Skills, not job titles, are the new metric for the labour market

The rise of tech is currently transforming the labour market, leading to the automation of some jobs and tasks on the one hand and the emergence of new kinds on the other. Proactively preparing for this new reality requires an in-depth, granular understanding of these changes and their impact on jobs and employment. LinkedIn data is able to provide additional insight on this by taking a skills-based approach to labour-market analysis.

Skills are the new currency on the labour market. Skills indicate demand and supply at a more nuanced level than occupations, whose required expertise and skills are changing increasingly quickly, and degrees, which are often already outdated by the time they are obtained. The current pace of change requires following the direction of a skills-based, rather than degree-based labor market, which is a much more dynamic variable. Using skills as a variable of analysis provides a powerful tool in helping policymakers prepare for the future while building resilience in the present day.

Based on these shifts, LinkedIn has developed the Skills Genome -- a new metric, which allows us to harness that analytical power to gain a more granular understanding of labour market trends and developments. Using skills information provided by LinkedIn’s Economic Graph, a digital representation of the global economy based on data generated from 630 million members with more than 35,000 skills globally, the metric allows us to define and analyse the unique skills profile of various segments of the labor market. We can use it to identify those skills that are more prevalent in one segment compared to others. These segments can include a geography (e.g. a city), an industry, a job type (e.g. data scientists), or a population (e.g. women).

In China, for example, we examined the dynamics of digital skills across two of the most economically active and open regions: Guangdong-Hong Kong-Macao Greater Bay Area and Yangtze River Delta. In a report on digital economy and talent development in the former, we found that China's Greater Bay Area has an overall net inflow of talent equipped with digital skills, and Shenzhen is a digital talent hub in the Greater Bay Area. We also found that talent in the region mainly majored in finance and technical fields of study, and possesses general-purpose skills such as project management and leadership, with a relatively low level of integration of digital skills. Soft skills like management, leadership and negotiation rank higher in this region, regardless of high-level talents or digital talents.

In a similar report for the Yangtze River Delta Region, we found that Shanghai plays an important role in training and developing junior-level talent with diversified skills to support other regions. We also found that the top 10 fastest growing positions in the past four years are all considered intermediate and senior management positions covering customer service, marketing, finance, products, operations and other functions. Skills that have seen the sharpest increase can be divided into four categories: (1) functional skills such as marketing and customer service; (2) soft-power skills such as leadership; (3) digital skills such as social media; and (4) value-added skills such as English. The categories of skills indicate that the Yangtze River Delta region is increasingly open to the wider world and has become increasingly linked to digital opportunities.

Findings like these are increasingly valuable as our society prepares for the future of work. Policymakers may want to use these skills profiles to determine future career paths for people in occupations declining in popularity. Education and training providers will be able to align curricula to the emerging skills trends. And as diversity becomes a more critical objective, skills profiles of members of different backgrounds can inform efforts to close gaps and reduce barriers.

Read the World Economic Forum's new Insight Report, Data Science in the New Economy, here. This post was originally published on the World Economic Forum blog.