If this sounds familiar, it should. It has been nearly two decades since retail overtook manufacturing as the nation’s most important job creator, employing roughly one of every 10 American workers—more people than in health care and construction combined. That’s a lot of jobs.
Of course, not all retail jobs qualify as what most of us consider good jobs. Today, the average hourly wage for a nonsupervisory retail worker is $11.24, and less than half of retail workers receive benefits of any kind. Still, as a nation, we’ve come to a sort of uneasy peace with this trend. We know that manufacturing employs far fewer Americans today than it once did—that iPads and Macs aren’t made in America and neither are many televisions, appliances, tools, toys or clothes. We also know that shopping for these appliances, tools, toys and clothes is an all-American pastime: On average, we spend nearly 45 minutes a day (more than 270 hours per year) purchasing goods and services. Retail has become the world as we know it, and many of us expect to make our living working in that world.
And yet, traditional retail is under threat—from the same forces that are disrupting virtually every sector of the American economy. Last month’s announcement of historically low unemployment numbers brought cheers but also confusion: Given what economists called the nation’s “full employment,” why did so many of us feel left behind? After all, Americans have acquired more education and are more productive than ever before. Yet, as it turns out, our feelings of being ripped off are justified. More than 80 percent of us are not reaping the bounty of our own education and productivity. For while unemployment is technically at a historic low point, underemployment is rampant. Fully 20 percent of men aged 24 to 55 do not have full-time jobs, and nearly half of all new college graduates are unable to find a job that comports with their education. (Contrary to popular thinking, college students are not impractical “basket weaving” majors—roughly 40 percent earn degrees in “occupational” disciplines such as business, legal studies and public administration, an 80 percent increase since 1970.)
And while Uber drivers and freelance dog walkers technically count as “employed,” they are not employed in the sort of occupation that typically offers a living wage. The bottom line is this: Technology has advanced at a breathtaking pace, while the policy designed to help workers deal with these changes has lagged far behind. Hence, the financial benefits of technological change accrue mainly to the few, while the majority of Americans are left with crumbs—precarious, unstable employment that reflects neither their abilities nor their potential.
“We’re at a unique point in human history,” Rice University computer scientist Moshe Vardi says. “We are sitting on the cusp of an enormous change.”
In retail, this is the challenge: When it comes to profits, no brick-and-mortar store—no matter how efficient—can hold a candle to e-commerce, which since 2014 has become the fastest-growing retail sector by far. China’s Alibaba Group—Asia’s most valuable company—is the world’s largest player in this keenly competitive arena. But Alibaba has so far failed to gain a foothold in the United States. In America, Amazon—the nation’s fastest-growing employer—reigns supreme.
Analysts predict that by 2020, one-fifth of the multitrillion-dollar U.S. retail market will have shifted to the web and that Amazon alone will reap two-thirds of that bounty. The company already captures one of every two dollars Americans spend online and is by far the nation’s biggest seller of books, music, video games, cellphones, electronics, small appliances, toys, magazine subscriptions and what seems like almost everything else—hence its nickname, “The Everything Store.”
The company grabs gobs of market share in nearly every retail category, including its own food line. It produces TV shows and movies; manufactures thousands of products, from batteries to baby food; and owns such familiar brands as Zappos, Shopbop, IMDb, Audible and Twitch. Amazon Handmade is challenging Etsy with the artisanal set, and Amazon Business is threatening Staples and other independent office suppliers. And with every click, the company gathers critical information—our addresses and credit histories, as well as everything we’ve ever bought or even looked at on the Amazon site—and uses the data to build an even more intimate relationship with each of us, with the goal of cultivating still more of our business.
Thanks to automation and a killer business model, Amazon is so efficient that it reaps nearly twice the revenue per employee of Walmart, despite the fact that Walmart, too, has a substantial online presence. Worldwide, Amazon has installed over 100,000 robots to labor in “perfect symbiosis” with humans in its warehouses and has plans to install many thousands more. While it’s not clear what constitutes perfect symbiosis, the robots are said to save the company $22 million annually, per warehouse. The company’s master plan of an autonomous future also includes goods delivered by drones and self-driving vehicles.
For while Amazon continues to open warehouses around the globe and staff them with many thousands of human beings, estimates are that every human on the Amazon payroll—whether full- or part-time—displaces two humans at traditional brick-and-mortar operations. And that’s a feature, not a bug: As Tim Lindner, a veteran IT analyst, confided in a note to industry insiders, eradicating jobs is the explicit goal of any online retailer. As he once wrote: “Labor is the highest-cost factor in warehouse operations. It is no secret that Amazon is moving to highly automated operations within its distribution centers, and…it has additional technology that can further reduce the number of humans it needs to process customer orders.… You have heard the old programmer’s phrase, ‘Garbage in, garbage out.’… [With] the diminishing reading abilities of humans on the Receiving dock, finding an automated solution to eliminate the ‘garbage in’ problem is the holy grail. Amazon may have just patented it.”
