Chapter 1 – Page 5 – The OM Blog by Heizer, Render, & Munson

OM in the News: Getting the U.S. Manufacturing Strategy Right

Manufacturing's technological revolution may not add jobs but will drive growth in the broader economy — Manufacturing’s technological revolution may not add jobs but will drive growth in the broader economy

For years, Washington has made increasing manufacturing employment a priority, hoping to engineer a return to the time when high-school graduates could use factory jobs as a route to the middle class. “Sadly, that isn’t going to happen,” writes the Brooking Institution’s Martin Baily, in The Wall Street Journal (June 3, 2015). Of the 5.7 million manufacturing jobs that disappeared in the 2000s, only 870,000 have returned and the claim that millions more are coming back is a myth.

But manufacturing will be crucial to the U.S. economy in the future not for its ability to create jobs but for its potential to drive innovation and productivity growth, and for its role in international trade and competitiveness. That means if the U.S. is serious about promoting a recovery in manufacturing, it will stop measuring success by the number of people employed in the sector and start supporting the technological advancements that are making factories more productive, competitive and innovative. This technological revolution may result in fewer factory jobs for low-skilled workers, but it promises to benefit society by driving growth not only in manufacturing but in the broader U.S. economy, as well. Already under way, the shift is being powered by three key technology developments.

The first is the Internet of things, in which embedded sensors transmit information from machine to machine, allowing them to work together and identify maintenance problems before a breakdown occurs. The second is advanced manufacturing, which includes 3-D printing, new materials and the “digital thread,” where companies use very accurate digital models to guide all stages of product development, speeding the time to market and improving quality. Finally, there is distributed innovation, in which crowdsourcing is used to find radical solutions to technical challenges much more quickly and cheaply than with traditional in-house R&D.

Classroom discussion questions:

1. Which is more important–number of jobs or technology?

2. Describe the Internet of things with several examples.

OM in the News: Weak Productivity Turns into a Problem of Global Proportions

“Output per worker grew last year at its slowest rate since the millennium, with a slowdown evident in almost all regions, underscoring how the problem of lower productivity growth is now taking on global proportions,” reports The Financial Times (May 25, 2015). Globally, the rate of growth decelerated to 2.1% in 2014, compared with an annual average of 2.6% between 1999 and 2006.

As we write in Chapter 1, the problem of low global productivity as one of the greatest threats to improved living standards, in rich and poor countries alike. The fact that companies have become less efficient at converting labor, buildings and machines into goods and services is beginning to trouble policy makers around the world. Janet Yellen just cited weak US productivity as a cause of “the tepid pace of wage gains in recent years.”

Raising productivity is seen as one of the only ways to improve living standards, at a time when advanced and some emerging economies are seeing aging populations and a rapidly increasing retirement rate. Without stronger productivity growth, the world may have to get used to much lower rates of economic growth. Emerging markets are reaching the limits of easy growth based on catch-up technology while advanced economies are concentrating on services, which tend to have less scope for rapid efficiency gains.

New technology has centered on consumer products, which have made people better off and able to do more than in the past, but have not necessarily improved the quantity or efficiency of their work. There is little evidence the slowdown stems from lazy or inefficient employees. “Something is going wrong with the way firms are equipping their workforces to produce more,” says the head of the Conference Board.

Classroom discussion questions:

1. What is the definition of productivity?
2. What is the impact of technology on manufacturing productivity? On service productivity?

OM in the News: Chobani Learns That Operations Management Can’t Be Ignored

Chobani's plant in New Berlin, N.Y. — Chobani’s plant in New Berlin, N.Y.

Hamdi Ulukaya used to say that no one could run his yogurt startup better than he could, proud that Chobani Inc. grew to $1 billion in annual sales without help from a “professional CEO.” Today, a professional CEO is exactly what Chobani is seeking, reports The Wall Street Journal (May 18, 2015). Ulukaya admits that Chobani has grown beyond his ability to run it. (Chobani’s share of Greek yogurt sales in the U.S. is down nearly 15 percentage points to 44% from its peak in 2012).

Chobani almost single-handedly set off a craze for Greek-style yogurt, growing explosively in the process. But it was in over its head: losing money, and building the world’s largest yogurt factory had saddled it with debt. Its operations were scattered, purchasing was inefficient and it lacked an adequate quality-control team—a deficiency that surfaced dramatically when Chobani had to recall yogurt from the new factory in 2013.

