Skip to content

OM in the News: Factories Demand White-Collar Education for Blue-Collar Work

December 13, 2019

An engineer creates 3-D blueprints to program machines that manufacture customer orders at a parts manufacturer

New manufacturing jobs that require more advanced skills are driving up the education level of factory workers who in past generations could get by without higher education, writes The Wall Street Journal (Dec. 10, 2019). American manufacturers are, for the first time, on track to employ more college graduates than workers with a high-school education or less, part of a shift toward automation that has increased factory output, opened the door to more women and reduced prospects for lower-skilled workers. “You used to do stuff by hand,” said a  U. of Chicago prof. “Now, we need workers who can manage the machines.”

U.S. manufacturers have added more than a million jobs since the recession.  Over the same time, they employed fewer people with at most a high-school diploma. Employment in manufacturing jobs that require the most complex problem-solving skills, such as industrial engineers, grew 10% between 2012 and 2018; jobs requiring the least declined 3%. (More than 40% of manufacturing workers have a college degree, up from 22% in 1991).

Improvements in manufacturing have made American factories more productive than ever and, despite recent job growth, require 1/3 fewer workers than the nearly 20 million employed in 1979, the industry’s labor peak. The workers that remain do much more cognitively demanding jobs. At Caterpillar, over 80% of job openings require or prefer a college degree. A majority of the company’s production jobs called for a degree or specialized skill.

At Harley-Davidson’s engine plant in Milwaukee, robotic arms now ferry motorcycle pieces, taking over the tough, repetitive work formerly done by employees. The machines have made the workplace safer, mirroring a national trend. In 2018, factory workers were hurt at half the rate as in 2003.

Classroom discussion questions:

  1. How do these changes impact productivity, as discussed in Chapter 1 of your Heizer/Render/Munson text?
  2.  How many students in your class are looking for jobs in manufacturing?

OM in the News: Electric Cars are Here. Buyers Aren’t

December 9, 2019

Ford unveiled the all-electric Mustang Mach-E last month

“It is no surprise auto executives worldwide have announced nearly 75,000 layoffs this past year,” writes The Wall Street Journal (Dec.7-8, 2019). This downsizing isn’t driven by market-share wars or oil shocks or economic crisis but by the belief that electric cars will soon boom. (Just 2 days ago, our blog spoke of the shortage of EV batteries worldwide).

Stop me if you’ve heard this before. Auto executives say they really, really mean it this time, though, as they point to technological advances, looming regulation and pent-up demand. The trouble is that EVs cost more than their gasoline counterparts, are cumbersome to charge and sell fewer in the U.S. than the Toyota Camry. For every 8 pickups sold there is one pure-plug-in vehicle sold.

Still, companies are preparing for the electric age by cutting workers. This is partly to save money needed for development, but it is primarily to prepare for a vehicle design-and-production process that will be, as they say in Silicon Valley, “asset light.” EVs are less complex than gasoline or diesel rivals, requiring fewer parts, people and suppliers. Ford says 30% fewer hours of labor and 50% less factory space will be needed for EVs.

But even the smartest auto exec doesn’t have a clue when the EV revolution will happen. Could be 2025, or it could be 2050. To date, the customer’s appetite for big trucks and SUVs running on cheap gasoline has ruled the market. Hype for EVs persists even as car makers lose money on them. For instance, amid $4-a-gallon gasoline earlier in the decade, GM predicted it would have 500,000 electric cars on the road by 2017. It missed badly. The U.S. market needed until mid-2018 to hit the 1-million-EV mark, with each sale bolstered by at least $7,500 in tax incentives (that are now ending).

Car makers, at the same time, have raised fuel-economy numbers on conventional cars, trucks and SUVs by using turbochargers, lighter materials, and smaller engines. This has gone a long way toward pleasing regulators and customers demanding better efficiency.

Classroom discussion questions:

  1. What is your forecast for when EV sales will exceed traditional gas rivals.
  2. How is this an operations issue? (Refer to the OM decisions in Chapters 5, 7, 8, 9,10, and 11 in your Heizer/Render/Munson text).

