Winners and losers
Jobs and Communities at Risk in the Age of Digital Dominance
(3rd article in a series – by Duncan Robins)
In the future of work, there will be winners and losers. During the next decade, industries, local economies and the nature of work will be transformed on a massive scale and at an accelerating pace. In the U.S., 40% of our workforce is employed in occupations that could see significant job losses(1). Although many new jobs will be created, the net impact on jobs will be felt unevenly by industries, communities and workers. The parts of rural and middle America that prospered during the Industrial Era may be at a greater risk in the Age of Digital Dominance. Many jobs requiring lower skills will be disproportionally disrupted. The new jobs created will favor those communities connected and committed to the future of work having made investments in digital and social infrastructure, business development, work-related skills-based training, and tax incentives.
SIX GLOBAL FORCES DRIVING THE TRANSFORMATION
As outlined in our second article in this series (The Future of Work – Transformation is Inevitable), three persistent forces are pushing this transformation (1. Globalization; 2. Knowledge Growth; and 3. Technology Adoption), three unstoppable forces are pulling the transition forward (1. Consumer Demand; 2. A Demographic Shift; and 3. A Cultural Revolution), and three enablers are greasing the wheels of change (1. Digital Communication; 2. Marketplaces and Co-working Spaces; and 3. Social Supports). These forces will drive rapid changes on a global scale, but the impacts will and are being felt unevenly by local communities and in every workplace throughout the U.S.
Technology will continue to impact jobs and the nature of work. During the last two decades, workplaces have realized efficiency gains from many new technologies including: a) the introduction of software like sales and office automation tools and relational databases; b) hardware improvements in computing, digital storage and communication devices, and c) infrastructure investments in communication networks and broadband. Capital expenditures and technological advancements in these areas will continue, but additional efficiency technology will be added. Automation hardware and software (i.e. robots and machine learning or AI) are becoming more capable, affordable, and accessible. With recent improvements in computing power and algorithms, physical robots and digital bots are ready to take their places in the U.S. workplace. (We will use the term ‘bots’ to refer to both types).
AUTOMATION RISK – POTENTIAL WINNERS AND LOSERS IN THE JOB MARKET
The implementation of bots will not be uniform across all occupations, companies or industries. Some jobs are more likely be automated than others. Work that requires lower skills, that is primarily repetitive and predictable, is most susceptible to automation. While those jobs that are primarily unpredictable, involve interpersonal interactions, and/or require high skills, expertise or creativity are least likely to be automated.
In 2018, the McKinsey Global Institute conducted a study of occupations(1) in order to determine which sectors of the U.S. economy are most at risk of being automated. The study concluded that all occupations and all sectors of the economy will be impacted by some amount of automation. The report suggests that as much as 20%(2) of time spent in U.S. workplaces involve ‘predictable, physical activity’, those activities most at risk of robotic automation. However, the relative amount of work at risk to automation varies by occupation and sector. The study concludes that the percent of work susceptible to automation across U.S. occupations ranges from five to one-hundred percent. The sectors of the U.S. economy that involve the highest percentage of work that is now automatable is in the Accommodation and Food Services sector (75%), Manufacturing (60%), and Agriculture (58%). The sectors that are least exposed to automation include Education (27%), Management (35%) and Professional Services (35%).
Automation in the U.S. workplace will come in two forms: 1) physical robots; and, 2) digital bots. Technology advancements that improve worker efficiency, including automation, will impact every U.S. job over the next decade, but it will be the robots that will be highlighted and reviled. While most news outlets will cover the ‘invasion’ of the physical over the implementations of the digital form of bots, both will play significant roles in reshaping the occupational landscape. The physical robots will have a greater impact on blue-collar jobs in the manufacturing, warehousing, agriculture and transportation sectors. While the more stealth, digital bots will quietly reduce the need for white-collar workers in clerical, customer service, and analytical roles.
The relative risk of exposure to automation is illustrated in Figure 1. Work Exposed to Automation Risk. This graph represents the relative risk for generalized occupations to automation based on: 1) the primary nature of the work conducted in the occupation (on the y-axis); and, 2) the assets core to creating value from the associated work (on the x-axis). The most at risk of being infiltrated by physical robots are in the lower left quadrant, those occupations that involve a large amount of physical assets mixed with repetitive, predictable work. Digital bots will impact a band that includes repetitive, low skilled, clerical jobs and those occupations that require knowledge or information that can be digitally collected, stored and analyzed by a computer. It is estimated that 51% of work activities in the U.S. fall into the 40% of occupations that could be plotted in one of the shaded areas, namely those that are at risk of being replaced by physical or digital bots.
The occupations that are the least at risk are represented in the upper right quadrant, which includes legal, education, management and personalized health and wellness professions. All of these occupations require specialized skills, expertise and interpersonal connections. The study projects that the total number of jobs in the U.S. will grow over time, which would require growth in upper quadrant occupations along with the addition of new jobs with similar characteristics. This outcome however, will require many workers to relocate and significant investments in retraining and education programs for displaced workers.
The likely result of this transformation is a labor market that grows increasingly polarized between those with, and those without the required skills, training or degree for the higher-level work. Unfortunately, those with a high school education (or less) are four times more likely to be impacted by automation(1). The middle class will also likely shrink if bots take-over the work in the 26 million jobs that are currently at risk of being automated. These jobs generate almost three trillion dollars in annual wages(2). Fifteen million of these jobs are occupied by Millennials. These workers will need to be retrained in order to restart their careers. However, over eleven million workers over the age of 50 are also exposed. These workers may find it difficult to retool by the time they are replaced.
