Guest Post: Rita’s Italian Ice and Seasonality

Prof. Howard Weiss shares his interest in Italian ice with us today, March 20th, the first day of Spring.

Rita’s Ice represents an example of seasonal operations, illustrating both the challenges and opportunities due to demand variability. Founded in 1984 in a Philadelphia suburb, the company has expanded to nearly 600 franchises across 463 cities in 30 states, becoming the largest Italian ice franchise in the U.S. Despite this growth, Rita’s core product offerings—Italian ice and frozen custard—remain strongly associated with warm-weather consumption. 

Most Rita’s locations operate as walk-up or drive-through outlets, opening by March 1 and closing no earlier than the third Sunday in September. This operational model results in an important inefficiency: franchisees incur fixed costs, particularly rent, for all 12 months while generating revenue for only about seven. Supplement 7 of your Heizer/Render/Munson textbook suggests developing complementary products with countercyclical demand– such as  jet skis and snowmobiles– thereby using the same resources all year long.

However, Rita’s appears to be considering an alternative approach—extending operations year-round. This shift reflects evolving consumer behavior, as frozen desserts such as ice cream increasingly exhibit steady demand even in colder months, particularly in warmer climates or high-traffic retail environments like shopping malls. By remaining open throughout the year, Rita’s could better leverage its fixed assets and enhance brand visibility. But this strategy would require careful demand forecasting and possibly localized adaptation, as consumer preferences in colder regions may still exhibit too much seasonal sensitivity to make it worthwhile to open all year.

From a production standpoint, Rita’s must also manage perishability constraints. Cream, a primary ingredient in frozen custard, necessitates reliance on local distributors to ensure freshness. Additionally, custard is discarded after 36 hours, underscoring the importance of accurate short-term demand forecasting and inventory control. Rita’s maintains a consistent gelato formula across franchises, it offers over 60 flavors, rotating them based on popularity data. This approach balances operational consistency with responsiveness to consumer preferences.

Finally, beginning in 1984, Rita’s has marked the beginning of Spring by offering free Italian Ice. This longstanding tradition on the first day of spring—March 20 this year—serves as an effective promotional tool. The initiative not only marks the seasonal reopening of many locations but also reinforces brand loyalty and drives customer engagement.

Classroom Discussion Questions:

  1. Name two products or services with complementary seasonal demands. 
  2. How would you determine if the demand for ice cream is high enough in the winter to warrant staying open all year?

 

OM in the News: FedEx Is Planning an AI Agent Workforce

FedEx is building out an army of AI agents to work alongside its human workforce, positioning itself to tap the latest wave of technology crashing through corporate America, reports The Wall Street Journal (March 13, 2026).

The shipping giant, which already deploys artificial intelligence in software development and other areas, is now looking to drive AI agents further into operations, including network planning and business processes. By 2028, FedEx expects to have AI integrated into more than half of its core operational workflows.  FedEx is currently focused on setting up the underlying data and management foundation to oversee its AI bots.

Though logistics providers like FedEx are aiming to adopt AI, they’re grappling with challenges like managing numerous, disconnected data sources. “Logistics can be very fragmented—especially if you think of a global organization with their network being everywhere, it makes it difficult to standardize,” said an industry consultant.

As its underlying tech is completed, FedEx expects to roll out AI and AI agents that connect macro and microeconomic trends to better plan its network. In marketing and campaign management, FedEx will create a hierarchy in which there’s a “manager agent,” an “audit agent” and a “worker agent.” The goal of the hierarchy is to ensure that the agents have a trail of accountability for their actions.

At the moment, FedEx’s enterprise data platform, called Atlas, supports more than 200 AI use cases across the supply chain, commercial teams and enterprise functions. It has already turned on AI agents in areas such as software development, where they are developing and testing code. In operations, agents are helping customers clear customs more quickly.

Plans for FedEx’s AI agents also involve getting its humans ready to interact with the technology. the company just launched an AI education program for 300,000 of its employees, as well as a more advanced version for its technology workers. Each employee received a customized training depending on their role. FedEx says it doesn’t plan for those agents to replace its workers.

