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The impact of the pandemic on real estate – McKinsey

When the COVID-19 pandemic began, it dramatically changed the way people worked, lived, and shopped in cities around the world. The starkest change was where and how they worked. Obeying lockdowns and office closures, tired of uncomfortable masks, and enabled by remote-work technology, many employees abruptly retreated from traditional offices to home offices. Many of those employees, newly freed from their daily commutes, chose to move out of urban cores. And now that fewer of them were working and living near urban stores, fewer of them shopped there. In recent months, some of those behavioral shifts have slowed. Others persist, particularly among office employees continuing to engage in hybrid work (that is, a combination of remote and in-office work).
The behavioral shifts have already had major effects on real estate in “superstar” cities—roughly speaking, cities with a disproportionate share of the world’s urban GDP and GDP growth. In superstar cities’ urban cores, the percentage of office and retail space that is vacant has grown sharply since 2019, and home prices have increased more slowly than in the suburbs and other cities.
This report is a collaborative effort by the McKinsey Global Institute and McKinsey’s Real Estate Practice.
The research was led by Jan Mischke, an MGI partner in Zurich; Ryan Luby, a senior knowledge expert and associate partner in New York; Brian Vickery, a McKinsey partner in Boston; Jonathan Woetzel, an MGI director and senior partner in Shanghai; Olivia White, an MGI director and senior partner in San Francisco; Aditya Sanghvi, a McKinsey senior partner in New York City; Rob Palter, a McKinsey senior partner in Toronto; André Dua, a McKinsey senior partner in Miami; and Sven Smit, a McKinsey senior partner in Amsterdam and MGI chairman. The project team was led by Jinnie Rhee, a consultant in San Francisco; Anna Fu, a consultant in New York; Isabella Mayorga, an alumna; and Chris Longman, an alumnus. The team included Cristina Barrantes, Maclaine Fields, Lily Highman, Ricardo Huapaya, Marty Kang, Gaby Pierre, Jose Maria Quiros, Akanksha Raina, Surya Tahliani, Paula Trejos, Valeria Valverde, Caitlin Wischermann, and Cody Wollin.
We thank Nicholas Bloom, professor, Stanford University; Michael Joyce, senior managing director, Greystar; Jonathan Lurie, managing partner, Realty Corporation; Janet Pogue McLaurin, global director of workplace research, Gensler; Andrew Min, senior vice president, RXR; Alan M. Taylor, professor, University of California, Davis; and Ko Wang, professor, Johns Hopkins Carey Business School for kindly sharing their insights.
The project benefited immensely from the expertise and perspectives of many McKinsey colleagues. Thanks go to Colleen Baum, Gemma D’Auria, Kevin Heidenreich, Phil Kirschner, Dymfke Kuijpers, Adrian Kwok, Daniel Läubli, James Patchett, Ben Safran, Anthony Shorris, and Alex Wolkomir.
The report was edited by MGI senior editor Benjamin Plotinsky, together with senior data visualization editor Chuck Burke and editorial operations manager Vasudha Gupta. We also thank our colleagues David Batcheck, Cecilia Bayer, Tim Beacom, Amanda Covington, Shannon Ensor, Vero Henze, Karen Jones, Stephen Landau, Janet Michaud, Diane Rice, Rebeca Robboy, Rachel Robinson, and Katie Shearer for their support.
This research contributes to MGI’s mission to help business and policy leaders understand the forces transforming the global economy. As with all MGI research, it is independent and has not been commissioned or sponsored in any way by any business, government, or other institution.
To what extent could real estate in superstar cities continue to suffer? In this research, the McKinsey Global Institute has modeled future demand for office, residential, and retail space in several scenarios.1 In those scenarios, demand for office and retail space is generally lower in 2030 than it was in 2019, though the anticipated reductions in our moderate scenario are smaller than those projected by many other researchers. Our analysis also shows that the ripple effects will be complex—for example, that certain kinds of cities and neighborhoods will be more heavily affected than others. We considered a wide variety of factors, including long-term population trends; employment trends, such as the ongoing effects of automation; office attendance patterns by industry; employee coordination, defined as the maximum share of workers in the office at a given time; workers’ ages and incomes; the share of a city’s population that commutes from elsewhere; housing price variation among neighborhoods; and shopping trends, such as the ongoing increase in online shopping. In addition to many secondary sources, our modeling includes information from a large global survey that we conducted to understand the behavioral shifts caused by the pandemic.
