treatment and brewing?

Guest Post: Target Tests New Paths to Faster, Cheaper Delivery

 

Dr. Jon Jackson is Professor of Operations Management at Providence College. Jon has created AI classroom exercises for every chapter of our text. They are found in the on-line Instructor’s Resource Manual.

Target is experimenting with new fulfillment models as it tries to reverse a multi-year sales slump and better compete with Amazon and Walmart (The Wall Street Journal, Dec. 4, 2025). With online orders now making up nearly 20% of total sales, the retailer is searching for faster, cheaper ways to deliver packages while also improving in-store conditions for shoppers frustrated by clutter, stockouts, and long wait times. To do this, Target is piloting three distinct approaches in Chicago, Cleveland, and San Diego.

Chicago: Shifting Fulfillment Away from Busy Stores
In Chicago, Target stopped fulfilling next-day, ship-to-home orders from 18 of its busiest stores. Those orders are now handled in less busy locations. The result: delivery times sped up by about a day, shipping costs dropped to the lowest level among all Target markets, and stores became cleaner, better stocked, and less chaotic for in-person customers.

 Cleveland: A Dedicated Sortation Center
Cleveland is home to a new 40,000-square-foot sortation center operated by Ryder. Stores still pick and pack orders, but the sortation center batches them by neighborhood and hands them off exclusively to Shipt drivers. This frees store teams from the labor-intensive sorting process and enables more frequent pickups than national or regional carriers typically provide.

San Diego: In-Store Sorting for Local Delivery
In markets without a sortation center (e.g., San Diego), Target is testing a lighter-weight model. Stores sort brown-box deliveries in the backroom and hand them directly to Shipt drivers for local delivery. It’s a hybrid approach that allows next-day delivery without major new infrastructure.

Classroom Discussion Questions

  1. Which model seems most scalable for Target nationally, and which seems most context-specific?
  2. How might competitors respond if one of these approaches proves highly successful?

OM Podcast #43: An Interview with Mike Rich, VP of Supply Chain at American Water

In our latest podcast episode Barry and co-host Misty Blessly welcome Mike Rich, Vice President of Supply Chain at American Water, the largest regulated water and wastewater utility in the United States.

Mike Rich

Mike shares his fascinating career journey—from managing thousands of SKUs at Home Depot to driving strategic sourcing initiatives at Arizona Public Service—and how those experiences shaped his leadership approach today. The discussion dives into:

  • Building a customer-service mindset in supply chain
  • Challenges in talent acquisition and team growth
  • Negotiation strategies and risk mitigation in procurement
  • The role of AI and Agentic AI in transforming category strategy and operations

 

Read the full transcript

Have you subscribed to this podcast on Apple Podcasts? Just open your Apple Podcasts app, search “Heizer Render Munson OM Podcast,” and subscribe to get all our episodes delivered straight to your device!

Prof. Misty Blessley
Prof. Barry Render

 

Guest Post: Omnichannel Operations–Where Technology Meets Retail Strategy

Dr. Prince Vijai is Assistant Professor of Operations at IBS Hyderabad, India. This post is based on his recent presentation at the DSI meeting in Orlando.

In today’s retail world, customers expect a smooth and unified experience across both online and offline channels. This customer expectation has turned omnichannel inventory management into a strategic necessity. By integrating supply chain management, information systems, and analytics, retailers can ensure that products are available where and when customers need them – across stores, warehouses, and digital channels.

Centralized inventory visibility is the key enabler of this unified commerce inventory strategy. Instead of managing separate stock pools, leading retailers maintain a unified view of inventory across all sales channels. This reduces overstocking, prevents stockouts, and supports flexible fulfillment options, such as ship-from-store, click-and-collect, buy online pickup in-store (BOPSIS), and dropshipping.

To achieve this omni-channel inventory visibility, real-time data synchronization is essential. Technologies like Shopify APIs and AWS Lambda update stock levels instantly as purchases occur, ensuring accuracy across systems. NoSQL databases, such as DynamoDB or Firebase, provide the scalability and speed necessary for these continuous updates.

Leading retailers clearly demonstrate the benefits of such integrated omnichannel operations. Zara uses RFID for item-level tracking, enabling rapid replenishment and online fulfillment from its stores. Nike uses a unified commerce platform to synchronize data across its physical and digital channels. Amazon exemplifies data-driven order routing and fulfillment efficiency.

As omnichannel operations mature, the role of the Omnichannel Planner is emerging. This is a professional skilled in analytics, ERP, and API integration who aligns supply with demand across channels. Such expertise ensures a balance between operational efficiency and superior customer experience.

The key omnichannel retail trends include unified commerce integration, adoption of practical generative AI, enhanced inventory visibility, flexible fulfillment options, and personalized in-store experiences. These strategies aim to strike a balance between customer value and operational efficiency, driving agility and competitiveness.

