ESCO facilitating labour market intelligence

ESCO facilitating labour market intelligence

ESCO (2015) SEC 102 DRAFT Document Date: 20/09/2015 Last update: 01/12/2015 1. Purpose of the document The purpose of this document is to describe how ESCO adds value to different classifications used for statistical research on the labour market. As several stakeholders pointed out at the ESCO goes live conference, ESCO could support the development of more precise labour market statistics and enhance the impact of existing projects in this domain. This paper shows how ESCO can benefit existing projects and programmes that aim at collecting statistics on the supply and demand of occupations and skills. 2. ESCO s support for statistics 2.1. Comparability of national data on an European level Labour market statistics are an important instrument for all stakeholders in the domains of employment and education, e.g. policymakers can use them to better understand labour market dynamics and react to them; employers can use them to optimise their recruitment activities; jobseekers can use them to make better career decisions; education and training institutions can use them to adapt curricula to the needs of the labour market. In databases across Europe there is a vast amount of labour market data available. However, in most cases these data is not suitable for statistical purposes since they are gathered using different classification systems. By transposing the data-points 1 in these databases in a manner that they reflect the concepts of the ESCO classification, it becomes possible to make use of these data sets for statistical analysis on an European level. 2.2. Interpreting data in context of NACE rev2 and ISCO-08 2.2.1. NACE rev2 ESCO maps the occupations and knowledge, skills and competences to the sectors of the Statistical Classification of Economic Activities in the European Communities (NACE rev.2 2 ). Eurostat developed the NACE classification in 2008 under the auspices of the United Nations Statistical Division as part of an integrated system to support statistical comparability. The European Commission and its Member States have adopted NACE. 1 The concept of transposing data-points is used to ensure that, in case of translating data from one classification scheme to another, the number of data-points is unaffected. This is a fundamental requirement when using data-sets for statistical purposes. 2 https://ec.europa.eu/esco/portal/escopedia/statistical_classification_of_economic_act ivities_in_the_european_community_%2528nace%2529 December 2015 2

The mapping to NACE enables statisticians to query and filter data expressed in terms of ESCO concepts using the NACE fields of economic activity. The mappings of ESCO occupations and knowledge, skills and competences to the NACE sectors are not necessarily singular. E.g. the occupation secretary may well be relevant for different fields of economic activity. As a result, it corresponds to multiple concepts from the NACE classification. This feature will need to be taken into account to avoid double counting, when using mappings for statistical purposes. 2.2.2. ISCO-08 The Commission delivers ESCO with a validated singular mapping to the 2008 version of International Standard Classification of Occupations (ISCO-08). The International Labour Organisation (ILO 3 ) developed this classification primarily to support international reporting, comparison and exchange of statistical and administrative data about occupations. Statisticians in most Member States use the ISCO classification. The mapping between ESCO and ISCO-08 is of significant value for the Member States, since it implies that more data and knowledge becomes available for ISCO-08 based reporting 4. Since ESCO has defined the occupations on a more granular level than ISCO, i.e. depending on the needs of the labour market, statisticians can report the data even on the more granular level. Since ESCO classifies the occupation concepts under the appropriate ISCO node, this added precision still supports the ISCO-08 comparability. ISCO ESCO 3 Technicians and associate professionals 35 Information and communications technicians 351 Information and communications technology operations and user support technicians 3512 Information and communications technology user support technicians ICT help desk agent ESCO is in most cases more detailed than ISCO-08, therefore each ESCO occupation is classified under an ISCO unit group (that is to say the lowest level of ISCO). 2.3. Interpreting data using the knowledge captured in ESCO The Commission captures with the ESCO classification various types of concepts and relations that represent knowledge of the labour market. These concepts will allow statisticians and researchers to produce information and statistics on demand for and supply of occupations, skills, competences, knowledge and qualifications. Additionally, ESCO captures which essential and optional knowledge, skills and competences are associated with occupations. Likewise, qualifications capture their learning outcomes in terms of knowledge, skills and competences. These features of ESCO empowers statisticians to draw conclusions based on the implied knowledge of the data. E.g. it becomes possible to infer which skill sets the labour market needs on the basis of the occupations expressed in job vacancies. 3 http://www.ilo.org/global/about-the-ilo/lang--en/index.htm 4 Additionally, Member States can use the ESCO to ISCO mappings to simplify the direct mapping of national occupation classifications to ESCO. December 2015 3