We performed this research during a time of exceptional macroeconomic uncertainty. Inflation and interest rates are high; fears of recession are mounting; stress in the financial system has been making headlines. Actual outcomes, of course, will depend on how those variables and others play out.
What is certain is that urban real estate in superstar cities around the world faces substantial challenges. And those challenges could imperil the fiscal health of cities, many of which are already straining to address homelessness, transit needs, and other pressing issues. But the challenges also provide an opportunity to spur a historic transformation of urban spaces. By becoming more flexible and adaptable in everything from the makeup of neighborhoods to the design of buildings—in essence, becoming more “hybrid” themselves—superstar cities can not only adapt but thrive.
During the pandemic, workers’ office attendance plummeted. Untethered from their daily commutes, urbanites moved away from urban cores in greater numbers than they had before the pandemic (and fewer people moved in), and people spent less in urban stores (see sidebar, “How we define cities”). The rate of out-migration has now returned to its prepandemic trend, but our research suggests that few of the people who left will return and that urban shopping will not fully recover.
This report is about real estate in superstar cities—roughly speaking, cities with a disproportionate share of the world’s urban GDP and GDP growth. We have borrowed the term and the concept from the 2018 MGI report Superstars: The dynamics of firms, sectors, and cities leading the global economy. The report does not examine real estate outside superstar cities.
By city, we usually mean a large metropolitan area. Our analysis often separates such a metropolitan area into two parts: the urban core, which refers to the densest part of the area, and the suburbs, which refers to everything outside the urban core. For example, when we discuss San Francisco’s urban core, we mean San Francisco County, Alameda County, and San Mateo County. And when we discuss San Francisco’s suburbs, we mean the rest of the San Francisco metropolitan area (that is, Marin County and Contra Costa County).
We focus most closely on nine superstar cities: Beijing, Houston, London, New York City, Paris, Munich, San Francisco, Shanghai, and Tokyo. However, in the survey that underlies much of this report, we collected data from a larger set of 17 superstar cities in six countries in order to better understand behavior. At one point in our research, we were able to extend our analysis to a still larger set of 24 superstar cities to help us identify patterns in suburbanization.
Employees still spend far less time working at the office than they did before the pandemic, according to our survey. In early 2020, as they adopted remote work and hybrid work in response to lockdowns and health concerns, office attendance in the metropolitan areas we studied dropped by up to 90 percent. It has since recovered substantially but remains down by about 30 percent, on average. As of October 2022, office workers were visiting the office about 3.5 days per week. That number varied among cities, from 3.1 days in London to 3.9 in Beijing. (For more information about the survey, see the technical appendix.)
Office attendance also varies by industry and neighborhood. In large firms in the knowledge economy—which we define as the professional services, information, and finance industries—employees tend to go to the office fewer days per week (Exhibit E1). Characteristics of areas with lower office attendance include expensive housing, a higher ratio of inbound commuters to residents, and a small share of retail, according to our research on US counties. Local culture also plays a role.
There are several reasons to believe that the current rate of office attendance could persist. First, the rate has remained fairly stable since mid-2022. Second, three key numbers—the number of days per week that survey respondents go to the office (3.5), the number of days they expect to go to the office after the pandemic ends (3.7), and their preferred number (3.2)—are not far apart. Third, 10 percent of the people we surveyed said that they were both likely to quit their jobs if required to work at the office every day and willing to take a substantial pay cut if doing so let them work from home when they wanted. That group contains many senior, high-income employees, suggesting that they may wield influence over companies’ decisions. Nevertheless, it is not certain that the current rate of office attendance will persist; it could change, for example, if labor market dynamics shift or if research conclusively indicates either a negative or a positive relationship between hybrid work and productivity.
