Abstract:

As the nature of work is changing, whether through rapid technological and social changes or unpredictable global disruptions, skills that are transferable become increasingly important in enabling the workforce to adapt to these changes quickly. There have been numerous studies on rankings of skills that are deemed to be important in the near future, but are these skills universal or dependent on broad occupational groups?

This research uses centrality analysis within a graph or network-theoretic framework to investigate the transferability of skills within and across broad occupation groups based on the US Bureau of Labor Statistics O*Net database, which contains the structured classifications of all occupations in the United States. Results show that while there are skills that are universally transferable, those with the highest levels of transferability tend to be most effective in facilitating occupational transitions within their specific occupational groups.

This study also contributes methodologically as this approach allows the transferability or cross-cutting properties of skills to be empirically quantified. This enables a data-driven approach towards targeted re-skilling or up-skilling within the industry. Implications for educational and workforce-related policies are discussed.

Keywords:

21st century skills, network analysis, skills valuation, centrality metrics, future of work.