OM in the News: The Key to Electric Cars is Batteries–And There Aren’t Enough of Them

December 7, 2019

GM and South Korea’s LG Chem plan to build a $2.3 billion battery factory in Ohio, the latest example of an auto maker plowing money into the development of electric cars. The new plant would be among the world’s biggest producing battery cells for electric cars, rivaling Tesla’s Gigafactory in the Nevada desert, reports The Wall Street Journal (Dec. 7, 2019). Auto makers have been joining forces with battery makers as they gear up to spend about $225 billion to develop new electric-vehicle models over the next several years. (GM plans to introduce at least 20 electric models globally by 2023).

GM said the new battery plant, which would employ more than 1,100 workers, would have a capacity to manufacture enough batteries annually to produce more than 30 gigawatt hours. (Tesla’s plant has output of about 24 gigawatt hours). GM and LG Chem will co-develop and assemble battery cells to be used in the auto maker’s electric vehicles, including a battery-powered truck GM plans to introduce in  2021. GM said the joint venture with LG will speed GM’s electric-vehicle development and reduce costs. Toyota, for example, is finding it hard to build enough batteries to keep up with rising demand for hybrids, which use a combination of gasoline and battery power. “We can assemble the cars,” said one Toyota exec.  “The assembly is not the bottleneck. It’s the battery itself.”

Auto union officials have expressed concern that the expansion of electric vehicles poses a long-term threat to auto-factory employment, because they require less manpower to produce than gasoline-powered cars. Battery-cell plants are highly automated and require different skills than those needed at traditional car factories. The plants’ employees include test technicians, computer programmers and equipment engineers.

Classroom discussion questions:

  1. Why is there a battery bottleneck?
  2.  Prepare a SWOT analysis of GM’s strategy.

OM in the News: Target’s New Online Staffing System

December 4, 2019

Target now sources 80% of its online orders from stores, not warehouses.

Retailers are trying to adapt to a world where shopper behavior is changing and competition for online spending is fierce, writes The Wall Street Journal (Dec. 2, 2019). Target, Walmart, and other retailers are staffing stores differently in an effort to meet new competitive challenges, as well as attract workers and control payroll costs amid the tightest labor market in decades. (Online sales reached $7.4 billion on Black Friday, up from $6.2 billion last year, while foot traffic to U.S. stores fell 6.2%). Big chains have posted strong sales in recent years by adapting to the shift to online shopping. They use their stores to handle deliveries or convince shoppers to pick up orders rather than wait for an Amazon package.

Target says it now sources 80% of its online orders from stores, not warehouses. At the Brooklyn store around 80 workers handle internet orders, collecting products from shelves or putting items into boxes in the backroom for delivery. Target retrained the bulk of its 300,000 U.S. workers over the past year, giving them new titles and responsibilities. It hopes to mold each into an expert for a specific area of the store such as the beauty department, toys or online fulfillment to offer better customer service and use labor spending more efficiently.

Under the new staffing system, more Target workers are responsible for the full chain of tasks needed to keep their department well stocked and shoppers happy, including finding products in the backroom and stocking shelves, tracking inventory and answering shoppers’ questions. Target added technology on hand-held devices to guide workers through the store more efficiently to gather or send out online orders. And more workers are putting products on shelves during the day, not at night, to be able to help customers at the same time.

Walmart uses stores to fulfill its online grocery orders, and is increasingly relying on stores for other types of e-commerce orders.

