LMI in transformation - why Big Data for which LMI
Big Data is all around us, but its potential and the ways it can be used in social research remain a novelty for many state institutions and stakeholders in ETF partner countries and beyond.
Big Data can be used to go beyond the frontiers of conventional approaches to labour market information systems (LMIS) and add value to established statistics. Traditional approaches to providing LMI, based essentially on surveys, have important caveats: cost, timeliness, accuracy, usage, integration and coverage.
These challenges are addressable but this will need the attention of governments, stakeholders and their donor partners to resolve them.
Big Data sources and analysis supplement and enrich established statistics. Big Data analytics can be used to map skills by occupations, to identify discrepancies in skills, to identify obsolete skills, to do predictive analysis of demand for new occupations and new skills – in quasi real time. Big Data analytics allow more refined (granular), space-related insights in real time, as well as predictive analysis.
The new “Skills Agenda for Europe”, adopted by the European Commission in June 2016, emphasises the need to improve skills intelligence and information for better career choices (strand 3), and explicitly mentions the use of big data: “Data on skills needs and trends will be improved by web crawling and the analysis of big data, and further underpinned by evidence from different sectors, bringing together accurate and real-time information in the service offered by the existing "Skills Panorama" tool as part of an integrated Europass service.” (European Commission, 2016).
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