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The ongoing Covid-19 pandemic has had a strong impact on the job market and on its evolution. The idea that once the pandemic will be over everything will go back to the previous normal is no longer viable. True, employment levels will start to grow but that will take time, measurable in years and during this time companies will have adapted to operate with low levels of workforce and, most important, with a different mix of workforce.
In this respect the analyses published by McKinsey on February 3rd, 2021, resulting from interviews with several key companies in the US and the analyses of the economic recovery, showing that by November 2020 75% of the GDP loss have been recovered (in the US) but only 60% of workers laid off have been re-instated (that is out of 25 million jobs lost, 10 millions are still unemployed), points out several differences in the “demographic” of recovery. It should also be noted that of the jobs recovered, many have shifted to the gig economy.
As shown in the first graphic, the recovery will not happen before the end of 2022, with the sole exception of jobs paying more than 75k per year (top jobs). Hence the completion of the vaccination, expected in 2021, will not be enough to lead to a full recovery. The reasons, to me, have to be found in the restructuring of companies that are transitioning to a digital space. The Digital adoption, first used as an emergency crutch by most business (even the solid brick and mortar business have been forced to look for a -temporary- alternative, like restaurants that had to convert to take away during the lock down), has introduced a number of permanent changes in processes (both operation and business processes) that have paved the way to a Digital Transformation of the business. Although in many businesses this DX has been limited in depth, it has changed at least partially the enterprise processes, affecting the workforce, in volume and quantity.
The social distancing has accelerated the shift to automation (decreasing human presence) and of course it has been easier to automate menial activities. This is reflected in the graphic by the expectation that a full recovery for workforce with an income lower than 25k per year and for the ones less educated (without an high school attendance), that in many cases overlap, is not expected to see a full recovery in the time frame considered (up to 2025), indicating that a permanent change has taken place.
Even more concerning is the estimate that 4.6 million jobs (see graphic on the side) will be permantly lost. It is important to notice that the amount of permanent losses has kept increasing during the pandemic, indicating a restructuring of the business sector (including automation of activities).
The growing impact of AI is also evident by the longer recovery time for the less educated workforce, as clearly shown in the first graphic. Interesting the fact that ethnicity does not seem to play a role (with the exception of Asian ethnicity that is expected to have a faster recovery, possibly resulting from higher education level on one side and of the clustering of this ethnicity -family work).
Also important to notice the different impact based on gender. Although men and women are almost equal in jobs (women 48%, men 52%) the number of women who lost (or decided to resign) represent 56% of the overall loss. In part this may be due to the choice of staying at home to take care of kids during the lock down but this does not explain the overall disparity,
It is also important to notice that these figures represent the US situation. Different Countries may have experienced a different impact. As an example, the latest figure of unemployment in Italy (December 2020) shows an increase in unemployment by 101,000 units (this is the “increase”, not the total!) and that increase is partitioned between 99,000 women and 2,000 men!