During the pandemic, a wave of households left the urban cores of superstar cities, and fewer households moved in. For example, New York City’s urban core lost 5 percent of its population from mid-2020 to mid-2022, San Francisco’s lost 6 percent during the same period, and London’s lost 7 percent from mid-2020 to mid-2021.2 The main reason was out-migration. In the suburbs, by contrast, populations grew, or they shrank less dramatically than populations in the urban cores did. In the United States, suburbanization had already been happening before the pandemic, and the shock accelerated an existing trend; by contrast, in most of the European and Japanese cities we studied, urbanization gave way to suburbanization (Exhibit E2).
The urban cores where population growth was smallest in relation to their suburbs tended to be those with expensive homes, high office density, a high share of workers in the knowledge economy, and limited retail presence—some of the same characteristics that shaped office attendance. London, Dallas, New York, San Francisco, and Boston were the most affected. In general, US urban cores were more affected than European and Japanese ones, which tend to have more mixed-use development, in which office, residential, and retail space exist alongside one another. The migration trends in Beijing were primarily shaped by prepandemic efforts to control the population size in urban cores by encouraging out-migration, efforts that were paused during the pandemic.
Out-migration from urban cores of superstar cities seems to have slowed, but it is still above prepandemic levels.
Hybrid work seems to have contributed significantly to out-migration. In our survey, among respondents who moved after March 2020, 20 percent said that their move was possible only because they could now work from home more frequently. In the United Kingdom and the United States, people who had moved from urban cores to suburbs, and who said that their move was possible only because they could now work from home, said that they were drawn by housing conditions: better neighborhoods, the prospect of homeownership, and outdoor space. In Japan and China, wanting to own a home was far and away the strongest factor motivating people’s moves to the suburbs.
Out-migration from urban cores of superstar cities seems to have slowed, but it is still above prepandemic levels. From 2019 to 2021, net out-migration from US superstar city cores doubled; then it fell in 2022, although it remained above 2019 rates. In other words, the people who moved out during the pandemic are not moving back, and others keep leaving.
As people stayed home during the pandemic, they radically shifted the way they shopped. Foot traffic plummeted near stores in the cities we studied, and online spending as a share of retail spending spiked.
More recently, foot traffic near stores in metropolitan areas has risen again, but it is still 10 to 20 percent lower than it was before the pandemic. A major reason for the decline is that online spending as a share of retail spending, which admittedly grew more slowly after the initial spike, nevertheless remains higher than it was in 2019.
Retailers in urban cores face particularly acute challenges in attracting customers. As of October 2022, foot traffic had recovered noticeably less near those stores than near suburban ones (Exhibit E3). In New York, for example, foot traffic near suburban stores was 16 percent lower than it had been in January 2020, but foot traffic near urban stores was 36 percent lower. And office-dense neighborhoods in urban cores are facing even more challenges. The reason seems to be that when people come to the office less often, they shop less often near the office. In our survey, respondents in the United States who worked at the office no more than one day per week reported doing much less of their total retail spending near the office than did those who worked in the office two to five days a week.
The behavioral changes caused by the pandemic—lower office attendance, accelerated out-migration from cities, and less shopping in office-heavy neighborhoods—will push down demand for real estate in most superstar cities. By 2030, in the scenarios we modeled, demand for office and retail space is generally lower than it was in 2019 (Exhibit E4). Residential space is less affected, though the price differences between urban cores and suburbs are narrower than they used to be. (Note that our model does not consider price elasticity; that is, it does not account for the fact that when demand decreases, prices fall, pushing demand partway back up. For more information about the model, see the technical appendix.)