Classroom discussion questions:

  1. Compare Target’s approach to that of Amazon.
  2.  What is Target doing to increase operational efficiency?

OM in the News: Israeli Startup Races to Roll Out 3D Printed Steaks

December 2, 2019

The walls of Redefine Meat Ltd.’s lab in Rehovot, Israel, are plastered with posters of cuts of beef, including sirloins, T-bones, and rib-eyes. But the startup isn’t looking to sell the perfect cut of beef. Instead, it wants to create a plant-based facsimile. The company is building a 3D printer that it says will produce a meatless steak that’s so fatty, juicy, and perfectly meaty that even the most dedicated carnivore won’t know the difference. “All meat alternatives today are basically a meat-homogeneous mass,” says  Redefine Meat’s CEO. “If you 3D-print it, you can control what’s happening inside the mass to improve the texture and to improve the flavor.”

Redefine Meat says that 3D printing promises to give diners the same sensory experience as eating a real T-bone or rump roast, writes BusinessWeek (Nov. 25, 2019). The technology involves developing a design that can then be printed countless times. First, proprietary computer software creates a detailed model of a steak, including the muscle, fat, and blood, based on whichever cut it’s emulating. That blueprint is then transmitted to a printer loaded with plant-based “inks.” Hit the start button and out comes a “steak.”

While ground-meat replacements are widely available, mimicking an actual cut of meat has proved far more challenging. That’s because replicating the mouthfeel and visual appeal of a juicy sirloin is a lot tougher than cranking out something that’s going to be slapped between a bun. “A beefsteak is the holy grail of plant-based meat,“ says one exec.

The faux-meat category has already reached an estimated $14 billion in annual sales worldwide, and will grow to $140 billion in 2029. Redefine Meat plans to introduce its plant-based steaks to the public in the first quarter of 2020. It will supply customers, including restaurants, meat distributors, and retailers, with both the printers and cartridges. Redefine Meat’s printer can now deliver five 7-ounce steaks in an hour. The company hopes to speed that up to 22 pounds by the end of 2020. That will mean 50 servings an hour, or the equivalent of a cow’s worth of steak a day.

Classroom discussion questions:

  1. What are the OM issues involved in “printing” a steak?
  2.  Will this new product be as successful as an Impossible Burger?

Guest Post: How Machine Learning Can Heal a Supply Chain

November 30, 2019

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: Are Ruthless Quotas at Amazon Maiming Employees?

November 27, 2019

Amazon’s famous speed and technological innovation have driven the company’s massive global expansion and a valuation over $800 billion, writes The Atlantic (Nov. 25, 2019). It’s also helped make Amazon the nation’s second-largest private employer. But now the Center for Investigative Reporting has found that the company’s obsession with speed has turned its warehouses into injury mills, finding the rate of serious injuries for Amazon facilities more than double the national industry average: 9.6 serious injuries per 100 full-time workers in 2018, compared with an industry average of 4. Some centers, such as the Eastvale, California warehouse, were especially dangerous, with 422 injuries–more than 4 times the industry average.

The former head of OSHA states: “According to Amazon’s own records, the risk of work injuries at fulfillment centers is alarmingly, unacceptably high. Amazon needs to take a hard look at the facilities where so many workers are being hurt and either redesign the work processes, replace the top managers, or both.”

Many workers spoke with outrage about having been cast aside as damaged goods or sent back to jobs that injured them further. The company does instruct workers on the safe way to move their bodies and handle equipment. But former workers said they had to break the safety rules to keep up. They would jump or stretch to reach a top rack instead of using a stepladder. They would twist and bend over to grab boxes instead of taking time to squat and lift with their legs. They had to, they said, or they would lose their jobs. So they took the risk.

The root of Amazon’s success appears to be the root of its injury problem: the blistering pace of delivering packages to its customers. And during Amazon’s busiest (“peak”) season, employees face the exhaustion of mandatory 12-hour shifts where expectations are precise. Workers have to pick 385 small items or 350 medium items each hour and are expected to meet 100% of this productivity performance standard. Amazon CEO Jeff Bezos, meanwhile, is focused on customers. “We are ramping up to make our 25th holiday season the best ever—with millions of products available for free 1-day delivery,” he said.

Classroom discussion questions:

  1. What are the ergonomic issues discussed in this article (which we encourage you to read in full)?
  2.  What is the solution?