Learning objectives
- To distinguish different types of labour market information (LMI).
- To consider why LMI is important for careers education and guidance.
- To identify a range of sources of LMI.
- To explore types of formats in which LMI is presented.
- To reflect on some limitations of LMI from different sources
- To examine tools for accessing different sources of LMI.
What is LMI?
There are different types of labour market information (LMI). For example:
- ‘Hard LMI’ typically refers to data gathered directly from the labour market and / or employer surveys on a geographic and / or sector basis to provide a statistical picture of current and likely future employment and skills trends.
- ‘Soft LMI’, in contrast, refers to information collected from a range of other, less official sources, like meetings or conversations with employers, or the experiences of particular jobs provided by people working in those jobs.
Labour market intelligence represents a further, important distinction. It refers to the interpretation of hard labour market data for different purposes and is what career practitioners and teachers find most useful for the career guidance process.
Video: What is LMI?
Watch this short video presentation (which explores different forms of labour market data)
Why is LMI important
LMI is pivotal to effective careers practice because high quality, impartial, current, expert knowledge about the labour market distinguishes careers support from other types of helping. A careers practitioner or teacher is likely to use LMI every time they interact with someone seeking help. Questions about course choice, self-employment, how much money could be earned in a particular job, where the local job vacancies can be found, what will the ‘hot jobs’ be when they leave education? None of these questions or issues could be addressed without LMI. LMI can help to demystify the world of work and can help individuals achieve their career goals.
LMI is also critical for not just young people planning their education and careers, but for those wishing to change their job or develop a new career in an adjacent or different occupation. LMI can allow them to find out the skills and knowledge required in different occupations. As well as the prospects for future pay and employment in that occupation. When linked to different datasets, for instance housing prices in different locations or transport links, it can allow them to plan life choices. LMI can support people in broadening horizons, exploring options, developing resilience, understanding the changing Labour Market and pursuing equity
But it is not just for career planning that LMI is critical. Educational administrators and planners use LMI for developing courses depending on labour market needs, LMI can report on changing skills demand in the regional economy. And economists and planners use LMI for planning future social and economic development. LMi is also important for staff working in Public Employment Services.
In summary, LMI provides the knowledge and understanding of how the labour market functions and is crucial for making sense of changing economic circumstances. It can also help when thinking about what the future might hold, so can support decision making.
Sources of labour Market Information
Labour market information comes in many types and forms. At national and regional level these include;
Statistical Agencies
- like the Instituto de Statistica (INE) in Spain, the Instituto Nacional de Estatistica in Portugal or the National Statistical Service in Greece. Different Government Departments and Agencies often produce their own statistics for instance about education. They also often commission research and reports about the labour market, including jobs and employment. In some countries with Federal or devolved governmental structures, regions have their own statistical agencies, for instance in Spain.
Sector Organisations
at national and regional level, often have their own researchers and can provide a rich source of LMI. However, whilst in some countries this LMI may be standardised in other countries, the structures of sector organisations differ and the LMI published is not standardised.
Local Sources
like enterprise and economic development partnerships, education and training providers and local newspapers.
Individuals
finally and by no means the least important is the knowledge of people, including careers education guidance practitioners themselves.
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.