2.4. Using ESCO s terminology base to support Big-Data Analysis ESCO s terminology base is well suited for making repositories in the domains of labour and education accessible for Big Data research. Statisticians can use ESCO s terms to identify relevant concepts in relevant repositories or on the Internet. E.g. they can measure over time the use of ESCO concepts (through the terms defined in ESCO) in job vacancies and CV repositories. This would allow getting new insights on the dynamics of the labour market. 3. Labour market intelligence examples in the European Commission 3.1. EU Skills Panorama Short description. The EU Skills Panorama (EUSP) collects information in the form of data reports on skills supply and demand. The EUSP makes use of existing data at EU and national level and aims at increasing the comparability of statistics across Europe. The EUSP portal provides access to the data using four different perspectives: sector, occupation, specific skills and country. Analytical highlights present and interpret data from different types of sources. Challenges. The main challenge for this project is that it collates research based on distinct national classifications that are not interoperable. Additionally, little data is available on skills (labour market statistics focus currently mostly on occupations). Potential benefits of ESCO. Once the Member States map their national classifications to ESCO or even directly collect data using ESCO, their statistical data will become comparable with data available for other countries. Additionally, EUSP can utilise the knowledge captured in ESCO and draw conclusions on knowledge, skills and competences based on data gathered on occupations and qualifications. 3.2. DG Connect web crawler Short description. DG Communications Networks, Content & Technology organised a pilot project to "evaluate the feasibility of a software-based monitor of vacancies which are published online for ICT practitioners in the 28 Member States of the EU" 5. The study focused on the technical requirements for an automated ICT job vacancy crawler. In the project a prototype job vacancy crawler was tested for the French labour market. The crawler classified ICT job vacancies by occupation, level of education required and industry. Challenges. The main challenges captured by the study are: In order to be able to determine the level of education and to make it comparable between Member States, it is necessary to define the qualifications in a comparable manner and have access to the information on qualifications. In order to classify occupations and skills properly, a reference classification is crucial. In each Member State, the professional register system of companies should provide a list of establishments broken down by NACE. However, the industry sector is not always clear in the job adverts. 5 http://bookshop.europa.eu/en/movip-pbkk0215113/downloads/kk-02-15-113-2a- N/KK02151132AN_002.pdf?FileName=KK02151132AN_002.pdf&SKU=KK02151132AN _PDF&CatalogueNumber=KK-02-15-113-2A-N December 2015 4

Potential benefits of ESCO. ESCO will provide a vocabulary of labour market concepts and terms (occupations and skills) compatible with both NACE and ISCO. It will allow DG Connect to extract relevant labour market concepts in the ICT sector from job vacancies and process them for further analysis. 3.3. ISA pilot testing semantic interoperability of ESCO Short description. Within the context of the ISA programme (Interoperability Solutions for European Public Administrations) DG DIGIT and DG EMPL have conducted a pilot that tests interoperability aspects of the ESCO v1 classification. For this purpose, curricula vitae from EURES and from the Belgium public employment service VDAB are matched against job vacancies from LinkedIn. This pilot will test and demonstrate the semantic interoperability capabilities of ESCO v1 across multiple systems and languages. The value of this project for labour market intelligence is related to: Measuring skill gaps on the individual level. Researchers could compare the skills expressed in a CV with the skills inferred from enriching the occupation mentioned in the job vacancy with the essential ESCO skills for the occupation; Measuring skill gaps on the labour market level. Researchers could compare the skills available in a set of CVs with the ESCO skills inferred from a set of occupations mentioned in job vacancies. Challenges. The project showed that ESCO enables the interoperability of labour market data originating from different languages and systems. However, the project showed as well that in many cases the data available is not necessarily complete, e.g. many of the job vacancies available did not come with a list of skills required. This made success of this pilot dependent on the knowledge, skills and competences captured in the ESCO occupational profiles. Potential benefits of ESCO. The skills and competences pillar in ESCO will allow statisticians to measure skill gaps on an aggregate level. Thanks to the wealth of relations in ESCO, researchers can identify skill gaps even indirectly, by looking at occupations that employers find challenging to recruit. 3.4. EURES business intelligence monitor Short description. DG Employment, Social Affairs and Inclusion (DG EMPL) developed a data warehouse for internal use. The main goal is to store labour market data from the EURES portal to create business intelligence reports. Historical data on CVs and job vacancies allows creating reports for any specific time interval, e.g. on the following items: Number of CVs and job vacancies stored; Inflow/outflow of job vacancies and CVs; Average number of days that job vacancies remain stored on the portal before they users delete them. Challenges. One of the main challenges for this project is that data on the EURES portal (especially CVs) can be very dynamic (e.g. users change their CV over time). Therefore, the system stores snapshots of data at different moments in time, ensuring to capture trends and keep the data up to date. Aggregating the stored data is particularly challenging without having a reference classification in place. Potential benefits of ESCO. DG EMPL is investigating how best to use ESCO to aggregate data (e.g. based on ESCO occupations together with NACE rev2, and ISCO- 08). The wealth of concepts and relations in ESCO would further allow different options using the data warehouse to analyse supply and demand of occupations and skills (e.g. top skills used in CVs, top skills required in job vacancies). December 2015 5

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