Skills have become the global currency of 21st century economies. Without sufficient investment in skills people languish on the margins of society, technological progress does not translate into productivity growth, and countries can no longer compete in an increasingly knowledge-based global economy. And, at a time when growing economic and social inequalities are a major challenge, effective skills policies must be part of any response to address this challenge. But this ‘currency’ depreciates as skill requirements of labour markets evolve and individuals lose the skills they do not use. For skills to retain their value, they must be continuously maintained and upgraded throughout life so that people can collaborate, compete and connect in ways that drive economies forward. With its skill assessment programmes PISA and PIAAC, the OECD has developed global metrics not only to assess the quality and quantity of the skills available in the population, but also to help policy-makers determine and anticipate the skills required in the labour market; develop and deploy those skills in the most effective and equitable ways; and establish sustainable approaches to who should pay for what, when and how. By Andreas Schleicher, OECD Deputy Director and Special Advisor on Education Policy to the Secretary-General, Directorate for Education and Skills.

1. Better skills, better jobs,
better lives
OECD EMPLOYER
BRAND
Playbook
Andreas Schleicher
5 February 2014
1

2. Problem solving skills
in a digital environment
Young adults (16-24 year-olds)
All adults (16-65 year-olds)
Sweden
Finland
Netherlands
Norway
Denmark
Australia
Canada
Germany
England/N. Ireland (UK)
Japan
Flanders (Belgium)
Average
Czech Republic
Austria
United States
Korea
Estonia
Slovak Republic
Ireland
Poland
%
100
Basic digital
problem-solving
skills
Advanced
digital problemsolving skills
80
60
40
20
0
20
40
60
80
100
2

3. Evolution of employment in occupational groups
defined by problem-solving skills
%
25
20
Medium-low
level of
problem-solving
15
10
5
0
Low level of
problem-solving
-5
-10
-15
-20
Medium-high
level of
problem-solving
3

4. 4
PISA in brief
• Over half a million students…
– representing 28 million 15-year-olds in 65 countries/economies
… took an internationally agreed 2-hour test…
– Goes beyond testing whether students can
reproduce what they were taught…
… to assess students’ capacity to extrapolate from what they know
and creatively apply their knowledge in novel situations
– Mathematics, reading, science, problem-solving, financial literacy
– Total of 390 minutes of assessment material
… and responded to questions on…
– their personal background, their schools
and their engagement with learning and school
• Parents, principals and system leaders provided data on…
– school policies, practices, resources and institutional factors that
help explain performance differences .

5. High mathematics performance
Mean score … Shanghai-China performs above this line (613)
580
Singapore
570
560
Chinese Taipei
Korea
550
540
Macao-China
Japan Liechtenstein
Switzerland
530
520
510
500
490
480
470
Hong Kong-China
Poland
Belgium
Germany
Austria
Slovenia
New Zealand Denmark
France
Czech Republic
Latvia
Luxembourg
Portugal Spain
Slovak Republic United States
Connecticut
Hungary
Massachusetts
Florida
Netherlands
Estonia Finland
Canada
Viet Nam
Australia
Ireland
United Kingdom
Iceland
Norway
Italy
Russian Fed.
Lithuania Sweden
Croatia
Israel
460
450
Greece
Serbia Turkey
Romania
440
430
420
410
Chile
… 12 countries perform below this line
Bulgaria
U.A.E.
Kazakhstan
Thailand
Malaysia
Mexico
Low mathematics performance
Average performance
of 15-year-olds in
Mathematics
Fig I.2.13

6. High mathematics performance
Singapore
Chinese Taipei
Hong Kong-China
Average performance
of 15-year-olds in
mathematics
Korea
Macao-China
Japan Liechtenstein
Switzerland
Strong socio-economic
impact on student
performance
Poland
Belgium
Germany
Austria
Slovenia
New Zealand Denmark
France
Czech Republic
Latvia
Luxembourg
Portugal Spain
Slovak Republic United States
Hungary
Netherlands
Estonia Finland
Canada
Viet Nam
Australia
Ireland
United Kingdom
Iceland
Norway
Italy
Russian Fed.
Lithuania Sweden
Croatia
Israel
Greece
Serbia Turkey
Romania
Chile
Bulgaria
U.A.E.
Kazakhstan
Thailand
Malaysia
Mexico
Low mathematics performance
Socially equitable
distribution of learning
opportunities

7. 2012
Shanghai-China
Singapore
Singapore
Chinese Taipei
Chinese Taipei
Hong Kong-China
Hong Kong-China
Korea
Macao-China
Japan
Switzerland
Switzerland
Liechtenstein
Korea
Japan
Liechtenstein
Estonia
Macao-China
Netherlands
Netherlands Estonia
Poland
Poland
Canada
Canada
Belgium
Belgium
Finland
FinlandViet Nam
Viet Nam
Germany
Germany
Strong socio-economic
Socially equitable
Austria
Denmark Austria
DenmarkAustralia Australia
New ZealandNew Zealand
impact on student
Slovenia Ireland
Ireland
Slovenia
distribution of learning
Iceland
Iceland
Czech Rep.
Czech Rep.
performance 22France 18
opportunities
France UK
26
24
20
1816
16 14UK14 12 12 10 10
0
24
22
20
8 8
6 6
44
22
0
Latvia
Latvia
Luxembourg
Norway
Luxembourg
Norway
Portugal
Portugal
Italy
Italy
Russian Fed. Russian Fed.
US
US
Spain
Lithuania
Spain
Lithuania
Sweden
Sweden
Slovak Rep.
Slovak Rep.Hungary
Hungary
Croatia
Croatia
Israel Israel
Bulgaria
Chile
Greece
Greece
Serbia
Serbia
Turkey
Turkey
Romania
Romania
Bulgaria
United Arab Emirates United Arab Emirates
Kazakhstan
Thailand
Chile Malaysia
Malaysia
Mexico
Kazakhstan
Thailand
Mexico

