Chapter 12 – Page 3 – The OM Blog by Heizer, Render, & Munson

Guest Post: Lobsters, Shrinkage, Process, and the Supply Chain

Our Guest Post today comes from Howard Weiss, Professor of Operations Management Emeritus at Temple University.

In Chapter 12’s discussion of inventory, your Heizer/Render/Munson textbook discusses shrinkage and notes that shrinkage is “inventory that is unaccounted for between receipt and time of sale, and occurs due to damage and theft as well as sloppy paperwork.” Shrinkage does not have to occur at any one particular facility but can occur at multiple points throughout the supply chain. A prime example of this is what happens with lobsters.

The usual steps in getting a live lobster from Maine to a restaurant are:
 Catch the lobster in a lobster trap
 Transfer the lobster to the to the ship’s storage well
 Transport the lobster to storage at the wharf
 Truck the lobsters to a dealer
 Transport the lobster to a restaurant
Shrinkage occurs because lobsters die as they move through the supply chain. Each 1% in shrinkage equates to a $5,000,000 loss in sales.

The goal of Process Analysis, as explained in Chapter 7, is to “continuously improve the process.” Currently, researchers at the University of Maine are doing just that by studying the above supply chain in order to try to reduce the time involved in any of the steps and determine which steps would give the greatest benefit if the time is reduced.

Of course, not all lobsters are shipped live and follow the steps above. Some lobsters are euthanized then sent to a processing plant where tails are separated from the rest of the lobster which is processed to produce raw lobster meat. In addition, during the pandemic some fisherman have resorted to selling the lobsters directly to local restaurants or consumers.

Classroom discussion questions:

What factors would be important when shipping live lobsters?
What Ch.7 process analysis tool would be most useful for improving the process?

OM in the News: Grocers Stockpile “Pandemic Pallets” Ahead of Winter

Grocery stores and food companies are preparing for a possible surge in sales amid a new rise in Covid-19 cases. Supermarkets are stockpiling groceries and storing them early to prepare for the coming months, when some health experts warn the country could see another widespread outbreak of virus cases and new restrictions. Food companies are accelerating production of their most popular items. These changes, a reaction to the sudden and massive shortages grocers experienced in the spring, amount to a shift from the JIT inventory management practices that have guided the retail business for decades, writes The Wall Street Journal (Sept 27, 2020).

Now, food sellers are stockpiling months, rather than weeks, worth of staples such as pasta sauce and paper products to better prepare for this winter, when people are expected to hunker down at home. Retailers are expanding distribution capacity, augmenting warehouse space and modifying shifts.

Associated Food Stores (a coop of over 400 stores) recently started building “pandemic pallets” of cleaning and sanitizing products so it always has some inventory in warehouses. The Giant and Food Lion chains already have holiday inventory in their warehouses. Those chains are also storing 10-15% more inventory than they did before the pandemic to ensure they won’t run out of fast-selling items. Still, some products such as cleaning wipes and canned vegetables remain hard for stores to obtain, partly because of continued high demand and because manufacturers are still trying to keep up.

General Mills said it hasn’t caught up with demand for Progresso soup, Betty Crocker cake mixes and Pillsbury refrigerated dough. It is increasing its production capacity, but the entire industry is still struggling to rebuild inventory on similar items. Manufacturers have given priority to making their fastest-selling products, which has helped some items recover inventory in recent months. Walmart is overriding its grocery-ordering algorithms to build up extra inventory now, after decades of becoming increasingly lean. Coke is still making fewer varieties of drinks to meet demand for its top beverages.

Classroom discussion questions:

Why a change from the JIT inventory approach?
Why is there still a shortage of some inventory items?

OM in the News: Fighting Pandemic Stockouts

Plenty of retailers and supply chains are still suffering from stockouts. From cleaning products, to kettlebells, to appliances, to meat, retailers, manufacturers and suppliers are coming up short. Forecasts need fixing in a period of severe economic upheaval such as a pandemic–and this article in Supply Chain Dive (Sept. 8, 2020), has 4 ideas for making the changes.