Executive offices were in the basement of the factory. Ulukaya handled most of the hiring himself, assembling a staff that suited a startup but not the large company Chobani was becoming. Ulukaya handled the books, too, using Quicken software for small businesses even after the company grew beyond such a status. “We didn’t have any corporate executive types,” said Ulukaya. “I didn’t want to hear all that marketing, supply chain, logistics stuff—most of it is BS.”

He would learn those operational systems couldn’t be ignored, even though rapid growth hid some problems. The drawbacks of the seat-of-the-pants style became clear starting in 2013. The previous December, Chobani had opened a $450 million factory in Twin Falls, Idaho, nearly 2,000 miles from its headquarters. Though it offered access to an abundant dairy supply, the plant’s remote location stretched Chobani’s management, and differences in the milk’s protein composition and in the machinery required tinkering with Chobani’s recipe.

This is a great story to share with your class, as most are familiar with the company. It appears OM is important after all!

Classroom discussion questions:

1. After the new CEO, what is Chobani’s next step?

2. What are the operations issues Chobani is facing?

Good OM Reading: The Productivity Challenge

Global economic growth is set to slow dramatically

“Over the past 50 years,” writes McKinsey’s Global Initiative Report (Jan., 2015), “global economic growth was exceptionally rapid.” The world economy expanded sixfold. Average per capita income almost tripled. Hundreds of millions of people were lifted out of poverty. Yet unless we can dramatically improve productivity, McKinsey thinks the next 1/2 century will look very different. The rapid expansion of the past five decades will be seen as an aberration of history, and the world economy will slide back toward its relatively sluggish long-term growth rate.

The world isn’t running out of technological potential for growth. But achieving the increase in productivity required to revitalize the global economy will force business owners, managers, and workers to innovate by adopting new approaches that improve the way they operate.

McKenzie found that about 3/4 of the potential productivity growth comes from the broader adoption of existing best practices, or catch-up improvements. The remaining 1/4 comes from technological, operational, or business innovations that go beyond today’s best practices and push the frontier of the world’s GDP potential. Efforts to improve the traditionally weak productivity performance of the large and growing government and healthcare sectors around the world will be particularly important.

Business must play a critical role: aggressively upgrading capital and technology, taking risks by investing in R&D and unproven technologies or processes, and mitigating the labor pool’s erosion by providing a more flexible work environment for women and older workers, as well as training and mentorship for young people. In an environment of potentially weaker global economic growth, and definitely evolving growth dynamics, executives need to anticipate where the market opportunities will be and the competitors they will meet in those markets. Above all, companies need to be competitive in a world where productivity will increasingly be the arbiter of success or failure.

OM in the News: Why Manufacturing Still Counts in the U.S.

“The U.S. economy,” writes The Wall Street Journal (Jan.14, 2015), “is dominated by service work but manufacturing matters because it includes many middle-class jobs.” The Bureau of Labor Statistics estimates that employers in manufacturing, mining and construction pay an average of $36.37 an hour in wages and benefits, compared with $31.46 paid by stores, restaurants and other service companies. The U.S. lost more than 6 million manufacturing jobs between 1998 and 2010, largely to low-cost countries. Since then, the number of U.S. factory jobs has recovered nearly 7% to 12.2 million, compared with about 17.5 million in 1998.

Manufacturing creates demand for supplies and raw materials, as well as such services as delivery and machinery repair. Every $1 of sales by U.S. manufacturers yields $1.37 of output in other parts of the economy. A dollar of retail sales adds 64 cents. Expanding U.S. manufacturing allows the country to export more and rely less on imports. (The U.S. has run trade deficits every year since 1976). Manufacturing also is a source of innovation. It accounted for 83% of R&D conducted by businesses in 2013.

More U.S. companies would shift production from abroad if they analyzed the costs of overseas production to include such things as the shuttling of executives abroad and holding large inventories as a hedge against supply disruptions, says the Reshoring Initiative. But Harvard Prof. Willy Shih is less optimistic. “China has really captured the whole electronic supply chain,” he said, “and that is unlikely to return to the U.S. Instead of trying to make established products in the U.S., we’re going to have to focus on next-generation technologies” in, for example, advanced pharmaceuticals.

Some of the hurdles are practical. The U.S. needs to rebuild its supplier base, as well as invest in more efficient manufacturing equipment. The average age of industrial equipment in the U.S. has passed 10 years old, the highest since 1938. This article is a good way to start off the new semester as it brings current OM issues to the fore.

