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IVETA Conference

Global drivers of change, policy priorities and the role of anticipating skill needs
by Olga Strietska-Ilina on 20 November 2013

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Transcript of IVETA Conference

Institutions
Data
Implications of change:
skills mismatch
Skill bottlenecks are already
ILO Approach to Anticipating Skill Needs
Global Drivers of Change
Technology and Innovation
Demographic Change
Climate Change and Transition to the Green Economy
The change has always been out there and has always been
a

challenge
But technology and innovation
drive the change
ever faster
We live in an ever-changing world
Increased competition not only for
new markets
but also: the global competition
for

talent !
Projected gap between labour supply and demand in selected countries by 2020
The developed world is ageing fast: labour shortages are expected
Workforce in most developing countries is still young
Solutions:
Shortage predicted (McKinsey Global Institute 2012):
What drives skills change here:
Transition to the green economy:
creative destruction of jobs
34% of employers report recruitment difficulties
due to lack of skills needed for jobs
The pool of available labour:
200 million
of the unemployed
Source: Manpowergroup
A mismatch between skills offered and
skills wanted is a major challenge
Consequences of skills mismatch:
unemployment
3500 B.C.
2008
1040 B.C.
(cc) image by jantik on Flickr
1896
1981
Predict the exact number of bricklayers, nurses or
engineers demanded on the labour market
Translate data into soft indicators, trends, scenarios and strategies
Identify relevant data and tools
Anticipating skill needs
Source: UN, ILO
skills for exporting industries, productivity and competitiveness
Source: WEF 2010
The global workforce is growing
75 million young people worldwide are already unemployed
Environmental degradation,
policy and regulation,
new clean technologies,
new types of market opportunities
may result in low productivity, low wage, low skill demand equilibrium – a vicious circle
concentrate in localities
impact on production and trade patterns
high staff turnover
low productivity
sub-optimal work organization
lower wages
suboptimal technologies
firms recruit at suboptimal skill levels
wage differentiation and growing inequality, inflation
18th century steam engine
Does
Does not
These predictions should be left to other professions
a major barrier
Higher global mobility of labour expected
Provide young people with the relevant skills to attract investments and create jobs
Skills for higher productivity and employment activation measures (e.g. LLL, technology skills for aging workers etc.)
in developing countries:
45 million
workers with
secondary education in manufacturing and services
globally: about
40 million
of college educated workers
Integrate skills into national and sector development strategies
Include skills in responses to global drivers of change
Globalization of Markets
Educational Attainment
More and better skills may lead to economic growth
The value of world trade in information and communication technology (ICT) goods increased from US$1,000 billion in 1996 to over US$3,500 billion in 2007
Skills Mismatch
A Dynamic Development Process
Match supply to current demand for skills and prepare for future jobs
Analyze and discuss which institutional arrangements are conducive to matching demand
and supply of skills
Key elements of skills anticipation
Progress in educational attainment: increase in average years of schooling among 15-24 year olds (UNESCO)
In
developing countries
: from 3.5 to over 8.5 years (between 1950 and 2010) but girls achieve only 84% of boys attainment
In
developed countries
: from 7 to 10 years during 1 decade
Skills
Jobs
Olga Strietska-Ilina
ILO, Geneva
Skills and Employability
Department
www.ilo.org/skills
Do we forecast jobs or skills, how to align them?
Do we forecast local/national or global market needs?
What is the silver bullet in skills anticipation?
How to kill the fast running rabbit?
More talents compete for (less) jobs
Non-routine skills become a critical source of competitive advantage
Demand for higher:
Jobs and talent become mobile with businesses
Flatter structures
Virtual work
flexibility
adaptability and
mobility,
team work,
initiative,
leadership,
management skills and
interpersonal/ intercultural communication
Labour market imperfections
Public goods
Market externalities
Limited geographical mobility
Behavioral factors: Irrational decisions of labour market actors (careers, wages)
Room for public policy
Why does not market solve the skills supply/demand mismatch?
Imperfect information on jobs and skills availability
Time lag between skill supply and labour market demand
knowledge of foreign languages
ICT skills
environmental awareness
retraining needs
changing occupations
emerging occupations
Skills implications:
Ability to innovate, adopt and maintain technologies
STEM skills (participation of women!)
Skills and policy implications:
portable skills
Skills and policy implications:
600 million new jobs needed in 2020 in order to keep current employment rates (majority of them in Asia and Sub-Saharan Africa) (WDR 2013)
“When the winds of change blow, some seek shelter, others build windmills” – an old Chinese Proverb
More than 70 % of citizens with tertiary education in Haiti, Jamaica, Trinidad and Tobago live abroad
20-27 % of all physicians in the US, Australia, and Canada are foreign-trained
What will be your strategy?
to ensure there is enough skilled workforce to attract investments, help businesses to be competitive and to move up in the value chain of global markets
To prepare our students for the jobs to come, and
to provide workers with skills, which could help them to adjust to change, and
a career counsellor
a policy maker
a worker
an employer
or just a citizen
an expert
a trainer
Whether you are:
The system has to be problem-solving driven
What is behind the need: policy or information function, or both?
Policy clarity: demand-driven or skills-driven?
The system has to be user oriented
The system has to be stakeholder-owned
The system has to be coordinated
Competent institutions and expert networks
Good data coverage and complementarity of information
Coverage of all relevant levels (macro, meso, micro)
When one driver / one policy changes it all
Checklist on skill needs assessment for broader national and sectoral employment policy analysis
Joint work with ETF and Cedefop on a family of guides:
Macroeconomic level skill needs forecasting and foresighting
Skills anticipation and matching by intermediary agencies
The use of LMI for skills anticipation and matching
Skills for Green Jobs
Renewables and Green Building
Skills for Trade and Economic Diversification (STED)
to retain and attract talent
who gets the skills = gets green jobs (women, youth, etc.)
Good-quality education is a foundation
Methods
PES data on vacancies and job seekers
LMI Building Blocks
LFS
Education
and training statistics
Coordination at national level
PPP's at all levels
Sectoral bodies
Guide on generic sectoral approaches in skills anticipation
When different drivers matter generic tools are more appropriate
Good practices in skills anticipation
Wages statistics
HRD Recommendation (no. 195), 2004
Conclusions on Skills for Improved Productivity, Employment, Growth and Development - adopted at ILC 2008
G20 Training Strategy, 2010
ILO Global Policy Framework Related to Skills
Institutional and analytical capacity
low or no ROI in training
Examples of skills mismatch measurement

Normative method
: levels of educational attainment attributed to occupations (e.g. ISCO) (vertical mismatch).
LFS.
Statistical method
: actual distribution of educational attainment or field per occupation (vertical and horizontal mismatch).
LFS.
Self-declared method
: workers’ views on matching between their education and job (vertical and horizontal mismatch).
Tracer studies, employees’ surveys
.
Share of graduates in science and technical fields (%)
Source: Eurostat - UOE statistics
LMI building blocks
(enrollments, graduation,
participation)
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