Supply chain managers should plan more often. Companies normally planning on a monthly cycle should switch to every 2 weeks; those on a 2-week cycle should shift to weekly. As demands related to coronavirus mash up with those of the upcoming holiday season, it is critical to have more data points and more sophisticated methods around demand planning to account for some of that volatility and surprises.
Focus on core products and customers. Companies can learn from how home improvement retailers operate during natural disasters. Instead of trying to keep everything in stock, they focus on the most in-demand items. Several large brands and retailers have employed the core product tactic during the pandemic, cutting back SKUs and, in some cases, entire product lines.
Shift more manufacturing to the U.S. A domestic U.S. industrial company with 2-3 factories with 4-5 distribution centers has a lot more ability to flex up and add shifts, even with the new social distancing and safety measures that are required because of COVID.
Give something new a shot. If items are in short supply, and not coming back on board anytime soon, companies can try a new brand or a new product — maybe one they have considered bringing in. Those items may be easier to get, and customers are more likely to be receptive to having an alternative option rather than nothing at all.

Classroom discussion questions:

Which of these would be most critical to a sports equipment manufacturer today?
How must forecast methods change?

OM in the News: Wrestling With Unsold Clothing Inventory

A new French law is forcing industry giants to donate or recycle unsold goods that they would have otherwise destroyed.

Apparel companies, from elite fashion houses to mass-market chains, are saddled with an inventory glut following months long closures during the pandemic. Now, they are trying to get rid of the excess without angering waste-conscious consumers—or harming their brands, reports The Wall Street Journal (Aug. 14. 2020). In the U.S., brands and retailers locked out of an entire fashion season are flooding charities with unsold products, in addition to sending goods to discount stores and liquidators.

Good360, a nonprofit that collects excess merchandise and distributes it to charities, expects more than $660 million in donations for the entire year, double what it received last year. “Brands don’t want their unsold products winding up at flea markets or on Craigslist,” said the CEO of Good360.

LVMH—which owns Louis Vuitton, Dior and other brands—booked a $200 million write-down on its inventories for the first half of the year, because many products destined for the spring/summer fashion season were ordered just before much of the West went into lockdown.

Big retailers sometimes destroy returned products rather than deal with the cost of trying to resell or even give them away. Brands that destroy unsold goods have sparked outrage from consumers, politicians and environmental groups. French businesses destroyed $700 million in unsold goods in the most recent year with available data– six times more than they donated. But high-end fashion companies fear angering clientele who would spend thousands on a designer dress or bag, only to see the same item a year later at a discount store selling for a fraction of the price.

Classroom discussion questions:

Why does French policy differ from that in the U.S?
How is the EOQ model (see Ch. 12 in your Heizer/Render/Munson OM text) impacted by the coronavirus?

Guest Post: Coffee Shops and the Pareto Principle

Our Guest Post today comes from Howard Weiss, Professor of Operations Management Emeritus at Temple University

In studying Chapter 12 on inventory we learn that ABC Analysis is founded on the Pareto principle that states that there are a “critical few and trivial many.” More specifically, this is phrased as “roughly 80%of the effects come from 20% of the causes.” An example of the Pareto Principle has to do with a couple of measures about Coffee Shop chains.

There are at least 12 coffee shop chains in the U.S,. with over 30,000 branded coffee shops. Starbucks and Dunkin’ accounted for 80% of the over 1400 new store openings in the U.S. over the past year. That is, Starbucks and Dunkin comprise fewer than 20% of the chains but accounted for 80% of the new store openings. Starbucks has a 40% share of the U.S. coffee shop market and Dunkin’ has a 26% share of the market. In other words, fewer than 20% of the coffee chains account for 66% of the market. This is not 80% but it is a considerably high percentage.

The figure below from Daily Coffee News (Oct. 25, 2019) exhibits pre-pandemic numbers.

Classroom discussion questions:
1. Analysts forecast that coffee sales will not rise to pre-pandemic levels until 2024. Should we
expect Starbucks and Dunkin to account for 80% of the coffee shop closings in the next 4 years?
2. Which organizations related to coffee shops will be affected by the current drop in sales due to
the pandemic?

OM in the News: Why the Consumer Has Fewer Choices–Maybe for Good

Consumer-oriented companies spent the past decades trying to please just about everyone, as we discuss in Chapter 7’s treatment of mass customization. The pandemic made that impossible, and now some no longer plan to try. Sellers of potato chips, cars, meals and more have been narrowing offerings since the coronavirus snarled supply chains and coaxed consumers back to familiar brands, writes The Wall Street Journal (June 27-28, 2020).