Classroom discussion questions:

  1. Why is FedEx pushing for more AI agents?
  2. How will agents be used in operations?

OM Podcast #47: Leadership and Continuous Improvement

In our latest podcast, Barry Render interviews John Dyer, a well‑known speaker, consultant, and expert in continuous improvement, and the author of The Façade of Excellence: Defining a New Normal of Leadership. With over 40 years of experience—including roles at GE, Ingersoll Rand, and years of consulting across manufacturing, government, and nonprofit sectors—John brings a depth of practical insight that leaders at every level can learn from.

In this episode, Barry and John discuss:

  • What operational excellence really means beneath the surface
  • Why so many continuous improvement initiatives fail after 12–18 months
  • The psychology behind middle‑management resistance
  • The shift from “manager” to “coach” as the core leadership evolution
  • How empowerment really works
  • How AI will reshape teamwork, decision‑making, and PDCA cycles
  • Real‑world examples of fully empowered, high‑performance teams

This is an outstanding conversation for instructors, operations leaders, and students who want an honest, experience‑grounded perspective on building sustainable cultures of excellence.

 

TRANSCRIPT LINK
A Word document of this podcast will download by clicking the word Transcript above.

John Dyer
Prof. Barry Render

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 our newest episodes as soon as they’re released!

Instructors: assignable auto‑graded exercises using this podcast are available in MyLab OM. To learn more, view our earlier blog post featuring Chuck Munson or contact your Pearson representative: Find your rep

 

OM in the News: The Robotics Supply Chain

The next 20 years are not just about making robots better, but also about how they will be used in all sorts of industries, from small tests to big factories. The real challenge is having specialized engineering skills, great manufacturing, and dominating software,  reports Industry Week (March 11, 2026). 

There are 6 key areas that make all the difference in this industry.  Here is a breakdown of the cost of the parts that go into a robot:

1. Actuators & Gearboxes (35-40%): The physical muscle.

2. Robot Structure / Manipulators (15-20%): The physical frame and integration.

3. Sensors & Perception (10-15%): The eyes and ears.

4. AI Compute / Control (10-15%): The operational brain.

5. Battery / Power Systems (10-15%): The energy storage for mobile units.

6. Precision Motion Components (5-10%): The components required for fine movements.

This list shows that a robotics breakthrough isn’t just software advances; it depends on physical components and the supply chains that produce them. But there are 3 chokepoints (bottlenecks).

 #1: Precision Reducers, controlled by Japan. Robots can’t move with a lot of power and precision without special parts (harmonic and cycloidal reducers). Two companies in Japan make 70% of these parts used all over the world. Spending more money won’t allow other companies to make these parts, because they need special knowledge about metals and years of experience making precise parts.

 #2: AI Compute (The Intelligence Standard), controlled by the  U.S. Today’s robots, especially those that use reinforcement learning, need powerful computers to work properly. NVIDIA’s CUDA system has become the leading platform used by robots that learn and think. Making a better chip is not enough if you can’t replace the software that all robotics engineers already use.

#3: Battery Supply Chain, controlled by China.  Robots are changing from big, stationary machines to mobile ones. This means batteries are now a crucial part of making them work. One company in China, CATL, controls 1/3 of the world’s battery market. China has a very strong grip on this supply chain.

The global map of robotics is specialized. There is a multi-polar supply chain that is difficult to disrupt:

USA: “The “Brain.” (software, autonomy, AI compute).

Japan: The “Hardware King.” (motors, gearboxes, precision engineering).

Germany: The “Precision Engineer.” ( mechanical systems, high-end production).

China: The “Scale & Power.” (manufacturing speed, massive infrastructure, battery supremacy).

Taiwan: The “Linear Specialist.” ( The linear guides and ball screws essential for motion).

Classroom discussion questions:

  1. Why must operations managers understand these costs and bottlenecks?
  2. What are the supply chain implications?

Guest Post: Fast or Free? The New Tradeoff in E-Commerce Shipping

Dr. Jon Jackson is Associate Professor – Operations Management at Providence College

For years, e-commerce conditioned shoppers to expect near-instant gratification. Fast shipping became the industry standard as retailers tried to keep pace with Amazon. First, it was 2-day shipping, then next day shipping, and ultimately same day shipping. But the economics behind those fast-shipping promises are starting to crack, and retailers are quietly resetting expectations, according to a recent report in The Wall Street Journal (Mar. 6, 2026).