Demand for office space has already declined, partly because of the increase in remote work and partly because of a challenging macroeconomic environment. Vacancy rates have increased in all the cities we studied. In the US cities, transaction volume (the total dollar value of all sales) fell by 57 percent, average sale price per square foot fell by 20 percent, and asking rents fell by nearly 22 percent (all in real terms) from 2019 to 2022. In San Francisco, the most strongly affected city in the United States, the share of office space that was vacant was ten percentage points higher in 2022 than it was in 2019, transaction volume was 79 percent lower, sale prices per square foot were 24 percent lower, and asking rents were 28 percent lower (also in real terms). The decline in demand has prompted tenants—wary about current macroeconomic conditions, uncertain about how much their workers will come to the office, and therefore uncertain about how much space they will need—to negotiate shorter leases from owners. Shorter leases, in turn, may make it more difficult for owners to obtain financing or may cause banks to adjust valuation models, which rely in part on the duration of existing leases.
In the scenarios we modeled, the amount of office space demanded in most cities does not return to prepandemic levels for decades. By 2030, demand is as much as 20 percent lower than it was in 2019, depending on the city.3 That estimate is what our model yields in a moderate scenario—one in which, by 2025, office attendance is higher than it is now but still lower than it was before the pandemic, and that partial recovery continues indefinitely.4 In a more severe scenario, in which attendance for all office workers in 2030 falls to the rate already seen in large firms in the knowledge economy, demand is as much as 38 percent lower than it was in 2019, again depending on the city.
Falling demand will drive down value. In the nine cities we studied, a total of $800 billion (in real terms) in value is at stake by 2030 in the moderate scenario. On average, the total value of office space declines by 26 percent from 2019 to 2030 in the moderate scenario and by 42 percent in the severe one. The impact on value could be even stronger if rising interest rates compound it. Similarly, the impact could be stronger if troubled financial institutions decide to more quickly reduce the price of property they finance or own.
Falling demand will also result in a surplus of office space, particularly in the lower-quality and older buildings that the real estate industry calls Class B and Class C. From 2020 to 2022, rents, demand, and sometimes prices generally grew more quickly (or fell less sharply) for Class A buildings than for Class B buildings in US superstar cities. For example, in New York City during that period, the average sale price per square foot rose 3 percent for Class A buildings but fell by 8 percent for Class B buildings.5 There are a number of reasons for this “flight to quality.” One is that many employers see high-quality space as a way to encourage office attendance among their employees. Another is that Class B and Class C office space is often not suited to hybrid work; for example, it may have less sophisticated audiovisual equipment. Also, now that hybrid work has reduced the total amount of space that employers need, they can spend their budgets on smaller amounts of higher-quality space rather than larger amounts of lower-quality space.
During the pandemic, partly because of out-migration, demand for residences grew less quickly in superstar urban cores than it did in suburbs and other cities. Residential vacancy rates increased from 2019 to 2022 in every superstar urban core that we studied, from a 0.8-percentage-point increase in Tokyo to a 9.9-percentage-point increase in London; meanwhile, in the suburbs, vacancy rates grew much less or even declined.6 Prices followed suit, rising eight percentage points more slowly in US superstar urban cores than in their suburbs and 13 percentage points more slowly than in non-superstar urban cores. In San Francisco, nominal prices in some neighborhoods fell by 12 percent from the end of 2019 to 2022. Residences in San Francisco’s urban core are now worth $750 billion less than they would have been if prices there had risen at the national average rate. The effect seems to be a global phenomenon.
Before price adjustments are accounted for, the demand for residences in superstar urban cores that we modeled is up to 10 percent lower by 2030 than it would have been if not for the pandemic. It is nevertheless higher than it was in 2019 in every city we studied except San Francisco and Paris. That estimate rests on the assumption that the wave of residents who left urban cores will not return but that population growth in each city will return to its prepandemic rate by 2024. Should population growth remain depressed for longer, the impact on demand would be even bigger.
However, prices will probably adjust, and so will rents. Again, our model does not account for such price adjustments, so we could not create demand scenarios that incorporated them. But we can say that homes in urban cores are unlikely to stay empty. Residential space differs from office space in that regard: once prices and rents fall, any available floor space is usually taken up quickly. Indeed, vacancy rates in urban cores have already increased less sharply than urban out-migration would suggest. Unfortunately, the downward pressure on prices and rents is unlikely to make residences in superstar cities—many of which suffer from expensive housing and homelessness—much more affordable.
