Where can we find LMI?

What kind of LMI is available? 

As we noted in Unit 1, different career and employment stakeholders (that is, practitioners, managers, educators, researchers, policy makers, funders etc.) will want different LMI for different purposes (for example, for use with clients / customers at different stages of their careers; to inform policy; to devise courses and curricula; for use with parents or carers, etc.). We reviewed different types of LMI and their sources (that is, hard LMI and soft LMI, information compared with intelligence). Here, we look in more detail at potential sources of LMI, consider limitations and review how we can make choices between different sources and make sense of the data available. We will also examine some of the myths and misunderstandings that can arise around LMI.

When reviewing different sources of LMI, we need to be  mindful of who collated them (that is, what methods of data collection were used) and for what purpose (for example, to inform government policy, to guide resource allocation, to support individuals in labour market transitions).

Official data sources

1. Official statistical agencies

Official national and regional statistical agencies are a major source of ‘official’ LMI for career and employment practice.

What agencies in your country are viewed as official sources of LMI?

Taking one country example, the UK, the Office of National Statistics (ONS) collects data relating, for example, to the overall numbers employed and unemployed in the population; average pay levels in different occupations; and on the numbers employed in different occupations. Data relating to occupations are collected as part of the Labour Force Survey, a subset of which is included in the European Labour Force Survey, compiled by Eurostat.Some of the data. for instance unemployment rates in different european countries, can be acced through the Eurostat visualisation tools.

Different data sets can be downloaded in spreadsheet format from the ONS web site (https://www.ons.gov.uk/). One problem for career and employment professionals is that it is very hard to make sense of large spreadsheets. ONS publish summary reports, but these are more geared to economic reporting for policy purposes than the type of LMI at which that we are looking.

ONS, in common with other statistical agencies, are increasingly providing access to data through tools that help users to visualise the data (that is, through graphs and charts). Although of only limited use for occupations, ONS Neighbourhood Statistics provides a visual overview of local communities and economies based on statistics. NOMIS also offers local labour market profiles, drawn from a range of indicators (see Figure 1, below).

Image title

Figure 1: NOMIS Labour Market Profile

Statistical agencies are not the only source of official data.

  • Organisations responsible for education and training (for example, universities and other education/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.

There may be the problem of accessing these official data because of the structure / 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 is becoming more common.

Image title                          Source: Open Data Institute

National censuses are another rich source of LMI. However, they are usually only undertaken on a periodic basis (in the UK, every 10 years, so 2020 is the year of the next census) and the lead time until the data is published can reduce the value for using in employment or careers practice.

Other organisations, like the European Centre for the Development of Vocational Training (CEDEFOP) collect data on a European level (e.g. skills forecasting).

2. Data Tools

Once more from the UK, the Department for Education has funded the development of ‘LMI for All’, an online data portal, which connects and standardises existing sources of high quality, reliable, up-to-date labour market information (LMI) for the purpose of informing careers decisions. This data is made freely available via an Application Programming Interface (API) for use in websites and applications. The portal makes data available and encourages open use by applications and websites that can bring the data to life for a range of audiences.

LMI for All is an open data project, which is supporting the wider UK government agenda to encourage use and re-use of government data sets. Tools built on top of LMI for All provide an easy way of accessing and querying a range of different labour market data. One of the tools, developed by the LMI for All team, is a widget called a Careerometer allowing the comparison of different occupations (see Figure 2, below). You can try out the widget for yourself on the Careerometer page of the LMI for All website.

Image titleFigure 2: Careerometer 

Other data sources

1. Sector organisations

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, such as the UK, the structures of sector organisations differ and the LMI published is not standardised.

2. Educational and training organisations

Education and training organisations provide data on courses and agencies such as the UK Skills Funding Agency and the Higher Education Statistical Agency may provide access to aggregated data. Issues can include non-standardised data and the lack of aggregated data. Another issue for making sense of LMI is how easy it is to link information about courses to information about occupations.

3. Newspapers

Local newspapers, both printed and online, offer access to local LMI which may be hard to find elsewhere. Often, they carry job advertisements, which depending on national regulations, may not be available through government job portals. Newspapers can also be a useful source of data about future developments in local labour markets, for instance planned new factories and enterprises or skills shortages.

