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Closing the Digital Skill Gap: The Potential of Online Platform Data for Active Labour Market Policies


As new tech favors new skills and makes others redundant, the digital skills gap in Europe widens, according to the third paper of the Digital Revolution and New Social Contract series by Fabian Stephany.

Automation, digital platforms, and other innovations are changing the fundamental nature of work. Task automation and rapidly changing occupations lead to the paradoxical situation of unemployment during a time of labour shortage. Today, many firms are not able to fill their job offerings due to technological and social transformation changing the necessary skill composition of work.

A conventional policy response has been to align national education systems with changing labour market demand. However, this solution is becoming increasingly ineffectual as technological and social transformations outpace national education systems. Workers have begun to assume greater personal responsibility for reskilling, via skill-based online training. Nevertheless, the economic benefits and costs of reskilling strategies are often unclear, as they are highly individual, and the precise skill requirements for mastering emerging technologies remain opaque. In this context, a central question for active labour market policies targeting a reduction of the skill mismatch is: What type of training can effectively allow people to upgrade skills and move to jobs that are less automatable?

Recent research shows that independent professionals today develop new skills incrementally, adding closely related skills to their existing portfolio. That particular study examined the skill development of freelancers using online labour platforms (OLPs), that is, global marketplaces that match millions of buyers and sellers of digitally delivered work in various occupational domains. Between 2017 and 2020, the global market for online labour grew by approximately 50%, with more than 160 million workers engaged worldwide. In light of the COVID-19 pandemic and its significant economic repercussions across industries, OLPs continue to increase in popularity due to a general trend of work at distance. 

While OLPs only cover a small segment of the labour market, their data contains useful information on both the demand and supply side of skills. In addition, it is possible to observe the job matching process and price (e.g., hourly rate) for each job with a certain skill bundle attached to it. These properties make OLPs an interesting data source for studying skill formation, skill matching, and the evaluation of individual skills or skill bundles.

Therefore, online generated labour market data could allow for multiple advances in understanding labour market developments. Reskilling institutions could use online generated data to describe skill profiles of individual workers and track their development over time. They could assess the individual complementarities of learning a new skill and receive targeted reskilling advice. This allows workers to switch to more sustainable occupations that are closely related to their existing skill set with minimal reskilling effort and supports education providers and vocational training organisations in addressing the urgent need for individualised solutions in adult reskilling. 

Additionally, official occupational and skill taxonomies could be improved with near real-time online generated data. As technology creates the demand for novel skills, new occupational clusters can quickly emerge and official taxonomies begin lagging behind. Online generated data, on the other hand, stems from most recent market development and allows identification of new occupational clusters including in-demand skills. Data-driven and near-real time taxonomies could complement conventional classifications. An immediate contribution to current policy efforts would be the continuous (re-)classification of “AI” and “green” skills or jobs, as the “twin-transition” has been identified as a catalyst for active labour market policies.

Nevertheless, a crucial bottleneck is (still) data access.

The platform providers that gather useful data on skills, jobs, and occupations often hide information behind paywalls, restrict automated access by researchers and, at times, even issue legal threats after retrieval of data via web-scraping. The integration of platforms into a renewed social contract will be crucial if we are to develop rigorous, data-driven advice on addressing the challenges of the digital skill mismatch. Therefore, automated data retrieval should be included in the Data Act as a valuable option if platform providers are too slow, unwilling or technically not capable of sharing data with public sector recipients acting in public interest according to Article 15 of the Data Act.

Fabian Stephany, Oxford Internet Institute, University of Oxford and Humboldt Institute for Internet and Society.

To read more about the topic and download the full paper, click here.