Ultimately, omnichannel inventory management represents more than just logistical coordination – it’s a foundation for business agility and customer satisfaction. Retailers mastering this capability gain a decisive edge in speed, accuracy, and trust in a competitive, data-driven marketplace.

 Classroom Discussion Questions

1.How does real-time data synchronization enhance both customer experience and retailer performance?

2. What future technologies could further improve omnichannel inventory visibility?

 

OM in the News: Salvaging Critical Minerals From Old Laptops and Phones Isn’t So Easy

While electronic waste (e-waste) seems almost infinite, from fried computers to dormant BlackBerry phones, securing discarded tech for metals recycling can be quite tricky.

Electronic waste is dropped on to a conveyor belt during a process to harvest rare earth and other metals in France.

Recycled lithium, copper and other critical minerals can find new life in everything from electric vehicles to battery storage. The push to recycle metals in the U.S. comes amid intensifying efforts to compete with China, which dominates the critical minerals market, reports The Wall Street Journal (Dec. 1, 2025).

“It’s like urban mining,”  said one industry CEO, explaining the benefits of reusing metals from old electronics and scrap waste instead of procuring it directly from the earth. “Rather than going into the mines, we go into our communities,” he said.

Collecting e-waste can be tricky because there isn’t a strong infrastructure to retrieve devices directly from homes, scrapyards, manufacturers or collection sites, and some consumers have privacy concerns when handing over old hardware that could hold personal information.

Meanwhile, large quantities of e-waste are being shipped abroad. About 2,000 shipping containers of electronic waste are sent each month from the U.S. to countries in Asia, particularly Malaysia. But the need to increase the domestic supply of critical minerals has become more urgent, as is evident in the U.S.’s near-total reliance on Chinese imports for lithium-ion batteries.

Shipping e-waste abroad rather than recycling it in the U.S. is “a tragic lose, lose, lose proposition,” said a second industry expert. “The country misses out on the value from the critical metals going to waste, as well as recycling jobs for local workers.”

Most lithium-ion batteries on the market are likely to be hazardous when they are disposed of because they could catch fire or explode if not handled carefully. The environmental footprint of lithium-ion battery recycling emits less than half the greenhouse gases of conventional mining and refinement of metals, and uses about one-fourth of the water and energy of mining.

The global consumption of lithium was estimated to be 220,000 metric tons in 2024—a 29% jump from 2023. But tech recycling in the U.S. has a long way to go. E-waste recycling collection, from relying on municipal return sites to retailer take-back programs, is irregular and fragmented, so recyclers often cannot rely on steady, predictable volumes.

Classroom discussion questions:

  1. Why doesn’t the U.S. recycle all its e-waste?
  2. Could AI help in recycling? (See Supp. 5 of your Heizer/Render/Munson text).

OM in the News: Robots Are Remaking Chinese Industry

Sam Altman wants AI to cure cancer. Elon Musk says AI robots will eliminate poverty. China is focused on something more prosaic: making better washing machines. While China’s long-term AI goals are no less ambitious than ours, its near-term priority is to shore up its role as the world’s factory floor for decades to come, reports The Wall Street Journal (Nov. 25, 2025).

Midea, an appliance maker, deploys robots to work under an AI ‘factory brain’ that acts as a central nervous system for its plant in Jingzhou.

The Chinese push is fueled by billions of dollars in government and private development– transforming every step of making and exporting goods. A clothing designer reports slashing the time it takes to make a sample by more than 70% with AI. Washing machines in China’s hinterland are being churned out under the command of an AI “factory brain.”

Port shipping containers whiz about on self-driving trucks with virtually no workers in sight, while the port’s scheduling is run by AI.

Chinese executives liken the future of factories to living organisms that can increasingly think and act for themselves, moving beyond the preprogrammed tasks at traditionally-automated factories. This could further enable the spread of “dark factories,” with operations so automated that work happens around the clock with the lights dimmed.

The advances can’t come quickly enough for China as its population is shrinking, young people are avoiding factory jobs, and pushback against Chinese exports has intensified.

AI offers a lifeline to head off those risks, by helping China make and ship more stuff faster, cheaper and with fewer workers. China wants to deploy what is available today quicker than the U.S. can, locking in any advantages. It installed 295,000 industrial robots last year, 9 times as many as the U.S. and more than the rest of the world combined. Its stock of operational robots surpassed 2 million in 2024

Today, China’s average factory wages are far higher than in countries such as India. Many young Chinese are unwilling to work in factories.  The shortage of skilled labor in key manufacturing sectors could reach 30 million this year. Since most Chinese are optimistic about AI, this allows the government to deploy the technology quickly. About 83% of Chinese believe AI-powered products and services are more beneficial than harmful, double the level in the U.S.

Classroom discussion questions:

  1. Why the push for robotics and AI in China?
  2. What can the U.S. and Europe do to remain competitive?