WEF Future of Jobs 2020 PDF
WEF Future of Jobs 2020 PDF
WEF Future of Jobs 2020 PDF
of Jobs
Report
2020
OCTOBER 2020
Cover: Unsplash/Joel Guerrero
Inside: Unsplash/Christina wocintechchat; Unsplash/Faruq Al Aqib; Unsplash/Rob Lambert
Contents
3 Preface
5 Executive Summary
8 1.1 Introduction
49 Conclusion
50 Notes
53 References
66 Country Profiles
157 Contributors
158 Acknowledgements
Preface
After years of growing income inequality, future of work. Now in its third edition, the report
concerns about technology-driven displacement maps the jobs and skills of the future, tracking
of jobs, and rising societal discord globally, the the pace of change and direction of travel.
combined health and economic shocks of 2020 This year we find that while technology-driven
have put economies into freefall, disrupted labour job creation is still expected to outpace job
markets and fully revealed the inadequacies destruction over the next five years, the economic
of our social contracts. Millions of individuals contraction is reducing the rate of growth in the
globally have lost their livelihoods and millions jobs of tomorrow. There is a renewed urgency to
more are at risk from the global recession, take proactive measures to ease the transition of
structural change to the economy and further workers into more sustainable job opportunities.
automation. Additionally, the pandemic and There is room for measured optimism in the
the subsequent recession have impacted most data, but supporting workers will require global,
those communities which were already at a regional and national public-private collaboration
disadvantage. at an unprecedented scale and speed.
We find ourselves at a defining moment: the The Platform for the New Economy and
decisions and choices we make today will Society at the World Economic Forum works
determine the course of entire generations’ as a “docking station” for such collaboration on
lives and livelihoods. We have the tools at our economic growth, revival and transformation;
disposal. The bounty of technological innovation work, wages and job creation; education,
which defines our current era can be leveraged skills and learning; and diversity, equity and
to unleash human potential. We have the means inclusion. By leveraging this publication and
to reskill and upskill individuals in unprecedented other insights, the Platform supports a range
numbers, to deploy precision safety nets which of consortia and action coalitions, including
protect displaced workers from destitution, and the Reskilling Revolution Initiative to provide
to create bespoke maps which orient displaced better jobs, skills and education to one billion
workers towards the jobs of tomorrow where they people by 2030. We are deeply grateful to the
will be able to thrive. New Economy and Society Stewardship Board
members for their leadership of this agenda, to
However, the efforts to support those affected the over 100 partners of the Platform, and the
by the current crisis lag behind the speed of expert guidance of Global Future Councils, the
disruption. It is now urgent to enact a Global communities of Chief Economists, Chief Human
Reset towards a socio-economic system that is Resource Officers, Chief Learning Officers and
more fair, sustainable and equitable, one where Chief Diversity Officers, and to a range of national
social mobility is reinvigorated, social cohesion ministries of economy, education and labour.
restored, and economic prosperity is compatible
with a healthy planet. If this opportunity is We are also grateful to the many partners whose
missed, we will face lost generations of adults views created the unique collection of insights
and youth who will be raised into growing in this report. It presents the workforce planning
inequality, discord and lost potential. and quantitative projections of Chief Human
Resource and Strategy officers through to 2025,
The Future of Jobs Report provides the timely while also drawing upon the qualitative expertise
insights needed to orient labour markets and of a wide range of World Economic Forum
workers towards opportunity today and in the executive and expert communities. In addition,
Executive Summary
The COVID-19 pandemic-induced lockdowns and destruction accelerates. Employers expect
related global recession of 2020 have created a that by 2025, increasingly redundant roles will
highly uncertain outlook for the labour market and decline from being 15.4% of the workforce
accelerated the arrival of the future of work. The to 9% (6.4% decline), and that emerging
Future of Jobs Report 2020 aims to shed light on: 1) professions will grow from 7.8% to 13.5%
the pandemic-related disruptions thus far in 2020, (5.7% growth) of the total employee base
contextualized within a longer history of economic of company respondents. Based on these
cycles, and 2) the expected outlook for technology figures, we estimate that by 2025, 85 million
adoption jobs and skills in the next five years. jobs may be displaced by a shift in the division
Despite the currently high degree of uncertainty, the of labour between humans and machines,
report uses a unique combination of qualitative and while 97 million new roles may emerge that
quantitative intelligence to expand the knowledge are more adapted to the new division of labour
base about the future of jobs and skills. It aggregates between humans, machines and algorithms.
the views of business leaders—chief executives,
chief strategy officers and chief human resources – Skills gaps continue to be high as in-
officers–on the frontlines of decision-making demand skills across jobs change in
regarding human capital with the latest data from the next five years. The top skills and skill
public and private sources to create a clearer picture groups which employers see as rising in
of both the current situation and the future outlook prominence in the lead up to 2025 include
for jobs and skills. The report also provides in-depth groups such as critical thinking and analysis
information for 15 industry sectors and 26 advanced as well as problem-solving, and skills in
and emerging countries. self-management such as active learning,
resilience, stress tolerance and flexibility. On
The report’s key findings include: average, companies estimate that around 40%
of workers will require reskilling of six months
– The pace of technology adoption is expected or less and 94% of business leaders report that
to remain unabated and may accelerate in they expect employees to pick up new skills on
some areas. The adoption of cloud computing, the job, a sharp uptake from 65% in 2018.
big data and e-commerce remain high priorities
for business leaders, following a trend established – The future of work has already arrived for
in previous years. However, there has also been a large majority of the online white-collar
a significant rise in interest for encryption, non- workforce. Eighty-four percent of employers
humanoid robots and artificial intelligence. are set to rapidly digitalize working processes,
including a significant expansion of remote
– Automation, in tandem with the COVID-19 work—with the potential to move 44% of their
recession, is creating a ‘double-disruption’ workforce to operate remotely. To address
scenario for workers. In addition to the concerns about productivity and well-being,
current disruption from the pandemic-induced about one-third of all employers expect to also
lockdowns and economic contraction, take steps to create a sense of community,
technological adoption by companies will connection and belonging among employees
transform tasks, jobs and skills by 2025. Forty- through digital tools, and to tackle the well-being
three percent of businesses surveyed indicate challenges posed by the shift to remote work.
that they are set to reduce their workforce due
to technology integration, 41% plan to expand – In the absence of proactive efforts,
their use of contractors for task-specialized inequality is likely to be exacerbated by
work, and 34% plan to expand their workforce the dual impact of technology and the
due to technology integration. By 2025, the pandemic recession. Jobs held by lower
time spent on current tasks at work by humans wage workers, women and younger workers
and machines will be equal. A significant share were more deeply impacted in the first phase
of companies also expect to make changes of the economic contraction. Comparing the
to locations, their value chains, and the size impact of the Global Financial Crisis of 2008
of their workforce due to factors beyond on individuals with lower education levels to
technology in the next five years. the impact of the COVID-19 crisis, the impact
today is far more significant and more likely to
– Although the number of jobs destroyed will deepen existing inequalities.
be surpassed by the number of ‘jobs of
tomorrow’ created, in contrast to previous – Online learning and training is on the rise
years, job creation is slowing while job but looks different for those in employment
Part 1
Tracking
the Future
of Jobs
1
The Labour
Market Outlook in the
Pandemic Economy
1.1 Introduction
Developing and enhancing human skills and in 2016 and 2018, this 2020 third edition of the
capabilities through education, learning and Future of Jobs Report provides a global overview
meaningful work are key drivers of economic of the ongoing technological augmentation of work,
success, of individual well-being and societal emerging and disrupted jobs and skills, projected
cohesion. The global shift to a future of work expansion of mass reskilling and upskilling across
is defined by an ever-expanding cohort of new industries as well as new strategies for effective
technologies, by new sectors and markets, workforce transitions at scale.
by global economic systems that are more
interconnected than in any other point in history, Over the past decade, a set of ground-breaking,
and by information that travels fast and spreads emerging technologies have signalled the start of
wide. Yet the past decade of technological the Fourth Industrial Revolution. To capture the
advancement has also brought about the looming opportunities created by these technologies, many
possibility of mass job displacement, untenable companies across the private sector have embarked
skills shortages and a competing claim to the on a reorientation of their strategic direction. By
unique nature of human intelligence now challenged 2025, the capabilities of machines and algorithms
by artificial intelligence. The coming decade will will be more broadly employed than in previous
require purposeful leadership to arrive at a future years, and the work hours performed by machines
of work that fulfils human potential and creates will match the time spent working by human
broadly shared prosperity. beings. The augmentation of work will disrupt the
employment prospects of workers across a broad
In 2020, economic globalization is stalling, social range of industries and geographies. New data from
cohesion is being eroded by significant unrest and the Future of Jobs Survey suggests that on average
political polarization, and an unfolding recession is 15% of a company’s workforce is at risk of disruption
threatening the livelihoods of those at the lower end in the horizon up to 2025, and on average 6% of
of the income spectrum. As a new global recession workers are expected to be fully displaced.
brought on by the COVID-19 health pandemic
impacts economies and labour markets, millions This report projects that in the mid-term, job
of workers have experienced changes which have destruction will most likely be offset by job growth
profoundly transformed their lives within and beyond in the 'jobs of tomorrow'—the surging demand
work, their well-being and their productivity. One for workers who can fill green economy jobs, roles
of the defining features of these changes is their at the forefront of the data and AI economy, as
asymmetric nature—impacting already disadvantaged well as new roles in engineering, cloud computing
populations with greater ferocity and velocity. and product development. This set of emerging
professions also reflects the continuing importance
Over the course of half a decade the World of human interaction in the new economy, with
Economic Forum has tracked the labour market increasing demand for care economy jobs; roles in
impact of the Fourth Industrial Revolution, identifying marketing, sales and content production; as well as
the potential scale of worker displacement alongside roles at the forefront of people and culture.1 Employers
strategies for empowering job transitions from answering the Future of Jobs Survey are motivated
declining to emerging roles. The fundamental rate to support workers who are displaced from their
of progress towards greater technological incursion current roles, and plan to transition as many as 46%
into the world of work has only accelerated over the of those workers from their current jobs into emerging
two years since the 2018 edition of the report. Under opportunities. In addition, companies are looking to
the influence of the current economic recession provide reskilling and upskilling opportunities to the
the underlying trends toward the technological majority of their staff (73%) cognizant of the fact that,
augmentation of work have accelerated. Building by 2025, 44% of the skills that employees will need to
upon the Future of Jobs methodology developed perform their roles effectively will change.
A significant volume of research has been published In reaction to the risk to life caused by the spread
on the future of work since the World Economic of the COVID-19 virus, governments have legislated
Forum published it first edition. To date, the full or partial closures of business operations,
conclusions drawn from that body of literature causing a sharp shock to economies, societies
appear to offer both hope and caution. The twin and labour markets. Many businesses have closed
forces of technology and globalisation have brought their physical office locations and have faced
profound transformations to labour markets and limitations in doing business face-to-face. Figure 2
in the near term.2 Few analysts propose that shows the trajectory of those closures. Beginning
technological disruption will lead to shrinking in mid-March and by mid-April, nearly 55% of
opportunities in the aggregate,3 and many of the economies (about 100 countries) had enacted
insights gathered point to the emergence of new workplace closures which affected all but essential
job opportunities. Across countries and supply businesses.6 During May and June, economies
chains, research has evidenced rising demand resumed some in-person business operations—yet
for employment in nonroutine analytics jobs limitations to the physical operation of business
accompanied by significant automation of routine continue, geographic mobility between countries
manual jobs.4 Empirically, these changes can be persist and the consumption patterns of individuals
observed in data tracking employment trends in the have been dramatically altered. By late June 2020,
United States between 2007–2018. The evidence about 5% of countries globally still mandated a full
indicates that nearly 2.6 million jobs were displaced closure of in-person business operations, and only
over a span of a decade.5 Figure 1 presents the about 23% of countries were fully back to open.7
types of roles that are being displaced—namely In addition, irrespective of legislated measures,
Computer Operators, Administrative Assistants, individuals have shifted to working remotely and
Filing Clerks, Data Entry Keyers, Payroll Clerks and enacting physical distancing.8
other such roles which depend on technologies and
work processes which are fast becoming obsolete.
Computer Operators
Executive Secretaries and Executive Administrative Assistants
Word Processors and Typists
Switchboard Operators, Including Answering Service
Machine Feeders and Offbearers
Telemarketers
File Clerks
Postal Service Mail Sorters, Processors, and Processing Machine Operators
Brickmasons and Blockmasons
Data Entry Keyers
Bill and Account Collectors
Mail Clerks and Mail Machine Operators, Except Postal Service
Order Clerks
Legal Secretaries
Information and Record Clerks, All Other
Sewing Machine Operators
Helpers–Installation, Maintenance, and Repair Workers
Payroll and Timekeeping Clerks
Cutting, Punching, and Press Machine Setters, Operators, and Tenders, Metal and Plastic
Drywall and Ceiling Tile Installers
Source
Ding, et al, 2020.
Collectively, the life-preserving measures to stop the four global recessions which have throughout
spread of the COVID-19 virus have led to a sharp history impacted employment levels in significant
contraction of economic activity, a marked decline ways. The figure shows that during periods of
in capital expenditure among several industries relative labour market stability unemployment
facing decline in demand for their products and stands at near or around 5% while during periods
services, and put new pressures on enterprises of major disruption unemployment peaks at or
and sectors. Not all companies have been equally exceeds 10%. During the financial crisis of 2010,
affected. Some businesses have the resources to unemployment peaked at 8.5% only to drop
weather the uncertainty, but others do not. Among to an average of 5% across OECD economies
those faltering are companies that typically don’t in late 2019.9 According to the International
hold large cash reserves such as SMEs (small- Labour Organization (ILO), during the first half
to-medium enterprises) or businesses in sectors of 2020 real unemployment figures jumped to
such as Restaurants and Hospitality. Some types an average of 6.6% in quarter 2 of 2020. The
of business operations can be resumed remotely, OECD predicts that those figures could peak at
but others, such as those in the Tourism or Retail 12.6% by the end of 2020 and still could stand
sectors that depend on in-person contact or travel, at 8.9% by end 2021.10 This scenarios assumes
have sustained greater damage (Figure 9 on page 17 that the economies analysed experience two
demonstrates some of those effects). waves of infection from the COVID-19 virus
accompanied by an associated slow-down of
The current health pandemic has led to an economic activity. It remains unclear whether
immediate and sudden spike in unemployment current unemployment figures have peaked or
across several key economies—displacing whether job losses will deepen over time. New
workers from their current roles. Since the end analysis conducted by the IMF has estimated
of the Global Financial Crisis in 2007–2008, that 97.3 million individuals, or roughly 15% of
economies across the globe had witnessed the workforce in the 35 countries included in
a steady decrease of unemployment. Figure the analysis, are classified as being at high risk
3 presents the historical time series of of being furloughed or made redundant in the
unemployment across a selection of countries current context.11
and regions. Annotated across the figure are the
27 Jan 2020
01 Feb 2020
01 Mar 2020
01 Apr 2020
01 May 2020
01 Jun 2020
01 Jul 2020
01 Aug 2020
01 Sep 2020
Source
Hale, et al, 2020. 28 Sep 2020
0 20 40 60 80 100
35
30
25
Uneymployment rate (%)
20
10
0
1960 1970 1980 1990 2000 2010 2020
South Africa USA OECD countries Mexico Korea, Rep. Japan Italy
United Kingdom France EA17 Germany Canada Australia
Source Notes
OECD Economic Outlook: Statistics and Projections, and Kose, Forecasts for Q3 2020 produced by the OECD assuming two waves of
M. Ayhan, et al. 2020. COVID-19, namely a "double hit" scenario. EA17 = Belgium, Germany,
Estonia, Ireland, Greece, Spain, France, Italy, Cyprus, Luxembourg, Malta,
Netherlands, Austria, Portugal, Slovenia, Slovakia, and Finland.