Shipping costs have risen sharply in recent years. Major carriers such as FedEx and UPS have increased base rates annually while adding fuel surcharges, residential delivery fees, and dimensional pricing rules. As a result, retailers are increasingly shifting their focus from “fastest delivery” to “lowest cost delivery.”
Amazon now offers customers a small discount if they choose a slower delivery date. Many other retailers have followed suit by introducing “no-rush” shipping that may take a week or longer.
Interestingly, customers appear willing to wait. McKinsey surveyed over 1,000 people in 2024, and speed of delivery dropped from the #1 priority in 2022 to the #5 priority in 2024. Meanwhile, the cost of delivery maintained its high priority, with more than 95% of surveyed shoppers saying that they prefer free standard shipping instead of paying for faster shipping.
Longer delivery windows help logistics networks operate more efficiently. When retailers promise delivery in 5-7 days instead of two, carriers can consolidate shipments onto fuller trucks, lowering the cost per package. Some retailers even encourage customers to choose delivery days later in the week when shipping networks are less congested.
Another unexpected benefit: fewer returns. Retailers report that extending delivery times leads to more intentional purchases and significantly lower return rates. The era of “fastest possible shipping” may not be ending, but it is becoming just one option among many.
Classroom Discussion Questions
  1. If customers say they prioritize low shipping costs over speed, how should retailers redesign their fulfillment and delivery strategies?
  2. Do you think slower shipping could become the new norm in e-commerce, or will competition eventually push retailers back toward faster delivery times? Why?

OM in the News: Bringing Mac Mini Production Stateside

Apple just announced a significant expansion of its Houston manufacturing operations, confirming that production of the Mac mini will move to the U.S. for the first time as part of a broader investment in advanced manufacturing and AI infrastructure. The move will also see Apple expand AI server production at the Texas site and open a new Advanced Manufacturing Center, initiatives that together are expected to create thousands of jobs.

The decision marks a notable shift in the company’s global manufacturing strategy, writes Yahoo Finance (Feb. 28, 2026). The move follows a wider trend among technology firms seeking to diversify supply chains and expand domestic production capacity, particularly in high-value electronics manufacturing.

Alongside Mac mini production, Apple is ramping up output of advanced AI servers at the Houston site, an initiative that began in 2025. The expansion reflects Apple’s growing investment in AI infrastructure, an area that has become central to both consumer devices and cloud services.

Beyond hardware production, Apple is also investing in workforce development with the launch of an Advanced Manufacturing Center in Houston. The facility will provide hands-on training in advanced manufacturing techniques. The center will train students, supplier employees, and manufacturers in processes used in Apple’s own production lines. Apple engineers will teach how U.S. manufacturers can adopt new technologies and improve efficiency,  strengthening the domestic manufacturing ecosystem while building a pipeline of skilled workers.

Apple’s expansion comes amid a broader push to localize manufacturing in North America, driven by supply-chain resilience concerns, geopolitical tensions, and government incentives. Bringing Mac mini production home signals that high-tech consumer electronics assembly—traditionally concentrated in Asia—may increasingly be split across multiple regions. Meanwhile, Apple’s investment in AI server production reflects surging demand for data-center hardware as AI applications expand.

By combining Mac mini assembly, AI server production, and advanced manufacturing training, Apple is positioning Houston as a key node in its global supply chain—while signaling a deeper commitment to U.S. manufacturing capacity. As reshoring momentum continues, Apple’s move could encourage other electronics manufacturers to consider similar strategies, particularly for high-value or strategically important products.

Classroom discussion questions:

  1. Why is Apple reshoring this particular product?
  2. Why is it difficult to bring manufacturing of high-tech products home?

 

Guest Post: Martin Guitars and Operations

Prof. Howard Weiss, retired from Temple U., illustrates his wide range of interests.

Martin is a guitar manufacturer that began operations in 1833. Martin specializes in acoustic guitars which account for about half as many guitars as electric guitars in the global guitar market. It is one of the most popular brands along with Fender, Gibson, Yamaha, Ibanez and Taylor.  

Location: Martin began its operation in Manhattan. In 1839 Martin opened a plant in Nazareth PA, 90 miles due west of its NYC plant. In 1989 Martin opened a plant in Sonora, Mexico in order to make guitars that were more affordable. It is worth noting that two of Martin’s competitors, Fender and Taylor guitars also have plants in Mexico. These guitars are commonly referred to as MIM (Made in Mexico). See Ch.8.

