Workshop on big data for skills anticipation and matching
The aim of this workshop is to allow all participating agencies to exchange experiences and ideas in relation to the use of big data for identifying labour market information.
Due to the limited seating capacity, there is no open registration for the event.In dynamic and constantly changing labour markets, identifying skills needs is an important challenge. Imbalances on the labour market, reflected by difficulties faced by businesses in sourcing the skills they need, high incidences of skills mismatch, and significant unemployment or underemployment especially among youth, are common to most countries. In order to tackle these issues, policy-makers, employers, workers, providers of education and training and students all need timely and accurate information about demand for skills on the labour market and how it relates to skills supply.
New sources of data on skills have potential to provide more current and more specific information on skills needs than is available from the existing sources, and to do so in a cost-effective way. Technological advances, digitalisation and Internet platforms have made it possible to collect very rich and big datasets, or so-called “big data” for many purposes. Data on the content of job advertisements has been collected systematically from online job postings in a range of countries, creating huge datasets containing detailed information on the requirements advertised. The richness of information featured in these datasets has drawn considerable attention, and has underpinned many publications, both from academia and from international organisations.
ObjectivesThe goal of the workshop is to allow all participating agencies to exchange experiences and ideas in relation to the use of big data for identifying labour market information. These discussions will consider:
- the feasibility of the use of big data in this context
- the potential of big data in skills analysis and the limitations associated with it
- how to advance the agenda in this area, share good practices, as well as find solutions to commonly found issues
- how these methods can best be deployed in developing economies