Comparing figures for quarter 2 of 2020 to the unemployment rate rose from 3.5% in February 2020
same quarter in 2019, unemployment in Australia to peak at 14.7% in April 2020. The unemployment
increased by 1.5 percentage points; in Brazil that rate for the United States has now dropped to stand
same figure was 1.6; in Canada, 6; in Chile, 5.5; closer to 10%. In contrast, during the Global Financial
Columbia, 9; and United States, 8.5. The relevant Crisis in 2009 the unemployment rate in the United
statistics for countries such as the United Kingdom, States rose from 4.7% in December 2007 to nearly
Germany, Japan, France and Italy show greater 10% by June 2009.14 In two months the COVID-19
resilience. The Country Profiles in Part 2 of this report pandemic has destroyed more jobs than the Great
present key labour market indicators showcasing the Recession did in two years. As the United States has
latest annual, monthly and quarterly figures for the lifted restrictions on the physical movement of people,
economies covered in this report, including the figures some workers have been recalled into employment
listed above. It is evident that the United States and while others have seen temporary redundancies
Canada experienced a significant disruption on an become permanent job displacement (some of this
unprecedented scale. Employment figures for the data can be observed in Figure 11 on page 19).
United States illustrated in Figure 4 show that the
15
12
Uneymployment rate (%)
0
1967 1970 1980 1990 2000 2010 2020
Date
Source Notes
United States Bureau of Labor Statistics. Unemployment Rate - Job Losers (U-2) [U2RATE], retrieved from FRED,
Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/U2RATE,
15 September 2020.
It appears increasingly likely that changes to reluctance to invest in new personnel. This means
business practice brought about by this pandemic that workers displaced from the labour market have
are likely to further entrench wholly new ways of fewer opportunities to return to work as businesses
working, and that the second half of 2020 will not reduce their workforce. This trend can be observed
see a return ‘back to normal’ but will instead see a through data from the professionals on the LinkedIn
return to ‘the new normal’. platform, which allows the LinkedIn Economic Graph
team to track changes in hiring rates for seven key
Early evidence from the World Economic Forum’s economies—Australia, China, France, Italy, Singapore,
Future of Jobs Survey presented in Figure 5 the United Kingdom and the United States. Those
suggests that, in addition to the labour market hiring rates are featured in Figure 6. They show that in
displacement caused by this health shock, China, for instance, hiring contracted to a low of -47%
employers are set to accelerate their job automation year-on-year rate at the end of February. In France
and augmentation agenda, raising the possibility and Italy, the contraction was more pronounced,
of a jobless recovery. Among the business reaching -70% and -64.5%, respectively, in mid-April.
leaders surveyed, just over 80% report that they Those low figures were approached by the United
are accelerating the automation of their work Kingdom and Australia, where contractions reached
processes and expanding their use of remote work. a relatively more robust -40%. Since then, hiring rates
A significant 50% also indicate that they are set to have gradually rebounded, with most of the seven key
accelerate the automation of jobs in their companies. economies tracked by these metrics trending towards
In addition, more than one-quarter of employers a 0% year-on-year change. By 1 July, China, France
expect to temporarily reduce their workforce, and the United States had seen the most recovery in
and one in five expect to permanently do so. The comparative hiring rates, at -6% or -7%. By the end of
International Labour Organization (ILO) projects that September the countries with the strongest recovery
by the second quarter of 2020, the equivalent of 195 in hiring were China (22%), Brazil (13%), Singapore
million workers will have been displaced and as jobs (8%) and France (5%). In those economies it appears
are transformed at a greater speed.15 that hiring is now compensating for the months in
which new personnel were not engaged, indicating
While many workers moved into unemployment some stabilization of the labour market.
during the period of mid-March to the end of July
hiring rates also remained low, reflecting business
Source
Future of Jobs Survey 2020, World Economic Forum.
FIGURE 6 Hiring rate trends in selected countries, February–October 2020, year-on-year changes
80
40
Hiring rate, year-on-year (%)
-40
-80
Australia Brazil China France Italy Singapore United Kingdom United States
Source
LinkedIn Economic Graph.
25 September
April May June July August
Industry Country/Economy (14-day rolling
(month) (month) (month) (month) (month)
average)
Source Note
LinkedIn Economic Graph. Values in brown indicate where the hiring rate The darker the colour, the lower/higher the rate.
is lower than in 2019, while values in green
indicate where the rate is higher than 2019.
100
Bangladesh
Mexico
80 Brazil
Germany
Workers unable to work from home (%)
40
20
0
0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000
Source
Dingel & Neuman, World Bank Home Based Work (HBW) index,
World Bank's World Development Indicators database.
Source
Brussevich, et al, 2020.
A. Changes to job-seeking behaviour, February-June 2020 B. Changes to job-posting behaviour, February-June 2020
300 300
Index of job searches, % (relative to 11 Feb)
250 250
200 200
150 150
100 100
50 50
0 0
11 Feb 10 Mar 07 Apr 05 May 02 Jun 30 Jun 11 Feb 08 Mar 05 Apr 03 May 07 Jun 28 Jun
Source
LinkedIn Economic Graph.
FIGURE 11 Outcomes for workers who lost their jobs in the United States, February–May 2020, by gender
Source
ADP Research Institute, produced for the World Economic
Forum's New Metrics CoLab.
Retained workers
Female - age: 42, wage ($): 26 45% 55% Male - age: 43, wage ($): 32
Recalled workers
Female - age: 40, wage ($): 32 44% 56% Male - age: 44, wage ($): 52
Female - age: 36, wage ($): 20 50% 50% Male - age: 37, wage ($): 24
Displaced workers
Female - age: 38, wage ($): 18 51% 49% Male - age: 39, wage ($): 22
Female Male
Source
ADP Research Institute, produced for the World Economic
Forum's New Metrics CoLab.
Figures 13 C and 13 D present the wage and age basic education as 7.5%. The latest available figures
dynamics of workers in the United States who were by economy are listed in the Country Profiles in Part
retained, recalled, displaced or transitioned. The 2 of the report. It must be noted that such figures
markers in brown denote displaced workers; in are still too rarely collected and that more timely
gold, those who transitioned to new opportunities; unemployment figures remain unreliable. This trend
in light blue, those who were recalled; and in dark can be further confirmed by focusing on country-
blue, those who were retained. Those recalled into level data with strong availability. Figure 14 presents
the labour market have the highest average wage of unemployment levels among workers in the United
the four cohorts, and those who are displaced have States by education level over time. It shows that
the lowest average wage. In Retail, those who were the unemployment rate among those with less than
displaced earn on average a low $17.80 an hour secondary education peaked at 21.2% in April, and
while those recalled are earning $27.00 an hour. In stills stands at 12.6% as of the end of August. On
Information and Media, those displaced earn $28.70 the other hand, unemployment levels among workers
an hour while those recalled earn $61.20 an hour. who hold at least a tertiary degree spiked at 8.4%
in April and stands at 5.3% as of the end of August.
In addition, retained and recalled workers are, on Comparing the impact of the Global Financial Crisis
average older, aged 40 and above, while displaced of 2008 on individuals with lower education levels to
workers are more typically in their mid-to-late thirties the impact of the COVID-19 crisis, it is clear that the
or have just turned 40. For example, in Education impact today is far more significant and more likely to
Services, those displaced are on average aged 35, deepen existing inequalities.
while those retained at nearing 43. In Retail and in
Accommodation and Food Services these average
ages are distorted by the relative youth of both
sectors. In Retail, the average age for a displaced
worker is 34, while those retained are nearing 40.
Across the board, younger workers (those in their
30s) are more likely to have transitioned to new roles
during these uncertain times.
0 20 40 60 80 100
B. Worker transitions into sub-industries, by relative volume of transitions and wage change accepted
Note
The wage change value shows the difference of starting and
ending wage as a share of the starting wage. It is calculated
from data showing transitions from one industry to another as
the unweighted median wage change of transitions from all
other industries into the destination industry.
30 32 34 36 38 40 42 44 46 48 50
10 20 30 40 50 60 70 80 90 100
Source
ADP Research Institute, produced for the World Economic
Forum's New Metrics CoLab.
25
20
Unemployment rate (%)
15
10
0
2001 2005 2010 2015 2020
Source Note
United States Bureau of Labor Statistics. Short-cycle tertiary education provides professional
knowledge, skills and competencies. Typically, programmes
are practically based and occupationally-specific.
Finally, such turbulent labour markets provide young professionals have targeted for their job
additional challenges to young professionals transitions after entering the world of work in one of
navigating their entry into working life. The FutureFit the six industries most affected by the COVID-19
AI global data map combines job automation pandemic. Figure 17 illustrates those next-step
and growth forecasts, real-time labour market possible opportunities, which include new roles in
information, learner resumes and the professional the Healthcare, Financial Services, Not-for-Profit and
profiles of individuals. As such, it can track the Information, Technology and Services industries—
historic job trajectories of professionals through roles such as Credit Analysts, Bank Tellers and
different roles and industries,30 and in this instance Public Relations Coordinators in the Not-for-Profit
the transition of young professionals who are sector, Certified Nursing Assistants in Healthcare,
in their first decade of working life in the United and Account Executives in the Information
States observed between 2008 and 2019.31 The Technology and Services sector.
data in Figure 15 A reveals that, historically, the
Retail, Restaurants, Hospitality, and the Food & This willingness to transition to new job
Beverage sectors, as well some parts of Higher opportunities, matched with new reskilling and
Education, have been among the top 20 starter- upskilling capabilities, can help place young
sectors for young people. However, as Figure 15 B professionals back on track, helping them find routes
indicates, these industries maintain a high attrition from affected to new, growing opportunities. While
rate as workers tend to be transient. Thirty-seven the data shared above suggests that businesses
percent of young professionals who work in Retail and individuals have taken on significant initiative
use the industry as a stepping-stone to another to adapt to the current labour market, economic
career and have historically moved onto another scarring and persistent damage to the labour market
industry beyond the six affected sectors. The have the potential to limit the scale of opportunities
same figure is at 32% for those in the Restaurant available to workers. However, governments have at
sector. As roles in these sectors are temporarily their disposal a range of tools that can alleviate the
or permanently displaced, those at the start of impact on workers as economies recover.
their careers will need to re-route and leapfrog into
aspirational opportunities to work in high quality,
well-remunerated jobs.
Higher Education
Retail
Hospital & Health Care
Restaurants
Financial Services
Military
Non-Profit Organization Management
Education Management
Information Technology and Services
Government Administration
Hospitality
Food & Beverages
Entertainment
Marketing and Advertising
Banking
0 2 4 6 8 10 12 14 16 18 20
Retail 37%
Entertainment 36%
Restaurants 32%
Hospitality 32%
0 20 40 60 80 100
Stay in sub-industry Transition to one of the six affected industries Transition out of the six affected industries
Source
FutureFit AI, produced for the World Economic Forum's New
Metrics CoLab.
In previous recessions, the long-term impact on The early indicators shared in this section signal
earnings among young people resulted in persistent that without adequate intervention, gains towards
earnings declines lasting up to 10 years, as young bridging societal inequalities might be reversed
professionals started to work for lower-paying and wages further polarized. While data for the
employers, then partly recover through a gradual United States cannot be generalized to the world,
process of mobility toward better firms. We have the availability of such granular insights in this one
also seen young professionals start to work in economy serves as a stark reminder of the potential
occupations that do not match their education impact of these disruptions on equality within and
levels.32 As we consider the ways to revive the across all economies.
labour market, such insights can point to ways
in which data-driven re-employment can support
not only re-entry into one’s original industry or to
an adjacent one, but also provide accelerated
transitions to the ultimate career designation
aspired to by young professionals.
Destination sub-industry
Source Apparel & Broadcast Education Financial Hospital & Non-Profit Information Marketing and Real
sub-industry Fashion Media Management Services Health Care Organization Technology Advertising Estate
Management and Services
Entertainment - 4% - 4% 5% 4% - 5% -
Food &
- - 4% 5% 6% 5% 3% - -
Beverages
Higher
- - 4% 4% 9% 6% 4% - -
Education
Hospitality - - - 7% 7% 5% - 4% 4%
Restaurants - - 3% 5% 8% 6% 3% - -
Retail 5% - 4% 6% 8% 4% - - -
Source Note
FutureFit AI, produced for the World Economic Forum's New Values refer to share of workers transitioning from source sub-
Metrics CoLab. industry to destination sub-industry.
Registered Nurse
Bank Teller
Account Executive
Restaurants
Financial Representative
Financial Analyst
Retail Financial Services
Customer Service Representative
Certified Nursing Assistant
Food & Beverages
Substitute Teacher Information Technology
and Services
Entertainment Consultant
Education Management
Sales Associate
Hospitality Medical Assistant Non-Profit Organization
Management
Pharmacy Technician
Teacher
Nursing Assistant
Social Worker
Tutor
Applications Analyst
Web Developer
Source
FutureFit AI, produced for the World Economic Forum's New
Metrics CoLab.
2
Forecasts for Labour
Market Evolution
in 2020-2025
Over the past five years, the World Economic the following chapter tracks technological adoption
Forum has tracked the arrival of the future of work, among firms alongside changing job requirements
identifying the potential scale of worker displacement and skills demand. These qualitative survey
due to technological automation and augmentation responses are further complemented by granular
alongside effective strategies for empowering job data from new sources derived from privately-held
transitions from declining to emerging jobs. At the data that tracks key jobs and skills trends. Together,
core of the report and its analysis is the Future of these two types of sources provide a comprehensive
Jobs survey, a unique tool which assess the short- overview of the unfolding labour market trends as
and long-term trends and impact of technological well as an opportunity to plan and strategize towards
adoption on labour markets. The data outlined in a better future of work.
0 20 40 60 80 100
Source
Future of Jobs Survey 2020, World Economic Forum.
FIGURE 19 Technologies likely to be adopted by 2025, by share of companies surveyed, selected sectors
AGRI AUTO CON DIGICIT EDU ENG FS GOV HE MANF MIM OILG PS TRANS
Technology/Sector
(%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%) (%)
3D and 4D printing
54 67 39 39 69 69 27 45 65 69 48 79 40 60
and modelling
Artificial intelligence
(e.g. machine
62 76 73 95 76 81 90 65 89 71 76 71 76 88
learning, neural
networks, NLP)
Augmented and
17 53 58 73 70 75 62 56 67 54 57 71 57 62
virtual reality
Biotechnology 50 18 48 40 46 47 46 38 65 31 16 36 28 23
Cloud computing 75 80 82 95 95 88 98 95 84 92 87 86 88 94
Distributed ledger
technology (e.g. 31 40 41 72 61 50 73 40 72 41 50 46 53 38
blockchain)
E-commerce and
80 75 85 82 72 71 90 67 78 82 62 62 70 87
digital trade
New materials
(e.g. nanotubes, 15 46 22 36 67 65 36 33 47 51 37 36 27 27
graphene)
Quantum computing 18 21 17 51 25 41 44 36 38 21 29 25 19 38
Robots, humanoid 42 50 38 44 47 24 47 31 47 41 15 17 25 21
Robots, non-
humanoid (industrial
54 60 52 61 59 65 53 50 56 79 90 79 35 69
automation, drones,
etc.)
Source Note
Future of Jobs Survey 2020, World Economic Forum. AGRI = Agriculture, Food and Beverage; AUTO = Automotive; CON = Consumer;
DIGICIT = Digital Communications and Information Technology; EDU =
Education; ENG = Energy Utilities & Technologies; FS = Financial Services;
GOV = Government and Public Sector; HE = Health and Healthcare; MANF =
Manufacturing; MIM = Mining and Metals; OILG = Oil and Gas; PS = Professional
Services; TRANS = Transportation and Storage.
0 10 20 30 40 50 60
Source
Future of Jobs Survey 2020, World Economic Forum.