Capacity: Martin has made over 3 million guitars since its inception, including one million since 2016. It currently produces a total of 500 guitars per day, 6 days per week, at the two plants. (See Supp. 7)

Forecasting: Clearly demand has been increasing. Martin’s forecasting needs to consider historical and causal analysis (see Ch. 4) since certain events can spike or drop the sales. For example, sales increased more than usual during the folk music craze and also when MTV was running its Unplugged series (featuring acoustic guitars). At first, COVID caused a decline in sales due to cancelled concerts and closed stores. But then there was an increase in demand, especially for beginner guitars since people were looking for activities while at home and could order guitars online.

Supply Chain: The supply chain (Ch. 11) begins in the forest and at the lumber facilities both in the U.S. and India.

Layout: Martin uses process layout–see Ch.7. Most of the work is done by hand but there are robots in the factory.

Safety: With all of the woodwork that is being performed the major safety concern is that of sawdust.

Quality Control: The incoming wood is inspected by humans because machines cannot pick up defects in the wood. Each guitar is checked for tone. The guitar gets put in a case, but then sits for 4 days and then undergoes rigorous testing to make certain the guitar parts, e.g. neck, bridge, tuning pegs, still work. (See Ch. 6).

Classroom Discussion Questions

  1. How could Martin use the Quality Control techniques discussed in Ch. 6 of your text book?
  2. What are some possible reasons Martin relocated from Manhattan to Nazareth, PA?

OM in the News: The Top 10 Most Dangerous Jobs in America

Every 104 minutes, the Bureau of Labor Statistics (BLS) says an American worker loses their life on the job. While some of us might consider a bad day at work to be a crashed computer or a long class or meeting, thousands of Americans face life-or-death stakes every day they begin their jobs.  From the peaks of skyscraper steel to the depths of the Pacific Northwest forests, here are the 10 most dangerous jobs in the U.S. today, according to Industrial Safety & Hygiene News (Feb, 26, 2026)

1. Logging Workers

Fatality Rate: 98.9 per 100,000 workers. Primary Cause of Death: Contact with objects/equipment (falling trees).  The Hazard: Falling trees and heavy machinery

2. Fishing and Hunting Workers

Fatality Rate: 86.9 per 100,000 workers.  Primary Cause of Death: Transportation incidents (drowning/capsizing).  The Hazard: Drowning and vessel capsizing

3. Roofers

Fatality Rate: 51.8 per 100,000 workers.  Primary Cause of Death: Falls to a lower level.  The Hazard: Gravity.

4. Refuse & Recyclable Collectors

Fatality Rate: 41.4 per 100,000 workers. Primary Cause of Death: Transportation (struck-by vehicle).  The Hazard: Being struck by passing motorists.

5. Aircraft Pilots & Flight Engineers

Fatality Rate: 31.3 per 100,000 workers.  Primary Cause of Death: Crashes in small aircraft.  The Hazard: Mechanical failure or weather in bush/regional flying

6. Construction Helpers

Fatality Rate: 27.4 per 100,000 workers.  Primary Cause of Death: Falls and exposure to harmful substances.  The Hazard: “The Fatal Four” (Falls, Struck-by, Caught-in, Electrocution)

7. Heavy & Tractor-Trailer Truck Drivers 

Fatality Rate: 26.8 per 100,000 workers.  Primary Cause of Death: Transportation incidents (roadway collisions).  The Hazard: Highway collisions and fatigue

8. Grounds Maintenance Workers

Fatality Rate: 20.5 per 100,000 workers.  Primary Cause of Death: Falls and landscaping equipment.  The Hazard: Equipment entanglement and heat stroke

9. Agricultural Workers

Fatality Rate: 20.2 per 100,000 workers.  Primary Cause of Death: Transportation and contact with machinery.  The Hazard: Tractor rollovers and silo entrapment

10. Iron and Steel Workers

Fatality Rate: 19.8 per 100,000 workers.  Primary Cause of Death: Falls, slips, and trips.  The Hazard: Falls and swinging heavy loads.

 

As we see, logging is the most dangerous profession by a massive margin. Logging workers are nearly 33 times more likely to die on the job than the average worker. The national average across all jobs is 3.3 per 100,000 workers.

While ” Construction Helpers” are No. 6, the broader construction industry saw the highest total number of deaths (1,032), even if their per-capita rate is lower than loggers. Nearly 11% of fatal falls result from a height of 30 feet or higher.

