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?

 

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?

Guest Post: Using Solver’s Nonlinear Programming Procedure for Operations Models

Prof. Howard Weiss shares his insights on the power of Excel’s Solver.

I previously have posted for The OM Blog that in the operations course it is important to help students develop their Excel skills. Today I will introduce students to nonlinear programming in Excel’s Solver for Trend Analysis models, a topic in Chapter 4 of your Heizer/Render/Munson text. It highlights to the students exactly what is being optimized – sum of squared errors.

Trend Analysis
Example 8 from Chapter 4 illustrates the Solver process. The initial intercept of 10 and slope of 10 yield the forecasts in column D. Errors and squared errors follow from the forecasts and demands with the sum of squared errors shown in cell F12. This is Solver’s objective. The changing cells are the intercept and slope, there are no constraints, and the method in Solver is GRG Nonlinear. In addition, for least squares the “Make Unconstrained Variables Non-Negative” needs to be unchecked since slopes/trends can be negative in forecasting– although not in this example.

After solving, the solution, not displayed here, appears as Intercept 56.71, slope=10.54 (as shown in the text) and the minimum sum of squares, not shown in the text or figure above, is 773.

Guest Post: Forecasting, Inventory Management, and “No-Buy 2025”

Professor Misty Blessley at Temple U. looks at the “No- Buy” movement.

Thanksgiving is just 3 months away, and Christmas only 4, but the holidays are long upon retail supply chains. At the same time, a growing number of consumers are pushing back against the pressure to spend, embracing a movement known as “No-Buy 2025,” which is gaining serious traction.

At its core the movement is a consumer mindset focused on refraining from non-essential purchases for a set period, for some an entire year. Trending on online communities are people sharing their No-Buy challenges and success stories. Some are motivated to cut debt or save for long-term goals, while others are concerned with sustainability, minimalism, or anti- consumption values. Participation is surging, especially among millennials and Gen Zs, who are juggling inflation, student debt, and climate anxiety.

Baby boomers, in contrast, are known to possess a large portion of total disposable income and to spend on luxury and leisure items. Participants are cutting back on categories often linked to impulse spending or excess and are instead using what they have:
 Apparel and accessories
 Home décor and seasonal items
 Beauty and skincare
 Toys and impulse gifts
 Functioning electronics

Why It Matters for Supply Chains
No-Buy 2025 has a ripple effect on retail supply chains. The holiday season typically drives massive retail volume, but with intentional non-buying, companies could face missed orders if underestimating demand or excess inventory if forecasts are too high.

Many demand forecasts rely on past trends, but for some generational cohorts demand is eliminated or potentially delayed. Retailers may need to reconsider their demand planning models, where inventory is held in the network, and be aware of consumer behavior (e.g., generational preferences, while remembering that generalizations are, by nature, generalizations). Supply chains that account for today’s values will be best positioned to respond.

Classroom discussion questions:
1.  What are the shortcomings with traditional time-series and seasonality forecasting methodologies given the no-buy movement?

2. Do you think the product categories identified above should be forecasted differently when compared to one another? Why?

3. How does the purchasing power of various generational cohorts come into play?

Note: The Silent Generation (born 1928-1945), Baby Boomers (born 1946-1964), Generation X (born 1965-1980), Millennials (born 1981-1996), Generation Z (born 1997-2012), and Generation Alpha (born 2013-2024).

Guest Post: The Waffle House Index and Hurricane Milton

Professor Howard Weiss provides a timely example of qualitative forecasting.

Waffle House is a restaurant chain with over 2,000 locations in 25 states ranging from Florida as far north as Pennsylvania and as far west as Arizona, operating all day every day. When you think of a Waffle House, you think about eggs, bacon, and, of course, waffles. What you don’t think about is forecasting. The Waffle House Index is a map that Waffle House provides of the status of its restaurants.

 Red means the restaurant is closed likely due to severe damage or unsafe conditions
 Yellow indicates that the restaurant is open but only serving a partial menu. The restaurant is working off of a generator and may not have water but has the ability to cook the meals.
 Green means the restaurant is fully operational.

From the closings one can see the severity of an upcoming storm as indicated by this map captured one day before Hurricane Milton is scheduled to strike Florida. Residents can use the information to decide on their storm strategy. One can also see the damage caused after the storm based on the open or closed Waffle Houses. The use of the index is a qualitative forecasting method as discussed your textbook.

