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Shift Change

‘Future of work’ expert Jeff Schwartz ’80 on coping in the COVID era—and how it has accelerated the evolution of the modern office



Veteran management consultant Jeff Schwartz ’80 (right) had been writing his nonfiction book for two years—with just a few months to go before his publisher expected the manuscript—when the COVID lockdown struck last March. Like workers worldwide, Schwartz went from commuting and taking business trips to hunkering down in a home office and holding meetings via Zoom. It was an ironic time to be putting the finishing touches on a management guide—particularly one entitled Work Disrupted. Published by Wiley and written with journalist Suzanne Riss, the book taps Schwartz’s expertise as a founding partner of Deloitte Consulting’s “future of work” practice to contemplate shifts in the modern office, from the role of technology to novel approaches for team collaboration. A College Scholar who studied government and history in Arts and Sciences, Schwartz served as a student-elected trustee on the Hill; he spent two years as a Peace Corps volunteer in Nepal, teaching math and science in a rural village, before earning a master’s in public affairs from Princeton and an MBA from Yale. He’s now a principal at Deloitte, where he has spent the past two decades.

Will COVID-driven work changes persist afterward?
Most of the things that have happened are trends that we were already seeing. COVID has been described as a time machine or a bullet train to the future, one of the biggest experiments in history: moving 3.2 billion people to remote work. Before COVID, something like 5 percent of the workforce that could work remotely was doing so. Then that number shot up dramatically; at one point almost half the workforce was working remotely. I certainly don’t expect that we’re going to go back to the office the way we did before; we’re going to see a hybrid approach. More people will spend two or three days at the office and two or three working from home, and management practices will be organized around that. We’re learning from the COVID era that where and how we work are not binary questions.

Is how people are dealing with remote work now different from last spring? Have things gotten easier?
I think it’s been very hard; people are exhausted, mentally and physically. That being said, we continue to show that we are remarkably adaptable. In March, April, and May we adopted a “lift-and-shift” mentality: “How do we lift the work we were doing before and put it on Zoom, Skype, Teams, and Slack, and operate in a fairly similar way?” What we’ve seen over the summer and fall is that we’ve begun to explore new ways to work remotely and virtually. It’s been difficult, but I believe we’ve been incredibly innovative—the same way that restaurants have split themselves among outdoor dining, limited indoor dining, and doing as much delivery as they can. We can run these global economies in dramatically new ways.

Could you give an example?
In the book, we talk about what we call “super teams”—teams of diverse individuals and technologies working together. I spoke recently with the executive of a pharmaceutical company that’s working on a COVID vaccine, and we talked about the team they’d put together: they had identified hundreds and actually thousands of people—both inside and outside the company, including research universities and other pharma companies—and it created a much more fluid way of working. I asked this executive, “So after COVID, is your company going back to what it did before?” And I got a version of, “No way.”

How has COVID changed your own work life?
I was a pretty intensive road warrior—I traveled somewhere every week and internationally almost every month. But I haven’t been on an airplane since March 3. I don’t think I’ve been in the same place for this long for thirty years. We have these great offices at 30 Rockefeller Plaza, and I’ve been there twice, both for photo shoots for the book. I’ve been working out of a small home office on the Upper West Side of Manhattan.

As an expert in the field of work, how are you coping?
The main thing I’ve learned was to try to create even a small bit of separation between work and your personal life. Getting ready for work in the morning, getting the cup of coffee before I sit down, establishing a schedule. One thing that has worked well for me is I do about an hour of calls walking in the neighborhood every day. Incorporating a little bit of wellness into my day has been extremely helpful.

Are there things you miss about that road warrior life?
I miss the social stimulation and the cultural aspects of traveling. I don’t miss being jet-lagged; I’ve learned something in the last eight or nine months about how hard that much travel is on physical and mental wellbeing.

Could you describe your book?
It’s organized around changing the mindsets and mental maps we have for work, careers, management, organizations—even for public policy around what twenty-first-century work and career looks like. The way I might describe it best is most of us are using twentieth-century maps to ride on twenty-first-century roads, and it’s not working out very well. One example is, What is the mental model we have of a career? The historical view is that you go to school, get a job, and retire; you follow a linear path, and maybe you change jobs once or twice in your life. That’s not what twenty-first-century careers look like. They’re not linear, they’re dynamic; they’re not pathways, they’re portfolios, with multiple chapters of lifelong reinvention.

One anecdote from the book relates to Cornellians: an ILR professor talks about how their perspective on their studies changes the longer they’ve been out of college.
Louis Hyman, who’s a labor economist, tells this great story about students and alumni at different points in their lives. When he talks to students in their last year at Cornell or the year after they graduate, they’re focused on operational stuff: learning technical data science languages, things that are current in the job market. When he talks to alumni who are five or ten years out, the focus sometimes shifts to management and organizational questions and being a team leader. And when he talks to alumni fifteen or twenty years later, they’re thinking more about history, philosophy, social dynamics. Of course these are generalizations. But Louis is reminding us that as we think about our careers and how we work, we need to combine all three—to be technically relevant and equipped, to think about how we manage a team, and to think about some of the larger historical, political, and social questions.