Classroom discussion questions:

  1. Ergonomics is an important part of job design (see Chapter 10 of your Heizer/Render/Munson text). How could it be used to improve safety in these jobs?
  2. Can the physical environment be changed to make any of the jobs safer?

 

 

Guest Post: Food Processing Ingredients

Prof. Howard Weiss shares his insights monthly. Howard created the Excel OM and POM software that we provide free with our book.

A recent Philadelphia Inquirer article (February 19, 2026) reports that “The grandson of the inventor of Reese’s Peanut Butter Cups has lashed out at the Hershey Co., accusing the candy company of hurting the Reese’s brand by shifting to cheaper ingredients in many products.” 

In prior years consumers expressed dissatisfaction when Nutella reduced the amount of cocoa in its product. One reason for the change in the recipes for these two products is the high cost of cocoa. Clearly, a change in a recipe will affect inventory, material (ingredient) costs, and the supply chain.

The most infamous recipe change is probably “New Coke” which was introduced in 1985. Consumer backlash forced Coke to revert to its original recipe. Recently, Coke announced it will add a new product made with cane sugar rather than corn syrup.

Food taste and recipes can vary for a number of legitimate reasons. The recipe for Twinkies was changed in order to extend its shelf life from 25 days to 45 days. Butterfinger took an alternative approach and double-wrapped its candy. Several food processors have changed recipes in order to eliminate certain food dyes or additives or reduce sodium, including Kraft Macaroni and Cheese and Turkey Hill ice cream.

The same product may have a different recipe for sales at bulk stores rather than supermarkets. Colas may have a different amount of corn syrup in bulk stores.

Sometimes recipe changes are inadvertent. In one case consumers complained about the taste of meals they cooked using 4C Italian Bread Crumbs. 4C investigated and found that trace amounts of cinnamon were in the bread crumbs and should not have been. There are many examples of bacteria being in processed food which would affect the health of the person eating the food. This is different. There is a processing problem but it will NOT cause health issues just taste issues.

The repercussions of food quality are different than the repercussions of food safety. Food safety problems can lead to recalls, liabilities, brand damage and penalties. Failure to maintain taste can result in brand damage and product returns.

Classroom discussion questions:
1. Identify other products in which change resulted in complaints or safety issues.

2. What are the main changes these days to food products?

 

OM Podcast #46: Logistics, Circularity & Vertical Integration at East Penn Manufacturing

In our latest podcast episode Barry Render and Misty Blessley speak with Harry Ziff, VP of Corporate Logistics at East Penn Manufacturing, one of the world’s largest lead‑battery producers. Harry shares highlights from his 37‑year supply chain career and explains how East Penn’s unique structure allows it to excel in reliability, sustainability, and customer service.

Harry discusses East Penn’s deep vertical integration, including in‑house lead refining, plastic molding, and battery case manufacturing. He also describes the company’s closed‑loop recycling system, where nearly 100% of batteries are collected, processed, and reused.  The episode also dives into East Penn’s large private fleet, which enables direct‑store delivery, consistent service, and strong customer relationships.

TRANSCRIPT LINK
A Word document of this podcast will download by clicking the transcript link above.
Prof. Misty Blessley
Prof. Barry Render
Harry Ziff

 

 

 

 

 

Have you subscribed to this podcast on Apple Podcasts?
Go to your Apple Podcasts app, search “Heizer Render Munson OM Podcast,” and subscribe to get new episodes as soon as they’re released!

 

OM in the News: One Way to Power New AI Data Centers

Where is the energy to power the hundreds of new data centers that are popping up to run artificial intelligence demands coming from? “In the battle for AI dominance, every engine of the economy is getting recruited into the fight—including jet engines'” writes The Wall Street Journal (Feb. 18, 2026). 

Jet engines are a natural fit. Power equipment giants GE Vernova, Siemens Energy, and Mitsubishi Heavy Industries  already sell power turbines—known as aeroderivatives—that are modeled after these very jet engines. Aircraft engine companies such as GE Aerospace , Howmet Aerospace and Woodward also sell land-based aeroderivative turbines or components.

