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Report Home

  • Data Explorer
  • Shareable Infographics
  • User’s Guide
  • [ — Divider — ]
  • Preface
  • Key Findings
  • Global Human Capital Report 2017
    • Underlying concepts
    • Subindexes
    • Index Construction
    • Results
    • Results by Region
      • East Asia and the Pacific
      • Eastern Europe and Central Asia
      • Latin America and the Caribbean
      • Middle East and North Africa
      • North America
      • South Asia
      • Sub-Saharan Africa
      • Western Europe
      • Box 1: G20
      • Box 2: European Union
    • Results by Income Group
    • Results by Subindex
    • Thematic Analysis
      • Capacity
      • Deployment
      • Development
      • Know-how
    • Conclusion
    • References
    • Appendices
      • A: Regional and Income Group Classifications, 2017
      • B: Technical Notes
  • Download full publication as PDF
  • Press Release
  • Blog and opinion
  • [ — Divider — ]
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  • System Initiative Partners
  • About the authors
  • Acknowledgements
  • Related Forum reports and activities
Human Capital Report 2017 Home
  • Report Home
  • Data Explorer
  • Shareable Infographics
  • User’s Guide
  • [ — Divider — ]
  • Preface
  • Key Findings
  • Global Human Capital Report 2017
    • Underlying concepts
    • Subindexes
    • Index Construction
    • Results
    • Results by Region
      • East Asia and the Pacific
      • Eastern Europe and Central Asia
      • Latin America and the Caribbean
      • Middle East and North Africa
      • North America
      • South Asia
      • Sub-Saharan Africa
      • Western Europe
      • Box 1: G20
      • Box 2: European Union
    • Results by Income Group
    • Results by Subindex
    • Thematic Analysis
      • Capacity
      • Deployment
      • Development
      • Know-how
    • Conclusion
    • References
    • Appendices
      • A: Regional and Income Group Classifications, 2017
      • B: Technical Notes
  • Download full publication as PDF
  • Press Release
  • Blog and opinion
  • [ — Divider — ]
  • System Initiative
  • System Initiative Partners
  • About the authors
  • Acknowledgements
  • Related Forum reports and activities

Development

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This subindex measures the human capital development of the current and future workforces through data on the current provision of education, the quality of the education system and the availability of employer-led re-skilling.

Figure 13: Relationship between Capacity subindex and Development subindex

The population structures of different countries provide distinctive opportunities for enhancing the development of human capital potential of the workforce across younger and older generations. According to United Nations population projections, while Sub-Saharan Africa is set to remain relatively young for decades, in Western Europe, by 2050, fully 35% of the population will be aged 60 and over, compared to just 9% in Sub-Saharan Africa.15 Therefore, for most Western European economies, priority areas for human capital development encompass a range of lifelong learning solutions that are effective at shifting the capabilities of the working age population. By contrast, in Sub-Saharan Africa, which continues to be the region which needs the largest investment in education across primary, secondary and tertiary education, significant efforts to integrate out-of-school children into education to avoid lost generations will have a particularly strong effect in transforming educational capacity for the coming decades.

Education systems today are increasingly at risk of being outdated, and modernization efforts are in most instances not in line with the demands of the wider economy or society. Constructing ‘future-ready’ curricula includes reviewing core linguistic, mathematical and technological literacies and ensuring sufficient attention to building digital fluency.16 Any curriculum reform and programme design will benefit from close attention to ensuring the availability of high-quality teaching, appropriate funding infrastructure, and effective incentives to all stakeholders—building on the motivation of learners, and appropriately including all relevant stakeholders from the public and private sector. Additionally, a core weakness across most education systems today remains the ecosystem for lifelong learning.17 Innovation in this area will need to encompass openness to different educational routes such as expanding the availability of technical and vocational education and training (TVET), ensuring higher education remains affordable and appropriate, and expanding the offer of lifelong learning opportunities at and beyond the workplace, using hybrid online and offline tools and taking into account learner-worker engagement.

With changes to the labour market brought about by the Fourth Industrial Revolution, governments, businesses and workers will also benefit from dynamically monitoring the labour market to ensure a stronger fit between people’s skills and the roles and occupations in which they are able to contribute. Three examples from LinkedIn’s data illustrate these opportunities for new insights and enhanced decision-making.

Table 3 displays the distribution of cross-functional skills by age group and by degree specialization. Values represent the unweighted average concentration of a skill for each family of degrees. Cross-functional skills are derived from the most commonly mentioned skills across LinkedIn’s global membership. Professionals from different generations report divergent skills in line with their progression in the labour market. For example, younger LinkedIn members are more likely to report mastery of office software, social media, teamwork and time management while those from older generations are more likely to point to their management skills and skills in strategic planning. The data also shows that cross-functional skills, acquired in large part through work, are concentrated differently across those with different original degree specializations. For example, comparison of the cross-functional skills developed among those who initially studied Engineering, Manufacturing and Construction and Information and Communication Technologies reveals that they are particularly likely to report having developed project management skills, but less likely to report having developed customer service skills as well as leadership skills. The data validates the notion that employers must not expect ready-made cross-functional skills but instead consider the development of these skills in the workplace an investment. At the same time, the data also points to opportunities for education systems to include more practical experience in cross-functional skills in addition to the formal specialization offered.

Table 3: Cross-functional skills of LinkedIn members, by age and degree specialization, percent

Table 4 explores the presence of specialist skills commonly held by those who have specialized in Information and Communication Technology degrees among graduates of other degrees. The distribution of commonly mentioned ICT skills highlights levels of commonality between engineering-track, natural sciences and mathematics-track and information and communication technologies-track specializations. It also highlights commonalities with arts and humanities-track specializations; business, administration and law specializations; and social science, journalism and information specializations—particularly in the use of databases (SQL), web technologies (web design, Javascipt, CSS, PHP), design (Adobe Creative Suite) and agile methodologies (lean manufacturing and product management).

Table 4: Specialist ICT skills of LinkedIn members, by degree specialization, percent

The data points to the possibility of transitions between different tracks thorough partial re-skilling building on existing skills, a factor for businesses to take into account when hiring as well as for governments to consider when promoting upskilling and reskilling programmes. The data also suggests that analysis of people’s acquired skillsets is an important complementary approach to using degree specializations to signal skillsets in today’s labour market.

Finally, Figure 14 reveals the age and geographical distribution of those holding specialist skills in Information and Communication Technologies. It shows that there has been a considerable expansion of this particular set of specialist skills. Yet this boom in ICT talent is not equally distributed across countries and generations. Economies such as Sweden, Australia, the United States, Switzerland and the United Kingdom have relatively more mature ICT talent. Others—such as Lithuania, Brazil, Romania and Estonia—have predominantly young pools of ICT talent. Meeting the growing demand for these skillsets should entail thinking more comprehensively across generational cohorts.

Figure 14: Distribution of specialist ICT skills of LinkedIn members, by age and geography

15
15 United Nations Population Division, World Population Prospects, 2017 Revision, 2017.
16
16 World Economic Forum, Realizing Human Potential in the Fourth Industrial Revolution: An Agenda for Leaders to Shape the Future of Education, Gender and Work, 2017.
17
17 World Economic Forum, Accelerating Workforce Reskilling for the Fourth Industrial Revolution: An Agenda for Leaders to Shape the Future of Education, Gender and Work, 2017.
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