FIGURE 21 Share of tasks performed by humans vs machines, 2020 and 2025 (expected),
by share of companies surveyed
Administering
All tasks
0 20 40 60 80 100
Extrapolating from the figures shared in the Future to the new division of labour between humans,
of Jobs Survey 2020, employers expect that by machines and algorithms, across the 15 industries
2025, increasingly redundant roles will decline from and 26 economies covered by the report.
being 15.4% of the workforce to 9% (6.4% decline),
and that emerging professions will grow from 7.8% The 2020 version of the Future of Jobs Survey
to 13.5% (5.7% growth) of the total employee also reveals similarities across industries when
base of company respondents. Based on these looking at increasingly strategic and increasingly
figures, we estimate that by 2025, 85 million jobs redundant job roles. Similar to the 2018 survey,
may be displaced by a shift in the division of labour the leading positions in growing demand are roles
between humans and machines, while 97 million such as Data Analysts and Scientists, AI and
new roles may emerge that are more adapted Machine Learning Specialists, Robotics Engineers,
At the opposite end of the scale, the roles which This resulting set of emerging professions reflects
are set to be increasingly redundant by 2025 remain the adoption of new technologies and increasing
largely consistent with the job roles identified in demand for new products and services, which are
2018 and across a range of research papers on the driving greater demand for green economy jobs,
automation of jobs.34 These include roles which are roles at the forefront of the data and AI economy,
being displaced by new technologies: Data Entry as well as new roles in engineering, cloud computing
Clerks, Administrative and Executive Secretaries, and product development. In addition, the emerging
FIGURE 22 Top 20 job roles in increasing and decreasing demand across industries
13 Database and Network Professionals 13 Sales Rep., Wholesale and Manuf., Tech. and Sci.Products
16 Management and Organization Analysts 16 Door-To-Door Sales, News and Street Vendors
Source
Future of Jobs Survey 2020, World Economic Forum.
Source
LinkedIn Economic Graph.
Data and AI
Cloud Computing
Product Development
Marketing
Engineering
Content Production
Sales
0 20 40 60 80 100
Same occupation Same emerging job cluster Any emerging cluster Any occupation outside emerging cluster
0 20 40 60 80 100
Share of transitions (%)
0 20 40 60 80 100
Engineering
Destination job
of tomorrow
Marketing
Cloud Computing
Information Technology
Engineering
Human Resources
Business Development
Research
Product Development
Operations
Sales
Quality Assurance
Support
Education Content
Administrative
Product Management
Finance
Community and Social Services
Consulting
Accounting
Real Estate
Purchasing
Legal
Healthcare Services
Military and Protective Services
Entrepreneurship
Source
LinkedIn Economic Graph.
Other 5.3
0 10 20 30 40 50 60
Source
Future of Jobs Survey 2020, World Economic Forum.
Since its 2016 edition, this report has tracked This report reveals in further granular detail the types
the cross-functional skills which are in increasing of insights that can guide job transitions through to
demand. Figure 27 shows the top skills and skill appropriate reskilling and upskilling. Figures 29 and
groups which employers see as rising in prominence 30 demonstrate those metrics. Figure 29 presents the
in the lead up to 2025. These include groups such set of high-growth, emerging roles that are currently
as critical thinking and analysis as well as problem- covered by the Data and AI job cluster, and the typical
solving, which have stayed at the top of the agenda skills gap between source and destination professions
with year-on-year consistency. Newly emerging this when workers have moved into those roles over the
year are skills in self-management such as active past five years. Figure 30 presents the typical learning
learning, resilience, stress tolerance and flexibility. curriculum of Coursera learners who are targeting a
In addition, the data available through metrics transition into Data and AI and the distance from the
partnerships with LinkedIn and Coursera allow us optimal level of mastery in the relevant job cluster,
to track with unprecedented granularity the types of and quantifies the days of learning needed for the
specialized skills needed for the jobs of tomorrow. average worker to gain that level of mastery. Figures
Figure 28 demonstrates the set of skills which are 29 and 30 together demonstrate that it is common
in demand across multiple emerging professions. for individuals moving into Data and AI to lack key
Among these ‘cross-cutting’ skills are specialized data science skills—but that individuals seeking to
skills in Product Marketing, Digital Marketing and transition into such roles will be able to work towards
Human Computer Interaction. the right skill set through mastery of skills such as
statistical programming within a recommended time
frame, in this case, 76 days of learning.
0 20 40 60 80 100
Source
Future of Jobs Survey 2020, World Economic Forum.
In addition to skills that are directly jobs-relevant, such as mindfulness, meditation, gratitude and
during the COVID-19 context of 2020, data from kindness are among the top 10 focus areas of those
the online learning provider Coursera has been in employment in contrast to the more technical
able to identify an increasing emphasis within skills which were in-focus in 2019. In contrast, those
learner reskilling and upskilling efforts on personal who are unemployed have continued to emphasize
development and self-management skills. This skills which are of relevance to emerging jobs in
echoes earlier findings on the importance of well- Engineering, Cloud Computing, Data and AI.37
being when managing in the remote and hybrid
work: demand for new skills acquisition has When it comes to employers providing workers with
bifurcated. Figure 31 A illustrates the changing training opportunities for reskilling and upskilling, in
demand for training by employment status, contrast to previous years, employers are expecting
comparing the April-to-June period this year with the to lean more fully on informal as opposed to formal
same period last year. This data reveals a significant learning. In the Future of Jobs Survey, 94% of
increase in demand for personal development business leaders report that they expect employees
courses, as well as for courses in health, and a to pick up new skills on the job, a sharp uptake from
clear distinction between those who are currently 65% in 2018. An organization’s learning curricula is
in employment and those who are unemployed. expected to blend different approaches—drawing
Those in employment are placing larger emphasis on internal and external expertise, on new education
on personal development courses, which have seen technology tools and using both formal and informal
88% growth among that population. Those who methods of skills acquisition.
are unemployed have placed greater emphasis on
learning digital skills such as data analysis, computer
science and information technology. These trends
can be observed in more granular detail in Figures
31 B and C. In particular, self-management skills
1. Product Marketing Data and AI, People and Culture, Marketing, Product Development, Sales (5)
2. Digital Marketing Content, Data and AI, Marketing, Product Development, Sales (5)
3. Software Development Life Cycle (SDLC) Cloud Computing, Data and AI, Engineering, Marketing, Product Development (5)
4. Business Management People and Culture, Marketing, Product Development, Sales (4)
7. Development Tools Cloud Computing, Data and AI, Engineering, Product Development (4)
8. Data Storage Technologies Cloud Computing, Data and AI, Engineering, Product Development (4)
9. Computer Networking Cloud Computing, Data and AI, Engineering, Sales (4)
11. Management Consulting Data and AI, People and Culture, Product Development (3)
13. Artificial Intelligence Cloud Computing, Data and AI, Engineering (3)
14. Data Science Data and AI, Marketing, Product Development (3)
Source Note
LinkedIn Economic Graph. Cross-cutting skills are those skills that are
applicable and easily transferable across many
occupations and roles.
FIGURE 29 Data and AI jobs of tomorrow, top roles and typical skills in past transitions
A. Opportunities within professional cluster B. Typical skills gaps across successful job transitions
11 Advertising 1.00
A. Typical learning agenda B. Top 10 skills by required level of mastery and time to achieve that mastery
Source Note
Coursera. Mastery score is the score attained by those in the top 80% transition to the occupation as a share of the score among
on an assessment for that skill. Mastery gap is measured as those already in the occupation.
a percentage representing the score among those looking to
According to data from the Future of Jobs Survey, of online learning. In fact, there has been a four-fold
formal upskilling appears to be more closely increase in the numbers of individuals seeking out
focused on technology use and design skills, while opportunities for learning online through their own
emotional intelligence skills are less frequently initiative, a five-fold increase in employer provision
targeted in that formal reskilling provision. Data from of online learning opportunities to their workers and
Coursera showing the focus areas of workforce an even more extensive nine-fold enrolment increase
recovery programmes and employer-led reskilling for learners accessing online learning through
and upskilling activities confirms that finding. In- government programmes.
focus courses are primarily those in technical skills
alongside a cohort of managerial skills in strategy Through focused efforts, individuals could acquire
and leadership. one of Coursera’s top 10 mastery skills in emerging
professions across People and Culture, Content
On average, respondents to the Future of Jobs Writing, Sales and Marketing in one to two months.
Survey estimate that around 40% of workers will Learners could expand their skills in Product
require reskilling of six months or less. That figure is Development and Data and AI in two to three
higher for workers in the Consumer industry and in months; and if they wish to fully re-pivot to Cloud
the Health and Healthcare industry, where employers and Engineering, learners could make headway
are likely to expect to lean on short-cycle reskilling. into that key skill set through a 4-5 month learning
The share of workers who can be reskilled within programme.38 Such figures suggest that although
six months is lower in the Financial Services and learning a new skill set is increasingly accessible
the Energy sectors, where employers expect that through new digital technologies, to consolidate
workers will need more time-intensive reskilling. new learning individuals will need access to the time
These patterns are explored more deeply in the and funding to pursue such new career trajectories.
Industry Profiles in Part 2. LinkedIn data presented in section 2.2 indicates that
although many individuals can move into emerging
According to Future of Jobs Survey data, employers roles with low or mid skills similarity, a low-fit initial
expect to lean primarily on internal capacity to transition will still require eventual upskilling and
deliver training: 39% of training will be delivered by reskilling to ensure long term productivity.
an internal department. However, that training will
be supplemented by online learning platforms (16%
of training) and by external consultants (11% of
training). The trend towards the use of digital online
reskilling has accelerated during the restrictions on
in-person learning since the onset of the COVID-19
pandemic. New data from the online learning
platform Coursera for April, May and June of 2020
(quarter 2) signals a substantial expansion in the use
Distribution of enrolled, April, May and June (Q2) Year-on-year change, Q2 2019 to 2020
2 Computer Science 18% 16% 17% 11% 23% 21% -8% -34% -7%
4 Data Science 20% 13% 22% 12% 28% 18% -37% -44% -35%
B. Top 10 in-focus skills of those in employment C. Top 10 skills for those who are unemployed
Source Note
Coursera, produced for the World Economic Forum's New Values in brown indicate where the hiring rate is lower than in 2019, while values in
Metrics CoLab. green indicate where the rate is higher than 2019. The darker the colour, the lower/
higher the rate.
3
Public and Private Sector
Pathways to Reviving
Labour Markets
The challenges facing labour markets today are effective systems for upgrading individual’s
significant but not insurmountable. To jointly lead skills and capabilities in line with emerging skills
economies and societies to greater prosperity, the demand—in essence, expanding access and
public and private sector will need to tackle the delivery of mid-career reskilling and upskilling
factors that lead to the misallocation and waste through private and public sector investment
of human capabilities and potential. For over half and to ensure that such efforts by workers are
a century, economic thinkers have been able rewarded with adequate job opportunities. To
to track the benefits of expanding human skills realize the value of such investments, businesses
and capabilities to economic prosperity.39 One and governments will need to accompany such
of the most valuable assets of any economy or efforts with policies and practices that ensure
company is its human capital–the skills, capabilities that workers are able to prosper on the basis of
and innovation of its citizens. Distortions that merit rather than the misallocation of talent due
undercut individuals’ skills development and their to social strata or characteristics such as race or
ability to find a job that matches their current and gender, strengthening the connection between
potential capabilities erode the factors of economic personal income and productivity, and expanding
productivity, innovation and growth that are derived safety nets to alleviate economic strain during
from harnessing human skills and capabilities.40 periods of transition.
United States
Japan
Germany
Australia
Brazil
United Kingdom
Canada
South Africa
China
Italy
Korea
Argentina
France
Indonesia
Saudi Arabia
Russia
India
Mexico
Turkey
0 2 4 6 8 10 12 14
Source Note
Policy Tracker 12 June 2020, International Monetary Values include 'above-the-line' measures but exclude 'below-
Fund (IMF); International Institute of Labour Studies; and the-line measures' (equity injections, loans, asset purchase or
Transatlantic Institute. debt assumptions, or guarantees).
A. Function
0 5 10 15 20
B. Instrument
0 5 10 15 20
Source Note
International Labour Organization (ILO) Social Protection The values represent the distribution of 1,218 measures
Monitor, July 2020. introduced across 203 countries.
Another set of key policies has been focused on While these temporary measures provide a lifeline to
preserving the retention of staff by businesses workers during this unprecedented crisis and ahead
through wage compensation schemes as well as of a future recovery, the need for an urgent response
tax or payment deferrals. Figure 35 presents the should be transformed into an impulse to enhance
unprecedented use of job-retention schemes across permanent social protection mechanisms. New data
several countries—notably New Zealand, France, from the OECD shows the projected employment
Switzerland and the United Kingdom—affecting growth of a number of economies in 2019–2020
close to 60 million workers across OECD countries.45 if countries experience a potential second wave of
While these measures have been broadly welcomed COVID-19 infections. Figure 36 plots that possible
and have been effective at buffering unemployment, new reality against the Social Resilience pillar of
such schemes obscure the possible true impact of the World Economic Forum’s Global Social Mobility
COVID-19 on the labour market. It is only as wage Index. The pillar score summarizes in one measure
support and replacement mechanisms begin to the level of social protection available in an economy
expire that some of the damage to the labour market alongside the presence of inclusive institutions.
will be revealed.
#$
%&'
Source
Gentilini, et al, 2020.
New Zealand
France
Switzerland
Italy
Austria
Portugal
United Kingdom
Germany
Luxembourg
Netherlands
Australia
Belgium
Ireland
Czech Republic
Spain
Canada
Sweden
Denmark
Norway
Finland
Latvia
United States
0 20 40 60 80
Source
OECD Economic Outlook June 2020, based
on national sources.
100
Denmark
Finland
Austria
90 Sweden
Belgium
France Netherlands
Germany United Kingdom
80 Japan Ireland
Norway Spain
Switzerland Australia Canada
Slovenia
70 Czech Republic Iceland Portugal
Poland
New Zealand Latvia Estonia
Lithuania Slovak Republic United States
60
Greece
Korea, Rep. Israel
Italy
50 Hungary Colombia
Mexico
40
Turkey
30
20
0 -3 -6 -9 -12 -15
Source Note
OECD Economic Outlook 2020, OECD, and Social Mobility Forecasts for Q4 2020 produced by the OECD assuming two
Index, World Economic Forum. waves of COVID-19, namely a "double hit" scenario.
The political will to expand social protection has wage. The economic strain on families subsisting
often been deadlocked, driven by concerns about on low wages is not conducive to maximizing long-
the long-term impact on labour market participation, term human potential and leaves workers vulnerable
the efficiency of current tools and the capacity of to disruptions. Legislating against bias on the basis
government to deliver these public services with the of gender, race or other characteristics protects the
adequate efficiency at scale. Given the large-scale connection between employment, wages and the
disruption to workers from both the pandemic-driven skills and capabilities of workers—guaranteeing
recession and the accelerated pace of technology that the talents of all parts of the population are
adoption, the question cannot be ‘if’ but should be used and can drive further growth and prosperity
‘how’ to expand some of these essential protections. in the economy.
Research shows that wages have, for some time, Past research has shown that long-term
been misaligned from productivity and that wage displacement from the labour market has a
level can be as much determined by the structure persistent, negative effect on workers.47 When social
of local labour markets or disadvantaged by race protection mechanisms are lacking, individuals
or gender as they are by workers receiving a in the midst of a career transition are forced to
reasonable return on their skills and productivity.46 maintain a dual focus—on the one hand trying to
When it comes to preserving worker’s ability to preserve their quality of life and keep poverty and
save, governments can cap the erosion of wages, potential destitution at bay, and on the other hand
ensuring that all workers are able to gain a living attempting to successfully transition to a new role.
Within 1–3
months
10.8%
B. Source of funding
Centralized budget
Budget per department
Use free learning to minimize cost
Budget per worker
Tap into government funding
Share costs with other companies in your industry
Share costs with other companies outside your industry
0 10 20 30 40 50 60 70 80
Source
Future of Jobs Survey 2020, World Economic Forum.