Yet designing the turbine, which keeps as much of the original jet engine features as possible, is a roughly 18-month undertaking.  Instead, it only takes 30 to 45 days to convert a plane’s jet engine to a power-generating turbine. (There are 2 main modifications to convert an aircraft engine to a land-based natural gas turbine. One is replacing the fuel nozzles to utilize natural gas instead of jet fuel. The other is replacing the large fan on the front of the flight engine with a much smaller fan).

Retired aircraft, at an Air Force base near Tucson, Ariz

A company can remanufacture jet-engine parts with a few years of remaining life for use in power turbines, where they can operate for many additional years. Narrow-body jet engines experience higher stress from repeated takeoffs and landings. Power turbines can run as peakers—turning on only when demand surges—or continuously as baseload. Either way, they accumulate less wear and tear.

About 1,600 commercial aircraft engines are retired every year. If a third of those engines get converted into turbines, that would represent about 13 GW of capacity, or more than a quarter of the existing global natural gas turbine capacity.

AI-obsessed tech giants are planning to spend more than $700 billion in capital expenditures this year. The lure of that cash pile will generate a lot of creativity in the power sector.

Classroom discussion questions:

  1. Why is there a need to convert jet engines?
  2. Discuss the growth of data centers and the demands they create. (See our recent post on that topic.)

Guest Post: FedEx Network 2.0– The Real-World Challenges of Facility Closures and Location Strategy

Dr. Jon Jackson is Associate Professor of Operations Management  and the MSBA Director in the School of Business at Providence College.

In 2022, FedEx announced its “Network 2.0” initiative, designed to streamline and integrate the resources of its Express, Ground, and Freight operations. This project was initially estimated to cost $2 billion, would result in the closure of 100 stations, and was targeted for completion by fiscal year 2027.

As of this month, February, 2026, FedEx has closed more than 200 stations, with projections indicating a total of 475 closures by the end of 2027 as part of the Network 2.0 initiative. This accounts for nearly 30% of the company’s facility footprint across the United States and Canada, writes Supply Chain Dive (Feb. 13, 2026). 

As discussed in Ch. 8 (Location Strategies) in your Heizer/Render/Munson textbook, location strategy involves not only selecting new sites but also making tough calls about which existing facilities to consolidate or close. For FedEx, network streamlining was prompted by significant overlap between Express and Ground operations. Scott Ray, the COO-elect for U.S. and Canada surface operations explained, “The concept is pretty straightforward: Our customers don’t need both an Express and a Ground truck in the same neighborhood on the same day, and they don’t need to separate their Express and Ground packages for two separate pickups.”

One of the main challenges for FedEx during this transformation is maintaining high service levels amid such a significant network overhaul. The company has addressed this challenge by creating dedicated routes for high-priority services and customers, as well as factoring in market-level characteristics.

(A regularly updated list of FedEx station closures is available on Supply Chain Dive)

 

Classroom Discussion Questions

  1. FedEx has already closed twice as many stations as originally projected in 2022. What factors could have led to this outcome? Do you see this as a cause for concern, or could it indicate greater-than-expected benefits?
  2. In your local metro area, what factors should FedEx consider when deciding which stations might be closed, if any?

OM in the News: The Memory-Chip Shortage

Memory is one of the tech world’s most ubiquitous and essential components that come in 2 major types. DRAM handles more fleeting, immediate tasks like using apps. The other kind, called NAND flash memory, provides long-term storage for photos, videos and other data. And there has been a 7-fold increase in contract prices for DRAM and NAND flash in the past year.

Facing soaring memory-chip prices, the world’s biggest electronics companies are staring at a list of unpalatable responses:(1) charging consumers more, (2) eating the costs or (3) rejiggering product specs. Such is the supply-chain disruption wrought by the global drive into AI, which requires fleets of data centers with servers needing gargantuan amounts of memory, reports The Wall Street Journal (Feb. 13, 2026). 

The memory crunch comes at an inopportune time for companies like Nintendo.

That has caused supply to dry up for the makers of smartphones, PCs, gaming consoles and various other electronic gadgets, and triggered a historic price uptick since early last year that is higher than any increase seen before.

Dell has raised prices for some commercial laptops by as much as 30%, while budget PCs from rival Acer now carry several gigabytes less of multitasking memory. Chinese smartphone maker Xiaomi recently discontinued the lower-memory variant of its new midtier device and raised prices. To summarize: A tough year for smartphones, PCs and game consoles is getting worse. Projected shipment declines are now stumbling deeper. PCs, with memory representing as much as 30% of their total costs, are particularly vulnerable.