4. Trade unions

Most major trade unions have their own research departments and often publish detailed analysis of economic and employment developments in different sectors.

5. People

People are perhaps the most undervalued source of LMI, especially when it comes to Labour Market Intelligence. In all our research with Public Employment and career guidance and counselling professionals we have always been impressed by how much they know about local labour markets. The challenge is to find mechanisms for sharing that knowledge with others.

What are the limitations?

There are several issues to bear in mind, when using different data sources. Important issues, discussed further in the video below, include:

  • Provenance of data

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

  • Classifications systems

Data are classified in different ways. In the UK, they are classified both by Standard Occupational Classification and Standard Industrial Classification. Although similar terminology may appear in datasets from other countries, this does not necessarily mean that the classifications systems are the same.

Classification systems may become outdated as industries and occupations change as statisticians are reluctant to change due to ‘breaking’ continuity with data collected earlier.

  • Boundary and geography

Boundaries can change over time. Also, the names of places may not have consistent boundaries between different surveys. A further complication is that sometimes data are 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.

  • Alternative Information sources

In order to answer a particular question or examine specific topic of interest, there may be a number of different data sources to which a career or employment professional  can turn.  While in some instances the sources will ‘tell the same story’, in other instances the details/ trends may be contradictory.  This may arise because different methodologies were used to collect information, coverage may vary, the concepts may be defined differently, different classification systems may have been used, the time period to which the information refers may be different, or the appropriateness of the analytical techniques used in manipulation of data may vary.  If ‘the stories are different’ 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 differences.

How do you choose between sources of LMI?

Given the range of sources from which LMI is available, career and employment practitioners need to be able to make their own judgements about the criteria they should use to choose between sources. The video above presents checklists of what you should be looking for.

A practitioner guide to the efficacy and quality of LMI

In unit 1 we talked about the difference between ‘hard’ and ‘soft’ information, as well as making the distinction between Labour Market information and intelligence.

The table below presents a checklist to guide a practitioner in assessing the efficacy and quality of LMI.

Checklist for choosing between sources of LMI

Who has produced the LMI?

Think about:

  • Whether the source of LMI can be regarded as trustworthy
  • What are the aims and objectives of the organisation producing the LMI?  Is it promotional (putting a positive spin on particular facts) or excluding facts?
  • Whether you have been able to get similar data from more than one source – as this will help you achieve a more balanced and reliable view on of a particular situation
How was the LMI collected?

Think about:

  • How and why data were collected? (i.e. methodology)
  • What is the coverage and degree of detail available?
  • Is the data presented reliability?
  • How valid is the data?
How is the LMI data disaggregated and classified?

Think about the:

  • Relevance and appropriateness of units of measurement
  • Disaggregation of data, particularly geographical boundaries
  • Classification systems applied
  • Comparability of data and consistency over time
  • Analysis in terms of your needs; and
  • Relevance to the area in which you are operating
Is the LMI up-to-date?

Think about:

  • When was the research carried out?
  • What period does the data relate to?
  • When was the LMI published?
  • Potential currency and usefulness of data to current situations
  • Timeliness
  • Frequency of update (and when the next data will be available); and
  • Where there is any more recent research that either supports or contradicts the data?
Is the LMI fit for purpose?

Think about the:

  • Relevancy to service needs
  • Aspirational attributes of LMI
  • Accessibility of language (i.e. jargon-free)
  • Length and presentation of data
  • Balance of data, charts and explanatory text; and
  • Whether the data is presented in different formats (i.e. textual and graphical)

Activity:

Think of a source of LMI, either from your own practice, or from one of the different sources discussed earlier in this unit.

  • Use the criteria presented in the table above to assess the provenance and value of these data for use in your practice.

Misunderstandings about Labour Market Information

Interpreting Labour Market Information is not straightforward. It is easy to slip into traps when trying to make sense of data. Here, we provide illustrations of common misunderstandings that can arise when interpreting LMI.