Company leaders can ensure the success of report has shown that a number of emerging
workforce strategies by directing the transition of roles are already staffed by individuals who first
employees with empathy, within the rule of law, in transition into those positions and then ‘grow
line with company values and culture, by ensuring into’ the full skill set required. As an overarching
outcomes are equitable, and by directing learning principle, business leaders need to place equity
to effective resources and meaningful curricula. and diversity at the heart of their talent ecosystem,
A range of motivating factors can fuel reskilling ensuring that employees believe in their capacity
and upskilling uptake—connected broadly to to prosper based on merit.
employees’ sense of purpose, meaning, growth
and achievement. Employers can signal the Expanding effective workforce strategies requires
market value of new online-first credentials by strong capabilities in real time, as well as
opening up role opportunities to new cohorts of dynamic mapping of the types of opportunities
workers who have completed mid-career reskilling that remain available to workers displaced by
and upskilling. Employers can make broader the COVID-19 pandemic and the fast pace of
use of hiring on the basis of potential rather than automation. A set of technology companies
current skill sets and match potential-based hiring which are broadly classed as EdTech and
with relevant training. The data featured in this reskilling services companies can support the
Conclusion
The ongoing disruption to labour markets from To address the substantial challenges facing the
the Fourth Industrial Revolution has been further labour market today, governments must pursue
complicated—and in some cases accelerated—by a holistic approach, creating active linkages and
the onset of the pandemic-related recession of 2020. coordination between education providers, skills,
workers and employers, and ensuring effective
The most relevant question to businesses, collaboration between employment agencies, regional
governments and individuals is not to what extent governments and national governments.
automation and augmentation of human labour
will affect current employment numbers, but under Such efforts can be strengthened by
what conditions the global labour market can be multistakeholder collaboration between companies
supported towards a new equilibrium in the division looking to support their workforce; governments
of labour between human workers, robots and willing to fund reskilling and the localization of
algorithms. The technological disruptions which were mid-career education programmes; professional
in their infancy in previous editions of the Future of services firms and technology firms that can
Jobs Report are currently accelerated and amplified map potential job transitions or provide reskilling
alongside the COVID-19 recession as evidenced services; labour unions aware of the impact of
by findings from the 2020 Future of Jobs Survey. those transitions on the well-being of workers; and
While it remains difficult to establish the long-term community organizations that can give visibility to
consequences of the pandemic on the demand for the efficacy of new legislation and provide early
products and services in severely affected industries, feedback on its design.
supporting workers during this transition will protect
one of the key assets of any company and country—
its human capital.
2. Baldwin, 2019.
4. World Economic Forum, 2018, DeVries, et al, 2020, and Frey and Osborne, 2013.
7. Ibid.
8. YouGov, 2020.
9. OECD, 2020a.
11. Ibid.
21. Job-seekers searching for roles on the LinkedIn platform using built-in remote job
filters, normalized against changes to all job searches.
22. The share of job postings, which use number of keywords (i.e. ‘remote work’,
‘work from home’, home office’) in 10 different languages, as well as built-in
remote job filters.
23. LinkedIn analysed data from job search behaviour and job postings of full-time
roles and its changes due to COVID-19 during the period of 11 February to 1
July. Analysts utilized the ‘remote work’ filter and a set of searchable key words
such as ‘remote work’, ‘work from home’, ‘homeoffice’ in 10 different languages.
The index is the start of the analysis period, 11 July. Results are normalized for
platform growth as well as in the case of job searchers against the volume of job
searches. The daily figures represent a seven-day smoothed proportion.
29. Workers are considered to have dropped out of employment if they disappear
from the ADP database. While some of those variations can reflect worker
movements to companies which do not use ADP’s services, the scale of that
effect is not typically as large; therefore, on the basis of past trends we can
deduce that what we are reporting are reach changes to employment.
30. Data from FutureFit AI combines over 50 data sources on workforce demand and
supply, translating a range of taxonomies of jobs and skills. Supply-side sources
include over 350 million talent profiles listing 30,000 skills clusters, 80,000 job
titles, hundreds of industries, thousands of learning opportunities and millions of
companies worldwide. The data set used comes from worker profile information
sourced from resumes and online professional profiles. It also includes key
data points for the analysis—such as employers, start and end dates, job role,
industries and employment sequence, among others.
31. This metric covers approximately 300,000 young professionals in the United
States, defined here as those who have graduated with an upper secondary
or tertiary (undergraduate) degree no earlier than 2008, and have held 15 or
less positions and have not been in the labour market for longer than 20 years.
These professionals have, on average, eight years of work experience after or
during a student’s first degree. The average work experience tenure following
graduation is 6.7 years. The overwhelming majority of this sample are in their
first working decade.
33. See, for example: Arntz, Melanie, Terry Gregory and Ulrich Zierahn, The risk of
automation for jobs in OECD countries: a comparative analysis, OECD Social,
Employment and Migration Working Papers No 189, Organization for Economic
Cooperation and Development (OECD), 2016; McKinsey Global Institute, A
Future That Works: Automation, Employment, and Productivity, McKinsey Global
Institute (MGI), 2017; PwC, Will robots really steal our jobs? An international
analysis of the potential long term impact of automation, 2018. For a range
of relevant additional considerations, see: van der Zande, Jochem, et al., The
Substitution of Labor: From technological feasibility to other factors influencing
job automation, Innovative Internet: Report 5, Stockholm School of Economics
Institute for Research, 2018.
36. For more details on how the clusters are computed please refer to World
Economic Forum, 2020a.
37. For an in-depth analysis of emerging jobs please see World Economic
Forum, 2020a.
38. According to Coursera data from individuals completing reskilling and upskilling
on its platform, working towards a new skill in Cloud Computing could take on
average 106 full calendrical days; in Content, 24 days; in Data and AI professions,
60; in Engineering, 77 days; in Marketing, 39; People and Culture, 36; Sales. 37;
and in Product Development professions, 44. We take the average month to have
21 working days.
50. For more details on the overall framework please see Word Economic
Forum, 2020b.
Part 2
Country
and Industry
Profiles
Part 2 of the report presents data findings through both an industry and country lens,
with the aim of providing specific practical information to decision-makers and experts
from academia, business, government and civil society. Complementing the cross-
industry and cross-country analysis of results in Part 1, this section provides deeper
granularity for a given industry and country through dedicated Industry Profiles and
Country Profiles. Profiles are intended to provide interested companies and policy-
makers with the opportunity to benchmark their organization against the range of
expectations prevalent in their industry and/or country. This User’s Guide provides
an overview of the information contained in the various Industry Profiles and Country
Profiles and its appropriate interpretation.
User’s Guide
How to Read the Country
and Industry Profiles
Country Profiles
71.7%
best Jobs & work
Labour force participation
2 01 9
worst
85.2%
best
Business relevance of basic education* 65.3% Working cond. impact of gig economy* 32.5%
W EI G HT ED AVE R AG E 2 01 9- 20 2 0 2 02 0
Unempl. rate among workers with adv. educ. 3.3% Unemployment rate change
20 17 —
Unempl. rate among workers with basic educ. 0.8% Unemployment rate change, women
20 17 —
Share of youth not in empl., educ. or training 11.4% Unemployment rate change, men
20 20 —
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Emerging and redundant jobs roles Power storage and generation 65%
Role identified as being in high demand or increasingly redundant within their
organization, ordered by frequency Augmented and virtual reality 57%
4
EMERGING
Distributed ledger technology (e.g. blockchain) 56%
1. Data Analysts and Scientists
2. Digital Marketing and Strategy Specialists
3. Business Development Professionals
4. AI and Machine Learning Specialists
Emerging skills
5. Digital Transformation Specialists
Skills identified as being in high demand within their organization, ordered by
6. Process Automation Specialists frequency
7. Organisational Development Specialists
8.
9.
General and Operations Managers
Database and Network Professionals
1.
2.
Analytical thinking and innovation
Complex problem-solving
5
3. Critical thinking and analysis
10. Big Data Specialists
4. Active learning and learning strategies
REDUNDANT
5. Leadership and social influence
1. Administrative and Executive Secretaries
6. Technology use, monitoring and control
2. Data Entry Clerks
7. Creativity, originality and initiative
3. Accounting, Bookkeeping and Payroll Clerks
8. Service orientation
4. Postal Service Clerks
9. Resilience, stress tolerance and flexibility
5. Business Services and Administration Managers
10. Emotional intelligence
6. Mechanics and Machinery Repairers
11. Technology design and programming
7. Accountants and Auditors
12. Troubleshooting and user experience
8. Material-Recording and Stock-Keeping Clerks
13. Quality control and safety awareness
9. Client Information and Customer Service Workers
14. Systems analysis and evaluation
10. Cashiers and Ticket Clerks
15. Persuasion and negotiation
2/2
1 to 3 months
21.4%
Responses to shifting skill needs Over 1 year
16.4%
Share of companies surveyed
9
Hire new temporary staff with skills relevant to
49%
new technologies 44.3% Internal learning and development
Period: 2020.
The bar chart shows the top strategies organizations Source: World Economic Forum, Future of Jobs
will undertake to address the shifting skills demand Survey 2020.
as a share of survey responses from companies
operating in the country. It is based on the
responses to the following multiple-choice question
“How likely is your organization to undertake the
following strategies to address the shifting skills
demand?” from the Future of Jobs Survey.
Period: 2020.
Source: World Economic Forum, Future of Jobs
Survey 2020.
Advanced Manufacturing
1 Expected redeployment
success rate of displaced
Average skills instability
among workforce
14%
workers
2
Technology adoption in industry
Share of companies surveyed
Emerging skills
Skills identified as being in high demand within their organization, ordered by 3
frequency
1. Technology use, monitoring and control
Cloud computing 89%
2. Critical thinking and analysis
Internet of things and connected devices 87% 3. Active learning and learning strategies
4. Leadership and social influence
Robots, non-humanoid (industrial automation, 85%
drones, etc.) 5. Analytical thinking and innovation
6. Reasoning, problem-solving and ideation
E-commerce and digital trade 83%
7. Complex problem-solving
Big data analytics 76% 8. Service orientation
9. Resilience, stress tolerance and flexibility
Encryption and cyber security 74%
10. Technology design and programming
2/2
Skills gaps among organization’s leadership 54.8% Expand its use of contractors doing task-specialized work
48.4%
Inability to attract specialized talent 45.2% Reduce its current workforce due to technological integration or automation
45.2%
Shortage of investment capital 41.9% Modify the locations where the organization operates
41.9%
Insufficient understanding of opportunities 38.7% Expand its current workforce due to technological integration or automation
41.9%
Lack of flexibility of the regulatory framework 25.8%
8 6.
7.
Technology design and programming
Quality control and safety awareness
Information and data processing 8. Service orientation
38.3% 9. Management of financial, material resources
Performing physical and manual work activities 10. Leadership and social influence
44.1%
48.5%
Less than 1 month 3 to 6 months
26.8% 16.6%
Identifying and evaluating job-relevant information
49.9%
Administering
52.2% 10
Performing complex and technical activities 6 to 12 months
20.6%
52.6%
62.5%
The table provides the list of skills the industry This bar chart shows the most common barriers
respondents have selected as being increasingly companies face when adopting new technologies.
This bar chart shows the expected impact of the The treemap shows the estimated time needed
current growth strategy of companies operating to reskill each share of the workforce that needs
in this industry on their workforce in the next four reskilling within the industry. It is based on the
years. It is based on the responses to the following responses to the following question “Bearing in mind
multiple-choice question “To deliver on your the evolving skill demand, how long do you expect
organization’s current growth strategy in the next the reskilling/upskilling of your employees to take?”
four years, your organization would need to?” from from the Future of Jobs Survey. Respondents were
the Future of Jobs Survey. asked to provide as share of their workforce for each
duration of reskilling/upskilling.
Period: 2020.
Source: World Economic Forum, Future of Jobs Period: 2020.
Survey 2020. Source: World Economic Forum, Future of Jobs
Survey 2020.
Period: 2020.
Source: World Economic Forum, Future of Jobs
Survey 2020.
Country
Profiles
Argentina 17,640,048
Education & skills worst best Jobs & work worst best
Digital skills among active population* 50.1% Labour force participation 65.7%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 45.9% Working cond. impact of gig economy* 48.7%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 3.4% Unemployment rate change
20 1 9 —
Unempl. rate among workers with basic educ. 9.6% Unemployment rate change, women
20 1 9 —
Share of youth not in empl., educ. or training 19.9% Unemployment rate change, men
20 2 0 —
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the digitalization of work processes (e.g. use of digital tools, video
Cloud computing 90%
conferencing)
87.5% Artificial intelligence (e.g. machine learning,
neural networks, NLP) 89%
Accelerate automation of tasks
56.2%
Big data analytics 80%
Accelerate the digitalization of upskilling/ reskilling (e.g. education technology
providers)
50% Internet of things and connected devices 75%
Accelerate the implementation of upskilling/ reskilling programmes E-commerce and digital trade 72%
37.5%
Encryption and cyber security 70%
EMERGING
3D and 4D printing and modelling 65%
1. AI and Machine Learning Specialists
2. Robotics Engineers
3. Digital Transformation Specialists
4. Software and Applications Developers Emerging skills
5. Internet of Things Specialists Skills identified as being in high demand within their organization, ordered
by frequency
6. FinTech Engineers
7. Data Analysts and Scientists 1. Creativity, originality and initiative
8. Business Services and Administration Managers 2. Complex problem-solving
9. Renewable Energy Engineers 3. Analytical thinking and innovation
10. Digital Marketing and Strategy Specialists 4. Reasoning, problem-solving and ideation
REDUNDANT 5. Active learning and learning strategies
1. Data Entry Clerks 6. Technology use, monitoring and control
2. Accounting, Bookkeeping and Payroll Clerks 7. Quality control and safety awareness
3. Electronics and Telecommunications Installers and Repairers 8. Emotional intelligence
4. Assembly and Factory Workers 9. Resilience, stress tolerance and flexibility
5. Administrative and Executive Secretaries 10. Persuasion and negotiation
6. Shop Salespersons 11. Critical thinking and analysis
7. Sales and Marketing Professionals 12. Coordination and time management
8. Relationship Managers 13. Technology installation and maintenance
9. Material-Recording and Stock-Keeping Clerks 14. Technology design and programming
10. Bank Tellers and Related Clerks 15. Troubleshooting and user experience
Over 1 year
Responses to shifting skill needs 1 to 3 months 18.4%
15.9%
Share of companies surveyed
Australia 17,332,023
Education & skills worst best Jobs & work worst best
Digital skills among active population* 65.5% Labour force participation 65.6%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 59.7% Working cond. impact of gig economy* 46.8%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. Unemployment rate change 1.5%
— 2 0 19 - Q 2 20 2 0 YOY C H .
Unempl. rate among workers with basic educ. Unemployment rate change, women 1.3%
— 2 0 19 - Q 2 20 2 0 YOY C H .
Share of youth not in empl., educ. or training 8.6% Unemployment rate change, men 1.7%
20 2 0 2 0 19 - Q 2 20 2 0 YOY C H .
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Emerging and redundant job roles Augmented and virtual reality 69%
Role identified as being in high demand or increasingly redundant within
their organization, ordered by frequency E-commerce and digital trade 68%
EMERGING
3D and 4D printing and modelling 58%
1. AI and Machine Learning Specialists
2. Data Analysts and Scientists
3. Information Security Analysts
4. Big Data Specialists Emerging skills
5. Process Automation Specialists Skills identified as being in high demand within their organization, ordered
by frequency
6. Digital Transformation Specialists
7. Remote Sensing Scientists and Technologists 1. Analytical thinking and innovation
8. Organizational Development Specialists 2. Active learning and learning strategies
9. Mechanical Engineers 3. Critical thinking and analysis
10. Internet of Things Specialists 4. Leadership and social influence
REDUNDANT 5. Technology use, monitoring and control
1. Data Entry Clerks 6. Emotional intelligence
2. Administrative and Executive Secretaries 7. Complex problem-solving
3. Accounting, Bookkeeping and Payroll Clerks 8. Resilience, stress tolerance and flexibility
4. Business Services and Administration Managers 9. Creativity, originality and initiative
5. General and Operations Managers 10. Technology design and programming
6. Assembly and Factory Workers 11. Systems analysis and evaluation
7. Credit and Loans Officers 12. Service orientation
8. Client Information and Customer Service Workers 13. Reasoning, problem-solving and ideation
9. Accountants and Auditors 14. Quality control and safety awareness
10. Cashiers and Ticket Clerks 15. Troubleshooting and user experience
Brazil 136,154,622
Education & skills worst best Jobs & work worst best
Digital skills among active population* 36.9% Labour force participation 64.2%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 32.1% Working cond. impact of gig economy* 44.7%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 6% Unemployment rate change 1.6%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Unempl. rate among workers with basic educ. 9.3% Unemployment rate change, women 1.4%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Share of youth not in empl., educ. or training 23.6% Unemployment rate change, men 1.8%
20 2 0 2 0 19 - Q 2 20 2 0 YOY C H .