The government, including FEMA, uses different methods to track storms, including airplanes and satellite. But FEMA also began to use the Waffle House Index in 2011 to gauge the severity of any storm. Waffle House has a reputation for staying open during storms as long as or even longer than any other restaurant so that people can get a hot meal, charge cell phones or just warm up or cool down. The map is not only useful before a weather event but also afterwards since it indicates how the recovery is going in an area served by a Waffle House.

Waffle House has chosen a strategy based on keeping their restaurants open 24/7. This includes purchasing generators for their stores and using what they term as “Jump Teams”. The jump team consists of volunteers who go to the affected location by car or even plane in order to help the employees get the restaurant open as soon as possible. These teams are, of course, examples of varying the workforce and/or subcontracting as described in the Aggregate Planning chapter (Ch. 13).

Classroom discussion questions
1. What other organizations use subcontracting in the event of a storm?
2. What companies are essential to re-open as soon as possible after a storm?

OM in the News: Retreating EVs and the Impact on Supply Chains

“Ford Motor’s decision this week to kill a highly touted future electric vehicle is a sign that the industry’s pullback on EVs is deepening,” writes The Wall Street Journal (Aug. 23, 2024).  It is canceling plans for an electric SUV once touted as a “personalized bullet train.” The move added to the drumbeat of news from carmakers of delayed or scrapped investments into EV models, factories and battery projects.

Dealers’ lots are getting pretty crowded as EVs from Tesla, Ford, Mercedes, and more fail to move.

GM, VW, Mercedes and other automakers also have curbed their EV ambitions in recent months. Taken together, the walked-back plans are an acknowledgment that the big investments outlined at the start of the decade got ahead of the consumer’s appetite for a full switch to EVs.

Delaying some EV investments will conserve cash and buy automakers time to lower their battery costs and other EV-related expenses.  EV startups including Rivian, Lucid and Polestar are laying off workers, and Fisker has declared bankruptcy.

But cuts to planned EV output have hurt the parts supplier base, which has had to adjust its business. Magna, one of the world’s largest auto-parts suppliers, had been gearing up to make battery trays, seats and other parts for Ford’s now-scrapped electric SUV. Dana, another large supplier serving Ford and Stellantis, had expected sales of battery-cooling systems and other EV-related components to jump by 1/3 this year. “Like most things that are new or disruptive, a lot of times forecasts and expectations can get ahead of some of the practicalities,” said Dana’s CFO.

The cost of batteries is so high that most big automakers are in the red on their electric offerings. Ford’s EV business is on pace to lose $5 billion this year, with losses averaging $44,000 per electric vehicle sold!

Instead of offering the electric SUV, Ford plans to produce hybrid, gas-electric versions. It also delayed for a second time the opening of a new EV truck factory, the largest investment in its history, which is now set for a 2027 opening, two years later than initially planned.

New emissions rules from the Biden administration will in effect require a heavy dose of EVs in the late 2020’s. To comply, automakers will need to introduce more plug-in hybrid vehicles. Car companies are likely to focus on fully electric systems for small- and midsize vehicles, and hybrids for larger ones.

Classroom discussion questions:

  1. Why has the shift to EVs cooled?
  2.  What is the impact on 1st and 2nd tier suppliers?

MyOMLab: Simulation Updates for Fall 2024

We want to let you know that our five simulations, which students really enjoy, have gotten these valuable enhancements. If you are not using them, checkout the features. The five are: supply chain management, quality management, forecasting, inventory management, and project management.

OM Podcast #12: Data Analytics and Operations Management

Our latest podcast is all about data analytics.  Barry Render speaks with his son, Charlie Render, president of Render Analytics, about his real world experience using data analytics to solve problems around forecasting, sustainability, and quality.  Charlie shares some recommendations for students who are considering studying or about to graduate in the field of data analytics.

 

 

 

Transcript

Word of this podcast will download by clicking on the word Transcript above.

Instructors, assignable auto-graded exercises using this podcast are available in MyLab OM.  See our  earlier blog post with a recording of author and user Chuck Munson to learn how to find these, or contact your Pearson rep to learn more!  https://www.pearson.com/us/contact-us/find-your-rep.html

Guest Post: Airline Loyalty Programs and Operations Management

Prof. Howard Weiss developed the POM and Excel OM software that we provide free with our text

To use one of Delta Airline’s more than 50 Sky Club airport lounges, a client can either purchase access from Delta, or use Delta SkyMiles, or gain access by owning an American Express (Amex) Platinum credit card. One of the Platinum card’s main selling point is its extensive lounge coverage for multiple airlines. During COVID, while there was less travel and thus less miles being accumulated due to travel, customers were charging more than usual to their Amex cards, enabling them to get elite status with Delta. It also allowed SkyMiles to rollover from one year to the next during COVID. This led to Delta’s lounges becoming overcrowded. And it turns out Delta does not have enough capacity on its special phone lines to afford its elite customers a pleasant experience.

