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As a part of its Digitalization and future of work project, Cedefop estimates the risks of automation for occupations. The most exposed occupations are those with significant share of tasks that can be automated – operation of specialised technical equipment, routine or non-autonomous tasks – and those with a small reliance on communication, collaboration, critical thinking and customer-serving skills. The risk of automation is further accentuated in occupations where employees report little access to professional training that could help them cope with labour market changes. The automation risk indicator brings together both views and calculates the share of people working in different occupations whose jobs are both exposed to high level of task automation and at the same time they lack access to appropriate training.

This indicator introduces detailed employment breakdown for economy sectors, and it makes use of Cedefop’s Skill Projections database.

The indicator provides the employment growth in manufacturing and service sectors that are considered to hi-tech, knowledge intensive ones. Data are provided for (i) high technology manufacturing; (ii) knowledge intensive hi-tech services; and (iii) the hi-tech economy as a whole which is the sum of hi-tech manufacturing and services employment. The indicator makes use of Cedefop’s Skill Projections database to show how the share of people employed in these sectors has changed over the recent past and how it is expected to change over the period to 2030.

The indicator shows how share of people employed in science, engineering and ICT occupations will change in the future across EU Member States and economy sectors. These occupations correspond to following ISCO occupations: 21 (Science and engineering professionals), 31 (21 (Science and engineering associate professionals), 25 (Information and communication technology professionals), 35 (Information and communication technicians). The share of these so-called "high-tech occupations" in total employment indicates the technology intensity of a sector or of a whole country. The indicator makes use of Cedefop’s Skill Projections database.

The indicator provides the share of people employed in manufacturing and service sectors that are considered to hi-tech, knowledge intensive ones. Data are provided for (i) high technology manufacturing; (ii) knowledge intensive hi-tech services; and (iii) the hi-tech economy as a whole which is the sum of hi-tech manufacturing and services employment. The indicator makes use of Cedefop’s Skill Projections database to show how the share of people employed in these sectors has changed over the recent past and how it is expected to change over the period to 2030.

The share of people employed in science, engineering and ICT occupations either as professionals or associate professionals. These occupations correspond to following ISCO occupations: 21 (Science and engineering professionals), 31 (Science and engineering associate professionals), 25 (Information and communication technology professionals), 35 (Information and communication technicians). The share of these so-called "high-tech occupations" in total employment indicates the technology intensity of a sector or of a whole country. The indicator makes use of Cedefop’s Skill Projections database to show how the share of people employed in these occupations has changed over the recent past and how it is expected to change over the period to 2030.

In order to develop coherent policies with regard to education, skills and employment in an economy, we need to know: how many people will be employed in the coming years, and what are the jobs in which they will be working. This is where projections of the future annual employment growth are of key importance. This indicator provides an estimate of the expected annual percentage change in employment demand for each country: that is, how much the demand for jobs is expected to grow or shrink each year, from 2018 to 2030. This indicator can be broken down to provide estimations of future changes in employment by sector of economic activity, occupational group and qualification level, both on a country-by-country basis and for the EU28 as a whole. In doing so, it provides an indication of how the skills demanded by employers are likely to change over the period to 2030. This, in turn, has implications for both: (a) the skills that future job seekers will need to acquire in order to meet the demand across occupations and sectors; and (b) the national education and training systems, which are mainly responsible for supplying the skills necessary to navigate the changing employment landscape. Note: The detailed estimates are subject to possibly large and uncertain margins of error. They should not be taken literally but suggestive of indicative trends and patterns. As a rough rule of thumb, any cell containing fewer than 10,000 people should be regarded with caution. Cells with fewer than 1,000 people should be regarded with considerable scepticism.

