Labour market information (LMI) for all

Labour market information (LMI) for all

LMI-web-images_labourmarketdataThe idea underpinning LMI for All is to provide a comprehensive careers labour market information1 (LMI) database that links and opens up career-focused LMI. Its aim has been to optimise access to, and use of, core national data sources that can be used by developers to create websites and applications2 to support individuals make better decisions about learning and work. It has been created as an open data project, which supports the wider government agenda to encourage use and re-use of government data sets. LMI for All was funded by the UK Commission for Employment and Skills (UKCES) up to 2017 and is currently funded by the Department for Education (2018-2020).

The LMIforAll website is here: www.lmiforall.org.uk

The development of LMI for All service spanned a five-year period (2012-2017).During this time, the feasibility of developing a comprehensive career LMI data tool that exploits open data sources that can be mainstreamed into service provision has been demonstrated. The overall aims of the project have remained constant:

  • To identify and investigate which robust sources of LMI can be used to inform the decisions people make about learning and work; and,
  • To bring these sources together in an automated, single, accessible location (referred to as the LMI for All database), so that they can be used by developers to create websites and applications for career guidance purposes.

Posts about LMI for All

Skills Gaps

January 16th, 2020 by Graham Attwell

A new report by the Learning and Work Institute for the Local Government Association (LGA) finds that by 2030 there could be a deficit of 2.5 million highly-skilled workers. The report, Local Skills Deficits and Spare Capacity, models potential skills gaps in eight English localities, and forecasts an oversupply of low- and intermediate -skilled workers by 2030. The LGA is calling on the government to devolve the various national skills, retraining and employment schemes to local areas. (via WONKHE)

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SMEs are not the same as large firms

December 18th, 2019 by Graham Attwell

Much of my work at the moment is focused in two different areas – the training and professional development of teachers and trainers for the use of technology for teaching and learning and the use and understanding of labour market data for careers counseling, guidance and advice. However as data increasingly enters the world of education, the two areas are beginning to overlap.

This morning I received an email from the European Network on Regional Labour Market Monitoring. Although the title may seem a little obscure, the network, which has been active over some time, organises serious research at a pan European level. Each year it selects a theme for research, publications and for its annual conference. Over the last year it has focused on informal employment. Next year’s theme is Small and Medium Enterprises (SMEs) which they point out can be viewed as perhaps the most vibrant and innovative area of the European economy. However, when it comes to researching and understanding SMEs it is not so easy

A number of European or national statistics exist to analyse SMEs’ but they generally use the same categories as for large firms and are, in general, constructed from a large firm perspective or in any case not from a framework based on SME characteristics. Many academic papers focusing on SMEs show that they cannot fully be understood using the same categories as with large firms. The general idea is that firstly, SMEs are same as large ones, just smaller. Secondly, the assumption that they will grow up to become Midcaps, then large firms, is incorrect. Torres and Julien (2005) start their article explaining that “Most, if not all, researchers in small business have accepted the idea that small business is specific (the preponderant role of the owner-manager, low level of functional breakdown, intuitive strategy, etc.)”. A 2019 French publication directed by Bentabet and Gadille tackles the issue of SMEs focussing on their specific “social worlds”, their “action models and logics”, while elsewhere the influences of institutional logics and multi-rationalities of SMEs have been considered. The entry of social worlds highlights the great diversity of micro-enterprises and SMEs, which often makes it difficult to analyse them. As a counterpoint, specific knowledge of these companies is required because they are at the heart of the debates on flexibility, labour market dynamics, skilled labour shortage and disruptions in the vocational training system.

SMEs will be the focus for the next Annual Meeting of the Regional Labour Market Monitoring to be held in September 2020 in Sardinia

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Understanding the gender pay gap

December 5th, 2019 by Graham Attwell

We have written before about the gender pay gap in the UK. According to the Office for National Statistics the average hourly (gross, excluding overtime) gender pay gap in the UK for all employees fell from 17.8 per cent in 2018 to 17.3 per cent in 2019. However, nee research has revealed cross-national gaps vary from as much as -5 per cent in Wigan to 32 per cent in Slough suggesting that only focusing on a national perspective might be overly simplistic.