With investments into AI infrastructure remaining hot, the prospects of memory prices falling soon don’t appear high. Supply is expected to remain tight through 2028.

Classroom discussion questions:

  1. What is the underlying issue?
  2. What can manufacturers of PCs, smartphones, and game consoles do to protect themselves?

 

OM in the News: AI Push Is Costing a Lot More Than the Moon Landing

It’s bigger than the railroad expansion of the 1850s, the Apollo space program that put astronauts on the moon in the 1960s and the decadeslong build-out of the U.S. interstate highway system that ended in the 1970s.

We’re talking about the data centers now being built and financed by some of the world’s biggest companies in the artificial-intelligence boom. Four U.S. tech giants—Microsoft, Meta, Amazon, and  Google—are planning to spend $670 billion to build out AI infrastructure this year alone as they scramble to increase the computing power needed to operate and scale their AI-related endeavors.

And if you compare this spending to some of the biggest capital efforts in U.S. history by percentage of gross domestic product, you can see exactly how staggering the figures are, reports The Wall Street Journal (Feb. 9, 2026). In fact, it’s dwarfed only by the Louisiana Purchase, completed in 1803, which doubled the size of the U.S. and consumed 3% of the GDP.  (The AI buildout is projected at 2.1% of GDP, while railroads in the 1850s were 2%, the US highway system was 0.4%, and the Apollo space program was 0.2%).

The four companies’ capital spending has been increasing as a percentage of their annual revenue the past few years. In 2026, Meta’s spending could amount to more than 50% of its sales for the first time ever.

How is this build-out an OM issue? First, as we discuss in Chapter 2, these four companies are betting that they will attain competitive advantage by competing on low-cost and response. Second, our chapter on sustainability (Supp. 5) points out the costs of carbon footprints, which data centers generate heavily. Third, as we note in the chapter on location strategies (Ch. 8), the centers locate where power is cheap and plentiful.

As of late 2025, Northern Virginia has 64 data centers under construction, solidifying its position as the world’s largest data center market. The region hosts over 550 existing facilities.  They consume massive amounts of power, comparable to the total usage of large states like Minnesota.

Classroom discussion issues:

  1. Discuss the plusses and minuses of this massive construction trend.
  2. What do the builders hope to obtain?

Good OM Reading: Supply Chains as a Source of Competitive Differentiation

A new report from the Kearney consulting group (Feb. 4, 2026), called The Top Five Supply Chain Bets for 2026, concludes that as customers punish inconsistency faster than ever, companies that can deliver reliability will expand market share. Kearney offers this analysis:

This forces a shift from one supply chain to a portfolio of capabilities designed around distinct value propositions including speed, reliability, customization, cost-to-serve, and compliance. Where commercial commitments are made in isolation from operations, the consequences surface later through margin erosion, excess inventory, and lost customers.

Supply chain becomes the operating core of the customer promise, and leadership must be explicit about where it will overperform and equally clear about where performance ambition can be more modest by design.

Leading organizations are becoming more deliberate about how they serve each channel, market, and customer, including the trade-offs required and their operational implications. Align those choices with differentiated supply chain capabilities for each segment and translate them into targets for the core KPIs (service, cost, cash, risk). Finally, leverage the integrated planning and execution process to deliver consistently against those objectives.

Another area of concern is AI as it moves along the continuum from experimentation to earnings impact. Kearney offers the following analysis:

In 2026, many pilots will fail to progress beyond experimentation. The root causes are predictable: unclear value cases, poor data quality, fragmented technology stacks, and pilots that were never designed to scale.

AI in supply chains needs to be treated as an industrial capability, with clear ownership, governance, monitoring, and integration into day-to-day processes. Organizations that remain in experimentation are accumulating prototypes and skepticism, while those that focus are translating AI into measurable improvements in cost, cash, service, and risk.

Leading organizations are managing AI use cases as a portfolio, with explicit scale and stop gates. A small number of use cases that materially affect service, cost, cash, or risk are being industrialized, while others are time-boxed with clear exit criteria. Investment is concentrating on priorities with the highest enterprise impact, including decision speed, resilience, and sharpening competitive supply chain advantage.

Classroom discussion questions:

  1. How might AI be used in supply chain management?
  2. Why does Kearney think supply chains are becoming the source of competitive differentiation?