Because of reduced foot traffic near urban stores during the pandemic, vacancy in retail space has increased and rents have declined, particularly in office-dense locations. As with office and residential space, vacancy rates increased from 2019 to 2022 in all the superstar urban cores we studied, ranging from a 1.8-percentage-point increase in San Francisco to a 6.2-percentage-point increase in London. From 2019 to 2022, asking retail rents declined an average of 5.4 percent (in real terms) in the cities we studied. The rents that were actually paid may have fallen even more.
Before price adjustments are accounted for, the demand for retail space in superstar urban cores that we modeled is lower in 2030 than it was in 2019, putting downward pressure on rents.7 In San Francisco’s urban core, for example, demand will be 17 percent lower. That estimate is what our model yields in a scenario in which there is a partial return to office (and therefore a partial recovery of retail spending near the office), people’s adoption of online shopping returns to its prepandemic rate of growth by 2025, and people who moved during the pandemic do not move back. In a more severe scenario, the decline in demand in San Francisco’s urban core would be as high as 42 percent. In most superstar urban cores, demand would be projected to decline even if the pandemic had not happened; the reasons are population trends and the increasing move to online shopping. As with residential real estate, however, prices are likely to adjust.
A review of various components of this research—regression analyses, survey responses, and literature reviews—suggests that cities where the pandemic has strongly affected real estate demand tend to have certain characteristics. (We were unable to determine which of those characteristics correlated most strongly with the impact on demand.)
Some of the characteristics are related to the business mix in a city. Specifically, cities with a larger share of workers in the knowledge economy, a higher number of large firms, a higher ratio of commuters to residents, and more cultural acceptance of remote work have tended to experience a greater impact on demand. Those factors lead to lower rates of office attendance, which reduce demand for office space directly, reduce demand for retail space by diminishing the number of office workers shopping at urban stores, and reduce demand for residential space by prompting people to move out of cities’ urban cores.
The larger the share of real estate in a neighborhood that was occupied by offices, the more out-migration from that neighborhood.
Other characteristics that correlate with the impact on demand are related to the urban structure of a city. Specifically, cities with office-dense real estate and little mixed-use development, as well as expensive housing and little green space, have tended to experience a greater impact on demand. Such characteristics make places less desirable for working, living, and shopping.
Two of those characteristics seem to correlate with the impact on demand at the neighborhood level as well. We examined neighborhoods defined by zip codes in Manhattan and San Francisco County (Exhibit E5). According to our analysis, the larger the share of real estate in a neighborhood that was occupied by offices, the more out-migration from that neighborhood. Similarly, home prices correlated with out-migration: pricier neighborhoods experienced more out-migration. (Data limitations prevented us from finding out whether the other characteristics also correlated with demand at the neighborhood level.)
Two very different Manhattan neighborhoods show that business mix and urban structure correlate with demand at the neighborhood level. The business mix of the first neighborhood, the Financial District, is heavily skewed toward the knowledge economy; 50 percent of all office space there is occupied by knowledge-economy tenants. The Financial District’s urban structure is office dense: 80 percent of real estate is dedicated to offices. And the average price of a home is roughly $1.5 million. Now consider the nearby Lower East Side, where just 22 percent of office space is dedicated to the knowledge economy, 7 percent of all space is dedicated to offices, and the average home price is about $1.0 million.
Those factors help us understand why the pandemic has driven such different outcomes in the two neighborhoods. The domestic out-migration rate from the start of 2020 to the start of 2022 was 2.2 times higher in the Financial District than in the Lower East Side, for example. It stands to reason that residents of the Financial District could easily work from home, as the prevalence of the knowledge economy there suggests, and were therefore likelier to move to bigger homes far from their offices; meanwhile, expensive housing may have given them another reason to leave.