Classroom discussion questions:

1. What factors work against the U.S. regaining the millions of manufacturing jobs that were lost?

2. Why is manufacturing so important?

OM in the News: Manufacturing in the U.S.–The Negative View

Exemplified by headlines such as “The Insourcing Boom” and “More U.S. Companies Are Reshoring,” the publicity for these cases has influenced public opinion and public policy. About 57% of U.S. manufacturing CEOs now believe that the U.S. is undergoing a manufacturing renaissance. But “the purported increase in the reshored jobs to offshored jobs ratio has not materialized,” writes Industry Week (Jan. 12, 2015). Around 30,000-40,000 manufacturing jobs are reshored while 30,000-50,000 jobs are offshored annually. Certainly this is an improvement from the 2000s, when the U.S. offshored as many as 150,000 jobs annually. U.S. manufacturing has been growing since 2010, adding 520,000 jobs and expanding 2.4% in real value added growth. But almost all of this growth represents cyclical recovery from the lows of the Great Recession.

Industries that suffered large declines in demand during the recession have increased production as demand has recovered. This is most evident in durable goods, which typically have the largest cyclical swings. In fact, durable goods have accounted for 72% of manufacturing job growth since 2010. By comparison, all non-durable goods together comprised just 3% of the job growth and had negative real value added growth of 6.8% from 2010 to 2013. So why is the reality so much more disappointing than the hype?

Experts cite increased global shipping costs with making producing in America more cost effective. In fact, global shipping costs, while elevated significantly in the late 2000s, have fallen dramatically and are back to normal. Likewise those who claim that a weak dollar will spur reshoring ignore that the value of the dollar is no lower than it was in mid-2000s when the U.S. lost a significant share of manufacturing to foreign competition, and has increased 13% in the last year.

Others write that labor cost differentials are narrowing with China. While this is true, the Chinese manufacturing laborer earns just 12% of U.S. wages and it appears that Chinese productivity is growing significantly faster than U.S. productivity. Finally, many tout the miracle of shale gas. While lower energy costs certainly help, energy costs are less than 5% of total costs in 90% of U.S. manufacturing industries. In other words, for most manufacturing industries energy savings are modest.

Classroom discussion questions:

1. Why is reshoring so difficult?

2. Is there a resurgence in American manufacturing?

Good OM Reading: Can Parking Behavior Predict Productivity Gains?

One of the well-known experimental studies of people’s behavior is the “Stanford marshmallow experiment” in 1970 in which children were put in an room and given the following instructions: they are given one marshmallow and can eat it immediately; however, if they wait for 15 minutes without eating it, they will receive another marshmallow. The most interesting finding is that more than 10 years later, the children who resisted the temptation to eat immediately and earned the second marshmallow “were significantly more competent” and achieved higher SAT scores. In general, people who exhibit the ability to delay gratification tend to do better in career and life.

And every once in a while, we come across an academic journal article that is equally fascinating. The concept is that at the macrolevel, a metric that measures the overall effort of delaying gratification across economies would better gauge or explain economic growth differences across countries. Prof. Shaomin Li, at Old Dominion U., proposes a novel metric in his fascinating article in The International Journal of Emerging Markets (No. 4, 2014): the way that people park their cars.

Back-in parking takes more time and effort than head-in parking. Yet, it is easier, quicker, and safer when exiting. Thus Li conjectures that people who take the trouble to back in demonstrate the ability to delay gratification; they want to invest more time and effort now so that they can enjoy the fruits of their labor later. They demonstrate a culture of long-term orientation. Such behavior, says Li, should be positively associated with taking time to study, saving more money and working harder in order to enjoy life later, a trait that contributes to national productivity gains and economic growth. The table summarizes the analysis.

OM in the News: Looking Back–and Forward–on Productivity

Frederick Taylor revolutionized manufacturing at the turn of the 20th century with a simple insight. Most manufacturing work was a sequence of physical motions. You would load coal onto a shovel, carry it to a furnace, throw it into the furnace, walk back to the coal pile and repeat. In a time and motion study, he quantified each step and how long it took. Then he analyzed how to improve the whole process. He noted, for example, that a typical worker could lift 21 pounds for maximum efficiency. Workers varied in size and strength, but on average this weight balanced the number of shovel lifts per minute against the volume per lift. In those early days, workers used the same shovel for all materials, regardless of the density of the stuff being lifted, so less weight was being lifted for the less dense materials. Taylor’s elegant and simple solution — bigger scoops for shovels used to haul the less dense materials — illustrates how careful analysis of a specific work process can increase productivity.