Some IGA grocery stores now offer only 4 choices of toilet paper. “We may not need 40 different choices of toilet paper.” says IGA’s CEO. Georgia-Pacific switched all production of its Quilted Northern toilet paper to 328-sheet rolls; it had been also producing the brand in 164-sheet rolls. It plans to stick with the bigger rolls even after the pandemic, which let it speed production and make distribution more efficient. Retailers also had an easier time keeping Northern toilet paper in stock by having fewer varieties on shelves.

In grocery stores, the average number of SKUs was down 7% over the past month, with some categories, such as baby care, bakery and meat, down 30%. Frito-Lay, featured in Chapter 13’s Global Company Profile, stopped producing 1/5 of its products. Over the past 45 years, Lay’s has gone to 60 varieties of chips from 4. Since 1984, Campbell Soup has quadrupled the types of soup it sells to about 400.

Those efforts helped consumer-goods makers claim more shelf space as supermarkets expanded into big-box stores. In 2018, the average U.S. food retailer stocked 33,000 different items, compared with 9,000 SKUs in 1975, But now food makers have cut back on options, streamlined supply chains and concentrated production on the most-demanded goods.

Darden Restaurants said it was going to largely keep slimmed-down menus it started during the pandemic, which have helped reduce prep work and costs. And while last year, auto makers offered more than 605,000 vehicle configurations (even before taking different colors into account), showrooms today offer choices more limited because of supply-chain bottlenecks and lower volumes.

Classroom discussion questions:
1. What are the advantages of stocking fewer SKUs?

2. Why is this a supply chain issue (see Ch. 11)?

OM in the News: Storing Fuel at Sea

The cost to ship gasoline, diesel and jet fuel around the world has soared to record highs, as traders look to dodge the commodity price crash by stashing refined oil at sea. The coronavirus lockdowns deterred activities like driving and flying that involve burning fuel. The resultant glut of oil sent prices into a tailspin. But with so much extra supply, the price to store or move oil products has moved in the opposite direction. The lack of on-land storage, surplus of supply and collapse of demand globally means the oil is on the water, writes The Wall Street Journal (May 3, 2020).

It now costs about $170,000 a day to charter a vessel from the Persian Gulf to Japan, 10 times the March 2020 rate of $17,000. Traders can make money storing cheap oil today and cashing in on it later. That creates more demand for tankers as traders are motivated to keep oil at sea, especially with almost nowhere to store it on land. Some vessels moving oil from Asia to Europe are skipping the Suez Canal and taking the long route around Africa for this reason.

Refiners, which distill thick crude oil into usable fuels, haven’t cut output fast enough to stop a surge in supply. So global stockpiles of petroleum products will grow by around 550 million barrels in the second quarter. A race is under way to store the surplus gasoline, diesel and jet fuel at sea. The number of available “clean tankers,” smaller ships that move refined petroleum products, has plummeted. “Dirty tankers” transport unrefined crude, and there are very few of these vessels left.

Logistical difficulties at ports pose further constraints. Tankers are taking longer to unload because there is so little free storage space on land. Coronavirus quarantine measures have added to delays. Bottlenecks are everywhere.

Classroom discussion questions:

What is the solution?
How has the U.S. benefitted form the oil glut? Been hurt?

OM in the News: Ships Turn Into Floating Storage Units

Shippers are warehousing fuel on the high seas as the coronavirus epidemic cuts China’s demand for fuel.

A new glut of oil and gas is emerging, floating at sea, as the coronavirus epidemic cuts China’s appetite for fuel and hampers work at Chinese ports. Dozens of ships are acting as floating storage vats for oil and liquefied natural gas because the owners of the fuel are unable to find buyers or places to store their cargo on land, according to The Wall Street Journal (March 4, 2020). Some 79 vessels are now storing crude oil at sea.

Traders. in the past decade, often loaded up ships with crude oil or gas with no immediate intention of moving the cargo around the world, seeking to profit by buying fuel on the cheap and locking in a higher price in the future. Such hedging made supertankers a modern version of an inventory warehouse. But the current situation is different for the 87 million barrels of crude stored on the high seas today. Rather than getting paid to store oil and gas in ships, many traders simply can’t find a home for their cargo. So storing oil at sea comes with costs for traders and owners.