San Francisco’s business mix helps explain the pandemic’s heavy impact there. The city has long cultivated a technology-focused economy with a large population of office workers, especially knowledge-economy workers. It has many inbound commuters, as the employment-to-population ratio shows: that ratio, a proxy for the prevalence of commuters, is 0.87 in San Francisco, starkly higher than the national average of 0.48. And the city’s employers, many of which are in the technology industry, may have been more likely to be aware of and adopt remote work technology when the pandemic began. San Francisco’s urban structure also helps explain why the pandemic affected demand so strongly there. Home prices in San Francisco County are five times higher than the national average and almost twice as high as prices in the suburbs. Furthermore, San Francisco has limited mixed-use development: offices represent 30 percent or more of all real estate in nine of San Francisco’s 26 neighborhoods.
The pandemic has affected demand less strongly in Paris than in San Francisco. Paris’s business mix helps show why: unlike San Francisco, which is heavily dependent on tech firms and the knowledge economy, Paris is home to companies that are global leaders in a wide variety of industries, such as beauty, hospitality, and consumer retail. But the city’s urban structure has features that push residents away as well as those that pull them in. On the one hand, home prices are twice as high in Paris’s urban core as in its suburbs and four times higher than the national average. On the other hand, Paris has a great deal of mixed-use development.
Finally, consider Tokyo, where real estate demand has been affected less than in most cities we studied. Most of Tokyo’s workers are in wholesale and retail trade, in contrast with technology-dependent San Francisco. Like Paris, Japan has a culture that values being present in the office, in particular among employees of small and medium-size businesses; in our survey, respondents in Tokyo said that they expected to be required to be in the office 3.7 days per week, a response noticeably higher than Paris’s 3.3. Loyalty to employers is also common in Japan, as are lower rates of technology adoption than in San Francisco. Furthermore, online spending as a share of retail spending was lower in Japan than in any other country we studied; that may have contributed to higher office attendance and continued in-person retail shopping. And in Tokyo, home prices in the urban core are 2.1 times higher than the national average—a starkly smaller number than Paris’s 4.1 and San Francisco’s 5.0.
Superstar cities are facing a new reality in which hybrid work worsens vacancy rates, threatens the vibrancy of neighborhoods, and thus makes urban cores less attractive to employers, employees, and residents. To adapt to that new reality, urban stakeholders could consider adopting more hybrid approaches themselves. At the neighborhood and building levels, and even in the design of the floors of buildings, choosing diversity, adaptability, and flexibility rather than homogeneity can help cities thrive.
One way cities could adapt is through mixed-use neighborhoods—that is, neighborhoods that are not dominated by a single type of real estate (especially offices) but instead incorporate a diverse mix of office, residential, and retail space. Such hybrid neighborhoods were becoming more popular even before the pandemic. And now that the pandemic has reduced demand for offices, cities have been left with vacant space that could be converted to other uses. Furthermore, our research shows that mixed-use neighborhoods have suffered less during the pandemic than office-dense neighborhoods have. That resilience gives investors, developers, and cities still more reason to engage in placemaking.
Redeveloping neighborhoods is an enormous undertaking, of course, so mobilizing the many stakeholders is important. Governments may be particularly helpful in reforming restrictive zoning policies. Investors would be needed to finance redevelopment. And developers would be the ones to turn mixed-use visions into realities.
Suburbs can benefit from hybridity as well. City dwellers, untethered from their daily commutes and thus less concerned about living far from urban cores, are increasingly seeking larger homes in greener areas. More housing and retail in the suburbs could help satisfy their preferences. More multifamily housing could be particularly beneficial because it would accommodate more people than single-family homes do. So long as the apartments are larger and more comfortable than apartments in urban cores, they could attract urbanites seeking space. Suburban policy makers could consider encouraging multifamily development by adjusting zoning, offering incentives to developers, and reexamining regulations that prevent housing from being built, such as those governing minimum dwelling sizes and window requirements.