By garbage, Lindner meant human error, the alternative to which is apparently robotic precision. And robots can be very precise, especially when it comes to routine tasks. Sawyer, an industrial robot created by the former Boston-based Rethink Robotics, offers an impressive illustration of how all-embracing a robot arm can be. Sawyer is the brainchild of Rodney Brooks, the inventor of both Roomba, the robotic vacuum, and PackBot, the robot used to clear bunkers in Iraq and Afghanistan and at the World Trade Center after 9/11. Unlike Roomba and PackBot, Sawyer looks almost human—it has an animated flat-screen face and wheels where its legs should be. Simply grabbing and adjusting its monkey-like arm and guiding it through a series of motions “teaches” Sawyer whatever repeatable procedure one needs it to get done. The robot can sense and manipulate objects almost as quickly and as fluidly as a human and demands very little in return: While traditional industrial robots require costly engineers and programmers to write and debug their code, a high school dropout can learn to program Sawyer in less than five minutes. Brooks once estimated that, all told, Sawyer (and his older brother, the two-armed Baxter robot) would work for a “wage” equivalent of less than $4 an hour.
Robots loom large in discussions of work and its future, a conversation that can get mired in false assumptions. Until recently, many economists were skeptical that automation could permanently displace human workers on a large scale. People have always shifted away from work better done by machines, but the economic principle of “comparative advantage” predicts that humans will maintain an edge in many fields. Under this logic, technology will not displace us but set us free to do less dangerous, more challenging things, essentially the very things that make humans human.
For example, in 2016, the National Highway Traffic Safety Administration officially recognized “software” as a driver of self-driving cars, thereby putting the nation’s 4.1 million paid motor vehicle operators—drivers of taxis, trucks, buses and Uber—on notice. Theoretically, this will free these drivers to fill new roles—such as ones in Amazon warehouses. But these warehouses are also becoming automated, as are any number of other places with jobs once filled by the vast majority of what economists call “middle-skill workers,” the very people who once populated—and bolstered—the American middle class. Workers like the thoughtful department store salesman who helped measure you for the suit you wore to your daughter’s wedding, the patient butcher who carved out the chops for the pre-wedding dinner or the travel agent who helped plan the honeymoon.
Of course, human workers are complicated. We get tired, hungry, distracted, angry, confused. We make mistakes, sometimes egregious ones. Machines lack our frailties and biases and are better equipped to weigh evidence fairly, without prejudice or false assumptions. Perhaps most critically, machines can retain and process data far more accurately than we can, and that data is growing exponentially.
Every minute of every day, Google services 3.6 million searches in the United States alone. Spammers send 100 million emails. Snapchatters send 527,000 photos, and the Weather Channel broadcasts 18 million forecasts. This and more data—properly collected, codified and analyzed—can be applied to automate almost any high-order task. Data can also serve as a surrogate for human experience and intuition. Online shopping and social media sites “learn” our preferences and use that information to make values-based assessments to influence our decisions and behavior. And, increasingly, machines excel in the tasks once thought uniquely human.
“Computers are able to see and hear, and have face-recognition capabilities that are significantly better than humans,” says Vardi. “Machines understand the human world far better than they did just a few years ago. And we haven’t discovered anything in the human brain that can’t be modeled.”
Bart Selman is a professor of computer science at Cornell University and an expert in knowledge representation—basically, translating the real world into terms computers can understand and act upon. He cautions that computers do not yet have full human capabilities. For example, they lack “common sense” and an ability to grasp the deep meaning of language. They are unable to “make meaning” in the human sense, and this sometimes leads them down the wrong path. Still, he says, these shortcomings are likely temporary. “The [artificial intelligence] community believes that machines will match human intelligence within the next 15 to 20 years,” he says.
And robots need not be perfect, only equal to—or a tad better than—complicated and expensive humans. And technologists are working hard to make sure they are a tad better. For example, in the case of retail, it’s become clear that many of us avoid the self-service checkout line—we prefer the cashier to punch in our purchases rather than do so ourselves. So it seems that the job of cashier—among the largest retail employment categories—is not directly at risk. But Zeynep Ton, an MIT management expert who focuses on the retail sector, says self-service checkout is only a first step and not a terribly smart one. “Customers recognized that self-service checkout is not an innovation, but merely a way of outsourcing the job to them, so they didn’t like it,” she says. “But new technology is coming that will make self-service checkout so much easier and faster, and that will have a real impact on retail employment.”