 

100 Person line waiting to enter JFK Sky Club

This capacity issue caused Delta to make changes effective in 2025 that will make it harder to access Sky Clubs, and thus reduce the crowding. Delta has raised the price of club membership for those purchasing access to the lounges, restricted membership to SkyMiles elite members, and placed a limit on how long one can stay in the lounge prior to a flight.

The Forecasting chapter in your Heizer/Render/Munson textbook discusses demand management and notes that Disney limits its “FastPass+” reservations, which is similar to Delta limiting its elite status members. But Disney can impose different limits on a daily or weekly basis based on the demand forecast, whereas Delta’s limits will be implemented over the long term. The Capacity Planning chapter (Supp. 7) notes that demand can be reduced by raising prices, which is identical to Delta’s actions of both raising the number of miles required for elite status benefits and raising prices to belong to SkyClub.

Needless to say this has caused a great deal of backlash from Delta customers. Surveys show that 81% of consumers say loyalty programs are important to their decision on which product or service to purchase. In addition, at the big five U.S. carriers, the share of revenue generated by loyalty programs increased from 12% in 2019 to 16% in 2021. Thus, Delta cannot afford to lose these customers.

Classroom discussion questions:

1. Why doesn’t Delta simply hire more staff for the lounges and the phone lines?
2. What factor besides loyalty programs would drive customers to a certain airline?

OM Podcast #8: Operations Management at Red Lobster

Welcome to a very exciting Operations Management podcast! Today, Barry Render and his guest, Executive Vice President of Red Lobster, Horace Dawson, talk about operations at Red Lobster.  They discuss the most important operations tasks to get right in any restaurant but especially the world’s largest seafood chain: forecasting, scheduling, supply chains, and quality.

 

Transcript

A transcript in Word of this podcast is available by clicking on the word Transcript above.

Instructors, assignable auto-graded exercises using this podcast are available in MyLab OM.  See our August 21st blog post with a recording of author and user Chuck Munson to learn how to find these, or contact your Pearson rep to learn more!  https://www.pearson.com/us/contact-us/find-your-rep.html

As a footnote, Horace Dawson was promoted to CEO at Red Lobster on Sept. 21, 2023.

Guest Post: New Technology, Analytical Tools and Information Sharing Help Retailers with Sales Forecasts in a Post-COVID World

Dr. Misty Blessley, Associate Professor of Statistics, Operations, and Data Science at Temple University, shares her insights with our readers monthly.

The COVID-19 pandemic changed the way people live. When viewing the demand side of a business-to-consumer (B2C) transaction, our behavior as consumers and the new normal are inextricably linked and continue to evolve. A recent Wall Street Journal article states that “merchants veered between product shortages and overstuffed inventories in rapidly changing consumer markets” as a result of the COVID-19 pandemic. But now that inventories have been worked through, companies are looking for better ways to manage the flow of goods on the fly and make sure they have merchandise where it needs to be to boost sales and maintain margins. What does this mean for post-COVID sales forecasting?

That past behavior is a good predictor of future behavior is the premise on which time- series forecasts (the topic of Chapter 4 in your Heizer/Render/Munson text) stand. Forecasts were based on known patterns of seasonality and the economic outlook over the forecast horizon. However, retailers increasingly recognize that boosting sales and maintaining margins requires them to see and respond to changes in demand as it is happening. In other words, in customer driven markets, the objective is to match the supply of merchandise to consumer demand.

Macy’s has been upgrading its forecasting abilities over the past several years with new technology

Retailers are looking to new technology and analytics that are capable of capturing trends in data that predict future demand. For example, Dr. Martens (a $1.2 billion shoe manufacturer) is currently working to leverage a new order-management system containing a customer-data platform to provide better insight into customer spending. Macy’s Department Store has benefitted from a recent forecasting system upgrade, by recognizing and responding to increasing demand for work-wear over leisure-wear. Retailers are turning to sophisticated algorithms but are also increasing their communications with suppliers as part of having merchandise where it needs to be, in lockstep response to consumer demand.

Classroom discussion questions:
1. What “new normal” could have driven the change to work wear from leisure-wear for Macy’s?
2. Who should be included in a firm’s post-pandemic sales and operations planning (S&OP) process?
3. What is the role of operations and supply chain managers in creating new forecasting methods and then monitoring, controlling, and adapting the forecasts resulting from these new approaches?