Furthermore, multifamily housing is more energy-efficient than single-family homes, so it could help push down carbon emissions. And because it accommodates many people, it could help alleviate the shortage of housing that many metropolitan areas suffer from, making living in those areas more affordable.
To adapt to declining demand for traditional office and retail space, developers could create hybrid buildings. The most ambitious vision is a universal, “neutral-use” building whose design, infrastructure, and technology could be easily modified to serve different uses. Imagine a medical building that could be easily converted into, say, a hotel or an apartment building if customers’ preferences changed. More modestly, buildings could be designed to accommodate different degrees of collaborative and individual work or different arrangements of open and closed offices. They could also include technology that promotes flexibility, such as sensors to track patterns of usage that could inform an employer’s approach to hybrid work.
Hybrid buildings would bring at least two advantages. One is that they would protect owners from shifts in preferences that are impossible to predict now. The second relates to a current trend toward shorter leases in the office sector. Because tenants will now be moving in and out more frequently, buildings might become more valuable if they grow more adaptable.
Developers could also try to convert offices into the kinds of space for which there is more demand, such as apartments, hotels, and schools. Conversions are very hard, however. Obstacles include rezoning, renegotiating existing lease commitments to allow for renovations, and dealing with physical limitations. Furthermore, in the cities we studied, even if all excess office space were converted into housing, the amount of residential space in each city would grow by less than 3 percent.8 Still, for owners facing the prospect of lower occupancy and lower rents in their office buildings, the opportunity cost of conversion has fallen, and the number of successful conversions may grow.
Developers of retail space too could keep adaptability in mind. Of late, retail tenants have been evaluating their footprints with a stricter eye, shutting down stores or moving into smaller spaces. If developers built more adaptable spaces, they would be likelier to remain relevant to tenants’ shifting needs. Developers might also offer new store formats, such as spaces intended for delivery and fulfillment or for logistics rather than traditional retail. Or they might design buildings that are more integrated with their environments—for example, with dining spaces that extend onto sidewalks.
Tenants in urban cores—both the employers who rent office space and the merchants who rent retail space—may have to start “earning the commute” from office workers and shoppers who would otherwise visit less often. Here too, thinking flexibly and adaptably can help. For example, the office does not have to be just a place to work; it can also be a place where employees genuinely enjoy spending time or where they can take part in compelling events and activities. Office tenants might try to attract them by building magnetic, hospitality-oriented workplaces. Office tenants might also design more modular spaces that can adapt to changes in work patterns from week to week. And the most forward-thinking tenants will provide an efficient, digital way to organize hybrid work patterns and preferences.
Turning empty spaces into hybrid places could be a way to transform superstar cities and prepare them for a dynamic, prosperous future.
Retailers too may have to “earn the commute” by designing spaces that cater to many different uses. A prime example is stores that easily accommodate omnichannel retail—a single, seamless experience for customers, whether they shop online or in person. Similarly, stores can provide experiential retail. For example, one department store brand is launching smaller stores where customers can pick up products bought online, get clothes altered, find style advice, and patronize a beauty salon.
Indeed, it is not hard to imagine more “hybrid floors” in which offices, residences, and stores exist side by side. For floors—as for buildings and neighborhoods—turning empty spaces into hybrid places may not simply be a way to counter the damage wrought by the pandemic. It could be a way to transform superstar cities and prepare them for a dynamic, prosperous future.
Jan Mischke is a McKinsey Global Institute partner in Zurich; Ryan Luby is a senior knowledge expert and associate partner in New York; Brian Vickery is a partner in Boston; Jonathan Woetzel is an MGI director and senior partner in Shanghai; Olivia White is an MGI director and senior partner in San Francisco; Aditya Sanghvi is a senior partner in New York; Jinnie Rhee is a consultant in San Francisco; Anna Fu is a consultant in New York; Rob Palter is a senior partner in Toronto; André Dua is a senior partner in Miami; and Sven Smit is a senior partner in Amsterdam and MGI chairman.
This report was edited by Benjamin Plotinsky, an MGI senior editor in Washington, DC.

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