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Temporarily reassign workers to different tasks Text, image and voice processing 84%
40%
E-commerce and digital trade 84%
Over 1 year
Responses to shifting skill needs 21%
Share of companies surveyed
Canada 26,359,853
Education & skills worst best Jobs & work worst best
Digital skills among active population* 67.9% Labour force participation 65.9%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 61.2% Working cond. impact of gig economy* 36.1%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 4.2% Unemployment rate change 6%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Unempl. rate among workers with basic educ. 8% Unemployment rate change, women 6.4%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Share of youth not in empl., educ. or training 12.8% Unemployment rate change, men 5.5%
20 2 0 2 0 19 - Q 2 20 2 0 YOY C H .
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
REDUNDANT
5. Complex problem-solving
3. Business Services and Administration Managers 8. Technology use, monitoring and control
6. Mining and Petroleum Extraction Workers 11. Creativity, originality and initiative
China -
Education & skills worst best Jobs & work worst best
Digital skills among active population* 71.7% Labour force participation 74%
20 2 0 2 0 10
Business relevance of basic education* 66.9% Working cond. impact of gig economy* 28.2%
20 2 0 2 0 20
Unempl. rate among workers with adv. educ. Unemployment rate change
— —
Unempl. rate among workers with basic educ. Unemployment rate change, women
— —
Share of youth not in empl., educ. or training 18% Unemployment rate change, men
20 2 0 —
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the implementation of upskilling/ reskilling programmes Robots, non-humanoid (industrial automation,
41% drones, etc.) 84%
Emerging and redundant job roles Augmented and virtual reality 73%
Role identified as being in high demand or increasingly redundant within
their organization, ordered by frequency Distributed ledger technology (e.g. blockchain) 69%
EMERGING
3D and 4D printing and modelling 66%
1. Data Analysts and Scientists
2. AI and Machine Learning Specialists
3. Big Data Specialists
4. Information Security Analysts Emerging skills
5. Digital Transformation Specialists Skills identified as being in high demand within their organization, ordered
by frequency
6. Internet of Things Specialists
7. Digital Marketing and Strategy Specialists 1. Analytical thinking and innovation
8. Supply Chain and Logistics Specialists 2. Active learning and learning strategies
9. FinTech Engineers 3. Complex problem-solving
10. Assembly and Factory Workers 4. Technology design and programming
REDUNDANT 5. Creativity, originality and initiative
1. Data Entry Clerks 6. Resilience, stress tolerance and flexibility
2. Accounting, Bookkeeping and Payroll Clerks 7. Critical thinking and analysis
3. Administrative and Executive Secretaries 8. Emotional intelligence
4. Business Services and Administration Managers 9. Technology use, monitoring and control
5. Assembly and Factory Workers 10. Reasoning, problem-solving and ideation
6. Accountants and Auditors 11. Leadership and social influence
7. General and Operations Managers 12. Troubleshooting and user experience
8. Client Information and Customer Service Workers 13. Service orientation
9. Human Resources Specialists 14. Systems analysis and evaluation
10. Financial and Investment Advisers 15. Quality control and safety awareness
3 to 6 months
Responses to shifting skill needs 20.9%
Share of companies surveyed
France 45,968,569
Education & skills worst best Jobs & work worst best
Digital skills among active population* 57.1% Labour force participation 58.4%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 55.7% Working cond. impact of gig economy* 49.7%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 4.6% Unemployment rate change -1.6%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Unempl. rate among workers with basic educ. 13.2% Unemployment rate change, women -2%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Share of youth not in empl., educ. or training 10.3% Unemployment rate change, men -1.2%
20 2 0 2 0 19 - Q 2 20 2 0 YOY C H .
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the implementation of upskilling/ reskilling programmes Augmented and virtual reality 78%
37.5%
Robots, non-humanoid (industrial automation,
drones, etc.) 77%
Emerging and redundant job roles E-commerce and digital trade 74%
Role identified as being in high demand or increasingly redundant within
their organization, ordered by frequency Distributed ledger technology (e.g. blockchain) 74%
EMERGING
Text, image and voice processing 72%
1. Data Analysts and Scientists
2. AI and Machine Learning Specialists
3. Big Data Specialists
4. Internet of Things Specialists Emerging skills
5. Software and Applications Developers Skills identified as being in high demand within their organization, ordered
by frequency
6. Assembly and Factory Workers
7. General and Operations Managers 1. Active learning and learning strategies
8. FinTech Engineers 2. Critical thinking and analysis
9. Digital Transformation Specialists 3. Analytical thinking and innovation
10. Business Services and Administration Managers 4. Technology design and programming
REDUNDANT 5. Complex problem-solving
1. Data Entry Clerks 6. Creativity, originality and initiative
2. Administrative and Executive Secretaries 7. Resilience, stress tolerance and flexibility
3. Accountants and Auditors 8. Emotional intelligence
4. Accounting, Bookkeeping and Payroll Clerks 9. Service orientation
5. Assembly and Factory Workers 10. Leadership and social influence
6. Financial Analysts 11. Reasoning, problem-solving and ideation
7. Human Resources Specialists 12. Systems analysis and evaluation
8. General and Operations Managers 13. Technology use, monitoring and control
9. Client Information and Customer Service Workers 14. Persuasion and negotiation
10. Claims Adjusters, Examiners, and Investigators 15. Troubleshooting and user experience
3 to 6 months
18%
Responses to shifting skill needs
Share of companies surveyed
Germany 62,281,725
Education & skills worst best Jobs & work worst best
Digital skills among active population* 62.5% Labour force participation 63.3%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 64.7% Working cond. impact of gig economy* 41.6%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 1.8% Unemployment rate change
20 1 9 —
Unempl. rate among workers with basic educ. 7.5% Unemployment rate change, women
20 1 9 —
Share of youth not in empl., educ. or training 5.4% Unemployment rate change, men
20 2 0 —
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the implementation of upskilling/ reskilling programmes Encryption and cyber security 81%
37.1%
Robots, non-humanoid (industrial automation,
drones, etc.) 76%
Emerging and redundant job roles Augmented and virtual reality 73%
Role identified as being in high demand or increasingly redundant within
their organization, ordered by frequency Text, image and voice processing 71%
EMERGING
Distributed ledger technology (e.g. blockchain) 60%
1. Data Analysts and Scientists
2. AI and Machine Learning Specialists
3. Digital Transformation Specialists
4. Big Data Specialists Emerging skills
5. Internet of Things Specialists Skills identified as being in high demand within their organization, ordered
by frequency
6. Information Security Analysts
7. Project Managers 1. Active learning and learning strategies
8. Software and Applications Developers 2. Analytical thinking and innovation
9. Database and Network Professionals 3. Complex problem-solving
10. Process Automation Specialists 4. Resilience, stress tolerance and flexibility
REDUNDANT 5. Leadership and social influence
1. Data Entry Clerks 6. Critical thinking and analysis
2. Administrative and Executive Secretaries 7. Creativity, originality and initiative
3. Accounting, Bookkeeping and Payroll Clerks 8. Technology design and programming
4. Accountants and Auditors 9. Emotional intelligence
5. Business Services and Administration Managers 10. Service orientation
6. General and Operations Managers 11. Systems analysis and evaluation
7. Client Information and Customer Service Workers 12. Reasoning, problem-solving and ideation
8. Financial and Investment Advisers 13. Technology use, monitoring and control
9. Assembly and Factory Workers 14. Instruction, mentoring and teaching
10. Human Resources Specialists 15. Troubleshooting and user experience
India 588,373,756
Education & skills worst best Jobs & work worst best
Digital skills among active population* 49.2% Labour force participation 55.5%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 18
Business relevance of basic education* 37.2% Working cond. impact of gig economy* 38.5%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 9.2% Unemployment rate change
20 1 8 —
Unempl. rate among workers with basic educ. 1.6% Unemployment rate change, women
20 1 8 —
Share of youth not in empl., educ. or training 31.1% Unemployment rate change, men
20 2 0 —
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the digitalization of work processes (e.g. use of digital tools, video
Encryption and cyber security 95%
conferencing)
87.1%
Internet of things and connected devices 90%
Accelerate automation of tasks
58.1% Big data analytics 88%
Accelerate the digitalization of upskilling/ reskilling (e.g. education technology
providers) Text, image and voice processing 86%
51.6%
Accelerate the implementation of upskilling/ reskilling programmes Artificial intelligence (e.g. machine learning,
neural networks, NLP) 81%
48.4%
Robots, non-humanoid (industrial automation,
drones, etc.) 77%
Emerging and redundant job roles Distributed ledger technology (e.g. blockchain) 75%
Role identified as being in high demand or increasingly redundant within
their organization, ordered by frequency E-commerce and digital trade 73%
EMERGING
Power storage and generation 64%
1. AI and Machine Learning Specialists
2. Data Analysts and Scientists
3. Information Security Analysts
4. Internet of Things Specialists Emerging skills
5. Big Data Specialists Skills identified as being in high demand within their organization, ordered
by frequency
6. Project Managers
7. FinTech Engineers 1. Analytical thinking and innovation
8. Digital Marketing and Strategy Specialists 2. Complex problem-solving
9. Software and Applications Developers 3. Active learning and learning strategies
10. Business Development Professionals 4. Critical thinking and analysis
REDUNDANT 5. Resilience, stress tolerance and flexibility
1. Administrative and Executive Secretaries 6. Technology design and programming
2. General and Operations Managers 7. Emotional intelligence
3. Assembly and Factory Workers 8. Creativity, originality and initiative
4. Accounting, Bookkeeping and Payroll Clerks 9. Leadership and social influence
5. Data Entry Clerks 10. Reasoning, problem-solving and ideation
6. Accountants and Auditors 11. Technology use, monitoring and control
7. Architects and Surveyors 12. Service orientation
8. Human Resources Specialists 13. Troubleshooting and user experience
9. Client Information and Customer Service Workers 14. Systems analysis and evaluation
10. Business Services and Administration Managers 15. Persuasion and negotiation
Indonesia 153,009,507
Education & skills worst best Jobs & work worst best
Digital skills among active population* 60.6% Labour force participation 74%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 55.3% Working cond. impact of gig economy* 30.5%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 2.5% Unemployment rate change
20 1 9 —
Unempl. rate among workers with basic educ. 1.4% Unemployment rate change, women
20 1 9 —
Share of youth not in empl., educ. or training 22.2% Unemployment rate change, men
20 2 0 —
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the digitalization of work processes (e.g. use of digital tools, video
Encryption and cyber security 95%
conferencing)
75%
Cloud computing 95%
Accelerate automation of tasks
58.3% Big data analytics 89%
Temporarily reduce workforce
41.7% Artificial intelligence (e.g. machine learning,
neural networks, NLP) 89%
Accelerate the implementation of upskilling/ reskilling programmes
41.7% Robots, non-humanoid (industrial automation,
drones, etc.) 84%
3 to 6 months
Responses to shifting skill needs 19.2%
Share of companies surveyed
Italy 46,122,130
Education & skills worst best Jobs & work worst best
Digital skills among active population* 50.7% Labour force participation 52.9%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 51.8% Working cond. impact of gig economy* 43.3%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 5.5% Unemployment rate change -1.8%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Unempl. rate among workers with basic educ. 12.3% Unemployment rate change, women -2%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Share of youth not in empl., educ. or training 19.1% Unemployment rate change, men -1.7%
20 2 0 2 0 19 - Q 2 20 2 0 YOY C H .
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
REDUNDANT
5. Resilience, stress tolerance and flexibility
4. Business Services and Administration Managers 9. Technology use, monitoring and control
5. Assembly and Factory Workers 10. Service orientation
9. Electronics and Telecommunications Installers and Repairers 14. Quality control and safety awareness
10. Credit and Loans Officers 15. Coordination and time management
9. Service orientation
10. Quality control and safety awareness
1 to 3 months
15.9%
Responses to shifting skill needs Over 1 year
Share of companies surveyed 18.6%
Japan 98,710,000
Education & skills worst best Jobs & work worst best
Digital skills among active population* 50.8% Labour force participation 63.7%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 56.3% Working cond. impact of gig economy* 45.6%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 1.9% Unemployment rate change 0.3%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Unempl. rate among workers with basic educ. Unemployment rate change, women 0.2%
— 2 0 19 - Q 2 20 2 0 YOY C H .
Share of youth not in empl., educ. or training 3.1% Unemployment rate change, men 0.4%
20 2 0 2 0 19 - Q 2 20 2 0 YOY C H .
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the implementation of upskilling/ reskilling programmes E-commerce and digital trade 81%
38.7%
Text, image and voice processing 78%
EMERGING
Robots, humanoid 59%
1. Data Analysts and Scientists
2. AI and Machine Learning Specialists
3. Internet of Things Specialists
4. Digital Marketing and Strategy Specialists Emerging skills
5. Big Data Specialists Skills identified as being in high demand within their organization, ordered
by frequency
6. Information Security Analysts
7. FinTech Engineers 1. Analytical thinking and innovation
8. Digital Transformation Specialists 2. Active learning and learning strategies
9. Project Managers 3. Creativity, originality and initiative
10. Management and Organisation Analysts 4. Complex problem-solving
REDUNDANT 5. Technology use, monitoring and control
1. Data Entry Clerks 6. Technology design and programming
2. Accounting, Bookkeeping and Payroll Clerks 7. Resilience, stress tolerance and flexibility
3. Administrative and Executive Secretaries 8. Reasoning, problem-solving and ideation
4. Sales Representatives, Wholesale and Manufacturing, Technic… 9. Technology installation and maintenance
5. General and Operations Managers 10. Critical thinking and analysis
6. Business Services and Administration Managers 11. Emotional intelligence
7. Assembly and Factory Workers 12. Troubleshooting and user experience
8. Mechanics and Machinery Repairers 13. Systems analysis and evaluation
9. Legal Secretaries 14. Leadership and social influence
10. Statistical, Finance and Insurance Clerks 15. Service orientation
Malaysia 16,231,000
Education & skills worst best Jobs & work worst best
Digital skills among active population* 66.3% Labour force participation 77.6%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 18
Business relevance of basic education* 58.4% Working cond. impact of gig economy* 32.7%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. Unemployment rate change
— —
Unempl. rate among workers with basic educ. Unemployment rate change, women
— —
Share of youth not in empl., educ. or training 12.2% Unemployment rate change, men
20 2 0 —
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the implementation of upskilling/ reskilling programmes Robots, non-humanoid (industrial automation,
33.3% drones, etc.) 73%
Emerging and redundant job roles E-commerce and digital trade 69%
Role identified as being in high demand or increasingly redundant within
their organization, ordered by frequency Distributed ledger technology (e.g. blockchain) 56%
EMERGING
3D and 4D printing and modelling 56%
1. Data Analysts and Scientists
2. Strategic Advisors
3. Internet of Things Specialists
4. Digital Transformation Specialists Emerging skills
5. Digital Marketing and Strategy Specialists Skills identified as being in high demand within their organization, ordered
by frequency
6. Big Data Specialists
7. AI and Machine Learning Specialists 1. Emotional intelligence
8. Cyber Security Specialists 2. Creativity, originality and initiative
9. Software and Applications Developers 3. Analytical thinking and innovation
10. Renewable Energy Engineers 4. Technology design and programming
REDUNDANT 5. Complex problem-solving
1. Data Entry Clerks 6. Active learning and learning strategies
2. Administrative and Executive Secretaries 7. Troubleshooting and user experience
3. Accounting, Bookkeeping and Payroll Clerks 8. Systems analysis and evaluation
4. Human Resources Specialists 9. Leadership and social influence
5. Mining and Petroleum Extraction Workers 10. Critical thinking and analysis
6. Mechanics and Machinery Repairers 11. Technology use, monitoring and control
7. Environmental and Occupational Health and Hygiene Professio… 12. Resilience, stress tolerance and flexibility
8. Assembly and Factory Workers 13. Reasoning, problem-solving and ideation
9. Accountants and Auditors 14. Service orientation
10. Business Services and Administration Managers 15. Instruction, mentoring and teaching
Mexico 73,069,000
Education & skills worst best Jobs & work worst best
Digital skills among active population* 42.9% Labour force participation 64.6%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 42.5% Working cond. impact of gig economy* 45.6%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 3.9% Unemployment rate change 1.4%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Unempl. rate among workers with basic educ. 2.4% Unemployment rate change, women 0.7%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Share of youth not in empl., educ. or training 18.9% Unemployment rate change, men 1.9%
20 2 0 2 0 19 - Q 2 20 2 0 YOY C H .