A similar story is unfolding in the gas market: Eleven ships are currently storing LNG at sea. Traders typically load up ships in the fall to take advantage of rising demand and higher gas prices when temperatures drop in December. Stored at minus-261 degrees, some LNG evaporates while at sea, which means owners are loath to store gas in vessels unless they can profit from it. “Everything that’s floating is probably distressed,” said an industry expert. “It’s something that’s trying to find a home. It’s floating until it can find storage.”

Classroom discussion questions:

What are the pluses and minuses of this hedging?
In Chapter 12 of your Heizer/Render/Munson OM text, we list the 4 functions of inventory. Which of these apply here?

OM in the News: Tyson’s Computer Vision Technology Improves Inventory Accuracy

Tyson is rolling out a computer-vision-enabled inventory tracking system at facilities where it packs chicken into trays for grocery stores, writes Supply Chain Dive (Feb. 11, 2020) The system can read SKU information and weight, replacing what Tyson described as communication by hand gestures followed by manual inventory entry. By the end of the year, Tyson’s automated inventory tracking technology will combine computer vision, machine-learning and edge computing to expand its speed and processing capability.

Automated inventory tracking using computer vision led to a double-digit increase in inventory accuracy in the 3 facilities currently using the technology. The company plans to expand the program to all 10 of its poultry plants.

Though cold, wet storage environments make implementing new technologies difficult, the payoff of real-time accurate inventory information is already evident for Tyson. The company recently opened the Tyson Manufacturing Automation Center, where it works with manufacturers and suppliers to develop new technologies and trains employees to use it. The company has spent $215 million on new technologies in the last 5 years.

Precise, real-time inventory visibility can increase the frequency with which Tyson fulfills grocery customer orders on time and in full in the best of times. But inventory management is particularly key in times of uncertainty, and Tyson is dealing with plenty. The disruptive forces of shifting global trade policy, a fire at an important Tyson facility, and African swine fever, which all distorted usual supply and demand patterns, made a relevant forecast next to impossible.

Major meat companies are leaning toward similar monitoring technologies and automation, whether through production or processing. Cargill is starting to use computer vision to track animal health in dairy operations. But a more consumer-directed application inspired Tyson’s work. Similar technology enables Amazon’s cashier-less stores, which led executives to explore applying it in poultry plants.

Classroom discussion questions:

Describe what a vision system is (See Chapter 7 of your Heizer/Render/Munson text).
How will this help Tyson control inventory?

Guest Post: Student Perspectives on the MyOMLab Inventory Management Simulation

Wende Huehn-Brown is Professor of Supply Chain Management at St. Petersburg College in Florida. She continues her review of our five OM simulations.

In prior guest posts, I evaluated 3 of the 5 simulations that are available free in MyOMLab with the Heizer/Render/Munson text. Today, I look at the Inventory Management simulation. I like that it deals with the retail industry, from the store manager perspective, because students feel more comfortable thinking about the physical needs of products in a retail scenario. The simulation quickly takes them from that initial comfort level as they get calls, emails, etc. about issues to manage decisions. Finding that balance between too much and too little inventory to achieve profitability goals is key in this simulation, just as in many real businesses.

This simulation requires students to apply holding and ordering costs, as well as watch for sales trends and think about forecasting orders. Many students often buy too much or too little until they start to think about EOQ and ROP to find a rhythm. They also see how their decisions impact profits as they work toward a $1 million goal. While difficult, students often say it is the best of the 5 MyOMLab simulations. Some even use the word fun!

Why? Because they feel the practical aspect of a simulation experiencing the needs and issues in these kinds of positions, with a chance to practice and not impact actual money. Inventory is always a delicate balance to keep customers happy and align to profit goals. Students often do this simulation more than once to challenge themselves to get the best results–building pride and confidence in making these managerial decisions.

Many students have work experiences in retail or hospitality and easily relate to this simulation. For example, this product does not perish as food items, so the cost of having too much inventory is a bigger challenge for them. Others find the simulation helps to refresh their skills or builds on past experiences to further learn some key skills employers need. Be sure to include these simulations in your lessons!

OM in the News: 150 Shades of Red Drown Mattel’s Supply Chain

Mattel has gotten to the heart of one of its problems: Too many reds aren’t a good thing. The company’s designers until recently could choose from about 150 types of red when making Barbie dolls, Hot Wheels cars or other toys in its stable. Each variation added storage costs and downtime at factories for cleaning equipment to swap out shades.

