Πως να χρησιμοποιήσετε τις πληροφορίες της αγοράς εργασίας για την ανάπτυξη μιας διαδρομής σταδιοδρομίας

At European level, the EU also has agencies which are collecting and analysing Labour Market Information.

EUROSTAT, the statistical office of the European Union, working in partnership with Member State statistical offices. publishes extensive data including Labour Market Data. It also provides access to many of these datasets through APIs. Data relating to occupations are collected as part of the Labour Force Survey, compiled by Eurostat. Some of the data, for instance unemployment rates in different European countries, can be accessed through Eurostat visualisation tools.

The EURES services for jobseekers and employers include:

Matching of job vacancies and CVs on the EURES portal

Information and guidance and other support services for workers and employers

Access to information on living and working conditions in the EU member states, such as taxation, pensions, health insurance and social security

Specific support services for frontier workers and employers in cross-border regions

Support to specific groups in the context of the EURES Targeted Mobility Schemes

Support to dynamic recruitment events through the European (Online) Job Days platform

Statistical agencies are not the only source of official data.

• Organisations responsible for education and training (for example, universities and other education and training  organisations) often publish their own data.
• Local governments may publish other types of data, for instance on travel-to-work times and distances involved.
• Additionally, labour market ministries and agencies within each country are likely to collect data about skills   shortages and projections of future employment by occupation.

Online Job Adverts

One of the issues with survey data is that it takes so long to collect and process. Another is that the samples are usually too small to provide accurate local or regional data. In the last two years we have seen a move toward analysing online job adverts, scraped from the internet. Benefiting from the advances in big data and AI, this approach can provide near real time Labour LMI and providing a sufficient number of adverts, can generate much more disaggregated data. A further advantage is that many job adverts ask for specific skills and skill sets providing an up to date snapshot of skills currently being asked for by employers in a city or region. Initially piloted by large private data providers including Burning Glass and Emsi, over the past  five years Cedefop has developed their OVATE portal for all European countries based on scraped data. Of course there are reservations. The percentage of jobs advertised online may vary between countries and regions. And there would seem to be a bias towards higher skilled and better paid jobs in online job adverts. In contrast, fewer low skilled and public sector jobs seem to be advertised online, with very restricted numbers in occupations such as agriculture. So the results of such an approach, while providing rich and detailed LMI, still requires careful interpretation. At a technical level, the major issue is cleaning the data, removing duplicates and standardising the outputs.

LMI formats

LMI is presented in many different formats. Examples include:

• Statistical formats: official LMI tends to come in spreadsheets which can be very difficult to interpret and technical reports that contain graphs, bar charts, etc., that tend to be geared towards economists and policy makers, rather than for use in careers education and guidance.
• Visualisations: advances in web technologies are making it increasingly easy to visualise complex data sets and to bring different data sources together. Check out how data from Cedefop OVATE service has been visualised on the Cedefop Skills Intelligence dashboards and on the OVATE Website.

A single  source of LMI may not meet all your needs, or even be the one that is necessarily the best for your purposes. Indeed, the best data source will often depend on the purpose(s) to which you want to use the data. It may be that you need to access multiple data sources.

Features of LMI

There are several features of LMI to bear in mind, when using different data sources. These important issues are discussed further in the video below, but summarised as follows:

Provenance of data

Keep in mind information on how the data was collected (i.e. methodology) and why it was collected.  This includes the coverage of the data and when it was collected. This will enable you to make an initial assessment about the likely reliability of the data and its robustness.

Classification systems

Data is classified in different ways. For example, in the European Union, they are classified by the European Skills, Competences, Qualifications and Occupations (ESCO) Standard Occupational Classification which develops a European multilingual classification of Skills, Competences and Occupations. The Nomenclature of Economic Activities (NACE) is the European classification of business activities, commonly referred to as an industry taxonomy.

Although similar terminology may appear in datasets from different countries that you may access and the US O*Net classification is also used in many countries, this does not necessarily mean that these classification systems are the same.  It is also worth remembering that classification systems may become outdated as industries and occupations change, with statisticians sometimes reluctant to change systems because this would mean ‘breaking’ continuity with data collected earlier.

Boundary and geography

Boundaries can also change over time and the names of places may not have consistent boundaries between different surveys. A further complication is that sometimes data is provided based on where people live, and sometimes on their place of work.

Survey non-response

In any data based on a survey it is important to consider the possibility of any potential bias caused by non-response, together with the impact of such non-response for the robustness and quality of the data.

Video High Quality Labour Market Information

Alternative information sources

To answer a particular question or examine a specific topic of interest, there is likely to be a number of different data sources that a career, employment practitioner or teacher can use. While in some instances the sources will ‘tell the same story’, in other instances the details/ trends may be contradictory. These discrepancies arise because: different methodologies have been used to collect information; geographical coverage of data collection varied; concepts were defined differently; varied classification systems were used; the time period to which the information refers differ; or the appropriateness of the analytical techniques used in the manipulation of data are varied. If contrasting stories emerge, it does not necessarily mean that one source is ‘right’ and the other ‘wrong’, or that one source is ‘better’ than the other is. It probably means that further investigation may be necessary to try and find reasons for the variation.

Some limitations of LMI

Different stakeholders in the careers field (for example, practitioners, managers, teachers, researchers, policy makers, funders etc.) will want different LMI for different purposes. For example, for different ages and stages, career practitioners will need different types of LMI for students in schools. In Year 9, LMI related to subject choices is needed, while in Year 13, LMI related to choices of education, training and career pathways are likely to be needed.

Official national and regional statistical agencies are a major source of official LMI. All data are collected for a purpose and the process of collection is usually costly. So, when reviewing different sources of LMI, we do need to be mindful of how they were collected (that is, what methods of data collection were used, like interviews compared with statistical surveys) and why (for example, to inform government policy, to guide resource allocation, or to support individuals in labour market transitions). Methods of data collection and purposes for which data are collected are likely to determine the type and sometimes the quality of data.

Statistical agencies are increasingly providing access to data through tools that help users to visualise the data (that is, through graphs and charts).

Limitations: Different data sets can often be downloaded in spreadsheet format from statistical agency websites. One problem is that it is hard to make sense of large spreadsheets. There is an increasing provision of  summary reports, but these are more often geared to economic reporting for policy purposes rather than the type of LMI that we are looking for.

Open data

There may be problems in accessing official data because of the structure and form in which they are being published (that is, for particular audiences, like policy makers), with different datasets sometimes linked together. But with the move towards ‘open data’, different agencies and organisations are starting to produce their own data portals, especially on a regional or city level. With fast growing research and development around big data, together with the use of cloud computing, access to graphical interfaces and visualisations are becoming more common.

More Resources

Check out your national, regional and local Careers Service. Most career services provide Labour Market Information.

LMI for All in the UK is a government funded service providing free access to an API for up to date data around LMI.

The Cedefop Skills-OVATE portal provide tools and reports for labour market information for Skills-OVATE offers detailed information on the jobs and skills employers demand based on online job advertisements (OJAs) in 32 European countries. It is powered by Cedefop's and Eurostat's joint work in the context of the Web Intelligence Hub.