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the digitalization of work processes (e.g. use of digital tools, video
Internet of things and connected devices 91%
conferencing)
88.9%
Cloud computing 91%
Accelerate automation of tasks
83.3% Big data analytics 91%
Accelerate the implementation of upskilling/ reskilling programmes
55.6% E-commerce and digital trade 86%
Accelerate the digitalization of upskilling/ reskilling (e.g. education technology
providers) Artificial intelligence (e.g. machine learning,
neural networks, NLP) 82%
44.4%
Encryption and cyber security 78%
Netherlands 12,236,238
Education & skills worst best Jobs & work worst best
Digital skills among active population* 77.4% Labour force participation 63.9%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 71.6% Working cond. impact of gig economy* 38.7%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 2.2% Unemployment rate change 0%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Unempl. rate among workers with basic educ. 4% Unemployment rate change, women 0%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Share of youth not in empl., educ. or training 2.8% Unemployment rate change, men 0%
20 2 0 2 0 19 - Q 2 20 2 0 YOY C H .
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate ongoing organizational transformations (e.g. restructuring) Encryption and cyber security 83%
40%
Robots, non-humanoid (industrial automation,
drones, etc.) 72%
Emerging and redundant job roles Text, image and voice processing 68%
Role identified as being in high demand or increasingly redundant within
their organization, ordered by frequency Augmented and virtual reality 65%
EMERGING
3D and 4D printing and modelling 58%
1. Data Analysts and Scientists
2. AI and Machine Learning Specialists
3. Big Data Specialists
4. Information Security Analysts Emerging skills
5. Food Scientists and Technologists Skills identified as being in high demand within their organization, ordered
by frequency
6. Organizational Development Specialists
7. Internet of Things Specialists 1. Analytical thinking and innovation
8. FinTech Engineers 2. Active learning and learning strategies
9. Digital Marketing and Strategy Specialists 3. Leadership and social influence
10. Business Development Professionals 4. Critical thinking and analysis
REDUNDANT 5. Creativity, originality and initiative
1. Data Entry Clerks 6. Complex problem-solving
2. Administrative and Executive Secretaries 7. Resilience, stress tolerance and flexibility
3. Accounting, Bookkeeping and Payroll Clerks 8. Technology use, monitoring and control
4. Assembly and Factory Workers 9. Service orientation
5. Client Information and Customer Service Workers 10. Technology design and programming
6. Business Services and Administration Managers 11. Emotional intelligence
7. Credit and Loans Officers 12. Reasoning, problem-solving and ideation
8. Bank Tellers and Related Clerks 13. Systems analysis and evaluation
9. Cashiers and Ticket Clerks 14. Troubleshooting and user experience
10. Insurance Underwriters 15. Instruction, mentoring and teaching
Pakistan 82,345,263
Education & skills worst best Jobs & work worst best
Digital skills among active population* 50.7% Labour force participation 56.3%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 18
Business relevance of basic education* 45.8% Working cond. impact of gig economy* 47.3%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 4.5% Unemployment rate change
20 1 8 —
Unempl. rate among workers with basic educ. 2.3% Unemployment rate change, women
20 1 8 —
Share of youth not in empl., educ. or training 31.1% Unemployment rate change, men
20 2 0 —
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the digitalization of work processes (e.g. use of digital tools, video
Big data analytics 91%
conferencing)
71.4%
Cloud computing 91%
Accelerate automation of tasks
57.1% Encryption and cyber security 86%
Temporarily reassign workers to different tasks
42.9% Text, image and voice processing 83%
Accelerate the implementation of upskilling/ reskilling programmes
38.1% Artificial intelligence (e.g. machine learning,
neural networks, NLP) 70%
Emerging and redundant job roles Distributed ledger technology (e.g. blockchain) 56%
Role identified as being in high demand or increasingly redundant within
their organization, ordered by frequency Augmented and virtual reality 55%
EMERGING
Poland 26,745,715
Education & skills worst best Jobs & work worst best
Digital skills among active population* 55.6% Labour force participation 59%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 40.7% Working cond. impact of gig economy* 42.1%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 1.8% Unemployment rate change
20 1 9 —
Unempl. rate among workers with basic educ. 7.9% Unemployment rate change, women
20 1 9 —
Share of youth not in empl., educ. or training 8.6% Unemployment rate change, men
20 2 0 —
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the implementation of upskilling/ reskilling programmes Robots, non-humanoid (industrial automation,
28.6% drones, etc.) 69%
Emerging and redundant job roles Text, image and voice processing 67%
Role identified as being in high demand or increasingly redundant within
their organization, ordered by frequency New materials (e.g. nanotubes, graphene) 60%
EMERGING
Augmented and virtual reality 46%
1. AI and Machine Learning Specialists
2. Big Data Specialists
3. Internet of Things Specialists
4. Database and Network Professionals Emerging skills
5. Software and Applications Developers Skills identified as being in high demand within their organization, ordered
by frequency
6. Social Media Strategist
7. Materials Engineers 1. Creativity, originality and initiative
8. Business Development Professionals 2. Active learning and learning strategies
9. Process Automation Specialists 3. Resilience, stress tolerance and flexibility
10. Robotics Engineers 4. Complex problem-solving
REDUNDANT 5. Analytical thinking and innovation
1. Data Entry Clerks 6. Technology use, monitoring and control
2. Administrative and Executive Secretaries 7. Service orientation
3. Accounting, Bookkeeping and Payroll Clerks 8. Critical thinking and analysis
4. Material-Recording and Stock-Keeping Clerks 9. Technology design and programming
5. Financial Analysts 10. Reasoning, problem-solving and ideation
6. Assembly and Factory Workers 11. Management of personnel
7. Accountants and Auditors 12. Emotional intelligence
8. Car, Van and Motorcycle Drivers 13. Management of financial, material resources
9. Business Services and Administration Managers 14. Leadership and social influence
10. Architects and Surveyors 15. Instruction, mentoring and teaching
Digital skills among active population* 66% Labour force participation 66.1%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 48% Working cond. impact of gig economy* 42.4%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 3.6% Unemployment rate change
20 1 9 —
Unempl. rate among workers with basic educ. 9.2% Unemployment rate change, women
20 1 9 —
Share of youth not in empl., educ. or training 15.9% Unemployment rate change, men
20 2 0 —
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the digitalization of work processes (e.g. use of digital tools, video
Big data analytics 76%
conferencing)
80.6%
Encryption and cyber security 73%
Accelerate automation of tasks
47.2% Text, image and voice processing 72%
Accelerate the digitalization of upskilling/ reskilling (e.g. education technology
providers) Artificial intelligence (e.g. machine learning,
neural networks, NLP) 71%
33.3%
Accelerate ongoing organizational transformations (e.g. restructuring) E-commerce and digital trade 67%
30.6%
Robots, non-humanoid (industrial automation,
drones, etc.) 66%
Emerging and redundant job roles Internet of things and connected devices 65%
Role identified as being in high demand or increasingly redundant within
their organization, ordered by frequency Augmented and virtual reality 50%
EMERGING
Power storage and generation 48%
1. AI and Machine Learning Specialists
2. Data Analysts and Scientists
3. Big Data Specialists
4. Software and Applications Developers Emerging skills
5. Sales Representatives, Wholesale and Manufacturing, Technic… Skills identified as being in high demand within their organization, ordered
by frequency
6. Process Automation Specialists
7. Management and Organisation Analysts 1. Complex problem-solving
8. Digital Marketing and Strategy Specialists 2. Analytical thinking and innovation
9. Database and Network Professionals 3. Active learning and learning strategies
10. Business Services and Administration Managers 4. Emotional intelligence
REDUNDANT 5. Resilience, stress tolerance and flexibility
1. Accounting, Bookkeeping and Payroll Clerks 6. Critical thinking and analysis
2. Administrative and Executive Secretaries 7. Technology use, monitoring and control
3. Data Entry Clerks 8. Creativity, originality and initiative
4. Sales Representatives, Wholesale and Manufacturing, Technic… 9. Troubleshooting and user experience
5. Accountants and Auditors 10. Technology design and programming
6. Lawyers 11. Service orientation
7. Mechanics and Machinery Repairers 12. Reasoning, problem-solving and ideation
8. Legal Secretaries 13. Leadership and social influence
9. Door-To-Door Sales Workers, News and Street Vendors, and R… 14. Persuasion and negotiation
10. Assembly and Factory Workers 15. Attention to detail, trustworthiness
Digital skills among active population* 73.9% Labour force participation 64.4%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 18
Business relevance of basic education* 51.1% Working cond. impact of gig economy* 30.3%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 7.6% Unemployment rate change
20 1 4 —
Unempl. rate among workers with basic educ. 0.8% Unemployment rate change, women
20 1 4 —
Share of youth not in empl., educ. or training 16.1% Unemployment rate change, men
20 2 0 —
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Strategic redundancies of staff who lack the skills Projected use of training providers
67%
to use new technologies Share of companies surveyed
Hire new temporary staff with skills relevant to
64%
new technologies
Hire freelancers with skills relevant to new
43%
technologies
49.3% Internal learning and development
Outsource some business functions to external
40%
contractors
Singapore 2,938,300
Education & skills worst best Jobs & work worst best
Digital skills among active population* 77% Labour force participation 73%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 67.6% Working cond. impact of gig economy* 32.6%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 2.6% Unemployment rate change
20 1 7 —
Unempl. rate among workers with basic educ. 3.4% Unemployment rate change, women
20 1 7 —
Share of youth not in empl., educ. or training 4.6% Unemployment rate change, men
20 2 0 —
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Temporarily reassign workers to different tasks E-commerce and digital trade 83%
50%
Distributed ledger technology (e.g. blockchain) 76%
Over 1 year
1 to 3 months 22.1%
Responses to shifting skill needs 15.8%
Share of companies surveyed
Hire new temporary staff with skills relevant to Projected use of training providers
67%
new technologies Share of companies surveyed
Hire freelancers with skills relevant to new
62%
technologies
Outsource some business functions to external
54%
contractors
42.4% Internal learning and development
Strategic redundancies of staff who lack the skills
43%
to use new technologies
Digital skills among active population* 29.9% Labour force participation 64.9%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 29.9% Working cond. impact of gig economy* 46.2%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 11.8% Unemployment rate change
20 1 9 —
Unempl. rate among workers with basic educ. 31.6% Unemployment rate change, women
20 1 9 —
Share of youth not in empl., educ. or training 32.7% Unemployment rate change, men
20 2 0 —
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Provide more opportunities to work remotely Artificial intelligence (e.g. machine learning,
62.5% neural networks, NLP) 93%
Accelerate the digitalization of work processes (e.g. use of digital tools, video
conferencing) Text, image and voice processing 87%
62.5%
Internet of things and connected devices 87%
Accelerate ongoing organizational transformations (e.g. restructuring)
37.5%
Encryption and cyber security 87%
Accelerate the digitalization of upskilling/ reskilling (e.g. education technology
providers) Big data analytics 87%
37.5%
Robots, non-humanoid (industrial automation,
drones, etc.) 86%
Emerging and redundant job roles Augmented and virtual reality 80%
Role identified as being in high demand or increasingly redundant within
their organization, ordered by frequency E-commerce and digital trade 79%
EMERGING
Distributed ledger technology (e.g. blockchain) 71%
1. Process Automation Specialists
2. Data Analysts and Scientists
3. Social Psychologists
4. Management and Organisation Analysts Emerging skills
5. Business Development Professionals Skills identified as being in high demand within their organization, ordered
by frequency
6. Big Data Specialists
7. Assembly and Factory Workers 1. Analytical thinking and innovation
8. Compliance Officers 2. Critical thinking and analysis
9. Chemists and Chemical Laboratory Scientists 3. Troubleshooting and user experience
10. AI and Machine Learning Specialists 4. Leadership and social influence
REDUNDANT 5. Complex problem-solving
1. Accounting, Bookkeeping and Payroll Clerks 6. Systems analysis and evaluation
2. Client Information and Customer Service Workers 7. Creativity, originality and initiative
3. Data Entry Clerks 8. Technology use, monitoring and control
4. Administrative and Executive Secretaries 9. Quality control and safety awareness
5. Vehicle, Window, Laundry and Other Hand Cleaning Workers 10. Persuasion and negotiation
6. Sales Representatives, Wholesale and Manufacturing, Technic… 11. Emotional intelligence
7. Insurance Underwriters 12. Technology installation and maintenance
8. Business Services and Administration Managers 13. Resilience, stress tolerance and flexibility
9. Assembly and Factory Workers 14. Reasoning, problem-solving and ideation
10. Accountants and Auditors 15. Active learning and learning strategies
Spain 35,092,188
Education & skills worst best Jobs & work worst best
Digital skills among active population* 55.2% Labour force participation 61.2%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 52.4% Working cond. impact of gig economy* 45.5%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 8% Unemployment rate change 1.1%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Unempl. rate among workers with basic educ. 18.2% Unemployment rate change, women 0.8%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Share of youth not in empl., educ. or training 12.2% Unemployment rate change, men 1.5%
20 2 0 2 0 19 - Q 2 20 2 0 YOY C H .
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate ongoing organizational transformations (e.g. restructuring) Text, image and voice processing 84%
50%
Augmented and virtual reality 77%
Switzerland 6,326,839
Education & skills worst best Jobs & work worst best
Digital skills among active population* 72% Labour force participation 68.5%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 77.9% Working cond. impact of gig economy* 40.9%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 3.2% Unemployment rate change 0.2%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Unempl. rate among workers with basic educ. 7.5% Unemployment rate change, women -0.4%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Share of youth not in empl., educ. or training 6.7% Unemployment rate change, men 0.8%
20 2 0 2 0 19 - Q 2 20 2 0 YOY C H .
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the digitalization of work processes (e.g. use of digital tools, video
Big data analytics 91%
conferencing)
90.9% Artificial intelligence (e.g. machine learning,
neural networks, NLP) 90%
Accelerate automation of tasks
72.7%
E-commerce and digital trade 90%
Accelerate the digitalization of upskilling/ reskilling (e.g. education technology
providers)
45.5% Internet of things and connected devices 86%
Accelerate the implementation of upskilling/ reskilling programmes Distributed ledger technology (e.g. blockchain) 80%
45.5%
Text, image and voice processing 77%
3 to 6 months
22.2%
Responses to shifting skill needs
Share of companies surveyed
Thailand 47,215,919
Education & skills worst best Jobs & work worst best
Digital skills among active population* 54.9% Labour force participation 72.2%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 46% Working cond. impact of gig economy* 39.7%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 0.6% Unemployment rate change 0.3%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Unempl. rate among workers with basic educ. 0.3% Unemployment rate change, women 0.2%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Share of youth not in empl., educ. or training 14.4% Unemployment rate change, men 0.3%
20 2 0 2 0 19 - Q 2 20 2 0 YOY C H .