Projected changes in employment to 2030. This provides an indication of projected changes in skills demand in terms of overall percentage change, and can be broken down by sector of economic activity, occupational group and level of education. The indicator makes use of Cedefop’s Skill Projections database. Note: The detailed estimates are subject to possibly large and uncertain margins of error. They should not be taken literally but suggestive of indicative trends and patterns. As a rough rule of thumb, any cell containing fewer than 10,000 people should be regarded with caution. Cells with fewer than 1,000 people should be regarded with considerable scepticism.

The future employment needs indicator offers an estimate of the total job openings in each occupation in the period to 2030. This is the sum of future needs that will arise due to a) the need to replace existing workforce and b) the need to cover new jobs because the economy is growing – which, if demand for workers is shrinking, may be negative. This means that future employment needs in a given occupation may be substantial (due to the need to replace workers) even if the total numbers in this particular occupation are expected to decline. A paradigmatic example is that of agricultural workers, for which even if future employed trends seem declining in most countries, the need to replace workers who are now close to retirement will create large numbers of new job openings. Sometimes job seekers are not aware of this, meaning employers may then find it difficult to fill vacancies because people regard some occupations or sectors as being associated with limited future job growth - even though they may offer many employment opportunities. Note: The detailed estimates are subject to possibly large and uncertain margins of error. They should not be taken literally but suggestive of indicative trends and patterns. As a rough rule of thumb, any cell containing fewer than 10,000 people should be regarded with caution. Cells with fewer than 1,000 people should be regarded with considerable scepticism.

The indicator provides a number of people who will be required to work in an occupation in forthcoming years. The demand for these people is broken down by: 'New/lost jobs' (it indicates net change in employment caused by creation of new jobs and destruction of some of the existing ones). It can be positive or negative, 'Replacements' (it captures the number of people needed to replace workers who changed jobs or left the labour market, such as retirees), and 'Total job openings' (the sum of 'New/lost jobs' and 'Replacements'). Although the labour market narrative often focuses on numbers of new jobs created, it is the need to replace workers leaving existing jobs that comprises most of the skills demand. More than 90 per cent of all job openings are driven by the replacement needs. Note: The detailed estimates are subject to possibly large and uncertain margins of error. They should not be taken literally but suggestive of indicative trends and patterns. As a rough rule of thumb, any cell containing fewer than 10,000 people should be regarded with caution. Cells with fewer than 1,000 people should be regarded with considerable scepticism.

The future job prospects indicator compares future number of job openings in a particular occupation to total employment in that occupation. If the number of future job opportunities is high compared to total employment (for example for scores above 60 it means that there will be more job openings than number of current jobs in the occupations), we say that there will be high job prospects. On the contrary, if the score is below 40, the job prospects will be relatively low. A score between 40-60 indicate average job prospects, i.e. the number of job openings is closer but below current employment.

Based on the indicator VET occupations, which estimates the share of people with vocational qualifications in employment across occupations, the Future of VET occupations indicator brings their employment outlook up to 2030. The VET occupations are evolving in time. As the concept of VET is changing, the definition of a VET occupations expands beyond its traditional meaning. This indicator tries to capture this by splitting VET occupations into three groups: (i) traditional VET occupations, which focus and level of education remain mostly unchanged (such as construction workers or plant operators); (ii) modern vocational occupations, such as care workers or personal service workers, which tend to require either a higher level of qualification than in the past (with strongly rising share of tertiary education graduates) or require the same level of skills but in subjects outside of traditional VET areas. Finally, (iii) new vocational occupations require a higher level of skill and in subjects outside the scope of traditional vocational education (for example ICT technicians or health associate professionals). In addition, the indicator compares employment outlooks of these VET occupations with those considered being non-VET, such as managers, professionals and most clerical jobs, but also those requiring lower level of skills (elementary jobs). Note: The detailed estimates are subject to possibly large and uncertain margins of error. They should not be taken literally but suggestive of indicative trends and patterns. As a rough rule of thumb, any cell containing fewer than 10,000 people should be regarded with caution. Cells with fewer than 1,000 people should be regarded with considerable skepticism.

