The 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.

geralt (CC0), Pixabay

COVID-19 is turning from a health crisis into an economic catastrophe, says the UK based Nesta. With the Government’s Coronavirus Job Retention scheme closing at the end of October, the coming labour market shock will be unprecedented in scale and there is a major risk of people being unable to meet housing or food costs and falling into debt.

Navigating the labour market will be challenging, especially for people in insecure and low-paid employment. Despite the emergence of a range of online products and services, some basic needs – like matching people to training and education courses that provide the best return – are not being met.

Further, although a range of financial services already exist to support vulnerable families, the scale and accessibility of these services are out of kilter with what is now required.

To stimulate innovation in these fields, Nesta launched the Rapid Recovery Challenge – a new £2.8 million challenge prize seeking scalable ways of giving vulnerable workers better access to jobs and financial help in the wake of COVID-19.

Find out more about the challenge prize.

Rezwan (CC0), Pixabay

I’ve written a lot of articles over the last year about labour market information and what it means both for careers guidance and support and for vocational education and training. But its all too easy to get blase about data, especially when each forecast seems to be worse than the last,

So I thought I would write something more personal, about the impact of Covid 18 and the recession on people around me. This is necessarily an impressionistic account. Since the 14 March when Spanish prime minister Pedro Sánchez declared a state of emergency, I doubt I have ventured more than two kilometers from the flat in Spain where I was at the start on the crisis. How, a sort of new normal is emerging. OK, schools are still closed as are vocational colleges the the universities, most people wear masks, the numbers allowed in bars and restaurants severely restricted and there are still very few flights in and out of the city. But the terraces are open, albeit with social distancing and the traffic appears to be getting back to its usual dreadful density.

But this isn’t a return to the old normal or even a new normal.Every time I goo out I see a new closed shop, bar or restaurant. The UK Centre for Cities has shown how Covid 19 is having a different impact on different cities. Interestingly, many of the cities being hit hardest in terms of employment and industries are those already under pressure from automation and AI. I am not sure what the overall impact will be on Valencia. To an extent it may depend on the future of large companies like Ford which is, I think, the city’s largest employer. But Valencia also has a considerable number of SMEs, mainly involved in manufacturing, in sectors like furniture. And of course Valencia is a major tourist centre, which even though now declared open to most European cities, is not going to really recover this year.

But it may well be that the impact is differentiated on a local as well as city basis. The area near me is a middle class district with most people seemingly able to work from home. Inevitably in teh crisis people have not ventured far for shopping so shops have been dependent on people living nearby. To some extent that has lessened the impact in my district, although small clothes ships have closed, many bars and restaurants are closed or struggling and even the local swimming pool is shuttered with a for sale notice on the facade. But on Tuesday I was in a nearby working class district. Here, where presumably more inhabitants had jobs which could not be undertaken from home, the impact is much starker. It is easier to count the shops that are open than those closed. Here the recession looks grim. I/m waiting to get data which may indicate just what is going on. But impressions may be nearly as useful.

katielwhite91 (CC0), Pixabay

Even before the COVIP 19 crisis and the consequent looming economic recession labour market researchers and employment experts were concerned at the prospects for the future of work due to automation and Artificial Intelligence.

The jury is still out concerning the overall effect of automation and AI on employment numbers. Some commentators have warned of drastic cuts in jobs, more optimistic projections have speculated that although individual occupations may suffer, the end effect may even be an increase in employment as new occupations and tasks emerge.

There is however general agreement on two things. The first is that there will be disruption to may occupations, in some cases leasing to a drastic reduction in the numbers employed and that secondly the tasks involved in different occupations will change.

In such a situation it is necessary to provide pathways for people from jobs at risk due to automation and AI to new and hopefully secure employment. In the UK NESTA are running the CareerTech Challenge programme, aimed at using technology to support the English Government’s National Retraining Scheme. In Canada, the Brookfield Institute has produced a research report ‘Lost and Found, Pathways from Disruption to Employment‘, proposing a framework for identifying and realizing opportunities in areas of growing employment, which, they say “could help guide the design of policies and programs aimed at supporting mid-career transitions.”

The framework is based on using Labour Market Information. But, as the authors point out, “For people experiencing job loss, the exact pathways from shrinking jobs to growing opportunities are not always readily apparent, even with access to labour market information (LMI).”

The methodology is based on the identification of origin occupations and destination occupations. Origin occupations are jobs which are already showing signs of employment. Decline regardless of the source of th disruption. Destination jobs are future orientated jobs into which individuals form an origin occupation can be reasonably expected to transition. They are growing, competitive and relatively resilient to shocks.

Both origin and destination occupations are identified by an analysis of employment data.

They are matched by analysing the underlying skills, abilities, knowledge, and work activities they require. This is based on data from the O*Net program. Basically, the researchers were looking for a high 80 or 90 per cent match. They also were looking for destination occupations which would include an increase in pay – or at least no decrease.