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
EMERGING
Distributed ledger technology (e.g. blockchain) 59%
1. Data Analysts and Scientists
2. Digital Marketing and Strategy Specialists
3. Big Data Specialists
4. AI and Machine Learning Specialists Emerging skills
5. Software and Applications Developers Skills identified as being in high demand within their organization, ordered
by frequency
6. Supply Chain and Logistics Specialists
7. Strategic Advisors 1. Analytical thinking and innovation
8. Database and Network Professionals 2. Complex problem-solving
9. Commercial and Industrial Designers 3. Active learning and learning strategies
10. Business Development Professionals 4. Critical thinking and analysis
REDUNDANT 5. Creativity, originality and initiative
1. Data Entry Clerks 6. Troubleshooting and user experience
2. Administrative and Executive Secretaries 7. Leadership and social influence
3. Accounting, Bookkeeping and Payroll Clerks 8. Resilience, stress tolerance and flexibility
4. Assembly and Factory Workers 9. Technology design and programming
5. Construction Laborers 10. Technology use, monitoring and control
6. Sales Representatives, Wholesale and Manufacturing, Technic… 11. Reasoning, problem-solving and ideation
7. Human Resources Specialists 12. Technology installation and maintenance
8. Financial and Investment Advisers 13. Management of personnel
9. Client Information and Customer Service Workers 14. Attention to detail, trustworthiness
10. Business Services and Administration Managers 15. Emotional intelligence
Digital skills among active population* 71.7% Labour force participation 85.2%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 65.3% Working cond. impact of gig economy* 32.5%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 3.3% Unemployment rate change
20 1 7 —
Unempl. rate among workers with basic educ. 0.8% Unemployment rate change, women
20 1 7 —
Share of youth not in empl., educ. or training 11.4% Unemployment rate change, men
20 2 0 —
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the digitalization of work processes (e.g. use of digital tools, video
Internet of things and connected devices 84%
conferencing)
77.1%
Encryption and cyber security 84%
Accelerate automation of tasks
47.9% Cloud computing 84%
Temporarily reassign workers to different tasks
45.8% E-commerce and digital trade 81%
Accelerate the implementation of upskilling/ reskilling programmes
39.6% Text, image and voice processing 77%
Emerging and redundant job roles Power storage and generation 65%
Role identified as being in high demand or increasingly redundant within
their organization, ordered by frequency Augmented and virtual reality 57%
EMERGING
1 to 3 months
21.4%
Over 1 year
Responses to shifting skill needs 16.4%
Share of companies surveyed
Digital skills among active population* 61% Labour force participation 64.3%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 52.6% Working cond. impact of gig economy* 47.5%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 2% Unemployment rate change -0.1%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Unempl. rate among workers with basic educ. 4.6% Unemployment rate change, women -0.2%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Share of youth not in empl., educ. or training 11.1% Unemployment rate change, men 0%
20 2 0 2 0 19 - Q 2 20 2 0 YOY C H .
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the implementation of upskilling/ reskilling programmes Text, image and voice processing 88%
48.6%
E-commerce and digital trade 81%
Digital skills among active population* 69.4% Labour force participation 64.3%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 19
Business relevance of basic education* 64.5% Working cond. impact of gig economy* 24.8%
W E IG H T ED AV E R AG E 2 0 19 - 2 02 0 2 0 20
Unempl. rate among workers with adv. educ. 2.2% Unemployment rate change 8.5%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Unempl. rate among workers with basic educ. 4.3% Unemployment rate change, women 9.3%
20 1 9 2 0 19 - Q 2 20 2 0 YOY C H .
Share of youth not in empl., educ. or training 14.1% Unemployment rate change, men 7.7%
20 2 0 2 0 19 - Q 2 20 2 0 YOY C H .
* The figures presented for these indicators are rebased 0-100% progress scores, with 0 being the worst performance, and 100 being the best performance.
Accelerate the implementation of upskilling/ reskilling programmes Text, image and voice processing 82%
44.1%
E-commerce and digital trade 81%
EMERGING
Distributed ledger technology (e.g. blockchain) 65%
1. AI and Machine Learning Specialists
2. Data Analysts and Scientists
3. Big Data Specialists
4. Internet of Things Specialists Emerging skills
5. Digital Transformation Specialists Skills identified as being in high demand within their organization, ordered
by frequency
6. Process Automation Specialists
7. Project Managers 1. Analytical thinking and innovation
8. Information Security Analysts 2. Active learning and learning strategies
9. Digital Marketing and Strategy Specialists 3. Complex problem-solving
10. Business Development Professionals 4. Critical thinking and analysis
REDUNDANT 5. Resilience, stress tolerance and flexibility
1. Data Entry Clerks 6. Creativity, originality and initiative
2. Accounting, Bookkeeping and Payroll Clerks 7. Leadership and social influence
3. Administrative and Executive Secretaries 8. Reasoning, problem-solving and ideation
4. Assembly and Factory Workers 9. Emotional intelligence
5. Accountants and Auditors 10. Technology design and programming
6. Client Information and Customer Service Workers 11. Technology use, monitoring and control
7. Business Services and Administration Managers 12. Systems analysis and evaluation
8. General and Operations Managers 13. Troubleshooting and user experience
9. Mechanics and Machinery Repairers 14. Service orientation
10. Human Resources Specialists 15. Persuasion and negotiation
Industry
Profiles
Advanced Manufacturing
Expected redeployment Average skills
success rate of displaced instability among
14%
workers workforce
41.3% 43.6%
Skills gaps among organization’s leadership 54.8% Expand its use of contractors doing task-specialized work
48.4%
Inability to attract specialized talent 45.2% Reduce its current workforce due to technological integration or automation
45.2%
Shortage of investment capital 41.9% Modify the locations where the organization operates
41.9%
Insufficient understanding of opportunities 38.7% Expand its current workforce due to technological integration or automation
41.9%
Lack of flexibility of the regulatory framework 25.8%
44.1%
48.5%
Less than 1 month 3 to 6 months
Identifying and evaluating job-relevant information 26.8% 16.6%
49.9%
Administering
52.2%
62.5%
47.6% 35.8%
Biotechnology 50%
Inability to attract specialized talent 52.9% Reduce its current workforce due to technological integration or automation
41.2%
Skills gaps among organization’s leadership 47.1% Expand its current workforce
35.3%
Lack of flexibility in hiring and firing 41.2% Modify the locations where the organization operates
29.4%
Insufficient understanding of opportunities 35.3% Expand its use of contractors doing task-specialized work
29.4%
Lack of flexibility of the regulatory framework 29.4%
Administering
64.8%
Automotive
Expected redeployment Average skills
success rate of displaced instability among
workers workforce
19.1%
44.4% 55.2%
Skills gaps among organization’s leadership 44.4% Reduce its current workforce due to technological integration or automation
61.1%
Inability to attract specialized talent 44.4% Modify the composition of the value chain
50%
Shortage of investment capital 38.9% Reduce its current workforce
38.9%
Lack of flexibility of the regulatory framework 33.3% Expand its current workforce due to technological integration or automation
33.3%
Lack of interest among leadership 27.8%
Consumer
Expected redeployment Average skills
success rate of displaced instability among
16.8%
workers workforce
49.9% 43.2%
Insufficient understanding of opportunities 42.4% Reduce its current workforce due to technological integration or automation
32.4%
Inability to attract specialized talent 36.4% Modify the locations where the organization operates
32.4%
Skills gaps among organization’s leadership 33.3% Expand its current workforce due to technological integration or automation
32.4%
Shortage of investment capital 24.2% Expand its current workforce
32.4%
Lack of interest among leadership 21.2%
45.5%
50.7%
Less than 1 month 3 to 6 months
Performing complex and technical activities 24% 22.4%
53.9%
Administering
56.4%
17.5%
workers workforce
49.4% 44.1%
Inability to attract specialized talent 55% Modify the composition of the value chain
48.8%
Skills gaps among organization’s leadership 45% Expand its use of contractors doing task-specialized work
48.8%
Lack of flexibility of the regulatory framework 42.5% Expand its current workforce
46.5%
Insufficient understanding of opportunities 32.5% Expand its current workforce due to technological integration or automation
39.5%
Shortage of investment capital 30%
41.7%
Administering
Average reskilling needs
46.6%
Share of workforce within this industry
All tasks
DURATION OF RESKILLING
49%
Less than 1 month 3 to 6 months
Performing complex and technical activities 26.2% 19.3%
49.5%
Education
Expected redeployment Average skills
success rate of displaced instability among
13.9%
workers workforce
30.9% 41.3%
Shortage of investment capital 50% Modify the locations where the organization operates
52.4%
Skills gaps in the local labour market 45.5% Modify the composition of the value chain
42.9%
Skills gaps among organization’s leadership 45.5% Expand its use of contractors doing task-specialized work
42.9%
Inability to attract specialized talent 45.5% Expand its current workforce due to technological integration or automation
38.1%
Lack of flexibility of the regulatory framework 31.8%
45.2%
49.1%
Less than 1 month 3 to 6 months
Performing physical and manual work activities 25.2% 17.2%
54.5%
All tasks
6 to 12 months
59.4% 12.2%
11.8%
workers workforce
51.1% 39.4%
Accelerate the digitalization of work processes (e.g. use of digital tools, video 3. Big Data Specialists
conferencing) 4. AI and Machine Learning Specialists
100% 5. Software and Applications Developers
Accelerate automation of tasks 6. Mechanics and Machinery Repairers
69.2%
7. Internet of Things Specialists
Accelerate the digitalization of upskilling/ reskilling (e.g. education technology
providers) 8. Construction Laborers
53.8% 9. Digital Transformation Specialists
Accelerate the implementation of upskilling/ reskilling programmes 10. Robotics Engineers
46.2%
REDUNDANT
Insufficient understanding of opportunities 58.8% Modify the locations where the organization operates
47.1%
Lack of flexibility of the regulatory framework 41.2% Expand its use of contractors doing task-specialized work
41.2%
Skills gaps among organization’s leadership 35.3% Reduce its current workforce due to technological integration or automation
29.4%
Shortage of investment capital 35.3% Expand its current workforce due to technological integration or automation
29.4%
Inability to attract specialized talent 35.3%
40.4%
54.6%
Less than 1 month 6 to 12 months
Administering 24% 12.8%
56.8%
Financial Services
Expected redeployment Average skills
success rate of displaced instability among
workers workforce
20.8%
50.5% 44.1%
Inability to attract specialized talent 51.2% Reduce its current workforce due to technological integration or automation
50%
Skills gaps among organization’s leadership 48.8% Modify the locations where the organization operates
38.1%
Lack of flexibility of the regulatory framework 43.9% Expand its current workforce due to technological integration or automation
38.1%
Insufficient understanding of opportunities 41.5% Expand its use of contractors doing task-specialized work
35.7%
Shortage of investment capital 19.5%
14.8%
workers workforce
39.5% 39.1%
Skills gaps in the local labour market 50% Modify the composition of the value chain
36.8%
Insufficient understanding of opportunities 50% Modify the locations where the organization operates
31.6%
Skills gaps among organization’s leadership 40% Expand its current workforce due to technological integration or automation
31.6%
Lack of flexibility in hiring and firing 40% Expand its use of contractors doing task-specialized work
26.3%
Shortage of investment capital 25%
65.8%
Over 1 year
10.1%
44.2% 48.2%
Accelerate the digitalization of work processes (e.g. use of digital tools, video 3. Social Science Research Assistants
conferencing) 4. Internet of Things Specialists
87.5% 5. Information Security Analysts
Accelerate automation of tasks 6. Digital Marketing and Strategy Specialists
56.2%
7. Biologists and Geneticists
Accelerate the digitalization of upskilling/ reskilling (e.g. education technology
providers) 8. Specialist Medical Practitioners
37.5% 9. Digital Transformation Specialists
Temporarily reassign workers to different tasks 10. Training and Development Specialists
31.2%
REDUNDANT
Skills gaps in the local labour market 42.1% Modify the composition of the value chain
52.6%
Inability to attract specialized talent 42.1% Expand its current workforce due to technological integration or automation
47.4%
Shortage of investment capital 36.8% Expand its use of contractors doing task-specialized work
42.1%
Lack of flexibility in hiring and firing 36.8% Modify the locations where the organization operates
26.3%
Skills gaps among organization’s leadership 31.6%
Over 1 year
7.8%
Manufacturing
Expected redeployment Average skills
success rate of displaced instability among
13.2%
workers workforce
44.6% 43.6%
Inability to attract specialized talent 59.1% Reduce its current workforce due to technological integration or automation
50%
Skills gaps among organization’s leadership 54.5% Expand its use of contractors doing task-specialized work
45.5%
Insufficient understanding of opportunities 38.6% Modify the locations where the organization operates
40.9%
Shortage of investment capital 31.8% Expand its current workforce due to technological integration or automation
36.4%
Lack of flexibility of the regulatory framework 31.8%
45.2%
All tasks
Average reskilling needs
51%
Share of workforce within this industry
Performing physical and manual work activities
DURATION OF RESKILLING
51.3%
Less than 1 month 3 to 6 months
Administering 23.8% 19.4%
51.4%
19.9%
49.5% 40.6%
Inability to attract specialized talent 56.7% Reduce its current workforce due to technological integration or automation
51.7%
Insufficient understanding of opportunities 50% Expand its use of contractors doing task-specialized work
51.7%
Skills gaps among organization’s leadership 46.7% Modify the locations where the organization operates
44.8%
Lack of flexibility in hiring and firing 36.7% Expand its current workforce due to technological integration or automation
27.6%
Lack of flexibility of the regulatory framework 26.7%
40.5%
46.3%
Less than 1 month 6 to 12 months
Identifying and evaluating job-relevant information 17.5% 19.5%
50.9%
Administering
51.1%
14.2%
workers workforce
48.1% 42.6%
Shortage of investment capital 42.9% Reduce its current workforce due to technological integration or automation
42.9%
Lack of flexibility in hiring and firing 42.9% Expand its use of contractors doing task-specialized work
42.9%
Lack of flexibility of the regulatory framework 35.7% Modify the locations where the organization operates
35.7%
Insufficient understanding of opportunities 35.7% Expand its current workforce
28.6%
Inability to attract specialized talent 35.7%
47.4%
58.8%
Less than 1 month 6 to 12 months
Performing complex and technical activities 13.6% 19.9%
59.2%
All tasks
64.8% 1 to 3 months
16.1%
Identifying and evaluating job-relevant information
66.8%
Over 1 year
Communicating and interacting 28.1%
73.5%
3 to 6 months
Coordinating, developing, managing and advising 22.4%
73.9%
Professional Services
Expected redeployment Average skills
success rate of displaced instability among
11.6%
workers workforce
41.3% 48%
Skills gaps in the local labour market 41.2% Expand its use of contractors doing task-specialized work
51.9%
Insufficient understanding of opportunities 39.2% Modify the composition of the value chain
48.1%
Skills gaps among organization’s leadership 35.3% Expand its current workforce due to technological integration or automation
42.3%
Lack of flexibility of the regulatory framework 35.3% Modify the locations where the organization operates
32.7%
Inability to attract specialized talent 35.3%
37.7%
Administering
Average reskilling needs
44.4%
Share of workforce within this industry
Identifying and evaluating job-relevant information
DURATION OF RESKILLING
45%
Less than 1 month 3 to 6 months
Performing physical and manual work activities 29% 17.1%
48.3%
14.7%
workers workforce
49.1% 38.2%
Inability to attract specialized talent 58.8% Modify the composition of the value chain
58.8%
Lack of flexibility of the regulatory framework 35.3% Reduce its current workforce due to technological integration or automation
47.1%
Shortage of investment capital 29.4% Expand its use of contractors doing task-specialized work
47.1%
Skills gaps among organization’s leadership 23.5% Expand its current workforce
47.1%
Lack of flexibility in hiring and firing 23.5%
43.2%
43.8%
Less than 1 month 6 to 12 months
All tasks 26.6% 16.1%
50.2%
Appendix A:
Report Methodology
The Future of Jobs Report is based on the results The survey consists of quantitative as well as
of the 2020 edition of the Future of Jobs survey, qualitative questions seeking to capture the
a unique source of information that gathers the strategic knowledge, projections and planning of the
insights from the largest companies worldwide on respondents. The study is designed to reveal the
the changing nature of work. world’s leading employers’ estimates on how the
labour force is transforming, their projections on how
The survey asks senior executives to share the planning quickly these shifts will happen, and their efforts in
for their companies’ workforce transformation with addressing these changes.
a time horizon up to 2024. It aims to provide timely
and unique insights on the trends affecting the labour In total the survey comprises 49 questions and was
market, the rate of technological adoption among made available in four languages: English, Spanish,
firms, the shifting job landscape and associated Japanese and Russian.
changes to skills needs as well as business planning for
appropriate upskilling and reskilling.