Today, his time and motion studies seem antiquated. Phone calls and memos have replaced shovels and picks for many workers. “Yet despite its association with early factories, a modern version of the spirit of Taylorism is sorely needed,” writes Harvard’s Prof. Sendhil Mullainathan in the New York Times (Sept. 28, 2014). “It’s time to identify and optimize the specific psychologies that constitute the mental alchemy of productivity,” he says.

In one Stanford experiment, some workers were randomly assigned to work at home, others worked in group call centers. The work habits of both groups were carefully monitored electronically, and the workers knew it. Those working at home were 13% more productive than those in call centers. With modern technology, we now have so many ways to quantify, track and motivate productivity, and are just beginning to scratch the surface of doing so.

Classroom discussion questions:

1. Why is productivity such an important issue in OM?

2. Describe how time and motion studies are conducted (see Chapter 10).

OM in the News: UPS Tries to Increase its E-Commerce Efficiency

In 1998, as much as 85% of e-commerce purchases were shipped between businesses. But along came Amazon, which helped convince a generation of Americans to buy even humdrum household items like diapers and toiler paper online rather than at the store. UPS drivers who used to drop off a bunch of heavy packages each day at one retailer, now make several stops scattered across a neighborhood, delivering one lightweight package per household. The shift required more fuel and more time, increasing the cost to deliver each package.

Last Christmas season, nearly 60% of all U.S. deliveries by UPS were e-commerce packages to consumers, compared with about 40% for all of 2012. Today, UPS’s haul includes much of Amazon’s 2-day-delivery Prime business. On residential routes, as much as 1/3 of trucks are filled each day with Amazon packages. And last Christmas, when UPS was overwhelmed by a pileup of online shipments at its massive Louisville facility, there were hundreds of trailers stacked up filled with Amazon orders.

UPS’s responses, reports The Wall Street Journal (Sept. 12, 2014): (1) Increase spending on new technology and extra manpower by 21% to $2.5 billion in 2014; (2) A pricing change that will encourage UPS customers to use boxes that fit the items being shipped, freeing up space in trucks for additional deliveries, or else pay extra; (3) Major savings from its route-optimization system, Orion. (Orion analyzes millions of pieces of data to predict the most efficient way to deliver and pick up packages along each driver’s route. Every mile cut saves the company $50 million a year, with half of UPS’s delivery routes in the U.S. using Orion by 2015.); and (4) My Choice, a service that alerts customers the day before a home delivery is set to arrive, provides an estimated delivery time and lets customers tell the driver where to leave the package. (Already 10 million customers have signed up for the $40/year service).

Classroom discussion questions:

1. How has OM helped UPS’s efficiency?

2. What new threats does UPS face in its shipping business?

OM in the News: The Downside of Increasing Productivity

“What has happened in agriculture over the past century is remarkable,” writes Harvard Prof. Larry Summers in The Wall Street Journal (July 8, 2014). The share of American workers employed in agriculture has declined from over 1/3 a century ago to 1-2% today. Why? Because agricultural productivity has risen spectacularly, with mechanization reducing the demand for agricultural workers even as food is more abundant than ever. What has happened in agriculture is happening to much of the rest of the economy.

In Marc Andreessen’s phrase, “Software is eating the world.” Already the number of Americans doing production work in manufacturing and the number on disability are comparable. Despite an expected uptick in the next few years in manufacturing employment, the long-term trend is inexorable and nearly universal. As in agriculture, technology is allowing the production of far more output with far fewer people. No country can aspire to more of an increase in competitiveness than China, yet even it has suffered a decline in manufacturing employment over the past 2 decades. And the robotics and 3-D printing revolutions are still in early stages.

What about services? A generation from now, Summers thinks taxis will not have drivers; checkout from any kind of retail establishment will be automatic; call centers will have been automated with voice-recognition technology; routine news stories will be written by bots; counseling will be delivered by expert systems; financial analysis will be done by software; single teachers will reach hundreds of thousands of students, and software will provide them with homework assignments customized to their strengths and weaknesses.

Those losing jobs due to increased productivity will be freed up to do things in other sectors. But there are many reasons to think the software revolution will be even more profound than the agricultural revolution. This time around, change will come faster and affect a much larger share of the economy. Workers leaving agriculture could move into a wide range of jobs in manufacturing or services. Today, however, there are more sectors losing jobs than creating jobs.