But even then, some qualitative analysis is needed. For instance, even with a strong skills match, a destination occupation might require certification which would require a lengthy or expensive training programme. Thus, it is not enough to rely on the numbers alone. Yet od such pathways can be identified then it could be possible to provide bespoke training programmes to support people in moving between occupations.

The report emphasises that skills are not the only issue and discusses other factors that affect a worker’s journey, thereby, they say “grounding the model in practical realities. We demonstrate that exploring job pathways must go beyond skills requirements to reflect the realities of how people make career transitions.”

These could include personal confidence or willingness or ability to move for a new job. They also include the willingness of employers to look beyond formal certificates as the basis for taking on new staff.

The report emphasises the importance of local labour market information. That automation and AI are impacting very differently in different cities and regions is also shown in research from both Nesta and the Centre for Cities in the UK. Put quite simply in some cities there are many jobs likely to be hard hit by automation and AI, in other cities far less. Of course, such analysis is going to be complicated by COVID 19. Cities, such as Derby in the UK, have a high percentage of jobs in the aerospace industry and these previously seemed relatively secure: this is now not so.

In this respect there is a problem with freely available Labour Market Information. The Brookfield Institute researchers were forced to base their work on the Canadian 2006 and 2016 censuses which as they admit was not ideal. Tn the UK data on occupations and employment from the Office of National Statistics is not available at a city level and it is very difficult to match up qualifications to employment. If similar work is to be undertaken in the UK, there will be a need for more disaggregated local Labour Market Information, some of it which may already be being collected through city governments and Local Economic Partnerships.

mohamed_hassan (CC0), Pixabay

Pontydysgu is very happy to be part of a consortium, led by DMH Associates, selected as a finalist for the CareerTech Challenge Prize!

The project is called CareerChat and the ‘pitch’ video above expalisn the ideas behind the project. CareerChat is a chatbot providing a personalised, guided career journey experience for working adults aged 24 to 65 in low skilled jobs in three major cities: Bristol, Derby and Newcastle. It offers informed, friendly and flexible high-quality, local contextual and national labour market information including specific course/training opportunities, and job vacancies to support adults within ‘at risk’ sectors and occupations

CareerChat incorporates advanced AI technologies, database applications and Natural Language Processing and can be accessed on computers, mobile phones and devices. It allows users to reflect, explore, find out and identify pathways and access to new training and work opportunities.

Nesta is delivering the CareerTech Challenge in partnership with the Department for Education as part of their National Retraining Scheme

• Nesta research suggests that more than six million people in the UK are currently employed in occupations that are likely to radically change or entirely disappear by 2030 due to automation, population aging, urbanisation and the rise of the green economy.
• In the nearer-term, the coronavirus crisis has intensified the importance of this problem. Recent warnings suggest that a prolonged lockdown could result in 6.5 million people losing their jobs. [1] Of these workers, nearly 80% do not have a university degree. [2]
• The solutions being funded through the CareerTech Challenge are designed to support people who will be hit the hardest by an insecure job market over the coming years. This includes those without a degree, and working in sectors such as retail, manufacturing, construction and transport.

You can find out more information about the programme here: https://www.nesta.org.uk/project/careertech-challenge/ and email Graham Attwell directly if you would like to know more about the CareerChat project

Comfreak (CC0), Pixabay

As reported in FE News, a new report based on analysis by London Economic, ‘Qualified for the Future: Quantifying demand for arts, humanities and social science skills’ provides quantitative evidence for the employment benefits of studying the arts, humanities and social sciences at university.

The report finds that:  

• Graduates of arts, humanities and social sciences are just as resilient to economic upheaval as other graduates and are just as likely to remain employed as STEM graduates during downturns
• Looking at the total UK workforce, arts, humanities and social science graduates are just as likely to be employed as their STEM counterparts; the 2017 Labour Force Survey shows that 88% of HSS graduates and 89% of STEM graduates were employed in that year
• Of the ten fastest growing sectors in the UK economy, eight employ more graduates from the arts, humanities and social science than other disciplines. They include the well-paid information and communication industry and finance sector
• HSS graduates are the backbone of the economy, with the majority working in the UK services sector. The service sector accounts for 81% of the UK’s total economic output and is second only to the US in export value globally
• HSS graduates will be essential to fill in the workforce gaps of the future, particularly those studying fine arts, history and archaeology, philosophy and theology, geography, sociology and anthropology

• While the health sector is the dominant destination for recent STEM graduates, HSS graduates choose to work in a wide range of sectors across the economy, including financial services, education, social work, the media and creative industries.

I have long been dubious of what I see as an overemphasis on STEM subjects from an employment perspective and this report would seem to support such scepticism. And I can well understand the advantages HSS graduates may have in their flexibility and employment resilience.  However, one worry lies in that focus on jobs in the services sector. Obviously as a sector accounting for 81% of the UK’s total economic output, the sector is very broad and will include a spread of occupations. Many, I fear will be in lower paid and precarious employment.

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)

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

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.

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.

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.”