You describe a “whitewater future.” What’s that?
One of my mentors and I talk about the differences between still water, moving water, and whitewater as a way to discuss how the nature of our work and careers have changed. When you’re on a lake, it’s pretty easy to navigate and stay in the rowboat. If you’re in a sailboat, you have other factors to consider: the wind, the movements of the tides. And when you’re rafting in whitewater—rapids—you have a destination, but you have to navigate constantly changing circumstances along the way. In the book, we talk about Eric Yuan and the team leading Zoom as an example of navigating whitewater when they were scaling up in the early days of the pandemic. Nothing against a rowboat, but there’s something much more exhilarating about whitewater.


Work & Tech

In an excerpt, Schwartz explores why ATMs didn’t make bank tellers obsolete

Book cover for Work DisruptedThe surprising story of automatic teller machines (ATMs) and bank tellers offers a fascinating illustration of how new technology, if properly harnessed, can change individual jobs—or the tasks that make up the job—without eliminating the worker. The transformation of bank tellers provides a useful counterpoint to arguments by automation alarmists. When ATMs were first introduced in the 1970s, many predicted that bank tellers would lose their jobs. After all, ATMs took over their basic job functions, making it possible to deposit a check or withdraw cash from a machine. This new “automatic” teller seemed to be able to do everything the human teller did. So what happened to bank tellers? Since ATMs appeared on the scene, the number of human bank tellers in the United States has roughly doubled, according to Boston University economist James Bessen. He has noted that the adoption of ATMs did not, in fact, reduce the number of teller jobs—it changed their jobs. Indeed, their jobs evolved. New skills were needed. Bank tellers took on different roles, learning to assist customers with loans, open new accounts, market financial products, troubleshoot, and more—jobs that machines were unable to do.

Bessen reports that between the mid-1990s, when about 400,000 ATMs were introduced, and the year 2000, the number of teller jobs grew faster than the labor force as a whole. And while that may eventually change, the near-term impact of ATM technology actually created more jobs. The ATM created more full-time teller jobs at banks because it allowed banks to open more branches, since each branch could operate with fewer tellers, which also meant banks could hire more tellers overall. It should be noted that the jobs of bank tellers are not forever secure, however, due to continued industry consolidation and technological changes. And let’s not forget about mobile banking, which also involves automation of work previously handled by humans. However, it is interesting to note that the evolution of bank tellers’ jobs is similar to what happened in the nineteenth century with the textile industry. Though most of the work suddenly was automated, the number of weavers continued to grow for decades. More automation meant the price of cotton cloth fell, and people used more of it.

Projections that the future of work will usher in mass unemployment rest upon several flawed assumptions. The first is that a job consists of a single task. Most jobs consist of many tasks, not all of which can be automated. The second is that technology is a substitute rather than a complement to human labor. In most cases to date, technology augments but does not wholly eliminate human workers. What we tend to forget is that technological innovation could create jobs that we have not yet imagined. Changes in how we work have been underway for decades, as the activities in most occupations have shifted from basic and repetitive tasks to more advanced tasks. This means we spend less time collecting data and more time solving problems.

Elevator operators have the distinction of being one of the very few occupations in the past sixty years that has been eliminated from the Census Bureau logs due to automation. Add to this list the switchboard operator and the bowling alley pinsetter. Meanwhile, new job titles like app developer, social media director, and data scientist have emerged. A rule of thumb today is that if your job is repetitive, routine, and predictable, and you can easily describe it, chances are large portions of it can be automated. If someone can write a script that describes the job, or create a set of algorithms or rules, then a machine will be able follow those rules and do the work.

Our cultural idea of work has undergone dramatic shifts before. In the preindustrial economy, work was synonymous with craftsmanship, with someone creating a product from start to finish. For example, a cobbler would do everything from measure the customer’s feet to make any adjustments in the finished pair of shoes. The Industrial Revolution changed this conception of work, as it became clear that products could be manufactured more quickly and cheaply if work was divided into smaller, repeatable tasks in which workers could specialize. For many, the notion of a “job” became a collection of distinct tasks. Today, we appear to be redefining work again, with the shift moving in the opposite direction: as computers can complete more tasks, people may increasingly move from completing tasks to the more human capabilities, such as problem-solving, communicating, interpreting, addressing unexpected challenges, asking questions, and managing human (and human and machine) relationships.

There’s a lot of debate over whether things will be different this time around in the so-called Fourth Industrial Revolution. In the past, industrial revolutions centering on mechanization, electrification, and computerization dramatically reshaped jobs, especially for low-skill workers in agriculture and manufacturing. A key difference today is that advances in digital technologies are poised to have an impact on every sector of the economy. Another difference is that we are building machines that can do more than mechanize routine tasks that people already do. Machine learning means machines are able to move beyond the script of an algorithm to actually learn to do something on their own by discovering patterns. Machines can therefore propose new solutions to problems. This type of autonomy is what makes people feel uneasy.



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