Experts caution that the so-called apocalypse in retail predicted a few years ago has not yet come to pass. In fact, for every company closing existing stores, two more are opening new stores. Retail is a highly competitive industry, and technology is transforming not only the way we shop but the way we connect with brands—for example, just a few years ago, who would have imagined that Amazon would open actual retail stores? And while e-commerce has grown to 10 percent of retail, that still leaves 90 percent for brick-and-mortar stores. But those brick-and-mortar stores, too, are undergoing radical change that has serious implications for America’s workforce.
Kasey Lobaugh is chief retail innovation officer at Deloitte Consulting LLP. “The loss of market share by traditional retail companies is not simply an online vs. bricks-and-mortar battle, with traditional retailers losing the e-commerce game,” he says. “Traditional retailers are also being challenged by what we call ankle biters,” small, nimble companies that—thanks to technology—can reach consumers without a massive capital outlay.
As example, Lobaugh cites food trucks, which he says increasingly pose a threat to many fast-food outlets. Unlike restaurants pinned down by a pair of Golden Arches, food trucks are nimble—they can home in on areas where customers are most likely to gather at any particular time. They can also tailor their offerings to a particular region or even a neighborhood, as well as use Facebook or other media to get out the word on their menu items and locations. Small, specialty stores also have far more flexibility than large department stores. “Technology has reduced the cost of entry into new markets, so in retail there are fewer big, monolithic companies, but more small competitors,” he says. “Companies are diversifying to meet the specific needs and desires of consumers—everyone’s piece is getting smaller, but there are many more pieces.”
Technology has engendered a two-tiered retail landscape—with more high-end boutique-type stores appealing mostly to high-wage earners, and many more discount stores appealing to price-sensitive customers. “More than 1,000 discount stores opened in the U.S. this year alone, as did a large number of what we call ‘premier’ high-end niche stores,” Lobaugh says. What’s declining is what marketers call the “balanced” store—department stores and other retailers that balance quality and price for mid-market customers.
Perhaps it is not surprising that the decline of the “balanced” store correlated with the decline of the American middle class over the past decade. “Between 2007 and 2017, income gains—an average increase of $50,000 in household income—went mostly to the top 20 percent of earners,” Lobaugh explains. “In fact, this group gained more than 100 percent of the increase, because the bottom 40 percent actually lost ground. The middle 40 percent gained $10,000 per household. But their expenses increased—food, housing, transportation. Health care skyrocketed. On top of that came digital necessities—things like cellphones and data plans. That leaves most people very little money to spend on retail, which means they have become very, very price sensitive.”
Lobaugh prefers not to speculate about what all this meant for the retail worker, other than to say the trend was “transformative.” But what is clear is that discount stores employ fewer workers per square foot of store space and tend to offer low wages and fewer hours: The number of hours per employee has actually dropped over the past decade. John Challenger, CEO of Challenger, Gray & Christmas, a Chicago-based global outplacement & career transitioning firm, said he sees more changes ahead. “I think we’re in the opening phase of what happened to manufacturing in the 1980s and 1990s,” he says. “There’s no question that store workers are vulnerable to technology and that untold numbers have already been displaced.”
Asked where all these retail workers had gone, he says it was likely many had found new jobs in trucking, shipping, distribution—that is, warehousing. And after all, in October, Amazon announced its decision to raise minimum wage at its warehouses and retail outlets to $15 an hour, a big jump for many retail workers.
But despite what it predicts will be a banner holiday season, this year Amazon took on far fewer seasonal employees than usual—100,000 employees versus 120,000 the previous two years. And while an Amazon spokeswoman insisted that automation is not a factor in this reduced workforce, others seem to not agree. In a recent report, Morgan Stanley analyst Brian Nowak soothed the fears of Amazon shareholders concerned with the wage increase by pointing out that automation had already and would continue to reduce the call for labor, and therefore reduce overall costs. When asked about this, Lobaugh again tactfully declined to comment—other than to say that while the retail sector had lost less ground than most people assume, retail employees were another matter. “There are winners,” he says, “and then there are losers.”
Hod Lipson, a professor of mechanical engineering at Columbia University, directs the Creative Machines Lab, where he and his students train machines to be reflective, curious and, yes, creative—including in the kitchen. When we spoke, he was putting the final touches on a device that uses software to concoct beautifully composed gourmet delights from a jumble of pastes, gels, powders and liquid ingredients. From the looks of it, this machine could compete with a three-star Michelin chef and her entire staff. When I ran this thought by Lipson, he groaned. He says scientists and engineers like himself have a reflexive urge to automate almost every difficult task. The whole point of engineering, he says, is to alleviate drudgery and increase productivity; in the past, that was almost always the right thing to do, the good thing to do. But now he’s not so sure.
“Automation and AI will take away pretty much all of our jobs,” he says. “If not within our lifetime, then within our grandchildren’s lifetime. This is a new situation in human history, and we’re not prepared for it. Maybe we think we are, but we’re not.”
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