Classroom discussion questions:

1. What are the OM implications of Summers’ article?

2. What do you think American manufacturing will look like in 20 years?

Good OM Reading: The State Of Operations Management in the Military

Seventy-five years ago, near the beginning of World War II, the field of operations research was born in Britain. Today, as the U.S. emerges from the longest sustained war in its history, the military faces a post-war drawdown. During the mid-1990s, much of the conventional wisdom was that the U.S. was in the midst of a so-called “Revolution in Military Affairs.” Technology would provide a global precision strike capability that would give us “an ability to bomb any target on the planet with impunity, dominate any ocean, and move forces anywhere to defeat just about any army.”

In an excellent article just published in OR/MS Today (Feb., 2014), we read of a “vigorous military science” in the 1990’s, resulting in an excessive focus on modeling and simulation technology. For example, medical “planning factors” were derived from attrition-based, theater-level campaign model casualty projections, vastly over predicting casualties, thereby creating unnecessary and unaffordable requirements for medical force and supply support. More recent analyses of casualties have yielded major improvements in forecast accuracy and an ability to better design more responsive, lower cost medical support requirements. Research efforts have expanded to other areas, identifying spare part consumption patterns and readiness “drivers.” Using empirically derived usage patterns, profiles, and trends, the operational planning, demand forecasting and budget requirements have been significantly improved.

Persisting supply chain problems that existed 10 years ago are now also becoming increasingly more apparent. With mounting pressures to generate savings and find efficiencies, these issues include the inability to relate resources to readiness due to poor inventory management and fragmented supply chain operations across the materiel enterprise. The promise for improved performance attributed to large investments in enterprise resource planning (ERP) systems has not been realized, continuing to plague the services. But a recent study suggests major OM improvements can be achieved using decision-support systems empowered with advanced analytics, including dramatically improved demand forecast methods, sensor-based technologies for part replacement, and integrated supply chain optimization methods. These effects are likely to be in the range of many billions of dollars, resulting in a ROI of several orders of magnitude.

OM in the News: Productivity and Technology Down on the Farm

An Iowa farmer using tractor-mounted computers to help make decisions about planting crops

We are fully aware that few of our students will be entering jobs in agriculture (see Figure 1.5 in Chapter 1 for employment figures in the U.S. manufacturing, service, and farm sectors). Yet this Wall Street Journal (Feb. 26, 2014) article on the next revolution on the farm is still worth sharing with your class. The revolution will come from feeding data gathered by tractors and other machinery into computers that tell farmers how to increase their output of crops like corn and soybeans.

Monsanto, DuPont, and other companies are racing to roll out “prescriptive planting” technology to farmers across the U.S. who know from years of experience that tiny adjustments in planting depth or the distance between crop rows can make a big difference in revenue at harvest time. Many tractors and combines already are guided by Global Positioning System satellites that plant ever-straighter rows while farmers, freed from steering, monitor progress on iPads and other tablet computers now common in tractor cabs. The same machinery collects data on crops and soil. But many farmers have haphazardly managed the information, scattered in piles of paperwork in their offices or stored on thumb drives clattering in their pickup truck ashtrays.

Algorithms and human experts crunch all the data and can zap advice directly to farmers and their machines. Supporters say the push could be as important as the development of mechanized modified seeds in the 1990s. Data-driven planting advice to farmers could increase world-wide crop production by about $20 billion a year, or about one-third the value of last year’s U.S. corn crop. The technology could help improve the average corn harvest to more than 200 bushels an acre from the current 160 bushels. Such a gain would generate an extra $182 an acre in revenue for farmers.

Classroom discussion questions:
1. Why are farmers concerned about Monsanto’s involvement?

2. How has productivity improved over the past decades on farms?

Guest Post: A Class Exercise Relating Productivity and the Olympics

Howard Weiss is Professor of Operations Management at Temple University. He has developed both POM for Windows and Excel OM for our text

When I teach productivity, I like to explain to the students that while output/input seems simple, it can be difficult to assess. The Heizer/Render textbook includes multifactor productivity (Chapter 1) where the multiple factors are all inputs, and I like to ask my students to take it a step further.

There are many web sites that list the Olympic medal count for any Olympics. I show my students the top medal-winning countries from one of the more recent Olympics, such as those listed at http://en.wikipedia.org/wiki/2012_Summer_Olympics_medal_table.