Replacement demand

News media frequently report stories about the rosy future for jobs in new and vibrant sectors, like bio-technology or robotics. On the other hand, jobs in areas like mechanical engineering are seen as part of the old industrial technology and in decline. Whilst true at a superficial level, this may conceal reality in terms of future employment prospects.

At one time, engineering, in all braches, employed something like 5.5 million people in the UK, while biotechnology, although a fast-growing business, only employed around 21,000.

To a great extent, future job opportunities depend on replacement demand – the number of people leaving an occupation and thus creating a vacancy. Replacement demand can arise because of the age structure of an industry. Workers in engineering are older than in biotech (which has tended to employ young graduates) and therefore replacement demand is likely to be higher as a percentage of those employed. Of course, retirement is not the only factor influencing replacement demand. Other factors include the attractiveness of the job, the level of pay and the availability of other options.

Skill shortages           

Skill shortages are another topic frequently in the news. The reasons for skill shortages are complex and are not just an issue of shortage of skills, but a mismatch between available jobs and the expertise/training in the labour force.

The UK Employer Skill survey (ESS) indicated that in 2013, some 15% of employers reported that they had employees with skill gaps, equivalent to 1.4 million staff or 5% of the workforce. At the same time, a large proportion of employers felt that they underutilise their workers’ skills, with 4.3 million people (16% of the workforce) over-skilled or over-qualified for their current roles.

Of course, skills shortages may also be just due to lack of opportunity for progression, poor pay and poor working conditions, for instance in the agricultural industry. And in big cities like London, skills shortages may be aggravated by a mismatch between the pay level in an occupation and the cost of living, including housing and transport.

Countries, regions, cities and towns

One problem with much LMI is that it is not disaggregated sufficiently to a local level, mainly due to sample sizes. Yet opportunities in different occupations can vary greatly from region to region and even for different towns within a region. Media is a fast-growing industry in the UK. Yet a close examination at LMI for this sector reveals that it is heavily clustered, with employment concentrated in a few cities such as London, Cardiff, Brighton and Manchester.

Even in an occupation with widespread demand, such as construction, job opportunities can vary greatly between regions, influenced by the vibrancy of local economies and distribution of major construction projects.

Misleading graphics

Graphics are frequently misleading and require careful interpretation. Many of the problems are caused by the spacing and scaling on the X and Y axis. Take the following example from the (now updated) version 1 of LMI for All Careerometer widget.

Misleading visualisations

Figure 3: Misleading visualisations.

On first appearance employment for mechanical engineers is increasing steadily, while employment for vehicle techncians is falling fast. On closer observation, the starting point for number employed on the left hand axis are greatly different and despite these trends there will still be demand for nearly double the number of vehicle techncians than mechanical engineers in 2023.

Beware of averages

LMI frequently relies on average numbers, for instance, when looking at typical pay rates in an occupation. But there are different measures of ‘average’ including mean and median. Frequently, what is referred to as average is the mean, the sum of a collection of numbers divided by the number of numbers in the collection. In contrast, the median is the value separating the higher half of a data sample, from the lower half. In simple terms, it may be thought of as the “middle” value of a data set. For example, in the data set {1, 3, 3, 6, 7, 8, 9}, the median is 6, the fourth number in the sample.

The basic advantage of the median in describing data compared to the mean is that it is not skewed so much by extremely large or small values, and so it may give a better idea of a ‘typical’ value. For example, in understanding statistics like pay in a skilled job, which varies greatly, a mean may be skewed by a small number of extremely high or low values. Median income, for example, may be a better way to suggest what a ‘typical’ income is. Where available, decile values which reveal the distribution in a statically set, can provide a much greater understanding.

Once more looking at pay, wage rates in the UK vary greatly between different regions.

 

More resources:

Gender pay gap: Edition of the BBC radio programme, More or Less, on the Gender Pay Gap.

Detailed checklist (download hand out 1) which can be used as a self-assessment tool to gauge compliance and identify areas for development with LMI.

Detailed hand out (download handout 2) on issues with LMI data.


Why is LMI important?

Where can we find LMI?

Using LMI in Practice

Reflection

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