“Complexity is really a killer,” said Mattel’s chief supply-chain officer. Mattel has chopped the choices of reds by more than 1/3 and is doing the same for other colors, part of a broad edict to simplify the company’s supply chain. The goal is to improve, modernize and ultimately tame a sprawling supply chain that operates 13 factories, employs 35,000 people and delivers toys to 375,000 retail locations world-wide, reports The Wall Street Journal (Jan. 2, 2020). “Supply chain had become one of our handicaps,” adds the CEO.

Mattel says it plans to keep factories that are “strategically important” or that can make certain products at a better quality and lower cost than a third party could, while consolidating plants that are underused. The company already changed how it sells and fulfills orders to retailers. In Europe, Mattel implemented an automated, online ordering system for wholesale orders, eliminating the need for its sales team to manually process orders. It also increased the minimum order size so that it wasn’t shipping orders valued at just a few hundred dollars into a fragmented retail market.

More broadly, Mattel is using new algorithms to tie its manufacturing output more closely to demand, helping the toy maker to gauge the right number of toys for the holidays. Mattel also will be making fewer products. The company is planning to cut the number of items it sells by 30%, targeting the 45% of the items it sells that only make up 6% of its revenue.

Classroom discussion questions:

Why does Mattel have so many plants? So many colors?
What inventory strategy is Mattel using to cut SKUs (see Ch. 12 of your Heizer/Render/Munson text)?

Guest Post: How Machine Learning Can Heal a Supply Chain

Our Guest Post today comes from Polly Mitchell-Guthrie, who is VP, Industry Outreach and Thought Leadership, at Kinaxis.

Machine learning has great potential to improve supply chains. So at my company, Kinaxis, when analysis of data from a major customer revealed that 55% of their lead times were wrong as designed, we began applying machine learning.

Lead times matter because overly optimistic planning assumptions mean supplies are expected to arrive sooner than they actually do. Waiting delays production and on-time customer delivery while building up parts that arrived on time but cannot be used until remaining parts needed arrive. Overly pessimistic planning assumptions mean actual lead times shorter than planned, so some parts arrive early, building up inventory and storage costs, while others are still in transit. If demand is slower than expected, parts accrue in inventory, unused due to obsolete needs.

More accurate planned lead times allow on-time customer orders, minimize inventory, and reduce buffer stocks necessary to ensure production. Predicting lead times is a problem well-suited to machine learning and automation. The planner sets tolerances for variations in lead times, which we use to configure processing rules for what actions to take. Our machine learning models use historical data to predict actual lead times, compare them to designed lead times, and then use the processing rules to improve decisions, leading to more realistic results.

We have taken a similar approach to predicting yield times. The results from these projects can be significant – for one company we were able to save $17 million in late revenues for their North American region over their 6 month planning horizon.

Minor deviations not worth the time to analyze but deemed worthy of a change are automatically accepted by the model, thereby “self-healing” the deviation. Those with a significant enough impact are flagged for manual review. Minor deviations with minimal impact are simply ignored by the processing rules. Planners can focus on decisions that matter most and let math automatically handle those that do not.

Here is a link to a longer version of the article I published in Analytics.

OM in the News: Fiat Chrysler and 40,000 Unordered Vehicles

Fiat Chrysler has been manufacturing more cars and trucks than its U.S. dealers are willing to accept, at one point creating a nationwide stock of about 40,000 unordered vehicles and stoking tension with some of its retailers. Dealers claim the company has revived what’s known in industry circles as a “sales bank,” writes Bloomberg (Nov. 12, 2019). The practice is decades old and frowned upon by investors because it can obscure an automaker’s inventory figures. Dealers don’t like it because it can amp up the pressure companies place on them to take delivery of vehicles they don’t want.

Fiat Chrysler denies the sales bank claim. The company says it put a predictive analytics system in place early this year that aims to better align its supply chain and manufacturing plans with anticipated dealer orders. But it recently paid a $40 million penalty related to filing years of sales reports the SEC said were fraudulent. One way the company inflated figures was by paying dealers to report fake sales. The predictive analytics strategy was implemented this year and has already increased the required lead time for dealers to order cars, saving the automaker $441 million.