When I am in the classroom I ask my students, “What information would you want in order to answer the question, “Which of the 5 countries shown below was the most productive in the 2012 Olympics?” This raises many interesting issues. Students will discuss the different inputs that might be used such as population, dollars spent training the Olympians and number of athletes competing. Some students will note that different outputs can be used. For example, outputs could be total medals or a weighted average of gold, silver and bronze medals. For the 2012 Olympics, I point out that based on the sorting in Wikipedia, it is using only gold measures, as its output measure as can be seen when comparing Great Britain and Russia or South Korea and Germany.

I also ask the students to find websites that list the countries in a manner that we would call productivity. This web site has a graph of the top 8 countries based on medals per athlete while this one includes the inverse of productivity in its table on athletes per medal.

The students generally find this to be a fun exercise and appreciate that inputs and outputs may not be as simple as one might think. In the course of searching for Olympic productivity on web sites, they also find sites that are interesting even though the site does not answer the productivity question. One example is this site, which explains that American workers are less productive during the Olympics. Finally, the exercise was very timely this past week since the Olympics are currently going on.

OM in the News: U.S. Factory Jobs are Gone?

The headline in the latest BusinessWeek article (Jan.27-Feb. 4, 2014) reads: Factory Jobs are Gone. Get Over It. The magazine writes: “Politicians think creating millions of high-tech manufacturing jobs is the answer. It isn’t.” Over the past 60 years, U.S. GDP increased from $2.6 trillion to $15.5 trillion, which means that absolute manufacturing output more than tripled. Those goods were produced by fewer people. As we note in Chapter 1, the number of employees in manufacturing was 16 million in 1953 (about a 1/3 of total nonfarm employment), 19 million in 1980 (about a 1/5), and 12 million in 2012 (about a 1/10). Service industries have taken up the slack. Even much of the value generated by U.S. manufacturing involves service work—about a 1/3 of the total. More than 1/2 of all people still employed in the U.S. manufacturing sector work in such services as management, technical support, and sales.

Over the past 30 years, manufacturers have spent more on labor-saving machinery and hired fewer (but more skilled) workers to run it. From 1980 to 2012 across the whole economy, output per hour worked increased 85%. In manufacturing output per hour climbed 189%. The proportion of manufacturing workers with some college education has increased from 1/5 to 1/2 since 1969.

Developing countries have taken over much of the low-skilled, low-capital production once done in the U.S. Consider the garment industry or tire manufacturing. Such low-tech work is even more mind-numbing and poorly paid than it was when the work was done in the U.S. through the 1970s. Many of the workers killed in the recent Rana Plaza garment factory collapse in Bangladesh earned just $3 a day. Some politicians have regretted the loss of similar jobs in the U.S. The question is: Do we want such jobs here now?

For every $1 spent by the federal government on retraining workers and helping them find jobs after they lost theirs to trade competition, the U.S. spends about $400 on Social Security and disability payments for those who exit the workforce rather than seek new work. So perhaps retraining programs are the solution.

Classroom discussion questions:

1. How has productivity impacted manufacturing in the U.S.?

2. Will the U.S. recover the millions of factory jobs it lost since 1953?

OM in the News: The Changing Workforce

IN 1930, John Maynard Keynes worried of a new disease: “technological unemployment…due to our discovery of means of economizing the use of labor outrunning the pace at which we can find new uses for labor.” Now, 2 Oxford professors are arguing that jobs are at high risk of being automated in 47% of the occupational categories into which work is sorted. That includes accountancy, legal work, technical writing and a lot of other white-collar occupations.

Automation processes have steadily and relentlessly squeezed labor out of the manufacturing sector in most rich economies, writes The Economist (Jan. 18-24, 2014). As we note in Chapter 1, the share of U.S. employment in manufacturing has declined sharply since the 1950s, from almost 30% to less than 10%. At the same time, jobs in services soared, from less than 50% of employment to almost 70% (see chart). It was inevitable that firms would start to apply the same automation to service industries.

The case for a highly disruptive period of economic growth is made by MIT profs in “The Second Machine Age.” Like the first great era of industrialization, they argue, it should deliver enormous benefits—but not without a period of uncomfortable change. They write that the amount of progress computers will make in the next few years will equal to the progress they have made since their very beginning!

The combination of big data and smart machines will take over some occupations wholesale; in others it will allow firms to do more with fewer workers. Some jobs—especially those currently associated with high levels of education and high wages—will survive (see table). Rich economies seem to be bifurcating into a small successful group of workers with skills highly complementary with machine intelligence, with the rest of workers less successful.

Classroom discussion questions:

1. In what service jobs will automation be a major factor?

2. Will manufacturing reverse its downward slope of employment?