The Centre for Cities has found that 7 of the 10 cities with the highest gender pay gap are located either in the South East or East of England. They say that “as cities in these regions tend to perform economically better than cities in the North of England, economic performance seems to influence the gender pay gap in cities. In general, cities with higher average weekly earnings (e.g. Cambridge, London, Reading, Crawley, Slough) tend to have a higher gender pay gap.”

Another factor the Centre for Cities things is driving higher gender pay gaps in the south of England is the bigger difference between men and women holding a managerial position. While 5.2 of men and 3.2 per cent of women in the north east hold such a position, 8.1 per cent of managers in the south east are men while only 4.4 per cent are women (data is not available below regional level).”

Six out of the ten cities with the smallest gender pay gap are located in the North of England: Wigan, Burnley, Warrington, Sunderland, Blackburn and Middlesbrough. These cities have weaker economies and lower rates of employment

The Centre for Cities has looked at the industrial composition of the labour market in Warrington and Wigan, finding that both cities have a higher share of jobs in education, human and health activities and social work than cities with higher gender pay gaps such as Slough and Crawley.

The composition of sectors in and around cities is seen as important and since women are more likely to be employed in the public sector, for instance, as teachers, social workers and nurses, the gender pay gap tends to be lower in cities with a higher proportion of public sector jobs such as in Middlesbrough, Blackburn, Swansea and Glasgow.

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Understanding Labour Market data

April 8th, 2019 by Graham Attwell

The increasing power of processors and the advent of Open Data provides us information in many areas of society including about the Labour Market. Labour Market data has many uses, including for research in understandings society, for economic and social planning and for helping young people and older people in planning and managing their occupation and career.

Yet data on its own is not enough. We have to make sense and meanings from the data and that is often not simple. Gender pay gap figures released by the UK Office of National Statistics last week reveal widespread inequality across British businesses as every industry continues to pay men more on average than women. This video Guardian journalist Leah Green looks at the figures and busts some of the common myths surrounding the gender pay gap.

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Where do graduates come from and where do they go?

February 21st, 2019 by Graham Attwell

I’ve written too many times about the problems in sense making from data – particularly where the labour market and education are involved. This presentation from the UK Centre for Cities makes an admiral attempt to use the data to tell a story about where students are coming from to study at Glasgow’s Universities and where they go afterwards.

It has its drawbacks – mainly due to the lack of data. For instance most of the slides fail to show movements in and out of the UK. Also, I would have loved to have more detailed data about what jobs students go into after university, but this data just is not available from UCAS at a more disaggregated level. And I am not very sure about the click bait title: “the Great British Brain Drain.” If there is a brain drain, nothing in the analysis points to one.

It is interesting to see that manufacturing still accounts for 44% of new graduate employment is Glasgow, despite manufacturing only constituting 30% of total employment in the city. This is much more that the 19& of new graduate working in the much heralded knowledge intensive business services sector.

One of their conclusions is very important: its not just about the student experience or the quality of nightlife in a city but more importantly “Ultimately it’s the jobs available to graduates which determine if they stay. By offering more, and better, opportunities the city will attract more graduates, both those who have studied in the city and those moving in for the first time from elsewhere.”

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The development of Labour Market Information systems

August 29th, 2018 by Graham Attwell

Over the past few years, part of my work has been involved in the design and development of Labour Market Information Systems. But just as with any facet of using new technologies, there is a socio-technical background to the emergence and use of new systems.

Most countries today have a more or less elaborated Labour Market Information system. In general, we can trace three phases in the development of these systems (Markowitch, 2017). Until the 1990s, Labour Market Information systems, and their attendant classification systems, mainly provided statistics for macroeconomic analysis, policy and planning. Between the 1990s and 2005 they were extended to provide data around the structuring and functioning of the Labour markets.

Mangozho (2003) attributes the change as a move from an industrial society to a post-industrial society (and the move to transition economies in Eastern Europe). Such a definition may be contentious, but he usefully charts changes in Labor market structures which give rise to different information needs. “While previously, the economic situation (especially the job structure) was relatively stable, in the latter phase the need for LMI increases because the demand for skills and qualifications changes fundamentally; the demand for skills / qualifications changes constantly, and because of these changes, Vocational Education and Training (VET) system has to be managed more flexibly (ETF, 1998)’.