The indicator shows how qualification levels of employed people shall change between 2018 and 2030. The level of qualification held by an individual can be classified as high (at ISCED levels 5 and above), medium (levels 3 and 4), or low (at level 2 and below). To show how the composition of occupational employment is projected to change in the future, the occupational qualification indicator shows the percentage change in the share of employment accounted for by each level of qualification for the period 2018 and 2030. The graphs show aggregate information for all countries and broad occupations covered. You can choose to select a country and/or detailed occupation in the filter options. Note: The detailed estimates are subject to possibly large and uncertain margins of error. They should not be taken literally but suggestive of indicative trends and patterns. As a rough rule of thumb, any cell containing fewer than 10,000 people should be regarded with caution. Cells with fewer than 1,000 people should be regarded with considerable scepticism.

This indicator introduces detailed employment breakdown for ISCO 3-digit occupations, and it makes use of Eurostat Labour Force Survey data.

The employed population refers to the total number of people of any age who are currently in work (defined as having worked at least one hour in the reference week). This may include people who are: employed in a traditional waged role; self-employed; or unpaid staff working for family-owned businesses. This indicator provides a baseline figure which we can use to derive important insights into the operation of the labour market: for example, by looking at how employment is shared out between men and women, or the extent to which people in work display higher levels of educational attainment over time. Looking at the total number of people employed by each sector allows us to draw conclusions about the types of economic activities that a country is engaged in, and how this has changed over the years. Similarly, by looking at the total number of people employed by occupation or level of education, we can develop an insight into the skills currently at work in the labour market. This type of information can be valuable to policymakers and researchers with an interest in the current state of employment in an economy – and how this employment landscape is changing over time Note: All estimations are Skills intelligence Team own calculations based on Eurostat data.

The participation rate in training or education of the employed population indicates the percentage of people aged 25 to 64 who received education or training over the employed population. The indicator can be broken down by sector, occupation, age, gender and educational qualification. Note: All estimations are Skills intelligence Team own calculations based on Eurostat data.

This indicator provides shares of people with certain field of study in total employment in an occupation. The fields of study are based on ISCED 2013 classification. Note: All estimations are Skills intelligence Team own calculations based on Eurostat data.

The part-time employment indicates the percentage of part-time workers over total employment, based on results from the European Labour Force Survey (EU LFS). People considered as working part-time involuntarily are those who want to have a full-time job but could not find it. Note: All estimations are Skills intelligence Team own calculations based on Eurostat data.

Temporary employment includes work under a fixed-term contract. The contract can end at a specific date, with an end of a task, or the return of another employee who has been temporarily replaced. People considered as having temporary employment involuntarily are those who have temporary contracts and want to have a permanent job but could not find it. Note: All estimations are Skills intelligence Team own calculations based on Eurostat data.

The job turnover indicator provides the percentage of employed people that started to work in a certain occupation during last 12 months. The indicator can serve as a tool how to assess the frequency of job change in an occupation and thus also approximate for the level of available job opportunities: the higher the percentage, the higher the chances people were able to find work in the occupation. It does not mean though that occupations with higher job turnover provide better prospects; the down side of the turnover is that there may be less stability and job security for people employed in the occupation. For example the highest job turnover for Elementary workers is also influenced by a lot of short term or seasonal work contracts. Note: All estimations are Skills intelligence Team own calculations based on Eurostat data.

For many people, unemployment may just last a few weeks or months, and, as such, does not pose a problem. Unemployment, however, for some people can last much longer – sometimes stretching to years. Whilst the total unemployment rate provides an indication of the number of workers in an economy who are currently out of work, the long-term unemployment rate measures something different: how many of these unemployed persons have been out of work for longer than 12 months. This is expressed as a percentage of the total number of unemployed persons in an economy. The reasons why people may find themselves in long-term unemployment are many and varied, but one of the major causes is a lack of the skills currently in demand by employers, which allow people to make a successful transition from being out of work to finding employment. The longer people are unemployed, the more outdated their skills may become, and the more difficult it may become for them to persuade employers to hire them. The effect of this is that they can become locked into a vicious spiral. Long-term unemployment is closely associated with poverty and social exclusion. Note: All estimations are Skills intelligence Team own calculations based on Eurostat data.