Survey distribution
The 2020 survey dissemination took place during
the first half of 2020. The survey provides a much- The survey was distributed via an online platform
needed compass for business, governments, civil through three dissemination networks. The primary
society Organizations as well as the public at large distribution route was to the World Economic Forum
on the short-and medium-term transformations to partners and constituents in collaboration with
the labour market. the World Economic Forum Regional and Industry
teams. The survey was further disseminated through
a network of Partner Institutes—local partner
Survey design organizations that administered the survey in their
respective economies. Further dissemination through
The survey builds on the methodology from the partner organizations enabled the strengthening of
2016 and 2018 survey editions. Following survey regional representation by extending the sample to
best practice and in consultation with the World local companies. As a third dissemination channel,
Economic Forum Global Future Council on the new the New Economy and Society team shared the
Education and Work Agenda, several questions were survey with the collaborators from the countries in
refined and new questions were added. The three which the Closing the Skills and Innovation Gap
core concepts that are key to the construction of Accelerators are present (South Africa, UAE, Bahrain,
the Future of Jobs Survey remain unchanged in this India, Pakistan). The Accelerator project brings about
edition. That is, the nature of work is broken down tangible change by building a national public-private
into three interrelated subcategories: job roles, tasks collaboration platform to increase employability of
and skills. Task are defined as the actions necessary the current workforce and increase work-readiness
to turn a set of inputs into valuable outputs. A and critical skills among the future workforce.
collection of tasks forms the content of job roles,
while skills are capabilities needed to be able to For the full overview of the survey partners, please
perform the tasks well. refer to the Survey Partners and Acknowledgements
sections at the end of the report.
The survey is structured into four parts. The first part
includes questions on the expected transformations The network of survey partners responsible for the
to the workforce, including the major trends that are dissemination followed clear sampling guidelines,
affecting the labour market and the technologies which specified the level of the respondent, the
that are being adopted. The second part focuses on target companies and the sample composition. As
jobs, skills and tasks and how these are expected to the questions in the survey require deep insight into
evolve over a four-year period. The third part collects an organization’s current strategy as well as talent-
information on training programmes and employee related aspects of operationalizing this strategy,
reskilling needs and efforts. Finally, to understand the target respondents were senior executives in
the shorter-term impacts of the global pandemic, charge of human resources, strategy and innovation
a fourth section was added on the effects of the departments.
COVID-19 on the workforce.
Automotive Automotive
Consumer Accomodation and Food Services Retail, Consumer Goods and Lifestyle
Government and Public Sector Government and Public Sector Public Administration / Government Administration
Infra, Urban Dev. & Real Estate Real Estate, Rental and Leasing
Manufacturing Aerospace
Military -
Mining and Metals Mining and Metals Mining, Quarrying, and Oil and Gas Extraction
Oil and Gas Oil and Gas Mining, Quarrying, and Oil and Gas Extraction
Oil and Gas Oil Field Services and Equipment Mining, Quarrying, and Oil and Gas Extraction
Source
World Economic Forum.
Understanding the implications of new information for both current and future
Active learning and learning strategies Active learning
problem-solving and decision-making.
Job requires analyzing information and using logic to address work-related issues
Analytical thinking and innovation Analytical thinking
and problems.
Job requires creativity and alternative thinking to develop new ideas for and
Innovation
answers to work-related problems.
Attention to detail, trustworthiness Attention to detail Job requires being careful about detail and thorough in completing work tasks.
Dependability Job requires being reliable, responsible and dependable, and fulfilling obligations.
Coordination and time management Time management Managing one's own time and the time of others.
Creativity, originality and initiative Initiative Job requires a willingness to take on responsibilities and challenges.
Using logic and reasoning to identify the strengths and weaknesses of alternative
Critical thinking and analysis Critical thinking
solutions, conclusions or approaches to problems.
Job requires being sensitive to others' needs and feelings and being understanding
Emotional intelligence Concern for others
and helpful on the job.
Job requires being pleasant with others on the job and displaying a good-natured,
Cooperation
cooperative attitude.
Job requires preferring to work with others rather than alone, and being personally
Social orientation
connected with others on the job.
Social perceptiveness Being aware of others' reactions and understanding why they react as they do.
Leadership and social influence Leadership Job requires a willingness to lead, take charge and offer opinions and direction.
Management of financial, material Determining how money will be spent to get the work done, and accounting for
Management of financial resources
resources these expenditures.
Obtaining and seeing to the appropriate use of equipment, facilities and materials
Management of material resources
needed to do certain work.
Motivating, developing and directing people as they work, identifying the best
Management of personnel Management of personnel resources
people for the job.
Manual dexterity, endurance and The ability to exert oneself physically over long periods without getting out of
Endurance
precision breath.
Flexibility, balance and coordination Abilities related to the control of gross body movements.
Control movement abilities Abilities related to the control and manipulation of objects in time and space
Reaction time and speed abilities Abilities related to speed of manipulation of objects.
Perceptual abilities Abilities related to the acquisition and organization of visual information.
Spatial abilities Abilities related to the manipulation and organization of spatial information
Persuasion and negotiation Negotiation Bringing others together and trying to reconcile differences.
Giving full attention to what other people are saying, taking time to understand
Reading, writing, math and active listening Active listening the points being made, asking questions as appropriate, and not interrupting at
inappropriate times.
Reading comprehension Understanding written sentences and paragraphs in work related documents.
Writing Communicating effectively in writing as appropriate for the needs of the audience.
Job requires accepting criticism and dealing calmly and effectively with high stress
Stress tolerance
situations.
Service orientation Service orientation Actively looking for ways to help people.
Considering the relative costs and benefits of potential actions to choose the most
Systems analysis and evaluation Judgment and decision-making
appropriate one.
Determining how a system should work and how changes in conditions, operations
Systems analysis
and the environment will affect outcomes.
Technology design and programming Programming Writing computer programmes for various purposes.
Technology design Generating or adapting equipment and technology to serve user needs.
Technology use, monitoring and control Equipment selection Determining the kind of tools and equipment needed to do a job.
Troubleshooting and user experience Troubleshooting Determining causes of operating errors and deciding what to do about them.
Visual, auditory and speech abilities Auditory and speech abilities Abilities related to auditory and oral input.
Source
World Economic Forum.
Analyticial thinking and Capacity to solve novel, ill-defined problems in complex, real-world
originality 3 settings.
Complex problem-solving Abilities that influence the acquisition and application of knowledge
in problem-solving.
Systems analysis and Capacities used to understand, monitor and improve socio-technical
evaluation systems.
Critical thinking and analysis Using logic and reasoning to identify the strengths and weaknesses
of alternative solutions, conclusions or approaches to problems as
well as assessing performance of yourself, other individuals or orga-
nizations to make improvements or take corrective action.
Digital Technology use and Creating and maintaining Capacity to use programming to design machines or technological
development technology 5 systems which fit user needs. In addition, understanding how others
use tools, determine the cause of operating errors and how to fix
them.
Skills include:
- Artificial Intelligence
- Computer Hardware & Networking Systems
- Cybersecurity and Application Security
- Data Science and Analysis
- Human Computer Interaction
- Scrum/Agile Product Development
- Software & Programming
- Technical Support and Maintenance
- Web Development
Using and operating Capacity to select the right tools needed to perform tasks, use
technology 6 those tools well and set up and operate technology.
Skills include:
- Accounting and Finance Software
- Construction Management Software
- Clininal Information Systems
- Digital Design
- Digital Literacy
- Digital Marketing
- Geographic Information Systems
- Human Resourse Management Systems
- Productivity Software
- Machining & Manufacturing Technologies
- Scientific Computing
Leadership and social Having an impact on others in the organization, and displaying
influence energy and leadership.
Learning strategies, instruc- Capacities for teaching others how to do something, including
tion, mentoring and teaching4 selecting and using training/instructional methods and procedures
appropriate for the situation when learning or teaching new things.
Active learning1 Understanding the implications of new information for both current
and future problem-solving and decision-making.
Attention to detail, trustwor- Dependability, commitment to doing the job correctly and carefully,
thiness being trustworthy, accountable and paying attentive to details.
Resilience, stress tolerance Maturity, poise, flexibility and restraint to cope with pressure, stress,
and flexibility criticism, setbacks, personal and work-related problems.
Social justice Awareness of the wider world, of history and of social justice issues
that result from historical inequalities. Playing an active role in the
global and local community and the appliation of civic values.
Abilites: The range of physical, Physical abilities Physical abilities Manual dexterity, endurance Abilities related to the capacity to manipulate and control objects,
psychomotor, cognitive and sensory and precision strength, endurance, flexibility, balance and coordination.
abilities that are required to perform Memory, verbal, auditory and Abilities that influence the acquisition and application of knowledge
a job role. spatial abilities in problem-solving.
Visual, auditory and speech Abilities that influence visual, auditory and speech perception.
abilities
Cognitive: Core literacies Core literacies Reading, writing, math, active Core literacies needed to work with and acquire more specific skills
Commonly cover conceptual listening in a variety of different domains.
thinking and the ability to process
thoughts and perform various mental
activities, and are most closely
associated with learning, reasoning
and problem-solving.
Source Note
World Economic Forum. 1 listed as "Active learning and learning strategies" throughout the report;
2 listed as "Creativity, originality and initiative" throughout the report; 3
listed as "Analytical thinking and innovation" throughout the report; 4 listed
as "Instruction, mentoring and teaching" throughout the report; 5 listed as
"Technology design and programming" throughout the report"; 6 listed as
"Technology use, monitoring and control" throughout the report.
Project team
Saadia Zahidi
Member of Managing Board
Vesselina Ratcheva
Insight Lead, Benchmarking Practice
Guillaume Hingel
Insight Lead, Benchmarking Practice
Sophie Brown
Project Specialist
Acknowledgements
We are extremely grateful to our colleagues on the Platform team for their collaboration, help
and efforts, and in particular to Ida Jeng Christensen, Eoin Ó Cathasaigh, Genesis Elhussein, Till
Leopold and SungAh Lee. A special thank you to Michael Fisher for his excellent copyediting work
and to Accurat for their outstanding graphic designing and layout of the report.
Collaborations
The Platform for the New Economy and Society aims to empower decision-making among leaders
in business and policy by providing fresh, actionable insight through collaboration with leading
experts and data-holding companies as part of its New Metrics Co-Lab. We would like to thank
the following contributors for their collaboration and support to this report:
Coursera
Emily Glassberg Sands, Head of Data Science
Vinod Bakthavachalam, Senior Data Scientist
Eric Karsten, Data Scientist
FutureFit AI
Hamoon Ekhtiari, CEO
Terralynn Forsyth, Head of Product
Linkedin
Rachel Bowley, Senior Data Scientist, Economic Graph
Murat Erer, Senior Insights Analyst
Mariano Mamertino, Senior Economist, Economic Graph Team
Kristin Keveloh, Manager, Economic Graph Team
Sein O Muineachain, Manager, Economic Graph Research and Insights (EMEA)
The World Economic Forum would like to thank the Partners of the Platform
for Shaping the New Economy and Society for their guidance and support
to this report.
Platform Partners
In addition, to our partners, the Platform for Shaping the Future of the New
Economy and Society would like to thank the members of the Stewardship
Board for their strategic guidance.
A. Michael Spence, William R. Berkley Professor Adam Grant, Saul P. Steinberg Professor of
in Economics and Business, NYU Stern School of Management and Psychology, The Wharton School,
Business University of Pennsylvania
Achim Steiner, Administrator, United Nations Ahmad bin Abdullah Humaid Belhoul Al Falasi,
Development Programme (UNDP) Minister of State for Entrepreneurship and SMEs,
United Arab Emirates Government
Alicia Bárcena Ibarra, Executive Secretary, United Lynda Gratton, Professor of Management Practice,
Nations Economic Commission for Latin America London Business School
and the Caribbean (ECLAC)
Magdalena Andersson, Minister of Finance, Ministry
Allen Blue, Co-Founder and Vice-President, of Finance of Sweden
Products, LinkedIn Corporation
Mariana Mazzucato, Professor of Economics of
Andrew McAfee, Co-Director and Co-Founder, MIT Innovation and Public Value; Founder and Director,
Initiative on the Digital Economy; Principal Research Institute for Innovation and Public Purpose,
Scientist, Massachusetts Institute of Technology University College London (UCL)
(MIT)
Martine Ferland, Chief Executive Officer, Mercer
Asheesh Advani, President and Chief Executive Limited
Officer, JA Worldwide
Minouche Shafik, Director, London School of
Badr Jafar, Chief Executive Officer, Crescent Economics and Political Science
Enterprises
Peter Hummelgaard, Minister for Employment,
Brian Gallagher, President and Chief Executive Ministry of Employment of Denmark
Officer, United Way Worldwide
Peter T. Grauer, Chairman, Bloomberg LP
Bruno Le Maire, Minister of Economy and Finance,
Ministry of the Economy, Finance and the Recovery Phumzile Mlambo-Ngcuka, Undersecretary-General
of France and Executive Director, United Nations Entity for
Gender Equality and the Empowerment of Women
Erik Brynjolfsson, Schussel Family Professor; (UN WOMEN)
Director, MIT Initiative on the Digital Economy, MIT -
Sloan School of Management Rania Al-Mashat, Minister of International
Cooperation, Ministry of International Cooperation of
Frank Appel, Chief Executive Officer, Deutsche Post Egypt
DHL Group
Ricardo Hausmann, Founder and Director, Growth
Guy Ryder, Director-General, International Labour Lab, Harvard University
Organization (ILO)
Rich Lesser, Global Chief Executive Officer, Boston
Henrietta H. Fore, Executive Director, United Nations Consulting Group
Children's Fund (UNICEF)
Robert E. Moritz, Global Chairman, PwC
Jo Ann Jenkins, Chief Executive Officer, AARP
Salil S. Parekh, Chief Executive Officer and Managing
John Goodwin, Chief Executive Officer, The LEGO Director, Infosys Limited
Foundation
Sharan Burrow, General Secretary, International
Jonas Prising, Chairman and Chief Executive Officer, Trade Union Confederation (ITUC)
ManpowerGroup
Sharon Thorne, Global Chair, Deloitte
Josephine Teo, Minister for Manpower and Second
Minister for Home Affairs, Ministry of Manpower of Stanley M. Bergman, Chairman of the Board and
Singapore Chief Executive Officer, Henry Schein Inc.
Khalid Al-Falih, Minister of Investment, Ministry of Tariq Al Gurg, Chief Executive Officer, Dubai Cares
Investment of Saudi Arabia
Xavier Sala-i-Martin, Professor, Department of
Laura D'Andrea Tyson, Distinguished Professor of Economics, Columbia University
the Graduate School, Haas School of Business,
University of California, Berkeley
To learn more about the Platform for Shaping the Future of the New Economy
and Society, please visit: https://www.weforum.org/platforms/shaping-the-future-
of-the-new-economy-and-society
To get involved, please contact cnes@weforum.org
Bahrain Switzerland
Bahrain Economic Development Board University of St. Gallen, Competence Centre for
Diversity and Inclusion (CCDI-HSG)
India
LeadCap Knowledge Solutions Pvt. Ltd (LeadCap South Africa
Ventures) Business Leadership South Africa
National Skill Development Corporation (NSDC) Business Unity South Africa
Trade & Industrial Policy Strategies (TIPS)
Indonesia
KADIN Indonesia Thailand
Chulalongkorn Business School, Chulalongkorn
Japan University
Waseda University Thailand Management Association (TMA)
Pakistan
Mishal Pakistan
Punjab Skills Development Fund
The World Economic Forum would like to thank Global Future Council on the New
Education and Work Agenda for their thought leadership and strategic guidance on
the Education 4.0 framework and the Schools of the Future campaign.
Sarah Kirby, Group Head, Organization Design and Human Resource Strategy, Zurich
Insurance Group, Switzerland (Council Co-Chair)
Erik Brynjolfsson, Schussel Family Professor; Director, MIT Initiative on the Digital
Economy, MIT - Sloan School of Management, USA
Jawad Khan, Chief Executive Officer, Punjab Skills Development Fund, Pakistan
Frida Polli, Co-Founder and Chief Executive Officer, Pymetrics Inc., USA
Dan Restuccia, Chief Analytics and Product Officer, Burning Glass Technologies,
USA
Bettina Schaller, Head, Group Public Affairs, The Adecco Group, Switzerland
Ray Tong Zhilei, Chairman and Chief Executive Officer, ChineseAll Digital
Publishing Group Co. Ltd, China
contact@weforum.org
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