Guest Post: What Does a Super Bowl Parade Cost?

Dr. Misty Blessley, Associate Professor of Statistics, Operations, and Data Science at Temple U., shares her sports preferences with us today.

Next week, the winners of Super Bowl LVII will be honored by their hometown fans in a Super Bowl Parade. This Sunday, the Kansas City Chiefs will face off against the Philadelphia Eagles. Everyone loves a victory parade, but how does a city plan for a parade that might not happen? As a faculty member at Temple University, upon seeing the Eagles clinch the NFL Conference Championship, on Sunday, January 29th, I looked into parade operations. In 2018, the parade celebrating the Eagles’ Super Bowl LII win was held the following Thursday. Public transit was halted to Temple’s campus, which disrupted a joint event with Institute for Supply Management.

If the parade were to be held on the Thursday following Super Bowl LVII, it would disrupt a Supply Chain Management consulting event. My first stop was to Google, When is the Super Bowl parade in Philadelphia?, and the response was,“omg, please stop Googling this until the big game actually happens.” (The Philadelphia Inquirer, January 30, 2023). As of earlier this week, Mayor Jim Kenney, “… doesn’t really want to talk about it.”(NBCSports.com, February 7, 2023).

The EA Madden game is going with an Eagles victory (Fortune, February 6, 2023), as are the legalized betting organizations. Still, we forge on with consulting event planning. I took a picture of a long line of portable toilets north of City Hall, which were in preparation for Pope Francis’ visit in 2015. It is to be food for thought about all that goes into planning a parade. “Kansas City officials are planning a multimillion-dollar parade for Feb. 15…,” (The Kansas City Star, February 2, 2023).

I’ll be cheering for the Eagles, but my heart belongs to the Pittsburgh Steelers. If you are like me, this Super Bowl commercial is for you – https://www.youtube.com/watch v=4taNFpPmZag . Still, enjoy the game!

Classroom discussion questions:
1. How can project management be used to plan a parade? What activities will most likely need to be crashed/require crashing cost payment?
2. What are the advantages and disadvantages of Philadelphia’s and Kansas City’s positions? Win or lose, what do they mean for city officials, planners and for workers employed in the hometown, in terms of productivity?
3. How can forecasting be used in the planning process?

OM in the News: Forecasting Fertilizer

Scotts Miracle-Gro’s warehouse at its Ohio headquarters this month.

Chapter 4 of your Heizer/Render/Munson text discusses many widely used forecasting techniques. And most companies use exactly these techniques. However, historical based techniques proved inadequate in a pandemic. Scotts Miracle-Gro fertilizer is a case in point. As The Wall Street Journal (Sept. 16, 2022) writes: “Never in the modern global economy have businesses seen such a rapid shift from shortage to glut.”

Scotts was in the middle of its selling season in 2020 when Covid-19 shut down much of the global economy. Scotts’ production had to respond, but like many firms, response was chaotic with production disruptions caused by sickness and an abundance of caution which eliminated entire shifts. It also soon became clear that homebound families were gardening more. Keeping stores stocked became a problem. And in spite of shortages, sales were up 20% in 2020 and another 10% in 2021.

So just months ago, Scotts was bracing for the biggest summer ever. After two years of struggling to fill store shelves, the company had ramped up production to catch up with consumer demand for lawn seed, fertilizer and other garden products. Massive investments in new manufacturing capacity were about to pay off as Scotts prepared for the usual rush of May orders from retailers looking to replenish their stocks. The CFO assured investors that Scotts was in a good place on inventory and that the firm was expecting banner 2022 sales.

But the orders never came. The pandemic was over, and inflation hit. Retailers cut orders. Scotts has cut 450 jobs and more layoffs are coming. Production schedules have been cut. Available cash is a fraction of what it was. Nobody is getting bonuses.  Scotts was largely a casualty of bloated inventory at big retailers like Walmart, Target and Home Depot. Those companies didn’t foresee the sharp reversal in buying behavior that has taken place in recent months as shoppers, squeezed by inflation, cut back on furniture, electronics and other goods and shifted spending to travel, food and fuel.

Classroom discussion questions:
1. Chapter 4 discusses seasonal adjustments to forecasts. How much would seasonal adjustments have helped Scotts in the past two years?
2. Your text (see page 138) suggests a forecasting technique know as Stagger Charts. How might Scotts implement this technique?