This indicator shows what occupations - such as managers, professionals or agriculture workers - are employed within a specific sector of the economy (for example agriculture, forestry and fishing sector). You may choose a different sector from the filter menu. The indicators includes employees of any age-group, either employed in a traditional waged role; self-employed; or unpaid staff working for family-owned businesses. Note: All estimations are Skills intelligence Team own calculations based on Eurostat data.

This indicator shows the share of young (aged 25-34), tertiary education (ISCED 5 or 6) graduates employed in posts not included in categories of managers (ISCO 1), professionals (ISCO 2), or technicians and associate professionals (ISCO 3). When individuals with tertiary education attainment occupy jobs demanding lower skills (e.g. sales, crafts, agriculture, elementary occupations), there is concern that there is a waste of public resources in higher education. An overqualified tertiary graduate receives lower wages on average and has lower job satisfaction than a tertiary graduate employed in a matched graduate job. This indicator is one of several measures of education-occupation mismatch. Caution in interpretation is required as the indicator assumes outright that all occupations in ISCO 4-9 categories do not require a higher education degree. Many young higher education graduates may also be overqualified for a temporary duration or choose their jobs for personal or other reasons (e.g. proximity to home). Moreover, even if overqualified, individual’s skills may be matched to the skill requirements of their job. Note: All estimations are Skills intelligence Team own calculations based on Eurostat data.

The part-time employment indicates the percentage of part-time workers over total employment, based on results from the European Labout Force Survey (EU LFS). Respondents reported that the main reasons for working part-time was “not finding a full- time job”, followed closely by “looking after children or incapacitated adults”. The indicator can be broken down by sector, occupation, age, gender and educational qualification. Note: All estimations are Skills intelligence Team own calculations based on Eurostat data.

This indicator shows where people with certain occupation - for example managers - work. "Where" means a sector of economic activity, such as manufacturing or construction. You may choose a different occupation from the filter menu. The indicator includes employees of any age, employed either in a traditional waged role; self-employed; or unpaid staff working for family-owned businesses. Note: All estimations are Skills intelligence Team own calculations based on Eurostat data

The self-employment indicates the percentage of self-employed workers over total employment, based on results from the European Labour Force Survey (EU LFS). The indicator can be broken down by occupation, age, gender and educational level. Note: All estimations are Skills intelligence Team own calculations based on Eurostat data.

The indicator shows the number of people that have temporary contract as a share of all people in employment, based on results from the European Labout Force Survey (EU LFS). Note: All estimations are Skills intelligence Team own calculations based on Eurostat data.

The indicator provides a share of unemployed people by occupation. It is calculated as number of unemployed (who lost their job in the last 2 years) whose last job was in a particular occupation, as a share of employed and unemployed in that occupation

The unemployment rate gives an indication of the extent to which there are more people looking for work than there are jobs available. This is formally expressed as the percentage of the economically active population (i.e. employed plus unemployed people looking for work) who are currently not in employment but are actively seeking and ready to commence employment. The unemployment rate is considered a key indicator, as it tends to signpost the overall health of the labour market. For example, looking at changes in the unemployment rate over time offers an indication of whether things are getting better or worse in the labour market. If unemployment rates are compared for people with different socio-economic and educational characteristics, then it is possible to gauge the extent to which those characteristics afford some protection against changes taking place in the wider economy (for example, if GDP falls). Generally speaking, people with higher levels of educational attainment are less likely to be unemployed. Note: All estimations are Skills intelligence Team own calculations based on Eurostat data.