He says: “In the industrial/pre-transition periods:

  • The relationship between the education and training system and the Labor market was more direct.
  • Occupational structures changed very slowly and as such, the professional knowledge and skills could easily be transferred.
  • Planning, even for short-term courses, could be done well in advance, and there was no need to make any projections about the future demands of occupations
  • The types of subjects and the vocational content required for specific jobs were easily identifiable.
  • There was little need for flexibility or to design tailor-made courses.
  • The education system concentrated on abstract and theoretical knowledge as opposed to practical knowledge.
  • Steady economic growth made it possible for enterprises to invest in on the job training.
  • There was less necessity to assess the relevance and adequacy of the VET system because it was deemed as adequate.
  • A shortage of skills could easily be translated into an increase of the number of related training institutions or student enrolments without necessarily considering the cost effectiveness of such measures. (Sparreboom, T, 1999).
  • Immediate employment was generally available for those who graduated from the education and training systems.”

Changes in the structure and functioning of Labour markets and the VET systems led to a greater need for comprehensive LMI to aid in the process of interpreting these structural shifts and designing effective HRD policies and programs, which provide for more linkages between the education and training systems and the Labor market.

At the same time, the reduction in the role of the state as a major employment provider and the development of market economies gave impetus to the need for a different approach to manpower planning, where the results of Labor market analysis as well as market based signals of supply and demand for skills are made available to the various economic agents responsible for the formulation and implementation of manpower and employment policies and programmes.

This led to the establishment of formal institutions to co-ordinate the generation of LMI, for instance internet based Labour Market Information Systems and the setting up of Labour Market Observatories and the development of more tangible LMI products, which provide a broad up, dated knowledge of the developments on the Labour market for different users.

Since 2005, Labour Market Information systems have been once more extended to incorporate both matching of jobs to job seekers and matching of supply and demand within Labour markets, particularly related to skills.

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Visualising jobs

April 26th, 2017 by Graham Attwell

bidigestersAs ever I am doing lots of work on labour market data and education and training. While we know pretty well how to take great slabs of data and turn it into various different charts – some more imaginative than others – this still leaves problems in how to illustrate ideas. data charts can be pretty dull – more than that they rely on the ability of the user to interpret that data – what we call the move from labour market information to labour market intelligence.

biodigester2

I have long been interested in the potential of info graphics in helping develop such intelligence but had yet to see any meaningful examples. Thus, I was very impressed with this graphic about the training and skills needs in the anaerobic digestion industry in the monthly newsletter from Cereq – the French Centre for Research Education, Training and Employment.

The only real problem is that the infographic – like many others is much too long for a small laptop screen (this I have only been able to capture parts of it). But it would be great as a poster.

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Interpreting and presenting data

March 1st, 2017 by Graham Attwell

I have been working on the contents for week 4 of the free #EmployID MOOC on The Changing World of Work, taking place on the European EMMA platform and starting in late March. Week 4 is all about Labour Market Information – or as I prefer to call it, Labour Market Intelligence – and how we can use labour market data both for job seekers and young people choosing careers and by advisers and other professionals working in the careers and labour market domain.

One of the major challenges is how to represent data. This presentation, Data is beautiful: Techniques, tools and apps for sharing your results by Laura Ennis, provides some good practical advice on how to present data. It come from a talk she did at Leap Into Research 2017.

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Project List

Current Projects

  • MediaInAction

    TACCLE 4 CPD

    CYCLE

    OurTown

    TACCLE 5 VET

    LMIforAll

    Past Projects

    Bazaar

    B-Learning4All

    EmployID

    Euronet-PBL

    EuroTrainer II

    EvoLearn

    FreeFolio/e-portfolio

    G8WAY

    IcoNet

    ICT and SMEs

    Interest and Desires

    LAAGG

    Learning Layers IP

    Learn2Teach

    MATURE

    Mosep

    POLITICS

    PwD-Employ

    RadioActive Europe

    Reflective Evaluation

    Seele

    Show your own Gold

    SMART

    Support Careers Guidance

    TACCLE

    TACCLE 2

    TACCLE 3 Coding

    TTplus

    WebQuest for HRM

    WLT

    YETI

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