OM in the News: Amazon’s Forecasting System Misfires

Amazon expanded operations and staff during the pandemic, but demand hasn’t kept pace.

As Covid-19 spread in 2020, homebound customers turned to Amazon at an unprecedented clip. Orders neared that of the holiday season and the company was short-staffed and often out of stock on key items, pushing delivery windows from 2 days to weeks on some items. Founder Jeff Bezos greenlighted a strategy, guided by a revered internal forecasting tool, that overshot the long-term projections for demand. Instead of a permanent shift in consumer behavior, the pandemic-fueled growth in online shopping has slowed as in-person shopping has bounced back.

Early in the pandemic, Amazon opened hundreds of new warehouses, sorting centers and other logistics facilities, and doubled its workforce from 2020 to 2022, to more than 1.6 million people. But demand hasn’t kept pace with that planned capacity. Now new CEO Andy Jassy is cutting back the excesses. He is subleasing at least 10 million square feet of warehouse space, deferring construction of new facilities, and finding ways to end leases with outside warehouse owners. Jassy has also abruptly closed down the company’s bricks-and-mortar retail operation—68 stores—and is paring back its bloated head count.

Part of Amazon’s e-commerce challenges today, writes The Wall Street Journal (June 17, 2022), stem from a piece of technology long prized as a secret weapon, an internal forecasting system called Supply Chain Optimization Technologies, or SCOT. It was designed to incorporate a multitude of factors and spit out projections for product demand and the growth in logistics needed to fulfill it.

SCOT forecasts produced low, medium and high estimates. Because of unprecedented volume in the early days of the pandemic, Amazon repeatedly chose the higher end of SCOT’s estimates. Those estimates meant that the company needed many more fulfillment centers and other infrastructure to keep up. So Amazon aggressively built out new warehouses and transportation hubs, and went on a hiring spree to get customers their packages. But the forecasting technology wasn’t equipped to process an unforeseeable event like the pandemic and caused the company to commit to building infrastructure early in the pandemic that take 18 months to 2 years to come online. When the virus receded, Amazon was left with more planned capacity than orders.  After being understaffed for 2 years, the company was suddenly overstaffed.

Classroom discussion questions:

  1. Using Chapter 4 terminology, what type of forecasting system did Amazon employ?
  2. What could the company have done differently, in hindsight?

OM in the News: The Wasted Vaccines

As demand for COVID-19 vaccines collapses in many areas of the U.S., states are scrambling to use stockpiles of doses before they expire and have to be added to the millions that have already gone to waste.  “It’s sad to say I’m in the process of throwing 30 million doses in the garbage because nobody wants them. We have a big demand problem,” says Moderna’s CEO in the Washington Examiner (May 26, 2022)

Germany may discard 3 million COVID-19 vials

Nearly 1.5 million doses in Michigan, 1.45 million in North Carolina, 1 million in Illinois, and almost 725,000 doses in Washington couldn’t be used. The national rate of wasted doses is about 9.5% of the more than 687 million doses that have been delivered. That equates to about 65 million doses.

The problem is not unique to the U.S. More than a million doses of the Russian Sputnik vaccine expired this week in Guatemala, because nobody wanted to take the shot. The pandemic has killed nearly 6 million people and shattered economies across the globe, and every dose that goes to waste feels like a potentially missed opportunity in preventing serious disease.

It also comes only about a year after people desperate to get the vaccine attempted to jump in line to get ahead of those deemed higher priority. Hospital board members donors around the U.S. got early access or offers for vaccinations, raising complaints about favoritism and inequity at a time when the developing world had virtually no doses.

And many poorer nations still have low vaccine rates, including 13 countries in Africa with less than 5% of their population fully vaccinated. They are plagued by unpredictable deliveries, weak health care systems, vaccine hesitancy and some supply issues. Redistributing states’ excess doses to other nations is not feasible because of the difficulty in transporting the shots, which must remain cold, in addition to not being cost effective because of the relatively small number concentrated at sites.

With demand so low, states will undoubtedly be confronted with more waste in the months ahead. Idaho, for example, has 230,000 doses on hand but is only averaging fewer than 2,000 doses administered a week.  West Virginia has offered to transfer Pfizer adult doses to nearby states. States are ordering prudently, paralleling the drop in demand. The minimum order for Pfizer used to be nearly 1,200 doses but now it’s 100.

Classroom discussion questions:
1. Why does the EOQ inventory model described in Chapter 12 of your Heizer/Render/Munson text not work well for this item?

2. What forecasting models in Chapter 4 could be used to predict demand for the shots?