The purpose of this indicator is to estimate size and share of employment of people with vocational (VET) qualifications across EU countries and in the United Kingdom. The share of people with VET qualifications is calculated from the the EU Labour Force Survey (LFS) data.
The EU LFS categorises individuals’ highest level of qualification as either general or vocational where that qualification is at ISCED Levels 3 or 4 and where they are currently aged between 15 and 34 years. Because of the measurement, the employment levels and shares of "VET occupations" presented in this indicator shall be treated as conservative estimates. Over the past 20 years, many countries have developed vocationally or professionally oriented programmes at higher levels, and there is evidence of programmes such as apprenticeships in some countries now being offered at ISCED level 5 above which the EU LFS is not able to capture. Based on this indicator, a related Future of VET occupations indicator has been also created to estimate employment trends up to 2030.

Youth unemployment is a problem which tends to affect all countries with weak or negative employment growth. When growth in the economy slows, so may employment growth, as businesses hold back on expanding and creating new jobs - or worse, go into reverse, as they make cuts to their workforce to decrease costs. It is often young people who bear the heaviest cost of this, as they compete for fewer jobs against older workers with much more experience under their belt. One way young people who cannot find work can improve their labour market prospects is to acquire, via education and training, those skills which employers are known to value. Where, however, young people are not in employment and neither are they participating in education nor training, they run an increased risk of becoming disconnected from the labour market and facing social exclusion. This has the potential to blight their entire working lives. The young persons neither in education nor employment or training (NEET) rate is an indication of how many people aged 15-24 in an economy are neither in work, nor in formal education or training. This is expressed as a percentage of the total population aged 15-24 . Note: All estimations are Skills intelligence Team own calculations based on Eurostat data.

The indicator provides information about usual range of monthly gross income for occupations in EUR. It takes into account the purchasing power of the country compared to other EU countries. It includes the value of any social contributions and income taxes payable by an employee or by the employer on behalf of the employee to social insurance schemes or tax authorities. Note: Choose an occupation from a drop-down menu on the right to display occupation-specific information.

The indicator compares median income of an occupation (such as "accounting clerks") to median income of "parent" occupation group (in this case "clerks"). If the value is above 100%, it means that income of the occupation is higher than average income of "parent" occupation group. If it is below 100%, it means that income of the occupation is lower than average income of "parent" occupation group.

The indicator analysis the importance of various tasks/skills required for occupations at the 2-digit ISCO code level. The importance is measured at 0-1 scale. You can choose a different occupation from the pull down menu on right. Read more about the task analysis in our blog article.

The indicator provides the share of people whose digital skills use is above basic. It provides an indicator (i) for all individuals (essentially a measure of potential digital skills supply); (ii) for individuals aged 25-34 years (a measure of new skills supply); and (iii) all in employment (employed, self-employed and family workers). Data for the digital skills indicator are derived from the European Union Survey on ICT Usage in Households and by Individuals which gauges individual’s digital skill capabilities in four domains: (i) information (e.g. moving and copying files); (ii) communication (e.g. sending and receiving emails); (iii) problem solving (e.g. installing software); and (iv) software (e.g. using software to edit photos, videos, or files). Notes: Slovakian data is missing because of insufficient reliability levels and "EU27_2019" is the average value for the EU excluding data for the United Kingdom.

Skills intelligence section brings insights on jobs and skills requested in online job advertisements. Based on an ongoing Cedefop project, these insights now cover 28 European countries. More than 67 million of online job ads were collected and analysed, covering period of July 2018 till December 2019. The analysis provides information on most required occupations and skills across European countries and regions based on established international classifications: ISCO-08 for occupations, NUTS-2 for regions, ESCO for skills and NACE rev. 2 for sectors. Cautionary notice: Cedefop has developed this analysis using a robust methodology and under substantial quality control mechanisms. However, online job ads are not a comprehensive source of skills and job demand and many factors influence its completeness and coverage. More analysis and testing will be done in the near future to provide sound evidence for informing policy developments. The fully-fledged system with expanded functions will be released by end of 2020.