LOCATION RISK – POTENTIAL WINNING AND LOSING COMMUNITIES
The magnitude of the impending transition in the labor market is not unprecedented in the U.S., but the pace of change will be. For comparison, it took 100 years (from 1900 to 2000) for the share of the U.S. workforce in agriculture to fall from forty percent to two percent. Similarly, the U.S. manufacturing workforce fell from a high of thirty percent in 1950 to single digits by 2010(2). New jobs were created as the U.S. economy grew, but the resulting disruption to local communities caused by these transitions can still be seen and felt today.
As the U.S. economy transitions from the Industrial Era and into the Age of Digital Dominance, each community will experience the transformation very differently—there will be obvious winners and losers. A pattern is emerging, but the future is not inevitable. In an excellent study by McKinsey Global Institute published this year(1), researchers considered the fate of U.S. counties and cities during the impending transformation. Their modeling suggested a significant correlation between the average education level attained by a workforce within a region and that region’s future (annual) growth potential.
Illustrated in Figure 2. Economic Potential of Communities in the Age of Digital Dominance is a summary of the McKinsey findings. When cities and regions were plotted on a graph on which the Y-axis represents their likely annual growth rates over the next decade, and the X-axis represents the average educational attainments of the city or region, a definite pattern emerged. Although there were outliers and overlaps, three primary regions took shape. In the lower-left quadrant were the struggling communities, those with the lowest average education levels attained (as low as 16% earning a BA or higher in parts of rural America and 20% to 25% in parts of middle America) and those likely to have flat or negative job growth rates. In the upper right quadrant were the vibrant college communities and megacities that had high levels of average workforce education (as high as 43% and 40% earning BAs or higher, respectively) and strong job growth expected. In the middle of the plot were the currently ‘stable’ communities and cities that could be considered on the bubble. For discussion purposes, a few cities have been placed on the illustration in each of these three clusters. (Note: The locations plotted represent the general findings, not the specific data).
WITHOUT INTERVENTION, ECONOMIC POLARIZATION WILL INCREASE
Regions and communities that have a large concentration of businesses operating in sectors most likely to be automated (e.g. manufacturing and agriculture) are also the same regions and communities most likely have the highest relative concentrations of low skilled, older and lower-educated workers. As a result, without collective intervention, these communities will likely be impacted the most by the impending transformation. The possibility of negative outcomes increase the more a community or region is: a) physically isolated; b) lacking economic diversity; c) of a size too small to self-regenerate: d) lacking a social draw for talent; or e) on the other side of the Educational and/or Digital Divides. Unfortunately, there a large number of communities in rural and middle America that are struggling.
At the other end of the spectrum, higher educated and younger Millennials are flocking to those vibrant cities and regions that offer them ways to participate in the Gig Economy, and for other economic and social opportunities. As more talent moves into these areas, more opportunities are created, and the winning cycle repeats and strengthens. Many of these regions can be found on the coasts and in the larger, education-centric cities and metropolitan centers scattered across the U.S.
With focused investments in education, worker training, business development and infrastructure, the regions on the bubble or struggling may avoid slipping as the U.S. economy becomes more polarized. There are a lot of secondary markets in middle America that are in this category that are working hard to adapt. Unfortunately, vast amounts of venture capital that could have a huge impact in these regions is being invested primarily on the coasts, in the cities that are already prospering. From 2009 to 2018, annual investments in venture-based deals have grown almost five-fold, from $27 billion to almost $130 billion(3). However, only 4% of that huge amount of capital was invested in the region encompassing the Mid-West and the Great Lakes, while 87% was put to work funding deals in the North East and West Coast(4).
CALL TO ACTION
The transformation from the Industrial Era to the Age of Digital Dominance is assured. This transformation is underway. The six forces driving the changes are massive, unstoppable and aligned.
Unfortunately, some industries, communities and workers will be impacted more than others. Those of us concerned about the future of work and life in rural and middle America must come together to chart a path forward. My community is one of those at risk of falling further behind. We, in the community, are engaged and motivated. But, we like many other communities facing similar challenges, can’t do it alone. We need a movement that results in new education paradigms, business development, investment in infrastructure, innovative tax incentives and new privacy, antitrust and intellectual property laws. We can do this if we work together.
Many organizations and thought leaders are attempting to predict the future of work during this time of unprecedented change. This article is part of a series written to add to that dialog with hopes of energizing action on solutions that will drive economic development and prosperity for workers, businesses and communities in rural and middle America.
The author, Duncan Robins, is the Chairman and a founder of TheFutureofWork.org. Duncan and his wife moved to a rural community to raise their family. For over two decades, Duncan has flown over the digital divide weekly to work as a CEO for Private Equity-backed businesses in larger cities. Currently, he is the CEO of Assemble Technologies, a Michigan-based, organization of the future. Duncan has worked to reduce the educational divide with leadership positions in Higher Education and two career-oriented training companies. He has also worked for Bain, McKinsey and Morgan Stanley. Duncan earned an MBA from Stanford and graduated summa cum laude from Harvard.
Other articles in this series:
(1) Lund, Susan, James Manyika, Liz Hilton Segel, André Dua, Bryan Hancock, Scott Rutherford, and Brent Macon, The future of work in America: People and places, today and tomorrow, McKinsey Global Institute, July 2019
(2) Manyika, James, Michael Chui, Mehdi Miremadi, Jacques Bughin, Katy George, Paul Willmott, Martin Dewhurst, A Future that Works: Automation, Employment and Productivity , McKinsey Global Institute, January 2017
(3) US VC Activity, January 2019, Pitchbook.com
(4) Szmigiera, M., Value of Venture Capital Investment the United States, July 2019. Statistica.com