8. Australia
Austria
Belgium
Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel socio-economic
Strong
Italy
impact on student
Japan
performance
Korea
Luxembourg
Mexico
Slovak Rep.
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain
Sweden
Switzerland
Turkey
UK
US
2012
Korea
Japan
Switzerland
Netherlands
Poland
Belgium
Germany
Estonia
Canada
Finland
Socially equitable
Austria
Australia
New Zealand Denmark
Ireland
Slovenia
distribution of learning
Iceland
Czech Rep.
opportunities
France
UK
Luxembourg
Norway
Portugal
Italy
US
Spain
Sweden
Hungary
Israel
Greece
Turkey
Chile
Mexico

9. Australia
Austria
Belgium
Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Slovak Rep.
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain
Sweden
Switzerland
Turkey
UK
US
Korea
Japan
Switzerland
Netherlands
Poland
Belgium
Germany
Estonia
Canada
Finland
Austria
Australia
New Zealand Denmark
Ireland
Slovenia
Iceland
Czech Rep.
France
UK
Luxembourg
Norway
Portugal
Italy
US
Spain
Sweden
Hungary
Israel
Greece
Turkey
Chile
Mexico

10. Contribution of various factors to upper secondary teacher
compensation costs, per student as a percentage of GDP per capita (2004)
Salary as % of GDP/capita
Instruction time
1/teaching time
1/class size
Difference with OECD average
15
Percentage points
10
5
0
-5
Slovak Republic
Poland
United States
Sweden
Finland
Mexico
Ireland
Iceland
Norway
Hungary
Czech Republic
Austria
Italy
Denmark
Netherlands
France
New Zealand
United Kingdom
Australia
Japan
Greece
Germany
Luxembourg
Korea
Belgium
Switzerland
Spain
Portugal
-10

11. Australia
Austria
Belgium
Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Slovak Rep.
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain
Sweden
Switzerland
Turkey
UK
US
Korea
Japan
Switzerland
Netherlands
Poland
Belgium
Germany
Estonia
Canada
Finland
Austria
Australia
New Zealand Denmark
Ireland
Slovenia
Iceland
Czech Rep.
France
UK
Luxembourg
Norway
Portugal
Italy
US
Spain
Sweden
Hungary
Israel
Greece
Turkey
Chile
Mexico

12. Australia
Austria
Belgium
Canada
Chile
Czech Rep.
Denmark
Estonia
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Israel
Italy
Japan
Korea
Luxembourg
Mexico
Slovak Rep.
Netherlands
New Zealand
Norway
Poland
Portugal
Slovak Rep.
Slovenia
Spain
Sweden
Switzerland
Turkey
UK
US
Shanghai
2003 - 2012
Singapore
Singapore
Korea
Japan
Switzerland
Netherlands
Poland
Belgium
Germany
Estonia
Canada
Finland
Austria
Australia
New Zealand Denmark
Ireland
Slovenia
Iceland
Czech Rep.
France
UK
Luxembourg
Norway
Portugal
Italy
US
Spain
Sweden
Hungary
Israel
Greece
Turkey
Chile
Mexico

13. 13
The American dream of social mobility
In some countries it is close to a reality

14. 10
Shanghai-China
Hong Kong-China
Macao-China
Viet Nam
Singapore
Korea
Chinese Taipei
Japan
Liechtenstein
Switzerland
Estonia
Netherlands
Poland
Canada
Finland
Belgium
Portugal
Germany
Turkey
OECD average
Italy
Spain
Latvia
Ireland
Australia
Thailand
Austria
Luxembourg
Czech Republic
Slovenia
United Kingdom
Lithuania
France
Norway
Iceland
New Zealand
Russian Fed.
United States
Croatia
Denmark
Sweden
Hungary
Slovak Republic
Mexico
Serbia
Greece
Israel
Tunisia
Romania
Malaysia
Indonesia
Bulgaria
Kazakhstan
Uruguay
Brazil
Costa Rica
Chile
Colombia
Montenegro
U.A.E.
Argentina
Jordan
Peru
Qatar
14
Percentage of resilient students
% 40
30
More than 40
% resilient
Fig II.2.4
80
70
60
50
Socio-economically disadvantaged students not
only score lower in mathematics, they also report
lower levels of engagement, drive, motivation and
self-beliefs. Resilient students break this link and
share many characteristics of advantaged highachievers.
20
Between 20%-40% of resilient students
Less than 20%
0

15. High impact on outcomes
15
15
Quick wins
Lessons from high performers
Must haves
Catching up with the top-performers
Low feasibility
High feasibility
Money pits
Low hanging fruits
Low impact on outcomes

16. High impact on outcomes
16
16
Quick wins
Must haves
Lessons from high performers
Commitment to universal achievement
Capacity
at point of delivery
Resources
where they yield most
Gateways, instructional
systems
Coherence
A learning system
Low feasibility
High feasibility
Incentive structures and
accountability
Money pits
Low hanging fruits
Low impact on outcomes

17. Find out more about PISA at www.pisa.oecd.org
• All national and international publications
• The complete micro-level database
Thank you !
Email: Andreas.Schleicher@OECD.org
Twitter: SchleicherEDU
and remember:
Without data, you are just another person with an opinion