Some dealers were looking to pare back inventory after being burned by rising interest rates that increased the cost of holding cars, and a lack of incentive support from the company to boost sales of older models. Just last week, Fiat Chrysler told dealers it would allocate them vehicles for both November and December all at once, and that it may restrict orders for certain models. Dealers viewed this as a bid by the company to work through inventory by prodding dealers to order cars that remain in the sales bank. Fiat Chrysler said the restrictions apply only to certain vehicle configurations where demand exceeds production capacity.

Classroom discussion questions:

Is there an ethical issue in this story?
Point out the forecasting (Ch.4), supply chain (Ch.11), analytics (Mod. G), and inventory (Ch.12) OM implications.

OM in the News: Picking Inventory at Amazon With Humans and Robots

While this Amazon center is highly automated, some tasks are likely to remain in human hands for years to come.

Every day, about 50 truckloads of merchandise turn up at Amazon’s warehouse in Staten Island, NY. One group of workers unloads the goods, and another group distributes them to work stations. There, a third group, stowers, transfers the items onto large shelving units that hold several dozen bins, and are attached to robots that move through the building. Stowers choose the bin where they want to place each item, trying to make the task as easy as possible for the worker, a picker, who will have to grab items out of the bin.

Picking inventory off shelves to fill customer orders is usually the most common job at an Amazon warehouse, and the company has worked for years to make its pickers more productive. At many warehouses, pickers walk miles each day in search of items, but algorithms provide them with the optimal route. In robotics fulfillment centers like the one on Staten Island, the pickers are stationary and the robots deliver items to them. (These warehouses account for more than 50% of its 175 centers).

The robots have raised the average picker’s productivity from 100 items per hour to 300 or 400 –and help explain why Amazon managed to ship more items than ever during last year’s holiday season with about 20% fewer seasonal workers. But robots have also made the job far more repetitive. Unlike pickers in manual warehouses, the pickers on Staten Island have almost no relief from plucking goods off shelves

Amazon plans to fully automate picking in the near future, reports The New York Times (July 7, 2019). It calculated that there was so much productivity to be gained from reducing the millions of miles its workers walk each year that it was better off finding robots well suited to moving goods all those miles, not worrying whether the system would later be compatible with robotic pickers.

Classroom discussion questions:

Why would it be hard to replace the human pickers?
Outline the process of merchandise flow in an Amazon warehouse that uses robots vs. one that does not.

OM in the News: Amazon Falls Short Over Food Delivery

A contract employee for Amazon picks up bags of groceries to deliver to Whole Foods customers

Amazon last year began offering some Prime members online grocery-shopping and delivery from Whole Foods, touting the service as another perk to customers after purchasing the organic grocery chain. But Whole Foods employees said Amazon workers routinely ask for help finding items on shelves or elsewhere, distracting them from their own duties. And technology that tracks Whole Foods’s inventory is old.

Amazon’s struggles aren’t unique, writes The Wall Street Journal (March 25, 2019). As supermarkets increasingly offer online grocery delivery to keep customers loyal, most services that fill orders from stores are struggling with execution. The challenges are numerous. Many grocers don’t have technology that can readily track inventory in real-time. That means items listed as available online often aren’t in the nearest stores filling a delivery order, leading employees to make their best guess or rely on computer recommendations that can suggest unsuitable substitutions.

Target recently introduced a new inventory-management system for stores and online to speed up replenishment. At Instacart, the largest third-party grocery-delivery service, incomplete orders were the second most frequent source of customer dissatisfaction, after price. Some 15% of consumer products listed on U.S. online ordering services are out of stock when it comes to fulfilling them, nearly double the rate in stores.

There are a number of reasons why many online grocery services struggle to offer substitutions customers want. Shoppers typically depend on suggestions from online tools, and algorithms can make mistakes or suggest inappropriate alternatives. Services that rely on gig-economy workers who pick items off store shelves can exacerbate the selection problem, since many aren’t food experts and juggle many orders a day. Mishandling substitutions is expensive for retailers, as it often leads to refunds or a replacement item that is pricier than the original. Refunding incorrect items decreases an online order’s profitability by 1% to 2% on average.

Classroom discussion questions:

What are the inventory issues that online grocers face?
What can be done to make the systems more efficient?